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Optimum design of grain impact sensor utilising polyvinylidene fluoride films and a floating raft damping structure
b i o s y s t e m s e n g i n e e r i n g 1 1 2 ( 2 0 1 2 ) 2 2 7 e2 3 5
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Research Paper
Optimum design of grain impact sensor utilising polyvinylidene fluoride films and a floating raft damping structure Zhan Zhao*, Yaoming Li, Zhenwei Liang, Yi Chen Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education & Jiangsu Province, Jiangsu University, Zhenjiang, Jiangsu 212013, China
article info
Grain losses are unavoidable during harvesting. In order to improve the efficiency and
Article history:
reduce grain losses, the major structural and operational parameters of combine
Received 5 December 2011
harvesters need to be adjusted accordingly. So, it is important to develop a sensor which
Received in revised form
can monitor the grain losses real-time. A sensor using piezoelectric polyvinylidene fluoride
8 April 2012
(PVDF) film as sensitive material for monitoring grain losses of combine harvesters is
Accepted 8 April 2012
described. A floating raft damping structure was used to construct the sensor to suppress
Published online 15 May 2012
the influence of vibrations. Based on a dynamic analysis of sensor model, response properties of the sensor under working conditions were calculated. The results indicated that the amplitude and frequency of vibration interference were both decreased by optimising the isolators. A signal processing circuit composed of charge amplifier, high-pass filter, absolute value amplifier, envelope detector and voltage comparator in series was designed to detect grain impact signal. A square wave voltage signal was produced while grain impact was detected, and the mean time width was <2.5 ms. Grain cleaning loss tests were carried out during harvesting rice and wheat by mounting the sensor at the rear of cleaning sieve, the results showed that the grain impact could be identified effectively from vibration noise. The measurement errors of grain cleaning loss recorded by the sensor, relative to the loss checked manually, were less than 15%. ª 2012 IAgrE. Published by Elsevier Ltd. All rights reserved.
1.
Introduction
The harvesting process is very complex and influenced by a wide range of factors such as machine settings, field and crop-related parameters, etc. Some harvesting losses are unavoidable because grain has to be properly cleaned within the available time. The two major sources of these losses arise in the separation of grain and other material from the threshing unit and in the separation of grain from lighter
material at the sieves. Various types of sensors are equipped on combine harvesters to monitor the working status of the different machine elements. It is well known that yield and crop properties can vary between fields and varieties. In order to cope with these different crop conditions, the major internal settings and working parameters of combine harvesters need to be adjusted and optimised accordingly. A lot of research has been carried out on combine harvesters with the objective of increasing efficiency through
* Corresponding author. E-mail address: [email protected] (Z. Zhao). 1537-5110/$ e see front matter ª 2012 IAgrE. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.biosystemseng.2012.04.005
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b i o s y s t e m s e n g i n e e r i n g 1 1 2 ( 2 0 1 2 ) 2 2 7 e2 3 5
Nomenclature c c1 E F G0 G1 G2 G3 h k k1 m m1 x0
1
viscous damping of upper isolator, N m s viscous damping of lower isolator, N m s1 elastic modulus of upper panel, GPa grain impact force, N transfer function of x3 excited by x0 transfer function of x3 excited by F transfer function of x1 excited by x0 transfer function of x1 excited by F thickness of upper panel, mm stiffness of upper isolator, N m1 stiffness of lower isolator, N m1 mass of upper rigid panel, g mass of floating raft, g displacement of base, m
automation (Glasbey & McGechan, 1983; Maertens & De Baerdemaeker, 2003; Mesri, Reza, & Shamsollah, 2010). Earlier studies found that grain losses were related to crop feed rate, so that electronic control systems were developed for adjusting combine forward speed to maintain constant grain losses (Flufy & Stone, 1983; Schueller, 1989). In recent years, with the advances in sensors and automatic technologies, researchers proposed some intelligent and complex control methods for combine harvesters. Craessaerts, Saeys, Missotten, & De Baerdemaeker (2010, Craessaerts, De Baerdemaeker, Missotten, & Saeys, 2010) identified optimum working conditions of a combine harvester based on experimental data and fuzzy modelling techniques. Grain detection sensors mounted at the rear section of the sieve were used to predict sieve losses, and a fuzzy-control system which combines the knowledge of experienced operators with databased models was developed. Omid et al. (2010) found that