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bainite mixed microstructures based on magnetic Barkhausen noise detection
Journal Pre-proofs Nondestructive evaluation of hot stamping boron steel with martensite/bainite mixed microstructures based on magnetic Barkhausen noise detection Bin Zhu, Ziqian Xu, Kai Wang, Yisheng Zhang PII: DOI: Reference:
S0304-8853(19)33272-X https://doi.org/10.1016/j.jmmm.2020.166598 MAGMA 166598
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Journal of Magnetism and Magnetic Materials
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16 September 2019 4 January 2020 8 February 2020
Please cite this article as: B. Zhu, Z. Xu, K. Wang, Y. Zhang, Nondestructive evaluation of hot stamping boron steel with martensite/bainite mixed microstructures based on magnetic Barkhausen noise detection, Journal of Magnetism and Magnetic Materials (2020), doi: https://doi.org/10.1016/j.jmmm.2020.166598
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Nondestructive evaluation of hot stamping boron steel with martensite/bainite mixed microstructures based on magnetic Barkhausen noise detection Bin Zhu, Ziqian Xu, Kai Wang*, Yisheng Zhang State Key Laboratory of Materials Processing and Die & Mould Technology, Huazhong University of Science and Technology, Wuhan 430074, China *Corresponding
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[email protected] Abstract: A nondestructive testing method based on magnetic Barkhausen noise (MBN) detection is developed to evaluate the microstructural and mechanical properties of hot stamping boron steel with martensite/bainite mixed microstructures. Firstly, boron steel specimens are heat treated by Gleeble thermo-mechanical simulator to prepare mixed microstructures with different bainite fractions. Based on the analysis of MBN signals of these specimens, the relation between MBN characteristics and bainite fraction is investigated. The results indicate that the MBN intensity firstly decreases and then increases with the increasing bainite fraction. The MBN peak shows a positive linear correlation with bainite fraction above 30%. The bainite fraction could be simply evaluated when MBN peak is above 65 mV. Furthermore, according to the assessed bainite fraction by MBN detection, the ultimate tensile strength (UTS) and yield tensile strength (YTS) of hot stamping steel sheets treated by heated tools are calculated and compared with tensile tests. It is suggested that it could be feasible to evaluate the mechanical properties especially UTS of hot stamping parts with martensite/bainite mixed microstructures based on MBN detection. Keywords: Nondestructive detection; Magnetic Barkhausen noise; Hot stamping; Mixed microstructure
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1. Introduction Hot stamping parts have been widely used in car bodies due to the increasing demand for high passive safety, energy saving and emission reduction in automobile industry. The conventional hot stamping parts quenched by cold tools have a tensile strength up to 1500 MPa, which could dramatically improve the anti-intrusive capacity [1]. However, for certain components such as B-pillar, the combination of both high anti-intrusive performance and good impact-absorptive performance in a single part is beneficial to enhance the overall crashworthiness. Therefore, the hot stamping parts with tailored properties are proposed [2]. One of the strategies to achieve tailored properties is to adjust the cooling rate of the ductile region by using heated tools [3]. As shown in Fig. 1, the upper region is quenched by cold tools to obtain full martensite microstructure with ultimate high strength. The lower region is held in heated tools to achieve high ductility owing to the formation of softer phases such as ferrite or bainite. Srithananan et al. [4] conducted a two-step quenching procedure to investigate the influence of holding time on the phase fraction and mechanical properties of boron steel. The results shows that longer holding time leads to increased bainite fraction, resulting in decreased yield and tensile strength and higher elongation. Zhang et al. [5] analyzed the effect of tool temperature on the microstructure of the softer region of a U-type part with tailored properties. At a holding time of 10 s in the heated tools, the microstructure mainly consists of martensite, bainite and ferrite, while the total fraction of martensite and bainite is approximately 90%. These research works suggest that the bainite fraction has a significant influence on the final mechanical properties. For the detection of components with tailored properties, the conventional traditional methods including metallographic observation, tensile test and hardness test are usually employed, which could provide detailed characterization of the microstructures and mechanical properties. However, these methods are destructive to the detected parts and time consuming. Therefore, it is necessary to establish a non-destructive and convenient detection method to provide real-time information 2
of microstructure compositions (martensite and bainite) and mechanical properties, which is quite practical for the quality control of hot stamping parts with tailored properties in production line.
Fig. 1. Schematic diagram of the process to achieve tailored properties by adjusting the cooling rate in different regions of the hot stamping part. Magnetic Barkhausen Noise (MBN) detection is a non-destructive technique which could characterize the microstructural and mechanical properties of ferromagnetic materials subjected to different treatment conditions [6-10]. The MBN effect is a complex phenomenon of abrupt changes during the magnetization of ferromagnetic materials [11, 12]. There are many tiny magnetic regions named domains in the ferromagnetic materials and these domains are separated from each other by domain walls [13]. When the ferromagnetic material is subjected to an external alternating magnetic field, the domain walls inside the material will reciprocate. MBN is produced when domain walls encounter pinning or defects inside the material during reciprocating movement [14], which could be acquired by magnetic sensor. Due to these principles, the MBN detection method does not require extensive sample preparation and could be used to detect samples in various size and shapes. It has been widely reported that the MBN method is used in microstructural and mechanical characterization of steels. Saquet et al. [15] compared the MBN signals of four 3
different microstructures (pearlite, ferrite/cementite, ferrite, and martensite) in carbon steel. The results suggest that the MBN signal of ferrite/cementite is most intensive, subsequently followed by the signals of pearlite, ferrite and martensite. Koo et al. [16] reported that the MBN signal increased monotonously with increasing pearlite fraction for plain carbon steel in both hypoeutectoid and hypereutectoid state. Kaplan et al. [13] investigated the influence of martensite fraction on MBN signal in martensite-ferrite dual-phase steel. The results show that the RMS voltage of the MBN signal decreases with the increasing martensite fraction. Luo et al. [17] performed frequency domain analysis and signal reconstruction of MBN of hot stamping steel sheet with different hardness. The power spectrum density analysis shows that the low frequency peaks of MBN signal increases as hardness decreases. However, little research work has been reported concerning the MBN-based nondestructive detection of the hot stamping steel with martensite/bainite mixed microstructures. The aim of this work is to investigate the relationship between MBN signal and martensite/bainite mixed microstructures as well as the corresponding mechanical properties of hot stamping boron steel.
