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Energy characteristics of droplet transfer in wire-arc additive manufacturing based on the analysis of arc signals
Accepted Manuscript Energy characteristics of droplet transfer in wire-arc additive manufacturing based on the analysis of arc signals Zhu Liang, Luo Yi, Han Jingtao, Zhang Chengyang, Xu Jie, Chen Dong PII: DOI: Reference:
S0263-2241(18)30986-2 https://doi.org/10.1016/j.measurement.2018.10.048 MEASUR 5988
To appear in:
Measurement
Received Date: Revised Date: Accepted Date:
8 October 2017 1 July 2018 15 October 2018
Please cite this article as: Z. Liang, L. Yi, H. Jingtao, Z. Chengyang, X. Jie, C. Dong, Energy characteristics of droplet transfer in wire-arc additive manufacturing based on the analysis of arc signals, Measurement (2018), doi: https://doi.org/10.1016/j.measurement.2018.10.048
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Energy characteristics of droplet transfer in wire-arc additive manufacturing based on the analysis of arc signals Zhu Liang a, b, Luo Yi a, b, c, Han Jingtao a, b, Zhang Chengyang a, b, Xu Jie a, b, Chen Dong a, b
a
School of Material Science and Engineering, Chongqing University of Technology, Chongqing 400054, People’s Republic of China b Chongqing
Municipal Engineering Research Center of Institutions of Higher
Education for Special Welding Materials and Technology, Chongqing 400054, People’s Republic of China c State
Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi’an 710072, People’s Republic of China
Corresponding author: Dr. Luo Yi Mailing Address: School of Material Science and Engineering, Chongqing University of Technology, Chongqing 400054, China Telephones: +86-13883008891 (Mobile) Fax: +86-23-62563178 E-mail: [email protected]
Abstract: The non-pulsed arc and pulsed arc were used in wire-arc additive manufacturing (WAAM) of aluminum alloys. Arc signals about arc current and 1
voltage synchronized with the acoustic emission (AE) detected in manufacturing were used as information source to identify the droplet transfer mode. The calculations of probability density distribution, power spectrum distribution and energy gradient to synchronous time-domain signals were used to investigate the characteristics of metal droplet transfer and energy transfer. As a result, it was found that the characteristics of arc power signals and AE signals in WAAM process have a close relationship with the droplet transfer and arc ignition, and could reflect the variations of energy characteristics. The energy output characteristics of non-pulsed arc and pulsed arc during droplet transfer process are different. The matching of pulsed arc and pulsed droplet transfer mode obtains the best thermal and mechanical transfer characteristics, which is more suitable for the WAAM manufacturing process. No matter whether pulsed arc or non-pulsed arc is adopted, the energy output of arc should not be excessive, otherwise the energy output and the impact effect of arc and droplet transfer may be not conducive to the forming efficiency and quality of WAAM manufacturing.
Keywords: Pulsed arc, Additive manufacturing, Power, Acoustic emission, Deposition layer, Energy gradient
2
1 Introduction Additive manufacturing (AM) is a novel technique for building up complex metal components by the deposition of materials layer-by-layer. Many techniques have been developed for manufacturing metal components in AM. According to the different energy sources used in manufacturing, these techniques can be mainly classified into three groups: laser based [1], electron beam based [2] and arc based [3]. Currently, either a powder-feed process or a wire-feed process is used in popular AM technologies to supply the additive materials [4]. Compared with the powder-feed process, the wire-feed approach is a cleaner and more environmental friendly process. But laser and electron beam have poor energy efficiency (2-5% and 15-20% respectively) [5, 6], which will restrict the improvement of deposition rate in wirefeed AM process. The energy efficiency of arc based techniques such as the gas metal arc welding (GMAW) or gas tungsten arc welding (GTAW) processes can be as high as 90% in some circumstances [4]. Almost 100% of the wire material can be deposited into the component in the arc based techniques. So, the arc is more readily available than laser and electron beam having suitable properties for wire-feed AM process. Accordingly, wire and arc additive manufacturing (WAAM) technology is proposed due to its combined advantages of higher deposition rate, energy efficiency and material usage efficiency. WAAM process uses an electric arc, either the gas metal arc (GMA), the gas tungsten arc (GTA) or the plasma arc (PA), as a heat source and filler wire as feedstock [7]. The filler wire is melted continuously by electric arc to form metal 3
droplet, which is transferred into the molten pool to form deposition layer in WAAM process. The deposition process of droplet is related to the thermal-mechanical effect of arc and metal droplet. In addition to gravity, arc force plays a most important role in the deposition process of metal droplet. The arc force is composed of the electromagnetic force, the plasma flow force, the evaporation recoil force and the charged particle impact force. It is precisely because of the arc force, the metal droplet transfer process in WAAM is complex. But, due to its high deposition rate, environmental friendliness and cost-competitiveness, the WAAM process becomes more attractive and much research has been focused on WAAM. At present, most of the research on WAAM is focused on the microstructure and properties of the deposition layer. Lin et al. [8] studied the microstructural evolution and mechanical property of Ti-6Al-4V wall deposited by continuous plasma arc. Asala et al. [9] performed a detailed microstructural study of ATI 718Plus superalloy produced by the GTA based AM process. Chen et al. [10] fabricated the austenitic stainless steel 316L by GMA based AM process and investigated its microstructure and room temperature tensile properties. Wu et al. [11] studied the influence of low heat input pulse on the fine microstructure and unsupported overhangs in GTA based AM process. Haden et al. [12] systematically investigated the mechanical properties of wire-based deposition of steel metal by GMA based AM process. These results indicated that the deposited thin wall consisted of various morphologies, which depends on the heat input, multiple thermal cycles and gradual cooling rate in the deposition process. Therefore, it is a basic research work to study the mechanism of 4
heat transfer in the WAAM process. Although, it is insufficient to study the mechanism of WAAM process, especially the characteristics of energy transfer of arc and droplet, there is some similar research in GMAW or GTAW providing useful information for study of WAAM. Kamal et al. compared the acoustic signals of P-GMA welding at various process parameters. The acoustic signals were found to be strongly related to both metal droplet transfer and weld quality [13]. Saad et al. investigated the relationships between the acoustic signals and the modes of the molten pool in variable polarity plasma arc welding. The results showed that the keyhole mode can be distinguished from the cutting mode under the experiment conditions [14]. Kamal et al. used the acoustic sensor and other sensors to properly monitor the depth of weld penetration. Finally, the weld penetration monitoring was found to be better with the arc sound kurtosis [15]. Tam [16] revealed strong correlation between welding parameters and arc-acoustic spectral characteristics in GMAW, and the result showed that acoustic emission is a process parameter feedback to successfully achieve a closed-loop control of GMAW processes. Cayo et al. [17] made the comparative analysis in time domain and frequency domain to the acoustic signals generated by the electric arc to evaluates the stability in GMAW process. The result concluded that the acoustic evaluation of the stability on the GMAW process presents more clarity for the analysis based in the time domain that the frequency domain. Much research in GMAW provides useful information for the study of WAAM process because of the similar characteristics of the energy transfer of arc and droplet. 5
Xiong et al. [18] analyzed the arc force of a force model for a pending molten pool, and the influences of offset distance, wire feed rate, and travel speed on the inclination angle were revealed and discussed. Based on which, an process approach was proposed to fabricate 104-layered cylindrical thin-walled part. Yang et al. [19] used an infrared camera to capture the surface temperature of the deposited thin-wall parts for investigating the thermal behavior of WAAM. The temperature field cloud pictures indicated that as the deposition height increased, the heat accumulation of the deposited parts became serious. Using the alternate inter-layer cooling time can improve the forming quality of the thin-wall part distinctly. Geng et al. [20] studied the droplet transfer behavior in GTA based AM of aluminum alloy. From the view point of wire feed manner regulation, a mathematical model is developed to calculate the wire flying distance in arc zone. According to the above research results, the thermal and mechanical behavior of arc and droplet indicated that the characteristics of energy transfer were closely related to the quality of deposition layer. However, the research on the multiple effects of thermal and mechanical behavior in WAAM process is relatively few. In this paper, the arc signals of current, voltage and acoustic emission (AE) were tested in WAAM process and were used to analyze the behavior energy transfer. The periodic behavior of both arc ignition and droplet transfer is related to the energy transfer process. Based on these, the arc information and its energy characteristics in manufacturing were applied to investigate the energy transfer process of GMA based AM in this work, which is missing in the work done by Cayo et al.[17]. And the 6
influence of the energy transfer on the final forming quality of the deposition layer also has been studied. 2 Experiment details The WAAM automatic processing system used in experiment consists of three parts: the arc system, the motion control system and the arc signals acquisition system. Figure 1 shows the schematic of experiment system. The arc system is a GMAW power source. The filler wire is fed to the torch tip coaxially. The filler wire tip is melted to form metal droplets by the arc discharge caused between the wire tip and substrate. The arc torch was kept stationary in wire-arc additive manufacturing. The workpiece was moved by the motion control system, which was a programmable 3axis linear stage system. As the workpiece moves along the targeted path, accumulated metal droplets are solidified and deposited. The arc signals acquisition system includes arc current (I(t)), arc voltage (U(t)) and AE sensing system. The dynamic waveforms of arc signals in processing were recorded in real-time. Hall sensor was used to measure the arc current and voltage signals. According to these two signals, the instantaneous output (P(t)) of arc power was calculated by P(t) = U(t)×I(t)
(1)
Piezo-electric sensor was mounted on the surface of substrate to measure the AE signals. All of the signals detected by sensor were processed by preamplifier and signal conditioner, and then they were synchronized and transferred to computer by data acquisition unit. Aluminum alloy wire (ER-4043), which diameter was 1.2mm, was used as filler 7
wire in the experiments. The shielding gas was pure argon (Ar) and the gas flow rate was set from 15 L/min to 20 L/min. 6061 aluminum alloy with 150mm length, 100mm width and 8mm thickness was used as substrate in the experiment. In view of the arc stability in electrode positive (EP) region, the direct-current electrode positive (DCEP) was used to govern the metal droplet dynamics. The matching of experiment parameters of the non-pulsed arc and the pulsed arc was shown in Table 1.