the grain harvesting was a non-linear process, and they designed a fuzzy logic controller incorporating human expert knowledge for automatic adjustment and control of combine harvesters to achieve minimal grain losses. The controller could automatically adjust cylinder speed, concave clearance, fan speed and forward speed based on the measured losses at straw walker and sieve sections. Maertens, Ramon, and De Baerdemaeker (2004) installed two impact-type sensors under the separation drum and proposed an on-the-go monitoring algorithm for separation processes in combine harvesters. With the algorithm it was possible to accurately estimate a local thresh-ability index by tracking the exponential relationship between both throughput and grain loss signals. The stabilities of these automatic control systems greatly depended on the measurement accuracy of grain losses. Piezoelectric ceramic is the most widely used material to develop grain impact sensors (Leonard & Larson, 1989; Liu & Leonard, 1993; Mao & Ni, 2008). Currently, both the crop feed rate of combine harvesters and the yield of grain are increasing. Because of the wide difference in grain properties, current sensors do not well satisfy requirements, especially in detection speed and sensitivity. There is a need to develop
displacement of floating raft, m displacement of the upper panel which F acting on, m x3, x4, x5 displacements of other upper panels excited by x0 and F, (x3 ¼ x4 ¼ x5), m deformation of lower isolator, m xr1 deformation of upper isolator, m xr2 z damping ratio l frequency ratio m mass ratio n Poison’s Ratio of upper panel r density of upper panel, kg m3 ɷ driving frequency, rad s1 ɷ0, ɷ1 natural frequencies of sensor, rad s1 ɷ01, ɷ02 natural frequencies excited by x0, rad s1 ɷ11, ɷ12, ɷ13 natural frequencies excited by F, rad s1 x1 x2
a new sensor which can accurately monitor the grain loss real-time. Polyvinylidene fluoride (PVDF) film is a new polymeric piezoelectric material. It became a research topic in recent years because of its advantages such as high sensitivity to weak impacts and acceleration, higher thermal, chemical stability, and flexible structures (Daku, Mohamed, & Prugger, 2004; Grinspan & Gnanamoorthy, 2010; Shirinov & Schomburg, 2008). Vibration is a major interference factor affecting sensor accuracy. In field situation, a combine harvester generally undergoes time-varying multiple frequency disturbances generated by the cleaning sieve, threshing drums, header and engine et al. It is therefore a difficult task to identify a grain impact signal from vibration noise. The objective was to develop a new grain impact sensor with higher detection speed and sensitivity. Piezoelectric PVDF films were selected as sensitive material. In order to attenuate the vibration interference, a floating raft damping structure, which is composed of double-layer isolators, was used to construct the sensor. Through the analysis of a mathematical model of the sensor and the vibration characteristics of installation position, resonances of the sensor under the field condition were calculated, and the optimum parameters for the isolators were derived. The performance of the sensor was verified by field experiments.
Fig. 1 e Structure of sensor.
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2. Structural design and theoretical consideration 2.1.
Structure of sensor
Floating raft is a special double-layer isolation system that reduces the level of noise and vibration. It provides much better damping performance than a single dynamic vibration absorber (Krenk & Høgsberg, 2008; Niu, Song, & Lim, 2005; Sun, Zhang, Zhang, & Chen, 2010). Fig. 1 gives the structure model of sensor which can be divided into six subsystems: (1) PVDF films, (2) upper rigid panels, (3) upper isolators, (4) rigid floating raft, (5) lower isolators and (6) bases. The size of the PVDF film was 25 mm 120 mm, its thickness was 50 mm, and the piezoelectric constant was 25 pC N1. Two electrodes were deposited on both sides of PVDF film. To avoid the scratching of electrode surfaces due to grain impact, two PET protective films (0.08 mm thickness) were adhered outside the electrodes. Then, a multi-layer film was pasted onto an upper rigid panel to construct an individual detection unit. When a grain impacts onto the film, due to its piezoelectric properties, an electric charge and voltage is generated at the electrodes. The film is flexible and lightweight enabling the vibration characteristics of the sensor to be neglected. The sensor has a high sensitivity because the grain impacts directly on the PVDF film. In order to increase the detection speed, four similar detection units were arranged as an array on a rigid floating raft with each unit designed an individual signal processing circuit. In order to avoid mutual vibrational interference between array units and the bases, upper isolators were added between the upper panels and the floating raft, and the floating raft was supported on the base by lower isolators.
2.2.