2. Experimental procedure 2.1 Heat treatment procedure and hot stamping tests The material used is uncoated hot stamping boron steel which belongs to 22MnB5 grade. The thickness of the steel sheet is 1.2 mm and the initial microstructure in as received condition is composed of pearlite and ferrite. Table 1 shows the chemical compositions of the material. Table 1. Chemical compositions of 22MnB5 boron steel (wt. %). C 0.23
Mn 0.95
P 0.01
S 0.002
Si 0.17
Mo 0.21
Cr 0.24
Al 0.03
Ti 0.023
B 0.002
To prepare microstructures with different martensite/bainite fractions, heat treatments of boron steel are conducted by Gleeble thermo-mechanical simulator which has been widely 4
adopted in physical simulation of materials behaviour under transient thermal conditions such as welding, continuous casting and hot forming [18]. The standard hot tensile specimen reported by Zhu et al. [19] is used for heat treatment. The uniform temperature region of the specimen is about 11 mm. Fig. 2 illustrates the heat treatment procedure of the first type specimens. Each specimen is heated to 930 °C at a heating rate of 8 °C/s and kept for 3 min for complete austenization. It has been reported that the temperature range of bainite transformation is between 400 °C and 600 °C for boron steel [4, 20]. Therefore, the specimens are then air cooled to 500 °C in 18 s and held for different times, so that the extent of bainite transformation could be adjusted. The holding times are respectively set as 0 s, 14 s, 21 s, 28 s, 35 s, 42 s, 54 s, 72 s, 102 s and 222 s. Finally, the specimens are cooled to room temperature by water to ensure that the remaining austenite transforms into martensite.
Fig. 2. Heat treatment procedure to prepare microstructures with different bainite fractions. Hot stamping tests of boron steel are carried out using flat tools as shown in Fig. 3. Rectangular sheet specimens with a size of 300 mm × 210 mm are heated at 930 °C for 5 min in a resistance furnace for complete austenization. Then the specimens are transferred to a servo press and held in the heated tools with a temperature of 400 °C. Four holding times of 30, 60, 90 and 120 s are respectively adopted to obtain hot stamping specimens with different microstructures. After holding, each specimen is taken out from the tools and air cooled to room temperature. In addition, a sheet specimen quenched to room temperature by cold tools is also prepared to test the mechanical property of full martensite microstructure.
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Fig. 3. Hot stamping tests of boron steel sheet using heated flat tools. 2.2 Detection and processing of MBN signal MBN detections are carried out using the self-developed detection system as shown in Fig. 4. The detection system consists of seven modules, including a wave generator which produces a 10 Hz sinusoidal signal with an amplitude of ±180 mV, a power amplifier to amplify the sinusoidal signal, two excitation coils (0.3 mm, 800 turns) wound around the U-shaped electromagnet composed of soft magnetic Fe-Si sheets to generate an excitation magnetic field, an search coil (0.1 mm, 2000 turns) wound around a ferrite core to pick up MBN signal, an operational amplifier to amplify the MBN signal, a DAQ card to convert the MBN signal to digital data, and a PC to record as well as process the MBN signal. It should be noted that the length of the magnetized region between two excitation coils is approximately 9 mm, which is shorter than the uniform temperature region with homogeneous microstructure in the Gleeble specimen. The total time of signal acquisition for each specimen is set as 10 s. There are two periods of MBN signal generated in each excitation signal period. As a result, the collected MBN signal has 200 periods.
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Fig. 4. Schematic illustration of the MBN detection system. To eliminate the excitation signal and reduce noise interference, the collected signal is filtered using a 2-20 kHz bandpass filter and the obtained signal is shown in Fig. 5. To extract the characteristic value of the MBN, the signal is then subjected to processing of overlaying and averaging. Wavelet denoising is also used to smooth the signal and the final MBN profile is marked with red line in Fig. 5. The MBN signal curve exhibits a maximum peak in one period. After subtracting the thermal noise resulting from random fluctuation of charge carriers [21], the value of MBN peak is obtained. In addition, the RMS of MBN signal in one period within the range of ±0.0125 s from the peak position is also calculated.
Fig. 5. The MBN signal processed by 2-20 kHz bandpass filter and final MBN profile.
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2.3 Microstructure detection and quantification Metallographic samples are cut from the Gleeble specimens and hot stamping specimens for microstructure characterization. The samples are prepared via typical procedures including grinding, polishing and etching. To clearly reveal details of the microstructures, the 3.0 vol.% nitric acid solution is used to etch the samples. A scanning electron microscopy (SEM, TM3030PLUS) is used to observe the microstructure of each sample. To distinguish and quantify different phases in the microstructure, the SEM micrographs of the specimens under different heat treatment conditions are processed using image processing code.