Fig.1
Schematic diagram of the experiment system. Table 1
Experimental parameters.
Current
Voltage
Frequency
Travel velocity
Shield gas flow rate
I/A
U/V
f /Hz
v/mm·s-1
Q/L·min-1
1
120
20.2
0
10
15
2
160
22.4
0
10
15
3
220
25.8
0
10
20
NO.
8
4
120
20.2
200
10
15
5
160
22.6
240
10
15
Acoustic emission is a transient elastic wave produced by the rapid release of energy from a local source in a material. The deformation and crack propagation of materials under stress can produce acoustic emission, which is a kind of acoustic emission source in manufacturing. Another source of acoustic emission in manufacturing is the combustion of the arc and the impact of the metal droplet on the molten pool. Figure 2 illustrates the generation mechanism of the latter AE source in WAAM and shows the detection of the AE signals. Electric arc has high temperature and mechanical effect. On the one hand, arc melts filler wire to form metal droplets. On the other hand, arc melts the base plate to form molten pool. The arc force continues to act on the molten pool and produces AE energy to the interior and surrounding of the materials. Similarly, the metal droplet moves from the end of the filler wire to the molten pool and impacts the molten pool, which also produces acoustic emission energy to the interior and surrounding of the materials. The result of high speed photography in the previous study has proved that captured acoustic emissions correspond to arc and droplets transfer [21]. In this study, the AE energy is sensed in the form of structure-borne. The structure-borne AE sensor was mounted on the surface of base plate and the base plate itself was set as the transmission medium of AE. Thus, the AE energy delivered to the interior of the materials can be detected by the structure-borne AE sensor, while which is insensitive to the AE energy 9
delivered to the surrounding of the materials. Because the AE wave travels very fast in the solid aluminum materials (travel velocity 6260 m/s) and the length of the workpiece is only 150mm, although the position of the piezo-electric sensor varies with respect to the arc heat source in experiment, the time error due to position change is less than 0.02ms, which is negligible. Therefore, the mechanical impact of the arc and the metal droplet on the substrate can be detected and expressed by AE signals.
Fig.2
Generation and detection of structure-borne AE signals in wire-arc additive manufacturing.
3 Results and discussion 3.1 Characteristics of arc signals in time-domain The arc is used to melt the filler wire and form continuous droplets transferred into the molten pool in WAAM manufacturing process. The characteristics of arc signals in time-domain reflect the continuous evolution of the WAAM manufacturing process. In this paper, arc power signals are used to represent the evolution of arc energy output, and AE signals are used to represent the mechanical effects of arc or droplet on the molten pool. In the present studies, three droplet transfer modes are recognized 10
for non-pulsed arc, which are short-circuit transfer mode, globular transfer mode and spray transfer mode [22]. But pulsed transfer mode of droplet is recognized for pulsed arc. No matter what kind of droplet transfer mode, it is accompanied by the thermalmechanical coupling impact between arc energy output and arc force on the molten pool in WAAM process, which characteristics could be indicated by the arc signals detected in manufacturing. Arc power and AE signal all can be used to monitor the process. It can be seen from Figure 3 and Figure 4 that the process characteristics of arc power and AE signal are distinguishable in short-circuit transfer mode and globular transfer mode for non-pulsed arc and pulsed transfer mode for pulsed-arc. But the process characteristics of AE signal is more advantageous and distinguishable to clarify the droplet in spray transfer mode for non-pulsed arc. Figure 3 shows the synchronous time-domain signals of arc power and AE detected in wire-arc additive manufacturing. Figure 3a～3c show the signals of non-pulsed arc accompanied with short-circuit transfer mode, globular transfer mode and spray transfer mode respectively. Figure 3d and 3e show the signals of pulsed arc working in pulsed transfer mode. It can be found that the difference of arc signals is very significant in different droplet transfer modes. There is a strict correspondence between AE signals and arc power signals in time domain, which indicates some phenomenons of thermal-mechanical effect generated from the behavior of arc and metal droplet. The correspondence between AE signals and arc power signals in time domain is showed in Figure 4.
11
(a)
(b)
(c) 12
(d)
(e) Fig.3
Time-domain signals of AE and arc power in wire-arc additive manufacturing.
(a) Short-circuit transfer mode for non-pulsed arc (I=120A), (b) globular transfer mode for non-pulsed arc (I=160A), (c) spray transfer mode for non-pulsed arc (I=220A), (d) pulsed transfer mode for pulsed-arc (I=120A) and (e) pulsed transfer mode for pulsed-arc (I=160A).
The synchronization waveforms of AE signals and arc power signals from 0.04s to 13
0.10s in Figure 3a were amplified in Figure 4a. When the droplet contacts the molten pool to produce short-circuit, the arc is extinguished temporarily and the output power is minimized. After the droplet transfers into the molten pool, the arc is reignited and the arc power output is resumed. Therefore, the process of droplet short-circuit transfer can be defined by arc power signals as shown in Figure 4a. Because the shortcircuit contact of droplet and the arc ignition produce the effect of the force affecting on the molten pool and stimulate the AE energy, the short-circuit AE event and arc ignition AE event could be distinguished from the AE signals according to the characteristics of arc power signals in time-domain. The synchronization waveforms of AE signals and arc power signals from 0.005s to 0.015s in Figure 3c were amplified in Figure 4b. The combustion of the arc in the non-pulsed arc mode is continuous during the spray transfer process of the metal droplet. So there is no arc reignition phenomenon and arc ignition AE event. However, each droplet transferred into the molten pool will stimulate AE energy. In view of the signal-to-noise ratio of the AE signals, the wavelet analysis was used to extract the droplet AE event. So the droplet AE event can be identified from the AE signals in Figure 4b. The waveform of arc power signals is smooth and it is difficult to identify the characteristic information of droplet transfer. The synchronization waveforms of AE signals and arc power signals from 0.008s to 0.017s in Figure 3e were amplified in Figure 4c. It can be seen that the arc ignition and droplet transfer are all controlled by arc pulse for pulsed arc . Because the arc ignition and the droplet transition will stimulate the AE energy and produce AE 14
events, the acoustic emission signals can be used to identify the arc ignition and droplet transfer in pulsed arc mode. According to the AE signals and the arc power signals, it can be seen that the arc is ignited at the rising edge of the pulse, and the droplet is transferred into the molten pool at the falling edge of the pulse. From the above analysis we can see that the characteristics of arc power signals and AE signals in WAAM process have a close relationship with the droplet transfer and arc ignition, and could reflect the variations of the manufacturing process. The following contents will analyze the energy characteristics and thermal-mechanical transfer in different droplet transfer modes on the basis of arc power signals and acoustic emission signals detected in WAAM process.