G1 ¼
G2 ¼
affect the output of the PVDF film, so only the vertical forces and the resulting motions of the sensor were involved in the presented model. Vibration performance of the sensor under two situations will be investigated: (a) motion due to displacement x0 of the base, and (b) excitation due to a grain impact force F acting on an upper panel. Considering that the displacements of others upper panels x3, x4 and x5 excited by x0 and F are same, x3 ¼ x4 ¼ x5, the equations of motion governing the sensor can be expressed as 8 < m1 x€1 þðc1 þ4cÞx_ 1 cx_ 2 3cx_ 3 þðk1 þ4kÞx1 kx2 3kx3 ¼c1 x_ 0 þk1 x0 mx€2 cx_ 1 þcx_ 2 kx1 þkx2 ¼F : 3mx€3 cx_ 1 þ3cx_ 3 kx1 þkx3 ¼0 (1)
Using Laplace Transformation and Cramer’s Rule, the displacement of upper panel and floating raft can be solved for as; x3 ¼ G0 x0 þ G1 F
(2)
x1 ¼ G2 x0 þ G3 F
(3)
Equations of motion
Figure 2 shows an analytical model of the sensor. The vertical vibration was more significant than other directions which
G0 ¼
Fig. 2 e Analytical model of floating raft structure.
where, the transmissibility equations are;
m1 l
u20
cc1 l2 u20 þ jlu0 ðkc1 þ k1 cÞ þ kk1 2 þ jlu0 ðc1 þ 4cÞ þ k1 þ 4k ml2 u20 þ jclu0 þ k 4ðjclu0 þ kÞ
(4)
m1 l
u20
jl3 u30 3c2 kl2 u20 þ 3jck2 lu0 þ k3 2 þ jlu0 ðc1 þ 4cÞ þ k1 þ 4k ml2 u20 þ jclu0 þ k 4ðjclu0 þ kÞ ml2 u20 þ jclu0 þ k
(5)
2
2
jmc1 l3 u30 ðcc1 þ mk1 Þl2 u20 þ jlu0 ck1 þ c1 k þ kk1 2 m1 l2 u20 þ jlu0 ðc1 þ 4cÞ þ k1 þ 4k ml2 u20 þ jclu0 þ k 4ðjclu0 þ kÞ
(6)
230
G3 ¼
b i o s y s t e m s e n g i n e e r i n g 1 1 2 ( 2 0 1 2 ) 2 2 7 e2 3 5
m1 l
2
u20
c2 l2 u20 þ 2jcklu0 þ k2 2 þ jlu0 ðc1 þ 4cÞ þ k1 þ 4k ml2 u20 þ jclu0 þ k 4ðjclu0 þ kÞ
pffiffiffiffiffiffiffiffiffiffi pffiffiffiffiffiffiffi where, j ¼ 1, u0 ¼ k=m and frequency ratio l ¼ ɷ/ɷ0. The deformation of the lower isolator xr1 and upper isolator xr2 are; xr1 ¼ x1 x0
(8)
xr2 ¼ x3 x1
(9)
The material of upper panels and the floating raft was stainless steel 304, its elastic modulus E was 190 GPa, Poison’s ratio n was 0.29, density r was 8000 kg m3, thickness h was 1 mm, and m was 25 g, m1 was 100 g and mass ratio m ¼ m/m1 was 0.25. Using the above transmissibility equations, the responses of sensor under different vibration loads can be calculated. The sensor was loaded via x0, Eq. (4) was calculated at different damping ratios z and the results of magnification ratio jG0j as a function of the frequency ratio l are plotted in Fig. 3. It can be seen that two natural frequencies ɷ01, ɷ02 are generated. Similarly, assuming a grain impact force F acts on the upper panel, Eq. (5) was calculated and the results of magnification ratio jG1j are shown in Fig. 4. It had three natural frequencies, ɷ11, ɷ12 and ɷ13.