3. Results and discussion 3.1 The influence of holding time on bainite fraction The SEM microstructure morphologies of the Gleeble specimens under different holding times at 500 °C and the corresponding images after processing are illustrated in Fig. 6. The specimen directly cooled to room temperature without holding has a full martensite microstructure as shown in Fig. 6(a). As for the specimen held for 222 s shown in Fig. 6(b), the microstructure is approximately composed of full bainite phase. When the holding time is between 0 s and 222 s [Figs. 6(c-j)], the specimens show mixed microstructures which are mainly composed of martensite and bainite. The bainite fractions of the specimens under different holding times are plotted in Fig. 7. It could be found that the bainite fraction increases with prolonged holding time. With a holding time ranging from 0 s to 42 s, the bainite fraction increases dramatically from 0 to 69.1 %. As the holding time prolongs from 42 s to 102 s, the bainite fraction just increases gradually to 94.8%. During subsequent holding procedure to 222 s, the increment of bainite fraction in 120 s is only 5.2%. Furthermore, the bainite transformation of boron steel during holding followed the Johnson-Mehl-Avrami-Kolmogorov (JMAK) theory which is generally used for description of the fraction of material transformed at a given time in terms of the nucleation and growth 8
rates of processes [22]. For an isothermal transformation process such as the bainite transformation in this study, the JMAK model could be described by Eq. (1) [23].
fb 1 exp(kt n )
(1)
Where fb is the bainite fraction, t is the holding time, k and n are parameters which could be obtained by fitting the measured bainite fractions at different holding times. As shown in Fig. 7, the fitted value of k and n are respectively 0.0063 and 1.365. The differences between the measured and predicted bainite fractions are relatively small.
Fig. 6. SEM microstructure morphologies of the Gleeble specimens under different holding times at 500 °C and the corresponding processed images (bainite region marked in red): (a): 0 s; (b): 222 s; (c): 14 s; (d): 21 s; (e): 28 s; (f): 35 s; (g): 42 s; (h): 54 s; (i): 72 s; (j): 102 s. 9
Fig. 7. The variation of bainite fraction with increasing holding time. 3.2 The characteristics of MBN signal under different bainite fractions The variations of peak value and RMS value of MBN signal with bainite fraction are illustrated in Fig. 8. In general, both of the MBN peak and RMS firstly decrease and then increase with bainite fraction increasing. When the bainite fraction is 30%, the MBN peak and the RMS have a minimum value of 57 mV and 39 mV respectively. Besides, the peak value and RMS value of MBN signal are approximately linearly proportional to the bainite fraction in the range from 30% to 100%. The enhancement of MBN signal with bainite fraction is mainly attributed to the fact that the resistance to domain walls in bainite is relatively lower than the resistance in martensite with small lath structure and high dislocation density [13]. Under external magnetic field, there are more unpinning events occurring in bainite due to greater domain wall displacements, which leads to stronger MBN signal with increasing bainite fraction above 30%. As for the increasing MBN signal with bainite fraction decreasing from 30% to 0, it is deduced to be the effect of residual internal stress caused by dominated martensite fraction [24]. The increasing martensite fraction generates more residual internal stress which is believed to strengthen the MBN [25-27]. As a result of these two aspects, the intensity of MBN signal decreases first and then increases with increasing bainite fraction.
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Fig. 8. The variations of (a) MBN peak and (b) MBN RMS with increasing bainite fraction. Based on linear fitting, the relation of MBN peak and RMS with the bainite fraction could be described by:
MBN p 0.258 fb 48.6
(2)
MBN R 0.172 fb 34.0
(3)
Where MBN p and MBN R are respectively the peak value of RMS value of MBN signal. According to the linear fitting results, it could be found that the fitting line of MBN peak has larger slope as well as R square compared with the RMS fitting line. This indicates that the MBN peak is more sensitive to the variation of bainite fraction. Besides, the error bar of the measured MBN peak is generally smaller than that of the RMS, which suggests smaller deviations between repeated detections. Therefore, the MBN peak is more suitable to be considered as a characteristic parameter of MBN signal for microstructures with different bainite fractions. However, it could be found from Fig. 8(a) that the MBN peak of full martensite microstructure equals to the peak value of the mixed microstructure with 61.0% bainite fraction, and the corresponding MBN peak is 64.4 mV. This indicates that unambiguous assessment of bainite fraction could not be achieved simply by MBN peak if the peak value is less than 65 mV. As a contrast, for the mixed microstructure with a MBN peak higher than 65 mV, the corresponding bainite fraction could be calculated according to Eq. (2).
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3.3 Feasibility evaluation of MBN detection of hot stamping parts Fig. 9 illustrates the SEM microstructure morphologies of the hot stamping specimens treated by heated flat tools for 30 s to 120 s and the corresponding images after processing. The bainite fractions measured by image processing as well as MBN detection are compared in Fig. 10. Similar to the Gleeble specimens, the hot stamping sheet specimens treated by heated tools have mixed microstructures mainly composed of martensite and bainite. Besides, the bainite fraction increases with the increasing holding time in heated tools. A holding time of 120 s is sufficient to obtain a microstructure which is almost entirely composed of bainite phase. In addition, when a shorter holding time of 30 s is used, the bainite fraction (73.9% ~ 74.8%) obtained by heated tools is much higher than the bainite fraction (47.7% ~ 54.5%) of the Gleeble specimens shown in Fig. 7. It is mainly due to the fact that the overall temperature of the sheet specimen in heated tools is higher than 500 °C during the short holding period of 30 s, which results in the formation of more bainite phase. Furthermore, it could be found from Fig. 10 that MBN peaks increase with the increasing bainite fractions as expected. The bainite fractions predicted using MBN peaks according to Eq. (2) show good agreement with the measurements by image processing, with the maximum difference of only 5.7 %. This indicates an adequate accuracy of bainite fraction evaluation based on MBN detection.
Fig. 9. SEM microstructure morphologies of the hot stamping specimens under different holding times and the corresponding processed images (bainite region marked in red): (a) 30 s; (b) 60 s; (c) 90 s; (d) 120 s.