(a)
15
(b)
(c) Fig.4
Correspondence between AE signals and arc power signals in time domain, (a)
Short-circuit transfer mode for non-pulsed arc, (b) spray transfer mode for non-pulsed arc and (c) pulsed transfer mode for pulsed-arc. 16
3.2 Energy characteristics and thermal-mechanical transfer Arc power reflects the energy output of the arc, and arc power signal is the realtime response of arc power output. Figure 5 shows the probability density distributions of arc power signals under different droplet transfer modes, namely, the arc power output characteristics under different droplet transfer modes. When the arc current is 120A, the arc power output is mainly distributed in two regions for the short-circuit transfer mode generated by non-pulsed arc. One is the low arc power region distributed from about 100W to 300W, which corresponds to the arc power output when the droplet is short-circuited, and the other is the high arc power region distributed from about 1000W to 3000W, which corresponds to the arc power output when the arc is burning. When the arc current is 160A, the arc power output is mainly distributed from about 2000W to 4000W for the globular transfer mode generated by non-pulsed arc. When the arc current is 220A, the arc power output is mainly distributed around 4300W for the spray transfer mode generated by non-pulsed arc. Clearly, the output energy of the arc is the highest under the spray transfer mode for non-pulsed arc. When the arc current is 120A or 160A, the pulsed arc power output is also mainly distributed in two regions for the pulsed transfer mode generated by pulsed arc. The arc power output is pulsing under the pulsed arc. The low arc power output region corresponds to the low level of the pulse energy output, and the high arc power output region corresponds to the high level of the pulse energy output. The arc ignition and 17
droplet transfer all occur at the high arc power output region of arc pulse according to the illustration of Figure 4c. In general, the average output power of non-pulsed arc in short-circuit transfer mode and pulsed arc is lower, while the average output power of non-pulsed arc in globular transfer mode and spray transfer mode is higher. These energy output characteristics determine the droplet deposition rate and the manufacturing efficiency of the WAAM process. It is generally known that higher arc energy output is beneficial to get high deposition rate. But, high arc energy output is more likely to cause some defects in manufacturing, such as heat distortion and excessive melting, which must be taken into consideration. Arc energy output is distributed in high and low level regions respectively because of the fluctuation characteristic of pulse, which effectively reduces the average arc energy output and ensures the energy required by the fusion of filler wire. Thus, pulsed arc seems to be a better choice, which would be proved in the later sections.
18
Fig.5
Probability density distribution of arc power signals.
Certainly, the mechanical effects of arc and droplet transfer are also related to the energy output of arc. The mechanical effects were analyzed by the AE energy released by the arc and droplets impinging on the molten pool. The power distribution in frequency domain of AE signals is described by power spectrum analysis. Figure 6 shows the power spectrum distribution of AE signals detected in different droplet transfer modes. From the view of frequency distribution, the frequencies of AE signals are below 20kHz and the positions of spectrum peaks are similar in addition to the globular transfer mode of non-pulsed arc (I=160A). In particular, the main spectrum peak (9.90kHz) of spray transfer mode in non-pulsed arc (I=220A) is very close to that (9.81kHz) of pulse transfer mode in pulsed arc (I=160A), which indicates that the droplet transfer processes in the two conditions have some similar characteristics. From the view of amplitude distribution, the AE signals of spray 19
transfer mode in non-pulsed arc have the lowest amplitude of main spectrum peaks, which indicates the mechanical effects of arc and droplet transfer in this condition are weakest. Instead, the AE signals of pulse transfer mode in pulsed arc (I=160A) have the highest amplitude of main spectrum peaks, which indicates that the mechanical effects of arc and droplet transfer in this condition are strongest. The main spectrum peak (8.92kHz) and its amplitude of short-circuit transfer mode in non-pulsed arc (I=120A) is closer to the main spectrum peak (9.04kHz) and its amplitude of pulse transfer mode in pulsed arc (I=120A), which indicates that the droplet transfer processes in the two conditions have some similar characteristics. In the following sections, the energy characteristics of droplet transfer and arc are further analyzed by means of energy gradient to find out the influence on the quality of the deposition layer.
20
(a)
21
(b) Fig.6
Power spectrum distribution of AE signals for (a) non-pulsed arc and (b) pulsed arc.
In engineering signal analysis, mean square is used to represent the average power of signal. Because the mean squares of arc power signals and AE signals are proportional to the energy of arc signals and AE signals, the mean square was used to characterize the energy. The energy gradient was used to describe the transient variation of impact energy coming from arc and metal droplet transferred into molten 22
pool in this study. We used Ge(t) as the symbol for energy gradient, which was defined as ∫𝑡2𝑃2(𝑡)𝑑𝑡
𝐺𝑒(𝑡) =
𝑡1
(2)
𝑡2 - 𝑡1
or ∫𝑡2𝑈𝐴2(𝑡)𝑑𝑡
𝐺𝑒(𝑡) =
𝑡1
(3).
𝑡2 - 𝑡1
Where, P(t) is the values of arc power signal varied with time, and UA(t) is the AE signal voltage varied with time. The total energy of signals from t1 to t2 was defined as 𝑡
(4).
𝐸 = ∫𝑡2𝐺𝑒(𝑡)𝑑𝑡 1
As mentioned in the second section in this paper, the mechanical impact of the arc and the metal droplet on the substrate can be detected and expressed by AE signals. Therefore, the energy gradient of AE signals was used to describe the transient variation of mechanical impact energy from the arc and droplet, and the total energy of AE signals was used to describe the total mechanical impact energy. Similarly, the energy gradient of arc power signals was used to describe the transient variation of arc output energy, and the total energy of arc power signals was used to describe the total arc output energy. The signals of a single metal droplet transfer cycle in Figure 3 were extracted to calculate the energy gradient in the metal droplet transfer process. Figure 7 showed the energy gradient curves of arc power signals and AE signals detected in non-pulsed arc. It can be seen that the transient variation of arc power output by 160A arc current is larger than that by 120A arc current. But the transient 23
variation of mechanical impact energy produced by 160A arc current is smaller than that by 120A arc current. As mentioned earlier, the droplet transfer of non-pulsed arc is short-circuit transfer mode as the arc current is 120A and is globular transfer mode as the arc current is 160A. Therefore, the short-circuit transfer mode is characterized with larger transient variation of mechanical impact energy and the globular transfer mode is characterized with larger transient variation of arc power output in a single metal droplet transfer cycle. Figure 8 showed the energy gradient curves of arc power signals and AE signals detected in pulsed arc. It can be seen that larger arc current (I=160A) improves not only the transient variation of mechanical impact energy but also the transient variation of arc power output. Thus, the energy transfer characteristics of non-pulsed arc and pulsed arc during droplet transfer are different. In order to compare the energy transfer characteristics between the non-pulsed arc and the pulsed arc, the arc power signals and the AE signals with the same droplet transfer frequency are extracted. Figure 9 showed the energy gradient curves of arc power signals and AE signals detected in non-pulsed arc (I=220A) and pulsed arc (I=160A). It can be seen that, as the droplet transfer frequency is similar, the non-pulsed arc has a greater transient variation of arc power output, while the pulsed arc has a greater transient variation of mechanical impact energy. We believe that proper transient variation of arc power output and mechanical impact energy is important to form the deposition layer with high quality.
24
(a)
(b) Fig.7
Energy gradient of non-pulsed arc in a single metal droplet transfer cycle, (a)
Energy gradient of arc power signals and (b) Energy gradient of AE signals.
25
(a)
(b) Fig.8
Energy gradient of pulsed arc in a single metal droplet transfer cycle, (a)
Energy gradient of arc power signals and (b) Energy gradient of AE signals.
26
(a)
(b) Fig.9
Comparison of energy gradient between non-pulsed arc (I=220A) and pulsed
arc (I=160A) in a single metal droplet transfer cycle, (a) Energy gradient of arc power signals and (b) Energy gradient of AE signals.
The signals within 0.025s were extracted from Figure 3 to calculate the total energy of signals according to formula (4), which indicated the total energy output as several metal droplets transferred into molten pool in a fraction of a second. Figure 10 27
showed the total energy of AE signals (Figure 10a) and arc power signals (Figure 10b) detected in non-pulsed arc and pulsed arc. It can be seen that, under the same arc current and arc power conditions, the pulsed droplet transfer mode produces lower total energy of AE signals relative to the short-circuit transfer mode and the globular transfer mode. According to the AE signals in Figure 3 and Figure 4, the energy of AE signals is mainly produced by the impact of arc ignition and droplet transfer on the molten pool. A lower total energy of AE signals indicates that the impact effect produced by the arc ignition and droplet transfer is lower. The high impact effect could easily lead to the collapse of the deposition layer, which is unfavorable to the forming quality, while the low impact effect is not conducive to the spreading of the droplets in the molten pool. Another factor determining the quality of the deposition layer is the arc power output, and Figure 10b shows the total energy output of the arc within 0.025s. It can be seen that, under the same arc current and arc power, the arc energy output produced in the pulsed droplet transfer mode is between the short-circuit transfer mode and the globular transfer mode. Excessively low arc energy output is not conducive to the melting of droplets and the formation of an effective droplet transfer, while excessive arc energy output is likely to cause excessive melting of droplets and molten pool, which is one of the reasons to cause the collapse of deposition layer and is not conducive to the forming quality. Therefore, the matching of pulsed arc and pulsed droplet transfer mode is 28
most suitable for WAAM manufacturing. 3.3 Morphology of the deposition layer Figures 11 and 12 show the cross-section morphology of the deposition layer manufactured by the non-pulsed arc and pulsed arc. According to the cross-section morphology of the deposition layer, the characteristics of deposition height (h) and width (w) are measured and shown in Figure 13. As mentioned above, the matching of pulsed arc and pulsed droplet transfer mode obtains the best thermal and mechanical transfer characteristics in WAAM manufacturing, which relates to the beads in Figure 12. As the arc current is 220A, the arc energy output is excessive and the melting of droplet and molten pool is enhanced. Although the maximum height of the deposition layer has been obtained as shown in Figure 13a (open square and triangle curves), the width of the deposition layer is larger, and the deposition layer is collapsing. In addition, pulsed arc obtains larger height and smaller width of deposition layer as shown in Figure 13a (open circles and star designated curves). Accordingly, the ratio of the height and width of the deposition layer is introduced to describe the forming characteristics of the deposition layer. It can be found from Figure 13b that a higher ratio of h/w is obtained by pulsed arc in these process parameters matchings. With the increase of arc current and arc power, the ratio of height to width decreases as shown in Figure 13b, which indicates that, even using the pulsed arc, the arc power output should not be excessive, otherwise the arc energy output and the impact effect also may be not conducive to the forming efficiency and quality of WAAM manufacturing. So, Figure 12a is chosen as the optimal bead. 29
(a)
(b) Fig.10
Total energy of (a) AE signals and (b) arc power signals.