u01;02 ¼ u11;12
sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 4u40 þ u41 u21 2 ; ɷ13 ¼ ɷ0 ¼ u0 þ 2 2
(7)
the frequencies of vibration interference and the grain impact signal. It is found that the natural frequencies were determined by the stiffness of the isolators, and decreasing the natural frequencies could be achieved by using isolators with lower stiffness. The frequency of grain impact signal mainly depended on the grain mass and stiffness. The frequencies for rice and wheat seeds are generally higher than 1 kHz (Ni, Mao, Zhang, & Chen, 2010; Wojtkowski, Pecen, Horabik, & Molenda, 2010; Zhao, Li, Chen, & Xu, 2011). While vibration interference due to base displacement (x0) is more complex, the floating raft structure generally needs to undergo time-varying multiple frequency disturbances. Although using isolators with lower stiffness is beneficial to reduce high frequency vibration, the deformation of isolators is increased by reducing the isolator’s stiffness at excitation of lower frequency. The greater deformation of isolators increases the size of the sensor, so the stiffness of isolators needs to be identified according to the spectral characteristics of actual conditions. Furthermore, it also can be seen from Figs. 3 and 4 that the introduction of damping ratio z into the isolators modifies the magnification ratio. The magnitude of resonance is greatly reduced if the damping ratio of isolator is increased. Therefore, the reduction of the magnification ratios jG0j and jG1j can be achieved by tuning the natural frequencies and by using isolators with larger damping ratios.
pffiffiffiffiffiffiffi pffiffiffiffiffiffiffiffiffiffiffiffiffiffi where, u1 ¼ k1 =m1 and damping ratio z ¼ c=2 mk. In order to improve the damping performance of sensor, its natural frequencies should be designed to be far lower than
2.3.
Grain impact resonance
Fig. 3 e Resonance amplitude response of the upper rigid panel jG0j under the exciting of base displacement x0.
Fig. 4 e Resonance amplitude response of the upper rigid panel jG0j under the exciting of impact force F.
Detection speed is an important index of a sensor. The upper panel fixed with a PVDF film is an elastic system, so
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Fig. 5 e Effect of upper isolator stiffness on grain impact resonance: (a) k [ 4000 N mL1; (b) k [ 15,000 N mL1; (c) k [ 30,000 N mL1.
the resonance wave will be generated when a grain impacts on it. It has been shown that the attenuation speed of a resonance wave is significantly affected by its supporting stiffness (Yang, Zhao, & Xi, 2005; Zhong, Sun, & Liu, 2006). A higher attenuation speed can shorten the detection time of a grain impact, and improve the sensor detection speed. In order to analyse the detection speed of the sensor, grain impact tests were carried out. Impact speeds between grain and the PVDF film were about 2 m s1. After charge amplifier, the output voltage of PVDF film was recorded through a highspeed data acquisition system. With upper isolator stiffness k in the range 4000 to 30,000 N m1, comparisons of grain impact resonance signals are shown in Fig. 5. No significant difference was found between peak amplitudes of the output voltage, but the attenuation speed of resonance wave increased as the stiffness of the upper isolator increased. It was also found that because of the isolation of floating raft, the stiffness of lower isolator has almost no effect on the sensor response of grain impact. Results from repeated experiments showed that the attenuation time was in the range of 15e20 ms when the stiffness of the upper isolator k was 4000 N m1, but the values were be reduced to the range
Fig. 6 e Installation position of the sensor on a combine harvester.
8e12 ms and 6e10 ms when k increased to 15,000 N m1 and 30,000 N m1, respectively.
2.4.
Base excitation resonance
To measure grain cleaning loss, a bracket was fixed to the rear of a cleaning sieve, and the sensors were mounted on the bracket (Fig. 6). The axial and radial installation position of the sensors was adjustable. When the combine harvester operated, the sensors vibrated at a same frequency as the sieve. Preliminary analysis of the vibration interference signals is essential to optimise the sensor design. When the sieve vibrated at a working frequency of 340 rpm, an accelerometer, rigidly mounted on the base, was used to sense the vibration signal. Figure 7 gives the magnitude of acceleration in the vertical direction. Besides the reciprocating vibration with
Fig. 7 e Vertical acceleration of base.
232
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Fig. 8 e Frequency spectrum of base vertical acceleration.
cleaning sieve, the sensor was also affected by the instantaneous impact. Although the displacement of such impact was generally <2 mm, the generated acceleration amplitude could be >1500 m s2, and its frequency spectrum distributed over a wide range (Fig. 8). It is almost impossible to identify a grain impact force from the vibration noise just using a signal processing circuit, so the damping structure of sensor had to be optimised for suppression of this noise. A low-density sponge was selected to make the isolators. Its damping ratio z was about 0.1. The dynamic properties of sensor were calculated by substituting the acquired vibration signals of base into the transmissibility equations, Eqs. (4)e(7).