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Fig. 10. Bainite fractions measured by image processing as well as MBN detection of the hot stamping specimens. With the bainite fraction obtained by MBN detection, the corresponding mechanical properties of hot stamping parts could be estimated by the linear mixture rules described by Eq. (4) and Eq. (5) [28]:
U (1 fb ) mU fb bU
(4)
Y (1 fb ) mY fb bY
(5)
Where U and Y are respectively the overall ultimate tensile strength (UTS) and yield tensile strength (YTS), mU
and mY respectively represent the UTS and YTS of full
martensite microstructure, bU
and bY
are respectively UTS and YTS of full bainite
microstructure. The nominal stress-strain curves of the hot stamping specimens are obtained by tensile tests and shown in Fig. 11. The values of mU and mY are respectively 1478 MPa and 1010 MPa. Besides, the microstructure of the hot stamping specimen held for 120 s could be approximately regarded as full bainite microstructure. Therefore, bU respectively set as 1044 MPa and 893 MPa.
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and bY
are
Fig. 11. Nominal stress-strain curves of the hot stamping specimens. For the four hot stamping specimens held for 30 s to 120 s in heated tools, the mechanical properties obtained by both of tensile test and MBN detection are compared in Fig. 12. With the increasing bainite fraction resulting from prolonged holding time, both of the UTS and YTS show an overall decreasing tendency, which is in agreement with previous reports about martensite/bainite mixed microstructures [29, 30]. The maximum differences between MBN detection and tensile test are respectively 1.8% for UTS and -1.6% for YTS. Although the YTS and UTS measured by MBN detection are approximately in the same level of accuracy, the UTS is more appropriate to be evaluated by MBN detection. On one hand, it is due to the fact that there is no obvious yield point for the hot stamping steel and the UTS is generally used as a characteristic parameter of mechanical properties. On the other hand, it could be found that the variation range of YTS is much smaller compared to that of UTS. In general, these results suggest that it could be feasible to evaluate the phase fractions as well as the mechanical properties (especially UTS) of the hot stamping parts with martensite/bainite mixed microstructures by MBN detection.
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Fig. 12. Mechanical properties of the hot stamping specimens obtained by MBN detection and tensile test: (a) UTS; (b) YTS.
4. Conclusions The main conclusions of this work are as follows. During isothermal treatment at 500 °C, the bainite fraction of hot stamping boron steel increases with prolonged holding time, while the increasing rate of bainite fraction gradually decreases. The full bainite microstructure is achieved at the holding time of 222 s. With bainite fraction increasing from 0 to 100%, the intensity of MBN signal firstly decreases and then increases. The MBN peak could be regarded as the characteristic parameter of MBN signal for martensite/bainite mixed microstructures, due to remarkable linear correlation with bainite fraction above 30%. Under the condition when MBN peak or bainite fraction is respectively above 65 mV or 61.0%, the bainite fraction could be unambiguously evaluated by MBN detection. According to the relation of bainite fraction with MBN peak, the bainite fraction of hot stamping steel treated by heated tools are assessed by MBN detection and the results have an adequate accuracy. Furthermore, in combination with linear mixture rule of mechanical property, it is feasible to evaluate the mechanical properties especially UTS of hot stamping parts with martensite/bainite mixed microstructures based on MBN detection.
Acknowledgements This study is supported by the National Natural Science Foundation of China (Grant No. 15
U1760205). The authors would like to acknowledge the State Key Laboratory of Materials Processing and Die & Mould Technology for the assistance in Gleeble and tensile tests.
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Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Figure 1 (Width: 165 mm; 2 columns)
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Fig. 1. Schematic diagram of the process to achieve tailored properties by adjusting the cooling rate in different regions of the hot stamping part. Figure 2 (Width: 89 mm; 1 column)
Fig. 2. Heat treatment procedure to prepare microstructures with different bainite fractions.
Figure 3 (Width: 182 mm; 2 columns)
Fig. 3. Hot stamping tests of boron steel sheet using heated flat tools. Figure 4 (Width: 132 mm; 1.5 columns)
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Fig. 4. Schematic illustration of the MBN detection system.
Figure 5 (Width: 88 mm; 1 column)
Fig. 5. The MBN signal processed by 2-20 kHz bandpass filter and final MBN profile.
20
Figure 6 (Width: 162 mm; 2 columns)
Fig. 6. SEM microstructure morphologies of the Gleeble specimens under different holding times at 500 °C and the corresponding processed images (bainite region marked in red): (a): 0 s; (b): 222 s; (c): 14 s; (d): 21 s; (e): 28 s; (f): 35 s; (g): 42 s; (h): 54 s; (i): 72 s; (j): 102 s.
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Figure 7 (Width: 88 mm; 1 column)
Fig. 7. The variation of bainite fraction with increasing holding time.
Figure 8 (Width: 172 mm; 2 columns)
Fig. 8. The variations of (a) MBN peak and (b) MBN RMS with increasing bainite fraction.
Figure 9 (Width: 162 mm; 2 columns)
Fig. 9. SEM microstructure morphologies of the hot stamping specimens under different holding times and the corresponding processed images (bainite region marked in red): (a) 30 s; (b) 60 s; (c) 90 s; (d) 120 s. Figure 10 (Width: 88 mm; 1 column)
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Fig. 10. Bainite fractions measured by image processing as well as MBN detection of the hot stamping specimens.
Figure 11 (Width: 88 mm; 1 column)
Fig. 11. Nominal stress-strain curves of the hot stamping specimens.
Figure 12 (Width: 175 mm; 2 columns)
Fig. 12. Mechanical properties of the hot stamping specimens obtained by MBN detection and tensile test: (a) UTS; (b) YTS.
Magnetic Barkhausen noise (MBN) is used to evaluate hot stamping steel with 23
martensite/bainite microstructure. Characteristics of MBN signal under different mixed microstructures are analyzed. The MBN intensity first decreases and then increases with increasing bainite fraction. The MBN peak shows a positive linear correlation with bainite fraction above 30%. The ultimate tensile strength (UTS) assessed by MBN detection has adequate accuracy.