(a) I=120A Fig.11
(b) I=160A
(c) I=220A
Cross-section morphology of deposition layer manufactured by non-pulsed 30
arc.
(a) I=120A Fig.12
(b) I=160A
Cross-section morphology of deposition layer manufactured by pulsed arc.
(a)
(b) 31
Fig.13
Characteristics of (a) height (h) and width (w) and (b) h/w of deposition layer manufactured by non-pulsed arc and pulsed arc.
4 Conclusions (1) The characteristics of arc power signals and AE signals in WAAM process have a close relationship with the droplet transfer and arc ignition, and can reflect the variations of energy characteristics in WAAM manufacturing process. (2) The energy output characteristics of non-pulsed arc and pulsed arc during droplet transfer process are different. The output power in short-circuit transfer mode and pulsed droplet transfer mode is lower, while in globular transfer mode and spray transfer mode is higher. The mechanical effects of arc and droplet transfer in pulsed droplet transfer mode of pulsed arc are strongest, while in spray transfer mode of nonpulsed arc are weakest. (3) The matching of pulsed arc and pulsed droplet transfer mode obtains the best thermal and mechanical transfer characteristics, which is more suitable for the WAAM manufacturing process. Accordingly, a higher ratio of h/w is obtained by pulsed arc in pulsed droplet transfer mode and the forming efficiency and quality of deposition layer are improved. (4) No matter whether pulsed arc or non-pulsed arc is adopted, the energy output of arc should not be excessive, otherwise the energy output and the impact effect of arc and droplet transfer may be not conducive to the forming efficiency and quality of WAAM manufacturing. In the future work, the microstructure of tacked structure 32
affected by low energy pulsed arc or non-pulsed arc in WAAM should be clarified.
Acknowledgements This work was supported by Basic Science and Frontier Technology Research Project of Chongqing Science and Technology Commission of China (Grant No. cstc2017jcyjBX0065 and No. cstc2015jcyjA60009), Scientific and Technological Research Program of Chongqing Municipal Education Commission of China (Grant No. KJ1709197) and the Fund of the State Key Laboratory of Solidification Processing in NWPU (Grant No. SKLSP201717).
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shaping process. Metall Mater Trans B 35 (2004) 143–52. [6] L.E. Rannar, A. Glad, C.G. Gustafson, Efficient cooling with tool inserts manufactured by electron beam melting. Rapid Prototyp J 13 (2007) 128–35. [7] J.F. Wang, Q.J. Sun, H. Wang, J.P. Liu, J.C. Feng, Effect of location on microstructure and mechanical properties of additive layer manufactured Inconel 625 using gas tungsten arc welding. Mater Sci Eng A 676 (2016) 395–405. [8] J.J. Lin, Y.H. Lv, Y.X. Liu, Z. Sun, K.B. Wang, Z.G. Li, Y.X. Wu, B.S. Xu, Microstructural evolution and mechanical property of Ti-6Al-4V wall deposited by continuous plasma arc additive manufacturing without post heat treatment. J Mech Behav Biomed Mater 69 (2017) 19–29. [9] G. Asala, A.K. Khan, J. Andersson, O.A. Ojo, Microstructural Analyses of ATI 718Plus® Produced by Wire-ARC Additive Manufacturing Process. Metall Mater Trans A 6 (2017) 1-18. [10] X.H. Chen, J. Li, Z. Huang, H.M. Wang, X. Cheng, B. He, Microstructure and mechanical properties of the austenitic stainless steel 316L fabricated by gas metal arc additive manufacturing. Mater Sci Eng A http://dx.doi.org/10.1016/j.msea.2017.05. 024. [11] Q.R. Wu, Z.S. Ma, G.S. Chen, C.M. Liu, D.X. Ma, S.Y. Ma, Obtaining fine microstructure and unsupported overhangs by low heat input pulse arc additive manufacturing. J Manuf Process 27 (2017) 198–206. [12] C.V. Haden, G. Zeng, F.M. Carter III, C. Ruhl, B.A. Krick, D.G. Harlow, Wire and arc additive manufactured steel: Tensile and wear properties. Add Manuf 16 34
(2017) 115–123. [13] P. Kamal, B. Sandip, K. Pal Surjya, Investigation on arc sound and metal transfer modes for on-line monitoring in pulsed gas metal arc welding. J Mater Process Technol 210 (2010) 1397–1410. [14] E. Saad, H.J. Wang, R. Kovacevic, Classification of molten pool modes in variable polarity plasma arc welding based on acoustic signature. J Mater Process Technol 174 (2006) 127–36. [15] P. Kamal, K. Pal Surjya, Monitoring of Weld Penetration Using Arc Acoustics. Mater Manuf Process 26 (2011) 684–93. [16] J. Tam, Methods of Characterizing Gas-Metal Arc Welding Acoustics for Process Automation. Master's degree thesis: University of Waterloo, Canada, 2005. [17] E. Huanca Cayo, S.C. Absi Alfaro, GMAW Process Stability Evaluation Through Acoustic Emission by Time and Frequency Domain Analysis. Journal of Achievements in Materials and Manufacturing Engineering 34 (2009) 157-164. [18] J. Xiong, Y.Y. Lei, H. Chen, G.J. Zhang, Fabrication of inclined thin-walled parts in multi-layer single-pass GMAW-based additive manufacturing with flat position deposition. J Mater Process Tech 240 (2017) 397–403. [19] D.Q. Yang, G. Wang, G.J. Zhang, Thermal analysis for single-pass multi-layer GMAW based additive manufacturing using infrared thermography. J Mater Process Tech 244 (2017) 215–224. [20] H.B. Geng, J.L. Li, J.T. Xiong, X. Lin, F.S. Zhang, Optimization of wire feed for GTAW based additive manufacturing. J Mater Process Tech 243 (2017) 40–47. 35
[21] Y. Luo, J.L. Li, J. Xu, L. Zhu, J. T. Han, C.Y. Zhang, Influence of pulsed arc on the metal droplet deposited by projected transfer mode in wire-arc additive manufacturing. J Mater Process Tech 259 (2018) 353–360. [22] A.R.D. Tipi, S.K.H. Sani, N. Pariz, Improving the dynamic metal transfer model of gas metal arc welding (GMAW) process. Int J Adv Manuf Tech 76 (2015) 657-668.
36
Figure captions: Fig.1
Schematic diagram of the experiment system.
Fig.2
Generation and detection of structure-borne AE signals in wire-arc additive
manufacturing. Fig.3
Time-domain signals of AE and arc power in wire-arc additive manufacturing.
(a) Short-circuit transfer mode for non-pulsed arc (I=120A), (b) globular transfer mode for non-pulsed arc (I=160A), (c) spray transfer mode for non-pulsed arc (I=220A), (d) pulsed transfer mode for pulsed-arc (I=120A) and (e) pulsed transfer mode for pulsed-arc (I=160A). Fig.4
Correspondence between AE signals and arc power signals in time domain, (a)
Short-circuit transfer mode for non-pulsed arc, (b) spray transfer mode for non-pulsed arc and (c) pulsed transfer mode for pulsed-arc. Fig.5
Probability density distribution of arc power signals.
Fig.6
Power spectrum distribution of AE signals for (a) non-pulsed arc and (b)
pulsed arc. Fig.7
Energy gradient of non-pulsed arc in a single metal droplet transfer cycle, (a)
Energy gradient of arc power signals and (b) Energy gradient of AE signals. Fig.8
Energy gradient of pulsed arc in a single metal droplet transfer cycle, (a)
Energy gradient of arc power signals and (b) Energy gradient of AE signals. Fig.9
Comparison of energy gradient between non-pulsed arc (I=220A) and pulsed
arc (I=160A) in a single metal droplet transfer cycle, (a) Energy gradient of arc power signals and (b) Energy gradient of AE signals. 37
Fig.10
Total energy of (a) AE signals and (b) arc power signals.