With the stiffness of the upper isolator k of 15,000 N m1, and the stiffness of lower isolator k1 in the range of 2000e40,000 N m1, the calculated results showed that the acceleration magnitude of upper panel due to the base excitation deceased with decreasing k1. The values were <150 m s2 for k1 < 5000 N m1, and >450 m s2 for k1 > 15,000 N m1. However, the maximum deformation of the isolators increased with decreasing k1. When k1 < 5000 N m1, the maximum deformation of the lower isolator xr1 was >10 mm. Using a lower stiffness isolator could improve the damping effect, but it will increase the geometrical size of sensor. So, taking the two effects into a comprehensive analysis, the optimum stiffness of the lower isolator was predicted to be w8000 N m1. Figures 9(a)e(d) give the calculated values and the frequency spectrum of acceleration of upper panel and deformation of the lower and upper isolators with k ¼ 15,000 N m1 and k1 ¼ 8000 N m1. It can be seen that the amplitude of acceleration after damping is suppressed below 200 m s2, and its peak frequencies were <250 Hz. So, by signal frequency analysis, the grain impact signal can be identified from the vibration noise. According to the calculation results of the deformations of lower isolators xr1 and upper isolator xr2 (Fig. 9(c) and (d)), their thicknesses were determined as 1 mm and 4 mm respectively. The natural frequencies of the sensor were ɷ01 ¼ ɷ11 ¼ 31.3 Hz, ɷ02 ¼ ɷ12 ¼ 177.3 Hz, ɷ13 ¼ 123.3 Hz.
2.5.
Design of signal process circuit
The electric charge output from PVDF film could not be measured directly. A charge amplifier was designed to convert the electric charge to a voltage signal. The output voltage of the charge amplifier included the impact signal of the grain,
Fig. 9 e Calculation results of dynamic properties of sensor with k [ 15,000 N mL1 and k1 [ 8000 N mL1: (a) Acceleration of PVDF film; (b) Frequency spectrum of PVDF film acceleration; (c) Deformation of lower isolator; (d) Deformation of upper isolator.
233
b i o s y s t e m s e n g i n e e r i n g 1 1 2 ( 2 0 1 2 ) 2 2 7 e2 3 5
PVDF film
charge amplifier
hgh-pass filter
absolute value amplifier
envelope detector
voltage comparator
square voltage signal
Fig. 10 e Schematic diagram of signal processing circuit.
Fig. 11 e Output voltage of sensor: (a) without the damping structure; (b) damping structure k [ 30,000 N mL1 and k1 [ 80,000 N mL1; (c) damping structure k [ 15,000 N mL1 and k1 [ 8000 N mL1.
materials other than grain (MOG) and vibration interference. According to their different frequency characteristics, the grain impact signal is distinguished by using a high-pass filter, with a critical frequency of 1 kHz. Peak voltage is another crucial index for identifying grain impact signal. Due to the stochastic attitude of grains impacting on the PVDF film, the generated peak voltage may be a positive or negative value (Fig. 5). In order to acquire the peak voltage accurately, an absolute value amplifier consisting of a precision detector and an adder is designed. Then, to avoid the influence of impact resonance wave, an envelope detector is added to extract signal envelop curve. Finally, the signal is transmitted to a voltage comparator to shape the wave. Therefore, the signal process circuit will output a square voltage signal while a grain impact occurs. Figure 10 shows the schematic diagram of signal processing circuit.
2.6.
Grain detection
Figure 11(a) shows the output voltage signal of the sensor without the use of isolators. Because of the interference of vibration noise at high frequency, the voltage value was
fluctuated in the range of 0e4 V. Grain impact signals were submerged in the noise. In order to analyse the effect of the physical properties of the isolators on the damping properties of sensor, two sets of isolators were manufactured using lowdensity sponge and rubber. The contrasting test results are shown in Fig. 11(b) and (c). When using the rubber isolators with greater stiffness (k ¼ 30,000 N m1 and k 1 1 ¼ 80,000 N m ), the output voltage of the sensor contained periodic vibration impact signal originated from the sieve, and the peak value is higher than 3 V. When using the low-density sponge isolators with stiffness (k ¼ 1500 N m1 and k1 ¼ 8000 N m1), this impact signal was suppressed effectively. Grain detection performance tests were carried out with the vertical impact velocity of 1.5e3 m s1 (Li et al., 2011). It was found that the output voltage increased monotonically with increasing vertical impact velocity, the voltage amplitudes of MOG were general below 1.0 V, and the voltage amplitudes of rice and wheat (Thousand seed mass 30e40 g) were mainly in the range of 2e5 V. Hence, the threshold value of comparator was set to 1.5 V, and the grain impact signals were successfully identified. The mean time width generated square voltage was generally <2.5 ms.