Table 1. Chemical compositions of 22MnB5 boron steel (wt. %). C 0.23
Mn 0.95
P 0.01
S 0.002
Si 0.17
Mo 0.21
Cr 0.24
24
Al 0.03
Ti 0.023
B 0.002
S0304-8853(19)33272-X https://doi.org/10.1016/j.jmmm.2020.166598 MAGMA 166598
To appear in:
Journal of Magnetism and Magnetic Materials
Received Date: Revised Date: Accepted Date:
16 September 2019 4 January 2020 8 February 2020
Please cite this article as: B. Zhu, Z. Xu, K. Wang, Y. Zhang, Nondestructive evaluation of hot stamping boron steel with martensite/bainite mixed microstructures based on magnetic Barkhausen noise detection, Journal of Magnetism and Magnetic Materials (2020), doi: https://doi.org/10.1016/j.jmmm.2020.166598
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Nondestructive evaluation of hot stamping boron steel with martensite/bainite mixed microstructures based on magnetic Barkhausen noise detection Bin Zhu, Ziqian Xu, Kai Wang*, Yisheng Zhang State Key Laboratory of Materials Processing and Die & Mould Technology, Huazhong University of Science and Technology, Wuhan 430074, China *Corresponding
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[email protected] Abstract: A nondestructive testing method based on magnetic Barkhausen noise (MBN) detection is developed to evaluate the microstructural and mechanical properties of hot stamping boron steel with martensite/bainite mixed microstructures. Firstly, boron steel specimens are heat treated by Gleeble thermo-mechanical simulator to prepare mixed microstructures with different bainite fractions. Based on the analysis of MBN signals of these specimens, the relation between MBN characteristics and bainite fraction is investigated. The results indicate that the MBN intensity firstly decreases and then increases with the increasing bainite fraction. The MBN peak shows a positive linear correlation with bainite fraction above 30%. The bainite fraction could be simply evaluated when MBN peak is above 65 mV. Furthermore, according to the assessed bainite fraction by MBN detection, the ultimate tensile strength (UTS) and yield tensile strength (YTS) of hot stamping steel sheets treated by heated tools are calculated and compared with tensile tests. It is suggested that it could be feasible to evaluate the mechanical properties especially UTS of hot stamping parts with martensite/bainite mixed microstructures based on MBN detection. Keywords: Nondestructive detection; Magnetic Barkhausen noise; Hot stamping; Mixed microstructure
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1. Introduction Hot stamping parts have been widely used in car bodies due to the increasing demand for high passive safety, energy saving and emission reduction in automobile industry. The conventional hot stamping parts quenched by cold tools have a tensile strength up to 1500 MPa, which could dramatically improve the anti-intrusive capacity [1]. However, for certain components such as B-pillar, the combination of both high anti-intrusive performance and good impact-absorptive performance in a single part is beneficial to enhance the overall crashworthiness. Therefore, the hot stamping parts with tailored properties are proposed [2]. One of the strategies to achieve tailored properties is to adjust the cooling rate of the ductile region by using heated tools [3]. As shown in Fig. 1, the upper region is quenched by cold tools to obtain full martensite microstructure with ultimate high strength. The lower region is held in heated tools to achieve high ductility owing to the formation of softer phases such as ferrite or bainite. Srithananan et al. [4] conducted a two-step quenching procedure to investigate the influence of holding time on the phase fraction and mechanical properties of boron steel. The results shows that longer holding time leads to increased bainite fraction, resulting in decreased yield and tensile strength and higher elongation. Zhang et al. [5] analyzed the effect of tool temperature on the microstructure of the softer region of a U-type part with tailored properties. At a holding time of 10 s in the heated tools, the microstructure mainly consists of martensite, bainite and ferrite, while the total fraction of martensite and bainite is approximately 90%. These research works suggest that the bainite fraction has a significant influence on the final mechanical properties. For the detection of components with tailored properties, the conventional traditional methods including metallographic observation, tensile test and hardness test are usually employed, which could provide detailed characterization of the microstructures and mechanical properties. However, these methods are destructive to the detected parts and time consuming. Therefore, it is necessary to establish a non-destructive and convenient detection method to provide real-time information 2
of microstructure compositions (martensite and bainite) and mechanical properties, which is quite practical for the quality control of hot stamping parts with tailored properties in production line.
Fig. 1. Schematic diagram of the process to achieve tailored properties by adjusting the cooling rate in different regions of the hot stamping part. Magnetic Barkhausen Noise (MBN) detection is a non-destructive technique which could characterize the microstructural and mechanical properties of ferromagnetic materials subjected to different treatment conditions [6-10]. The MBN effect is a complex phenomenon of abrupt changes during the magnetization of ferromagnetic materials [11, 12]. There are many tiny magnetic regions named domains in the ferromagnetic materials and these domains are separated from each other by domain walls [13]. When the ferromagnetic material is subjected to an external alternating magnetic field, the domain walls inside the material will reciprocate. MBN is produced when domain walls encounter pinning or defects inside the material during reciprocating movement [14], which could be acquired by magnetic sensor. Due to these principles, the MBN detection method does not require extensive sample preparation and could be used to detect samples in various size and shapes. It has been widely reported that the MBN method is used in microstructural and mechanical characterization of steels. Saquet et al. [15] compared the MBN signals of four 3
different microstructures (pearlite, ferrite/cementite, ferrite, and martensite) in carbon steel. The results suggest that the MBN signal of ferrite/cementite is most intensive, subsequently followed by the signals of pearlite, ferrite and martensite. Koo et al. [16] reported that the MBN signal increased monotonously with increasing pearlite fraction for plain carbon steel in both hypoeutectoid and hypereutectoid state. Kaplan et al. [13] investigated the influence of martensite fraction on MBN signal in martensite-ferrite dual-phase steel. The results show that the RMS voltage of the MBN signal decreases with the increasing martensite fraction. Luo et al. [17] performed frequency domain analysis and signal reconstruction of MBN of hot stamping steel sheet with different hardness. The power spectrum density analysis shows that the low frequency peaks of MBN signal increases as hardness decreases. However, little research work has been reported concerning the MBN-based nondestructive detection of the hot stamping steel with martensite/bainite mixed microstructures. The aim of this work is to investigate the relationship between MBN signal and martensite/bainite mixed microstructures as well as the corresponding mechanical properties of hot stamping boron steel.