Fig.11
Cross-section morphology of depositon layer manufacturred by non-pulsed
arc. Fig.12
Cross-section morphology of depositon layer manufacturred by pulsed arc.
Fig.13
Characterisitics of (a) height (h) and width (w) and (b) h/w of deposition
layer manufacturred by non-pulsed arc and pulsed arc.
38
Table captions: Table 1
Experimental parameters.
Current
Voltage
Frequency
Travel velocity
Shield gas flow rate
I/A
U/V
f /Hz
v/mm·s-1
Q/L·min-1
1
120
20.2
0
15
2
160
22.4
0
15
3
220
25.8
0
4
120
20.2
200
15
5
160
22.6
240
15
NO.
10
39
20
Graphical Abstract
40
Research Highlights > Signals tested in manufacturing were used to reflect the energy characteristics. > The energy output of non-pulsed arc and pulsed arc is different. > Pulsed arc matched with pulsed droplet transfer is more suitable for WAAM. > A higher h/w is obtained by pulsed arc in pulsed droplet transfer mode.
41
Table 1
Experimental parameters.
Current
Voltage
Frequency
Travel velocity
Shield gas flow rate
I/A
U/V
f /Hz
v/mm·s-1
Q/L·min-1
1
120
20.2
0
10
15
2
160
22.4
0
10
15
3
220
25.8
0
10
20
4
120
20.2
200
10
15
5
160
22.6
240
10
15
NO.
42
S0263-2241(18)30986-2 https://doi.org/10.1016/j.measurement.2018.10.048 MEASUR 5988
To appear in:
Measurement
Received Date: Revised Date: Accepted Date:
8 October 2017 1 July 2018 15 October 2018
Please cite this article as: Z. Liang, L. Yi, H. Jingtao, Z. Chengyang, X. Jie, C. Dong, Energy characteristics of droplet transfer in wire-arc additive manufacturing based on the analysis of arc signals, Measurement (2018), doi: https://doi.org/10.1016/j.measurement.2018.10.048
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Energy characteristics of droplet transfer in wire-arc additive manufacturing based on the analysis of arc signals Zhu Liang a, b, Luo Yi a, b, c, Han Jingtao a, b, Zhang Chengyang a, b, Xu Jie a, b, Chen Dong a, b
a
School of Material Science and Engineering, Chongqing University of Technology, Chongqing 400054, People’s Republic of China b Chongqing
Municipal Engineering Research Center of Institutions of Higher
Education for Special Welding Materials and Technology, Chongqing 400054, People’s Republic of China c State
Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi’an 710072, People’s Republic of China
Corresponding author: Dr. Luo Yi Mailing Address: School of Material Science and Engineering, Chongqing University of Technology, Chongqing 400054, China Telephones: +86-13883008891 (Mobile) Fax: +86-23-62563178 E-mail: [email protected]
Abstract: The non-pulsed arc and pulsed arc were used in wire-arc additive manufacturing (WAAM) of aluminum alloys. Arc signals about arc current and 1
voltage synchronized with the acoustic emission (AE) detected in manufacturing were used as information source to identify the droplet transfer mode. The calculations of probability density distribution, power spectrum distribution and energy gradient to synchronous time-domain signals were used to investigate the characteristics of metal droplet transfer and energy transfer. As a result, it was found that the characteristics of arc power signals and AE signals in WAAM process have a close relationship with the droplet transfer and arc ignition, and could reflect the variations of energy characteristics. The energy output characteristics of non-pulsed arc and pulsed arc during droplet transfer process are different. The matching of pulsed arc and pulsed droplet transfer mode obtains the best thermal and mechanical transfer characteristics, which is more suitable for the WAAM manufacturing process. No matter whether pulsed arc or non-pulsed arc is adopted, the energy output of arc should not be excessive, otherwise the energy output and the impact effect of arc and droplet transfer may be not conducive to the forming efficiency and quality of WAAM manufacturing.
Keywords: Pulsed arc, Additive manufacturing, Power, Acoustic emission, Deposition layer, Energy gradient
2
1 Introduction Additive manufacturing (AM) is a novel technique for building up complex metal components by the deposition of materials layer-by-layer. Many techniques have been developed for manufacturing metal components in AM. According to the different energy sources used in manufacturing, these techniques can be mainly classified into three groups: laser based [1], electron beam based [2] and arc based [3]. Currently, either a powder-feed process or a wire-feed process is used in popular AM technologies to supply the additive materials [4]. Compared with the powder-feed process, the wire-feed approach is a cleaner and more environmental friendly process. But laser and electron beam have poor energy efficiency (2-5% and 15-20% respectively) [5, 6], which will restrict the improvement of deposition rate in wirefeed AM process. The energy efficiency of arc based techniques such as the gas metal arc welding (GMAW) or gas tungsten arc welding (GTAW) processes can be as high as 90% in some circumstances [4]. Almost 100% of the wire material can be deposited into the component in the arc based techniques. So, the arc is more readily available than laser and electron beam having suitable properties for wire-feed AM process. Accordingly, wire and arc additive manufacturing (WAAM) technology is proposed due to its combined advantages of higher deposition rate, energy efficiency and material usage efficiency. WAAM process uses an electric arc, either the gas metal arc (GMA), the gas tungsten arc (GTA) or the plasma arc (PA), as a heat source and filler wire as feedstock [7]. The filler wire is melted continuously by electric arc to form metal 3
droplet, which is transferred into the molten pool to form deposition layer in WAAM process. The deposition process of droplet is related to the thermal-mechanical effect of arc and metal droplet. In addition to gravity, arc force plays a most important role in the deposition process of metal droplet. The arc force is composed of the electromagnetic force, the plasma flow force, the evaporation recoil force and the charged particle impact force. It is precisely because of the arc force, the metal droplet transfer process in WAAM is complex. But, due to its high deposition rate, environmental friendliness and cost-competitiveness, the WAAM process becomes more attractive and much research has been focused on WAAM. At present, most of the research on WAAM is focused on the microstructure and properties of the deposition layer. Lin et al. [8] studied the microstructural evolution and mechanical property of Ti-6Al-4V wall deposited by continuous plasma arc. Asala et al. [9] performed a detailed microstructural study of ATI 718Plus superalloy produced by the GTA based AM process. Chen et al. [10] fabricated the austenitic stainless steel 316L by GMA based AM process and investigated its microstructure and room temperature tensile properties. Wu et al. [11] studied the influence of low heat input pulse on the fine microstructure and unsupported overhangs in GTA based AM process. Haden et al. [12] systematically investigated the mechanical properties of wire-based deposition of steel metal by GMA based AM process. These results indicated that the deposited thin wall consisted of various morphologies, which depends on the heat input, multiple thermal cycles and gradual cooling rate in the deposition process. Therefore, it is a basic research work to study the mechanism of 4
heat transfer in the WAAM process. Although, it is insufficient to study the mechanism of WAAM process, especially the characteristics of energy transfer of arc and droplet, there is some similar research in GMAW or GTAW providing useful information for study of WAAM. Kamal et al. compared the acoustic signals of P-GMA welding at various process parameters. The acoustic signals were found to be strongly related to both metal droplet transfer and weld quality [13]. Saad et al. investigated the relationships between the acoustic signals and the modes of the molten pool in variable polarity plasma arc welding. The results showed that the keyhole mode can be distinguished from the cutting mode under the experiment conditions [14]. Kamal et al. used the acoustic sensor and other sensors to properly monitor the depth of weld penetration. Finally, the weld penetration monitoring was found to be better with the arc sound kurtosis [15]. Tam [16] revealed strong correlation between welding parameters and arc-acoustic spectral characteristics in GMAW, and the result showed that acoustic emission is a process parameter feedback to successfully achieve a closed-loop control of GMAW processes. Cayo et al. [17] made the comparative analysis in time domain and frequency domain to the acoustic signals generated by the electric arc to evaluates the stability in GMAW process. The result concluded that the acoustic evaluation of the stability on the GMAW process presents more clarity for the analysis based in the time domain that the frequency domain. Much research in GMAW provides useful information for the study of WAAM process because of the similar characteristics of the energy transfer of arc and droplet. 5
Xiong et al. [18] analyzed the arc force of a force model for a pending molten pool, and the influences of offset distance, wire feed rate, and travel speed on the inclination angle were revealed and discussed. Based on which, an process approach was proposed to fabricate 104-layered cylindrical thin-walled part. Yang et al. [19] used an infrared camera to capture the surface temperature of the deposited thin-wall parts for investigating the thermal behavior of WAAM. The temperature field cloud pictures indicated that as the deposition height increased, the heat accumulation of the deposited parts became serious. Using the alternate inter-layer cooling time can improve the forming quality of the thin-wall part distinctly. Geng et al. [20] studied the droplet transfer behavior in GTA based AM of aluminum alloy. From the view point of wire feed manner regulation, a mathematical model is developed to calculate the wire flying distance in arc zone. According to the above research results, the thermal and mechanical behavior of arc and droplet indicated that the characteristics of energy transfer were closely related to the quality of deposition layer. However, the research on the multiple effects of thermal and mechanical behavior in WAAM process is relatively few. In this paper, the arc signals of current, voltage and acoustic emission (AE) were tested in WAAM process and were used to analyze the behavior energy transfer. The periodic behavior of both arc ignition and droplet transfer is related to the energy transfer process. Based on these, the arc information and its energy characteristics in manufacturing were applied to investigate the energy transfer process of GMA based AM in this work, which is missing in the work done by Cayo et al.[17]. And the 6
influence of the energy transfer on the final forming quality of the deposition layer also has been studied. 2 Experiment details The WAAM automatic processing system used in experiment consists of three parts: the arc system, the motion control system and the arc signals acquisition system. Figure 1 shows the schematic of experiment system. The arc system is a GMAW power source. The filler wire is fed to the torch tip coaxially. The filler wire tip is melted to form metal droplets by the arc discharge caused between the wire tip and substrate. The arc torch was kept stationary in wire-arc additive manufacturing. The workpiece was moved by the motion control system, which was a programmable 3axis linear stage system. As the workpiece moves along the targeted path, accumulated metal droplets are solidified and deposited. The arc signals acquisition system includes arc current (I(t)), arc voltage (U(t)) and AE sensing system. The dynamic waveforms of arc signals in processing were recorded in real-time. Hall sensor was used to measure the arc current and voltage signals. According to these two signals, the instantaneous output (P(t)) of arc power was calculated by P(t) = U(t)×I(t)
(1)
Piezo-electric sensor was mounted on the surface of substrate to measure the AE signals. All of the signals detected by sensor were processed by preamplifier and signal conditioner, and then they were synchronized and transferred to computer by data acquisition unit. Aluminum alloy wire (ER-4043), which diameter was 1.2mm, was used as filler 7
wire in the experiments. The shielding gas was pure argon (Ar) and the gas flow rate was set from 15 L/min to 20 L/min. 6061 aluminum alloy with 150mm length, 100mm width and 8mm thickness was used as substrate in the experiment. In view of the arc stability in electrode positive (EP) region, the direct-current electrode positive (DCEP) was used to govern the metal droplet dynamics. The matching of experiment parameters of the non-pulsed arc and the pulsed arc was shown in Table 1.