Table 1 e Properties of grains.
Grain moisture content, % MOG moisture content, % Average length of the stems, m MOG/Grain mass ratio Thousand seed mass, g Grain yield, t ha1
Rice # 1 Long Jing 29
Rice # 2 Wu 2645
Wheat # 1 Yang Mai 158
Wheat # 2 Yang Mai 16
18.6 50.4 0.84 1.78 37.7 8.2
24.1 68.0 1.03 1.92 30.6 9.8
14.7 40.8 0.91 1.32 41.0 6.6
12.8 44.1 0.95 1.43 35.8 5.9
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Table 2 e Error analysis of cleaning losses obtain using the sensor compared to manual measurement. Variety
Forward velocity, m s1 Sensor
Manual a
Total mass, g Ratio, % Rice # 1 Rice # 2 Wheat # 1 Wheat # 2
1.0 1.2 1.0 1.2 1.0 1.2 1.0 1.2
Absolute error, %b Relative error, %c
Cleaning loss
607.3 653.2 1264.0 1203.8 233.4 247.6 121.6 136.3
0.99 1.06 1.72 1.64 0.47 0.50 0.27 0.31
Total mass, g Ratio, %a 651.9 719.6 1227.5 1117.2 257.4 227.7 141.6 154.9
1.06 1.17 1.67 1.52 0.52 0.46 0.32 0.35
0.073 0.108 0.050 0.118 0.049 0.040 0.045 0.042
6.84 9.23 2.98 7.75 9.33 8.73 14.09 12.01
a Grain mass ratio at the exit. b Absolute dispersion of grain mass ratio at the exit obtained by the sensor and by manual. c The ratio of absolute error and grain mass ratio at the exit obtained by manual.
3.
Field experiment
3.1.
Method
To test the performance of the sensor, cleaning loss monitoring experiments were carried out in different rice and wheat fields. Table 1 gives the cultivars and the major properties of grains. Three similar sensors were assembled on a conventional 4LQZ combine harvester (Fig. 6, Foton Lovol International Heavy Industry Co., Ltd, China), and a secondary instrument based on AT89C52 (Atmel Co., USA) single chip microcomputer was designed to count the total number of square voltage outputted from the three sensors. The width of header was 4.5 m and the width of the cleaning sieve was 1 m. Because the grain detected by the sensor was only a part of the total loss of grain, the proportional relationship between the counting result of sensor and the total loss grain needed to be identified. The forward velocities of combine harvester were 1.0 and 1.2 m s1, the harvesting distance was 15 m, and the corresponding feeding rates were 8e10 kg s1 for rice and 7e8.5 kg s1 for wheat. An oil skin was used to collect the total material escaping from the end of the cleaning sieve, and the entrained free grains were cleaned out by hand (cleaning loss). The tests were repeated twice for each parameter. It was found that the proportional relationship mainly depended on the grain physical characteristics and the cleaning operating parameters; the effect of forward velocity on the proportional relationship was not significant. Because the rice grain was lighter and the MOG/Grain mass ratio was larger, the proportional relationship of rice was slightly less than for wheat. From comprehensive analysis of the tests results, the average values of proportional relationships were about 0.11 for rice and 0.14 for wheat.
3.2.
Results and discussion
Based on the number of seeds counted by the sensor and the average proportional relationship, total grain cleaning losses were calculated. For the same operating parameters, Table 2 gives the error analysis results of grain cleaning losses obtained by the sensor and by manual. It was found that the
relative measurement error of rice cleaning loss was <10%, and the relative measurement error of wheat cleaning loss was a little higher. It was known that the moisture content and the MOG/ Grain mass ratio of the wheat were lower and the grain surface was smoother; these factors were beneficial to improve the cleaning performance, so the wheat cleaning loss ratio was <0.5% in general. The process of grain cleaning is complex and it is affected by the vibration parameters of the cleaning sieve, cleaning flow field and the grain physical characteristics. The motion of grain escaping from the outlet of the cleaning sieve is a stochastic process, and there are some variations in the proportional relationship between the counted grains and the total cleaning loss. For wheat # 2 tests, the total number of lost grains in the harvesting area 4.6 m 15 m was in the range 3000e4000, and only 500e600 grains were detected by sensors. Small variations in the number of detected grains will lead to a larger relative error, this is why the relative measurement error increased to 14.09%, and the absolute measurement error was limited to 0.05%. In addition, small stones, or MOG, ejected from sieve at high speed and impacting on the PVDF films can all possibly influence the measurement results. They will lead to a reduction in monitoring accuracy in the field.