2. Experimental procedure 2.1 Heat treatment procedure and hot stamping tests The material used is uncoated hot stamping boron steel which belongs to 22MnB5 grade. The thickness of the steel sheet is 1.2 mm and the initial microstructure in as received condition is composed of pearlite and ferrite. Table 1 shows the chemical compositions of the material. Table 1. Chemical compositions of 22MnB5 boron steel (wt. %). C 0.23
Mn 0.95
P 0.01
S 0.002
Si 0.17
Mo 0.21
Cr 0.24
Al 0.03
Ti 0.023
B 0.002
To prepare microstructures with different martensite/bainite fractions, heat treatments of boron steel are conducted by Gleeble thermo-mechanical simulator which has been widely 4
adopted in physical simulation of materials behaviour under transient thermal conditions such as welding, continuous casting and hot forming [18]. The standard hot tensile specimen reported by Zhu et al. [19] is used for heat treatment. The uniform temperature region of the specimen is about 11 mm. Fig. 2 illustrates the heat treatment procedure of the first type specimens. Each specimen is heated to 930 °C at a heating rate of 8 °C/s and kept for 3 min for complete austenization. It has been reported that the temperature range of bainite transformation is between 400 °C and 600 °C for boron steel [4, 20]. Therefore, the specimens are then air cooled to 500 °C in 18 s and held for different times, so that the extent of bainite transformation could be adjusted. The holding times are respectively set as 0 s, 14 s, 21 s, 28 s, 35 s, 42 s, 54 s, 72 s, 102 s and 222 s. Finally, the specimens are cooled to room temperature by water to ensure that the remaining austenite transforms into martensite.
Fig. 2. Heat treatment procedure to prepare microstructures with different bainite fractions. Hot stamping tests of boron steel are carried out using flat tools as shown in Fig. 3. Rectangular sheet specimens with a size of 300 mm × 210 mm are heated at 930 °C for 5 min in a resistance furnace for complete austenization. Then the specimens are transferred to a servo press and held in the heated tools with a temperature of 400 °C. Four holding times of 30, 60, 90 and 120 s are respectively adopted to obtain hot stamping specimens with different microstructures. After holding, each specimen is taken out from the tools and air cooled to room temperature. In addition, a sheet specimen quenched to room temperature by cold tools is also prepared to test the mechanical property of full martensite microstructure.
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Fig. 3. Hot stamping tests of boron steel sheet using heated flat tools. 2.2 Detection and processing of MBN signal MBN detections are carried out using the self-developed detection system as shown in Fig. 4. The detection system consists of seven modules, including a wave generator which produces a 10 Hz sinusoidal signal with an amplitude of ±180 mV, a power amplifier to amplify the sinusoidal signal, two excitation coils (0.3 mm, 800 turns) wound around the U-shaped electromagnet composed of soft magnetic Fe-Si sheets to generate an excitation magnetic field, an search coil (0.1 mm, 2000 turns) wound around a ferrite core to pick up MBN signal, an operational amplifier to amplify the MBN signal, a DAQ card to convert the MBN signal to digital data, and a PC to record as well as process the MBN signal. It should be noted that the length of the magnetized region between two excitation coils is approximately 9 mm, which is shorter than the uniform temperature region with homogeneous microstructure in the Gleeble specimen. The total time of signal acquisition for each specimen is set as 10 s. There are two periods of MBN signal generated in each excitation signal period. As a result, the collected MBN signal has 200 periods.
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Fig. 4. Schematic illustration of the MBN detection system. To eliminate the excitation signal and reduce noise interference, the collected signal is filtered using a 2-20 kHz bandpass filter and the obtained signal is shown in Fig. 5. To extract the characteristic value of the MBN, the signal is then subjected to processing of overlaying and averaging. Wavelet denoising is also used to smooth the signal and the final MBN profile is marked with red line in Fig. 5. The MBN signal curve exhibits a maximum peak in one period. After subtracting the thermal noise resulting from random fluctuation of charge carriers [21], the value of MBN peak is obtained. In addition, the RMS of MBN signal in one period within the range of ±0.0125 s from the peak position is also calculated.
Fig. 5. The MBN signal processed by 2-20 kHz bandpass filter and final MBN profile.
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2.3 Microstructure detection and quantification Metallographic samples are cut from the Gleeble specimens and hot stamping specimens for microstructure characterization. The samples are prepared via typical procedures including grinding, polishing and etching. To clearly reveal details of the microstructures, the 3.0 vol.% nitric acid solution is used to etch the samples. A scanning electron microscopy (SEM, TM3030PLUS) is used to observe the microstructure of each sample. To distinguish and quantify different phases in the microstructure, the SEM micrographs of the specimens under different heat treatment conditions are processed using image processing code.