Fig.1
Schematic diagram of the experiment system. Table 1
Experimental parameters.
Current
Voltage
Frequency
Travel velocity
Shield gas flow rate
I/A
U/V
f /Hz
v/mm·s-1
Q/L·min-1
1
120
20.2
0
10
15
2
160
22.4
0
10
15
3
220
25.8
0
10
20
NO.
8
4
120
20.2
200
10
15
5
160
22.6
240
10
15
Acoustic emission is a transient elastic wave produced by the rapid release of energy from a local source in a material. The deformation and crack propagation of materials under stress can produce acoustic emission, which is a kind of acoustic emission source in manufacturing. Another source of acoustic emission in manufacturing is the combustion of the arc and the impact of the metal droplet on the molten pool. Figure 2 illustrates the generation mechanism of the latter AE source in WAAM and shows the detection of the AE signals. Electric arc has high temperature and mechanical effect. On the one hand, arc melts filler wire to form metal droplets. On the other hand, arc melts the base plate to form molten pool. The arc force continues to act on the molten pool and produces AE energy to the interior and surrounding of the materials. Similarly, the metal droplet moves from the end of the filler wire to the molten pool and impacts the molten pool, which also produces acoustic emission energy to the interior and surrounding of the materials. The result of high speed photography in the previous study has proved that captured acoustic emissions correspond to arc and droplets transfer [21]. In this study, the AE energy is sensed in the form of structure-borne. The structure-borne AE sensor was mounted on the surface of base plate and the base plate itself was set as the transmission medium of AE. Thus, the AE energy delivered to the interior of the materials can be detected by the structure-borne AE sensor, while which is insensitive to the AE energy 9
delivered to the surrounding of the materials. Because the AE wave travels very fast in the solid aluminum materials (travel velocity 6260 m/s) and the length of the workpiece is only 150mm, although the position of the piezo-electric sensor varies with respect to the arc heat source in experiment, the time error due to position change is less than 0.02ms, which is negligible. Therefore, the mechanical impact of the arc and the metal droplet on the substrate can be detected and expressed by AE signals.
Fig.2
Generation and detection of structure-borne AE signals in wire-arc additive manufacturing.
3 Results and discussion 3.1 Characteristics of arc signals in time-domain The arc is used to melt the filler wire and form continuous droplets transferred into the molten pool in WAAM manufacturing process. The characteristics of arc signals in time-domain reflect the continuous evolution of the WAAM manufacturing process. In this paper, arc power signals are used to represent the evolution of arc energy output, and AE signals are used to represent the mechanical effects of arc or droplet on the molten pool. In the present studies, three droplet transfer modes are recognized 10
for non-pulsed arc, which are short-circuit transfer mode, globular transfer mode and spray transfer mode [22]. But pulsed transfer mode of droplet is recognized for pulsed arc. No matter what kind of droplet transfer mode, it is accompanied by the thermalmechanical coupling impact between arc energy output and arc force on the molten pool in WAAM process, which characteristics could be indicated by the arc signals detected in manufacturing. Arc power and AE signal all can be used to monitor the process. It can be seen from Figure 3 and Figure 4 that the process characteristics of arc power and AE signal are distinguishable in short-circuit transfer mode and globular transfer mode for non-pulsed arc and pulsed transfer mode for pulsed-arc. But the process characteristics of AE signal is more advantageous and distinguishable to clarify the droplet in spray transfer mode for non-pulsed arc. Figure 3 shows the synchronous time-domain signals of arc power and AE detected in wire-arc additive manufacturing. Figure 3a～3c show the signals of non-pulsed arc accompanied with short-circuit transfer mode, globular transfer mode and spray transfer mode respectively. Figure 3d and 3e show the signals of pulsed arc working in pulsed transfer mode. It can be found that the difference of arc signals is very significant in different droplet transfer modes. There is a strict correspondence between AE signals and arc power signals in time domain, which indicates some phenomenons of thermal-mechanical effect generated from the behavior of arc and metal droplet. The correspondence between AE signals and arc power signals in time domain is showed in Figure 4.
11
(a)
(b)
(c) 12
(d)
(e) Fig.3
Time-domain signals of AE and arc power in wire-arc additive manufacturing.
(a) Short-circuit transfer mode for non-pulsed arc (I=120A), (b) globular transfer mode for non-pulsed arc (I=160A), (c) spray transfer mode for non-pulsed arc (I=220A), (d) pulsed transfer mode for pulsed-arc (I=120A) and (e) pulsed transfer mode for pulsed-arc (I=160A).
The synchronization waveforms of AE signals and arc power signals from 0.04s to 13
0.10s in Figure 3a were amplified in Figure 4a. When the droplet contacts the molten pool to produce short-circuit, the arc is extinguished temporarily and the output power is minimized. After the droplet transfers into the molten pool, the arc is reignited and the arc power output is resumed. Therefore, the process of droplet short-circuit transfer can be defined by arc power signals as shown in Figure 4a. Because the shortcircuit contact of droplet and the arc ignition produce the effect of the force affecting on the molten pool and stimulate the AE energy, the short-circuit AE event and arc ignition AE event could be distinguished from the AE signals according to the characteristics of arc power signals in time-domain. The synchronization waveforms of AE signals and arc power signals from 0.005s to 0.015s in Figure 3c were amplified in Figure 4b. The combustion of the arc in the non-pulsed arc mode is continuous during the spray transfer process of the metal droplet. So there is no arc reignition phenomenon and arc ignition AE event. However, each droplet transferred into the molten pool will stimulate AE energy. In view of the signal-to-noise ratio of the AE signals, the wavelet analysis was used to extract the droplet AE event. So the droplet AE event can be identified from the AE signals in Figure 4b. The waveform of arc power signals is smooth and it is difficult to identify the characteristic information of droplet transfer. The synchronization waveforms of AE signals and arc power signals from 0.008s to 0.017s in Figure 3e were amplified in Figure 4c. It can be seen that the arc ignition and droplet transfer are all controlled by arc pulse for pulsed arc . Because the arc ignition and the droplet transition will stimulate the AE energy and produce AE 14
events, the acoustic emission signals can be used to identify the arc ignition and droplet transfer in pulsed arc mode. According to the AE signals and the arc power signals, it can be seen that the arc is ignited at the rising edge of the pulse, and the droplet is transferred into the molten pool at the falling edge of the pulse. From the above analysis we can see that the characteristics of arc power signals and AE signals in WAAM process have a close relationship with the droplet transfer and arc ignition, and could reflect the variations of the manufacturing process. The following contents will analyze the energy characteristics and thermal-mechanical transfer in different droplet transfer modes on the basis of arc power signals and acoustic emission signals detected in WAAM process.