4.
Conclusions
A grain impact sensor, utilising PVDF films and floating raft damping structure, was designed to monitor grain losses in the field. Based on the dynamic analysis of the sensor and the analysis of the vibration interferences, the sensor resonances were calculated. It was found that the amplitude of acceleration generated by the vibration of the combine harvester could be >1500 m s2. Therefore, machine vibration was an important interference factor that reduced sensor accuracy. By using a floating raft damping structure, the acceleration amplitude and corresponding frequency spectrum of the PVDF films could be suppressed. An appropriate increase in the stiffness of the upper isolator can increase the attenuation speed of resonance wave. A signal processing circuit composed of
b i o s y s t e m s e n g i n e e r i n g 1 1 2 ( 2 0 1 2 ) 2 2 7 e2 3 5
charge amplifier, low-pass filter, absolute value amplifier, envelope detector and voltage comparator in series was used to detect grain impact signals. The detection time of a grain impact was <2.5 ms. Sensors were installed at the end of the sieve of a combine harvester and cleaning loss monitoring tests were carried out in rice and wheat fields. The results indicated that the relative measurement error was <15%.
Acknowledgements This research was supported by the National HighTechnology Research and Development Program of China (863Program) (No. 2010AA101402), China Postdoctoral Science Foundation (No. 20110490124), Postdoctoral Science Foundation of Jiangsu Province (No. 1102131C) and Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PADP).
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Li, Y. M., Liang, Z. W., Zhao, Z., & Xu, L. Z. (2011). Real-time monitoring system of grain loss in combine harvester. Transactions of the Chinese Society for Agricultural Machinery, 42(s), 99e102. Liu, C., & Leonard, J. (1993). Monitoring actual grain loss from an axial flow combine in real time. Computers and Electronics in Agriculture, 9(3), 231e242. Maertens, K., & De Baerdemaeker, J. (2003). Flow rate based prediction of threshing process in combine harvesters. Applied Engineering in Agriculture, 19(4), 383e388. Maertens, K., Ramon, K., & De Baerdemaeker, J. (2004). An on-thego monitoring algorithm for separation processes in combine harvesters. Computers and Electronics in Agriculture, 43(3), 197e207. Mao, H. P., & Ni, J. (2008). Finite element analysis and measurement for array piezocrystals grain losses sensor. Transactions of the Chinese Society for Agricultural Machinery, 39(12), 123e126. Mesri, G. T., Reza, G. H., & Shamsollah, A. (2010). Application of artificial neural network in prediction of the combine harvester performance. Journal of Food Agriculture & Environment, 8(2), 721e724. Ni, J., Mao, H. P., Zhang, X. D., & Chen, X. H. (2010). Application of Butterworth filter for testing grain cleaning loss. Transactions of the Chinese Society for Agricultural Machinery, 41(6), 172e176. Niu, J. C., Song, K. J., & Lim, C. W. (2005). On active vibration isolation of floating raft system. Journal of Sound and Vibration, 285(1e2), 391e406. Omid, M., Lashgari, M., Mobli, H., Alimardani, R., Mohtasebi, S., & Hesamifard, R. (2010). Design of fuzzy logic control system incorporating human expert knowledge for combine harvester. Expert Systems with Applications, 37(10), 7080e7085. Schueller, J. K. (1989). Digital simulation of combine reel and forward speed controllers. Computers and Electronics in Agriculture, 4(1), 59e71. Shirinov, A. V., & Schomburg, W. K. (2008). Pressure sensor from a PVDF film. Sensors and Actuators A: Physical, 142(1), 48e55. Sun, H. L., Zhang, K., Zhang, P. Q., & Chen, H. B. (2010). Application of dynamic vibration absorbers in floating raft system. Applied Acoustics, 71(3), 250e257. Wojtkowski, M., Pecen, J., Horabik, J., & Molenda, M. (2010). Rapeseed impact against a flat surface: physical testing and DEM simulation with two contact models. Powder Technology, 198(1), 61e68. Yang, Z. A., Zhao, X. J., & Xi, X. Y. (2005). Primary parametric resonance of thin rectangular plate on nonlinear elastic foundation. Rock and Soil Mechanics, 26(12), 1921e1925. Zhao, Z., Li, Y. M., Chen, J., & Xu, J. J. (2011). Grain separation loss monitoring system in combine harvester. Computers and Electronics in Agriculture, 76(2), 183e188. Zhong, Y., Sun, A. M., & Liu, W. G. (2006). Free vibration of rectangular thin plate on elastic foundation with four edges free. Journal of Vibration Engineering, 19(4), 566e570.