3. Results and discussion 3.1 The influence of holding time on bainite fraction The SEM microstructure morphologies of the Gleeble specimens under different holding times at 500 °C and the corresponding images after processing are illustrated in Fig. 6. The specimen directly cooled to room temperature without holding has a full martensite microstructure as shown in Fig. 6(a). As for the specimen held for 222 s shown in Fig. 6(b), the microstructure is approximately composed of full bainite phase. When the holding time is between 0 s and 222 s [Figs. 6(c-j)], the specimens show mixed microstructures which are mainly composed of martensite and bainite. The bainite fractions of the specimens under different holding times are plotted in Fig. 7. It could be found that the bainite fraction increases with prolonged holding time. With a holding time ranging from 0 s to 42 s, the bainite fraction increases dramatically from 0 to 69.1 %. As the holding time prolongs from 42 s to 102 s, the bainite fraction just increases gradually to 94.8%. During subsequent holding procedure to 222 s, the increment of bainite fraction in 120 s is only 5.2%. Furthermore, the bainite transformation of boron steel during holding followed the Johnson-Mehl-Avrami-Kolmogorov (JMAK) theory which is generally used for description of the fraction of material transformed at a given time in terms of the nucleation and growth 8
rates of processes [22]. For an isothermal transformation process such as the bainite transformation in this study, the JMAK model could be described by Eq. (1) [23].
fb 1 exp(kt n )
(1)
Where fb is the bainite fraction, t is the holding time, k and n are parameters which could be obtained by fitting the measured bainite fractions at different holding times. As shown in Fig. 7, the fitted value of k and n are respectively 0.0063 and 1.365. The differences between the measured and predicted bainite fractions are relatively small.
Fig. 6. SEM microstructure morphologies of the Gleeble specimens under different holding times at 500 °C and the corresponding processed images (bainite region marked in red): (a): 0 s; (b): 222 s; (c): 14 s; (d): 21 s; (e): 28 s; (f): 35 s; (g): 42 s; (h): 54 s; (i): 72 s; (j): 102 s. 9
Fig. 7. The variation of bainite fraction with increasing holding time. 3.2 The characteristics of MBN signal under different bainite fractions The variations of peak value and RMS value of MBN signal with bainite fraction are illustrated in Fig. 8. In general, both of the MBN peak and RMS firstly decrease and then increase with bainite fraction increasing. When the bainite fraction is 30%, the MBN peak and the RMS have a minimum value of 57 mV and 39 mV respectively. Besides, the peak value and RMS value of MBN signal are approximately linearly proportional to the bainite fraction in the range from 30% to 100%. The enhancement of MBN signal with bainite fraction is mainly attributed to the fact that the resistance to domain walls in bainite is relatively lower than the resistance in martensite with small lath structure and high dislocation density [13]. Under external magnetic field, there are more unpinning events occurring in bainite due to greater domain wall displacements, which leads to stronger MBN signal with increasing bainite fraction above 30%. As for the increasing MBN signal with bainite fraction decreasing from 30% to 0, it is deduced to be the effect of residual internal stress caused by dominated martensite fraction [24]. The increasing martensite fraction generates more residual internal stress which is believed to strengthen the MBN [25-27]. As a result of these two aspects, the intensity of MBN signal decreases first and then increases with increasing bainite fraction.
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Fig. 8. The variations of (a) MBN peak and (b) MBN RMS with increasing bainite fraction. Based on linear fitting, the relation of MBN peak and RMS with the bainite fraction could be described by:
MBN p 0.258 fb 48.6
(2)
MBN R 0.172 fb 34.0
(3)
Where MBN p and MBN R are respectively the peak value of RMS value of MBN signal. According to the linear fitting results, it could be found that the fitting line of MBN peak has larger slope as well as R square compared with the RMS fitting line. This indicates that the MBN peak is more sensitive to the variation of bainite fraction. Besides, the error bar of the measured MBN peak is generally smaller than that of the RMS, which suggests smaller deviations between repeated detections. Therefore, the MBN peak is more suitable to be considered as a characteristic parameter of MBN signal for microstructures with different bainite fractions. However, it could be found from Fig. 8(a) that the MBN peak of full martensite microstructure equals to the peak value of the mixed microstructure with 61.0% bainite fraction, and the corresponding MBN peak is 64.4 mV. This indicates that unambiguous assessment of bainite fraction could not be achieved simply by MBN peak if the peak value is less than 65 mV. As a contrast, for the mixed microstructure with a MBN peak higher than 65 mV, the corresponding bainite fraction could be calculated according to Eq. (2).
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3.3 Feasibility evaluation of MBN detection of hot stamping parts Fig. 9 illustrates the SEM microstructure morphologies of the hot stamping specimens treated by heated flat tools for 30 s to 120 s and the corresponding images after processing. The bainite fractions measured by image processing as well as MBN detection are compared in Fig. 10. Similar to the Gleeble specimens, the hot stamping sheet specimens treated by heated tools have mixed microstructures mainly composed of martensite and bainite. Besides, the bainite fraction increases with the increasing holding time in heated tools. A holding time of 120 s is sufficient to obtain a microstructure which is almost entirely composed of bainite phase. In addition, when a shorter holding time of 30 s is used, the bainite fraction (73.9% ~ 74.8%) obtained by heated tools is much higher than the bainite fraction (47.7% ~ 54.5%) of the Gleeble specimens shown in Fig. 7. It is mainly due to the fact that the overall temperature of the sheet specimen in heated tools is higher than 500 °C during the short holding period of 30 s, which results in the formation of more bainite phase. Furthermore, it could be found from Fig. 10 that MBN peaks increase with the increasing bainite fractions as expected. The bainite fractions predicted using MBN peaks according to Eq. (2) show good agreement with the measurements by image processing, with the maximum difference of only 5.7 %. This indicates an adequate accuracy of bainite fraction evaluation based on MBN detection.
Fig. 9. SEM microstructure morphologies of the hot stamping specimens under different holding times and the corresponding processed images (bainite region marked in red): (a) 30 s; (b) 60 s; (c) 90 s; (d) 120 s.