(a)
15
(b)
(c) Fig.4
Correspondence between AE signals and arc power signals in time domain, (a)
Short-circuit transfer mode for non-pulsed arc, (b) spray transfer mode for non-pulsed arc and (c) pulsed transfer mode for pulsed-arc. 16
3.2 Energy characteristics and thermal-mechanical transfer Arc power reflects the energy output of the arc, and arc power signal is the realtime response of arc power output. Figure 5 shows the probability density distributions of arc power signals under different droplet transfer modes, namely, the arc power output characteristics under different droplet transfer modes. When the arc current is 120A, the arc power output is mainly distributed in two regions for the short-circuit transfer mode generated by non-pulsed arc. One is the low arc power region distributed from about 100W to 300W, which corresponds to the arc power output when the droplet is short-circuited, and the other is the high arc power region distributed from about 1000W to 3000W, which corresponds to the arc power output when the arc is burning. When the arc current is 160A, the arc power output is mainly distributed from about 2000W to 4000W for the globular transfer mode generated by non-pulsed arc. When the arc current is 220A, the arc power output is mainly distributed around 4300W for the spray transfer mode generated by non-pulsed arc. Clearly, the output energy of the arc is the highest under the spray transfer mode for non-pulsed arc. When the arc current is 120A or 160A, the pulsed arc power output is also mainly distributed in two regions for the pulsed transfer mode generated by pulsed arc. The arc power output is pulsing under the pulsed arc. The low arc power output region corresponds to the low level of the pulse energy output, and the high arc power output region corresponds to the high level of the pulse energy output. The arc ignition and 17
droplet transfer all occur at the high arc power output region of arc pulse according to the illustration of Figure 4c. In general, the average output power of non-pulsed arc in short-circuit transfer mode and pulsed arc is lower, while the average output power of non-pulsed arc in globular transfer mode and spray transfer mode is higher. These energy output characteristics determine the droplet deposition rate and the manufacturing efficiency of the WAAM process. It is generally known that higher arc energy output is beneficial to get high deposition rate. But, high arc energy output is more likely to cause some defects in manufacturing, such as heat distortion and excessive melting, which must be taken into consideration. Arc energy output is distributed in high and low level regions respectively because of the fluctuation characteristic of pulse, which effectively reduces the average arc energy output and ensures the energy required by the fusion of filler wire. Thus, pulsed arc seems to be a better choice, which would be proved in the later sections.
18
Fig.5
Probability density distribution of arc power signals.
Certainly, the mechanical effects of arc and droplet transfer are also related to the energy output of arc. The mechanical effects were analyzed by the AE energy released by the arc and droplets impinging on the molten pool. The power distribution in frequency domain of AE signals is described by power spectrum analysis. Figure 6 shows the power spectrum distribution of AE signals detected in different droplet transfer modes. From the view of frequency distribution, the frequencies of AE signals are below 20kHz and the positions of spectrum peaks are similar in addition to the globular transfer mode of non-pulsed arc (I=160A). In particular, the main spectrum peak (9.90kHz) of spray transfer mode in non-pulsed arc (I=220A) is very close to that (9.81kHz) of pulse transfer mode in pulsed arc (I=160A), which indicates that the droplet transfer processes in the two conditions have some similar characteristics. From the view of amplitude distribution, the AE signals of spray 19
transfer mode in non-pulsed arc have the lowest amplitude of main spectrum peaks, which indicates the mechanical effects of arc and droplet transfer in this condition are weakest. Instead, the AE signals of pulse transfer mode in pulsed arc (I=160A) have the highest amplitude of main spectrum peaks, which indicates that the mechanical effects of arc and droplet transfer in this condition are strongest. The main spectrum peak (8.92kHz) and its amplitude of short-circuit transfer mode in non-pulsed arc (I=120A) is closer to the main spectrum peak (9.04kHz) and its amplitude of pulse transfer mode in pulsed arc (I=120A), which indicates that the droplet transfer processes in the two conditions have some similar characteristics. In the following sections, the energy characteristics of droplet transfer and arc are further analyzed by means of energy gradient to find out the influence on the quality of the deposition layer.
20
(a)
21
(b) Fig.6
Power spectrum distribution of AE signals for (a) non-pulsed arc and (b) pulsed arc.
In engineering signal analysis, mean square is used to represent the average power of signal. Because the mean squares of arc power signals and AE signals are proportional to the energy of arc signals and AE signals, the mean square was used to characterize the energy. The energy gradient was used to describe the transient variation of impact energy coming from arc and metal droplet transferred into molten 22
pool in this study. We used Ge(t) as the symbol for energy gradient, which was defined as ∫𝑡2𝑃2(𝑡)𝑑𝑡
𝐺𝑒(𝑡) =
𝑡1
(2)
𝑡2 - 𝑡1
or ∫𝑡2𝑈𝐴2(𝑡)𝑑𝑡
𝐺𝑒(𝑡) =
𝑡1
(3).
𝑡2 - 𝑡1
Where, P(t) is the values of arc power signal varied with time, and UA(t) is the AE signal voltage varied with time. The total energy of signals from t1 to t2 was defined as 𝑡
(4).
𝐸 = ∫𝑡2𝐺𝑒(𝑡)𝑑𝑡 1
As mentioned in the second section in this paper, the mechanical impact of the arc and the metal droplet on the substrate can be detected and expressed by AE signals. Therefore, the energy gradient of AE signals was used to describe the transient variation of mechanical impact energy from the arc and droplet, and the total energy of AE signals was used to describe the total mechanical impact energy. Similarly, the energy gradient of arc power signals was used to describe the transient variation of arc output energy, and the total energy of arc power signals was used to describe the total arc output energy. The signals of a single metal droplet transfer cycle in Figure 3 were extracted to calculate the energy gradient in the metal droplet transfer process. Figure 7 showed the energy gradient curves of arc power signals and AE signals detected in non-pulsed arc. It can be seen that the transient variation of arc power output by 160A arc current is larger than that by 120A arc current. But the transient 23
variation of mechanical impact energy produced by 160A arc current is smaller than that by 120A arc current. As mentioned earlier, the droplet transfer of non-pulsed arc is short-circuit transfer mode as the arc current is 120A and is globular transfer mode as the arc current is 160A. Therefore, the short-circuit transfer mode is characterized with larger transient variation of mechanical impact energy and the globular transfer mode is characterized with larger transient variation of arc power output in a single metal droplet transfer cycle. Figure 8 showed the energy gradient curves of arc power signals and AE signals detected in pulsed arc. It can be seen that larger arc current (I=160A) improves not only the transient variation of mechanical impact energy but also the transient variation of arc power output. Thus, the energy transfer characteristics of non-pulsed arc and pulsed arc during droplet transfer are different. In order to compare the energy transfer characteristics between the non-pulsed arc and the pulsed arc, the arc power signals and the AE signals with the same droplet transfer frequency are extracted. Figure 9 showed the energy gradient curves of arc power signals and AE signals detected in non-pulsed arc (I=220A) and pulsed arc (I=160A). It can be seen that, as the droplet transfer frequency is similar, the non-pulsed arc has a greater transient variation of arc power output, while the pulsed arc has a greater transient variation of mechanical impact energy. We believe that proper transient variation of arc power output and mechanical impact energy is important to form the deposition layer with high quality.
24
(a)
(b) Fig.7
Energy gradient of non-pulsed arc in a single metal droplet transfer cycle, (a)
Energy gradient of arc power signals and (b) Energy gradient of AE signals.
25
(a)
(b) Fig.8
Energy gradient of pulsed arc in a single metal droplet transfer cycle, (a)
Energy gradient of arc power signals and (b) Energy gradient of AE signals.
26
(a)
(b) Fig.9
Comparison of energy gradient between non-pulsed arc (I=220A) and pulsed
arc (I=160A) in a single metal droplet transfer cycle, (a) Energy gradient of arc power signals and (b) Energy gradient of AE signals.