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Fig. 10. Bainite fractions measured by image processing as well as MBN detection of the hot stamping specimens. With the bainite fraction obtained by MBN detection, the corresponding mechanical properties of hot stamping parts could be estimated by the linear mixture rules described by Eq. (4) and Eq. (5) [28]:
U (1 fb ) mU fb bU
(4)
Y (1 fb ) mY fb bY
(5)
Where U and Y are respectively the overall ultimate tensile strength (UTS) and yield tensile strength (YTS), mU
and mY respectively represent the UTS and YTS of full
martensite microstructure, bU
and bY
are respectively UTS and YTS of full bainite
microstructure. The nominal stress-strain curves of the hot stamping specimens are obtained by tensile tests and shown in Fig. 11. The values of mU and mY are respectively 1478 MPa and 1010 MPa. Besides, the microstructure of the hot stamping specimen held for 120 s could be approximately regarded as full bainite microstructure. Therefore, bU respectively set as 1044 MPa and 893 MPa.
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and bY
are
Fig. 11. Nominal stress-strain curves of the hot stamping specimens. For the four hot stamping specimens held for 30 s to 120 s in heated tools, the mechanical properties obtained by both of tensile test and MBN detection are compared in Fig. 12. With the increasing bainite fraction resulting from prolonged holding time, both of the UTS and YTS show an overall decreasing tendency, which is in agreement with previous reports about martensite/bainite mixed microstructures [29, 30]. The maximum differences between MBN detection and tensile test are respectively 1.8% for UTS and -1.6% for YTS. Although the YTS and UTS measured by MBN detection are approximately in the same level of accuracy, the UTS is more appropriate to be evaluated by MBN detection. On one hand, it is due to the fact that there is no obvious yield point for the hot stamping steel and the UTS is generally used as a characteristic parameter of mechanical properties. On the other hand, it could be found that the variation range of YTS is much smaller compared to that of UTS. In general, these results suggest that it could be feasible to evaluate the phase fractions as well as the mechanical properties (especially UTS) of the hot stamping parts with martensite/bainite mixed microstructures by MBN detection.
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Fig. 12. Mechanical properties of the hot stamping specimens obtained by MBN detection and tensile test: (a) UTS; (b) YTS.
4. Conclusions The main conclusions of this work are as follows. During isothermal treatment at 500 °C, the bainite fraction of hot stamping boron steel increases with prolonged holding time, while the increasing rate of bainite fraction gradually decreases. The full bainite microstructure is achieved at the holding time of 222 s. With bainite fraction increasing from 0 to 100%, the intensity of MBN signal firstly decreases and then increases. The MBN peak could be regarded as the characteristic parameter of MBN signal for martensite/bainite mixed microstructures, due to remarkable linear correlation with bainite fraction above 30%. Under the condition when MBN peak or bainite fraction is respectively above 65 mV or 61.0%, the bainite fraction could be unambiguously evaluated by MBN detection. According to the relation of bainite fraction with MBN peak, the bainite fraction of hot stamping steel treated by heated tools are assessed by MBN detection and the results have an adequate accuracy. Furthermore, in combination with linear mixture rule of mechanical property, it is feasible to evaluate the mechanical properties especially UTS of hot stamping parts with martensite/bainite mixed microstructures based on MBN detection.
Acknowledgements This study is supported by the National Natural Science Foundation of China (Grant No. 15
U1760205). The authors would like to acknowledge the State Key Laboratory of Materials Processing and Die & Mould Technology for the assistance in Gleeble and tensile tests.
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Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Figure 1 (Width: 165 mm; 2 columns)
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Fig. 1. Schematic diagram of the process to achieve tailored properties by adjusting the cooling rate in different regions of the hot stamping part. Figure 2 (Width: 89 mm; 1 column)
Fig. 2. Heat treatment procedure to prepare microstructures with different bainite fractions.
Figure 3 (Width: 182 mm; 2 columns)
Fig. 3. Hot stamping tests of boron steel sheet using heated flat tools. Figure 4 (Width: 132 mm; 1.5 columns)
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Fig. 4. Schematic illustration of the MBN detection system.
Figure 5 (Width: 88 mm; 1 column)
Fig. 5. The MBN signal processed by 2-20 kHz bandpass filter and final MBN profile.
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Figure 6 (Width: 162 mm; 2 columns)
Fig. 6. SEM microstructure morphologies of the Gleeble specimens under different holding times at 500 °C and the corresponding processed images (bainite region marked in red): (a): 0 s; (b): 222 s; (c): 14 s; (d): 21 s; (e): 28 s; (f): 35 s; (g): 42 s; (h): 54 s; (i): 72 s; (j): 102 s.
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Figure 7 (Width: 88 mm; 1 column)
Fig. 7. The variation of bainite fraction with increasing holding time.
Figure 8 (Width: 172 mm; 2 columns)
Fig. 8. The variations of (a) MBN peak and (b) MBN RMS with increasing bainite fraction.
Figure 9 (Width: 162 mm; 2 columns)
Fig. 9. SEM microstructure morphologies of the hot stamping specimens under different holding times and the corresponding processed images (bainite region marked in red): (a) 30 s; (b) 60 s; (c) 90 s; (d) 120 s. Figure 10 (Width: 88 mm; 1 column)
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Fig. 10. Bainite fractions measured by image processing as well as MBN detection of the hot stamping specimens.
Figure 11 (Width: 88 mm; 1 column)
Fig. 11. Nominal stress-strain curves of the hot stamping specimens.
Figure 12 (Width: 175 mm; 2 columns)
Fig. 12. Mechanical properties of the hot stamping specimens obtained by MBN detection and tensile test: (a) UTS; (b) YTS.
Magnetic Barkhausen noise (MBN) is used to evaluate hot stamping steel with 23
martensite/bainite microstructure. Characteristics of MBN signal under different mixed microstructures are analyzed. The MBN intensity first decreases and then increases with increasing bainite fraction. The MBN peak shows a positive linear correlation with bainite fraction above 30%. The ultimate tensile strength (UTS) assessed by MBN detection has adequate accuracy.
Table 1. Chemical compositions of 22MnB5 boron steel (wt. %). C 0.23
Mn 0.95
P 0.01
S 0.002
Si 0.17
Mo 0.21
Cr 0.24
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Al 0.03
Ti 0.023
B 0.002