The signals within 0.025s were extracted from Figure 3 to calculate the total energy of signals according to formula (4), which indicated the total energy output as several metal droplets transferred into molten pool in a fraction of a second. Figure 10 27
showed the total energy of AE signals (Figure 10a) and arc power signals (Figure 10b) detected in non-pulsed arc and pulsed arc. It can be seen that, under the same arc current and arc power conditions, the pulsed droplet transfer mode produces lower total energy of AE signals relative to the short-circuit transfer mode and the globular transfer mode. According to the AE signals in Figure 3 and Figure 4, the energy of AE signals is mainly produced by the impact of arc ignition and droplet transfer on the molten pool. A lower total energy of AE signals indicates that the impact effect produced by the arc ignition and droplet transfer is lower. The high impact effect could easily lead to the collapse of the deposition layer, which is unfavorable to the forming quality, while the low impact effect is not conducive to the spreading of the droplets in the molten pool. Another factor determining the quality of the deposition layer is the arc power output, and Figure 10b shows the total energy output of the arc within 0.025s. It can be seen that, under the same arc current and arc power, the arc energy output produced in the pulsed droplet transfer mode is between the short-circuit transfer mode and the globular transfer mode. Excessively low arc energy output is not conducive to the melting of droplets and the formation of an effective droplet transfer, while excessive arc energy output is likely to cause excessive melting of droplets and molten pool, which is one of the reasons to cause the collapse of deposition layer and is not conducive to the forming quality. Therefore, the matching of pulsed arc and pulsed droplet transfer mode is 28
most suitable for WAAM manufacturing. 3.3 Morphology of the deposition layer Figures 11 and 12 show the cross-section morphology of the deposition layer manufactured by the non-pulsed arc and pulsed arc. According to the cross-section morphology of the deposition layer, the characteristics of deposition height (h) and width (w) are measured and shown in Figure 13. As mentioned above, the matching of pulsed arc and pulsed droplet transfer mode obtains the best thermal and mechanical transfer characteristics in WAAM manufacturing, which relates to the beads in Figure 12. As the arc current is 220A, the arc energy output is excessive and the melting of droplet and molten pool is enhanced. Although the maximum height of the deposition layer has been obtained as shown in Figure 13a (open square and triangle curves), the width of the deposition layer is larger, and the deposition layer is collapsing. In addition, pulsed arc obtains larger height and smaller width of deposition layer as shown in Figure 13a (open circles and star designated curves). Accordingly, the ratio of the height and width of the deposition layer is introduced to describe the forming characteristics of the deposition layer. It can be found from Figure 13b that a higher ratio of h/w is obtained by pulsed arc in these process parameters matchings. With the increase of arc current and arc power, the ratio of height to width decreases as shown in Figure 13b, which indicates that, even using the pulsed arc, the arc power output should not be excessive, otherwise the arc energy output and the impact effect also may be not conducive to the forming efficiency and quality of WAAM manufacturing. So, Figure 12a is chosen as the optimal bead. 29
(a)
(b) Fig.10
Total energy of (a) AE signals and (b) arc power signals.
(a) I=120A Fig.11
(b) I=160A
(c) I=220A
Cross-section morphology of deposition layer manufactured by non-pulsed 30
arc.
(a) I=120A Fig.12
(b) I=160A
Cross-section morphology of deposition layer manufactured by pulsed arc.
(a)
(b) 31
Fig.13
Characteristics of (a) height (h) and width (w) and (b) h/w of deposition layer manufactured by non-pulsed arc and pulsed arc.
4 Conclusions (1) The characteristics of arc power signals and AE signals in WAAM process have a close relationship with the droplet transfer and arc ignition, and can reflect the variations of energy characteristics in WAAM manufacturing process. (2) The energy output characteristics of non-pulsed arc and pulsed arc during droplet transfer process are different. The output power in short-circuit transfer mode and pulsed droplet transfer mode is lower, while in globular transfer mode and spray transfer mode is higher. The mechanical effects of arc and droplet transfer in pulsed droplet transfer mode of pulsed arc are strongest, while in spray transfer mode of nonpulsed arc are weakest. (3) The matching of pulsed arc and pulsed droplet transfer mode obtains the best thermal and mechanical transfer characteristics, which is more suitable for the WAAM manufacturing process. Accordingly, a higher ratio of h/w is obtained by pulsed arc in pulsed droplet transfer mode and the forming efficiency and quality of deposition layer are improved. (4) No matter whether pulsed arc or non-pulsed arc is adopted, the energy output of arc should not be excessive, otherwise the energy output and the impact effect of arc and droplet transfer may be not conducive to the forming efficiency and quality of WAAM manufacturing. In the future work, the microstructure of tacked structure 32
affected by low energy pulsed arc or non-pulsed arc in WAAM should be clarified.
Acknowledgements This work was supported by Basic Science and Frontier Technology Research Project of Chongqing Science and Technology Commission of China (Grant No. cstc2017jcyjBX0065 and No. cstc2015jcyjA60009), Scientific and Technological Research Program of Chongqing Municipal Education Commission of China (Grant No. KJ1709197) and the Fund of the State Key Laboratory of Solidification Processing in NWPU (Grant No. SKLSP201717).
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(2017) 115–123. [13] P. Kamal, B. Sandip, K. Pal Surjya, Investigation on arc sound and metal transfer modes for on-line monitoring in pulsed gas metal arc welding. J Mater Process Technol 210 (2010) 1397–1410. [14] E. Saad, H.J. Wang, R. Kovacevic, Classification of molten pool modes in variable polarity plasma arc welding based on acoustic signature. J Mater Process Technol 174 (2006) 127–36. [15] P. Kamal, K. Pal Surjya, Monitoring of Weld Penetration Using Arc Acoustics. Mater Manuf Process 26 (2011) 684–93. [16] J. Tam, Methods of Characterizing Gas-Metal Arc Welding Acoustics for Process Automation. Master's degree thesis: University of Waterloo, Canada, 2005. [17] E. Huanca Cayo, S.C. Absi Alfaro, GMAW Process Stability Evaluation Through Acoustic Emission by Time and Frequency Domain Analysis. Journal of Achievements in Materials and Manufacturing Engineering 34 (2009) 157-164. [18] J. Xiong, Y.Y. Lei, H. Chen, G.J. Zhang, Fabrication of inclined thin-walled parts in multi-layer single-pass GMAW-based additive manufacturing with flat position deposition. J Mater Process Tech 240 (2017) 397–403. [19] D.Q. Yang, G. Wang, G.J. Zhang, Thermal analysis for single-pass multi-layer GMAW based additive manufacturing using infrared thermography. J Mater Process Tech 244 (2017) 215–224. [20] H.B. Geng, J.L. Li, J.T. Xiong, X. Lin, F.S. Zhang, Optimization of wire feed for GTAW based additive manufacturing. J Mater Process Tech 243 (2017) 40–47. 35
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36
Figure captions: Fig.1
Schematic diagram of the experiment system.
Fig.2
Generation and detection of structure-borne AE signals in wire-arc additive
manufacturing. Fig.3
Time-domain signals of AE and arc power in wire-arc additive manufacturing.
(a) Short-circuit transfer mode for non-pulsed arc (I=120A), (b) globular transfer mode for non-pulsed arc (I=160A), (c) spray transfer mode for non-pulsed arc (I=220A), (d) pulsed transfer mode for pulsed-arc (I=120A) and (e) pulsed transfer mode for pulsed-arc (I=160A). Fig.4
Correspondence between AE signals and arc power signals in time domain, (a)
Short-circuit transfer mode for non-pulsed arc, (b) spray transfer mode for non-pulsed arc and (c) pulsed transfer mode for pulsed-arc. Fig.5
Probability density distribution of arc power signals.
Fig.6
Power spectrum distribution of AE signals for (a) non-pulsed arc and (b)
pulsed arc. Fig.7
Energy gradient of non-pulsed arc in a single metal droplet transfer cycle, (a)
Energy gradient of arc power signals and (b) Energy gradient of AE signals. Fig.8
Energy gradient of pulsed arc in a single metal droplet transfer cycle, (a)
Energy gradient of arc power signals and (b) Energy gradient of AE signals. Fig.9
Comparison of energy gradient between non-pulsed arc (I=220A) and pulsed
arc (I=160A) in a single metal droplet transfer cycle, (a) Energy gradient of arc power signals and (b) Energy gradient of AE signals. 37
Fig.10
Total energy of (a) AE signals and (b) arc power signals.
Fig.11
Cross-section morphology of depositon layer manufacturred by non-pulsed
arc. Fig.12
Cross-section morphology of depositon layer manufacturred by pulsed arc.
Fig.13
Characterisitics of (a) height (h) and width (w) and (b) h/w of deposition
layer manufacturred by non-pulsed arc and pulsed arc.
38
Table captions: Table 1
Experimental parameters.
Current
Voltage
Frequency
Travel velocity
Shield gas flow rate
I/A
U/V
f /Hz
v/mm·s-1
Q/L·min-1
1
120
20.2
0
15
2
160
22.4
0
15
3
220
25.8
0
4
120
20.2
200
15
5
160
22.6
240
15
NO.
10
39
20
Graphical Abstract
40
Research Highlights > Signals tested in manufacturing were used to reflect the energy characteristics. > The energy output of non-pulsed arc and pulsed arc is different. > Pulsed arc matched with pulsed droplet transfer is more suitable for WAAM. > A higher h/w is obtained by pulsed arc in pulsed droplet transfer mode.
41
Table 1
Experimental parameters.
Current
Voltage
Frequency
Travel velocity
Shield gas flow rate
I/A
U/V
f /Hz
v/mm·s-1
Q/L·min-1
1
120
20.2
0
10
15
2
160
22.4
0
10
15
3
220
25.8
0
10
20
4
120
20.2
200
10
15
5
160
22.6
240
10
15
NO.
42