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Research Paper
Optimum design of grain impact sensor utilising polyvinylidene fluoride films and a floating raft damping structure Zhan Zhao*, Yaoming Li, Zhenwei Liang, Yi Chen Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education & Jiangsu Province, Jiangsu University, Zhenjiang, Jiangsu 212013, China
article info
Grain losses are unavoidable during harvesting. In order to improve the efficiency and
Article history:
reduce grain losses, the major structural and operational parameters of combine
Received 5 December 2011
harvesters need to be adjusted accordingly. So, it is important to develop a sensor which
Received in revised form
can monitor the grain losses real-time. A sensor using piezoelectric polyvinylidene fluoride
8 April 2012
(PVDF) film as sensitive material for monitoring grain losses of combine harvesters is
Accepted 8 April 2012
described. A floating raft damping structure was used to construct the sensor to suppress
Published online 15 May 2012
the influence of vibrations. Based on a dynamic analysis of sensor model, response properties of the sensor under working conditions were calculated. The results indicated that the amplitude and frequency of vibration interference were both decreased by optimising the isolators. A signal processing circuit composed of charge amplifier, high-pass filter, absolute value amplifier, envelope detector and voltage comparator in series was designed to detect grain impact signal. A square wave voltage signal was produced while grain impact was detected, and the mean time width was <2.5 ms. Grain cleaning loss tests were carried out during harvesting rice and wheat by mounting the sensor at the rear of cleaning sieve, the results showed that the grain impact could be identified effectively from vibration noise. The measurement errors of grain cleaning loss recorded by the sensor, relative to the loss checked manually, were less than 15%. ª 2012 IAgrE. Published by Elsevier Ltd. All rights reserved.
1.
Introduction
The harvesting process is very complex and influenced by a wide range of factors such as machine settings, field and crop-related parameters, etc. Some harvesting losses are unavoidable because grain has to be properly cleaned within the available time. The two major sources of these losses arise in the separation of grain and other material from the threshing unit and in the separation of grain from lighter
material at the sieves. Various types of sensors are equipped on combine harvesters to monitor the working status of the different machine elements. It is well known that yield and crop properties can vary between fields and varieties. In order to cope with these different crop conditions, the major internal settings and working parameters of combine harvesters need to be adjusted and optimised accordingly. A lot of research has been carried out on combine harvesters with the objective of increasing efficiency through
* Corresponding author. E-mail address: [email protected] (Z. Zhao). 1537-5110/$ e see front matter ª 2012 IAgrE. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.biosystemseng.2012.04.005
228
b i o s y s t e m s e n g i n e e r i n g 1 1 2 ( 2 0 1 2 ) 2 2 7 e2 3 5
Nomenclature c c1 E F G0 G1 G2 G3 h k k1 m m1 x0
1
viscous damping of upper isolator, N m s viscous damping of lower isolator, N m s1 elastic modulus of upper panel, GPa grain impact force, N transfer function of x3 excited by x0 transfer function of x3 excited by F transfer function of x1 excited by x0 transfer function of x1 excited by F thickness of upper panel, mm stiffness of upper isolator, N m1 stiffness of lower isolator, N m1 mass of upper rigid panel, g mass of floating raft, g displacement of base, m
automation (Glasbey & McGechan, 1983; Maertens & De Baerdemaeker, 2003; Mesri, Reza, & Shamsollah, 2010). Earlier studies found that grain losses were related to crop feed rate, so that electronic control systems were developed for adjusting combine forward speed to maintain constant grain losses (Flufy & Stone, 1983; Schueller, 1989). In recent years, with the advances in sensors and automatic technologies, researchers proposed some intelligent and complex control methods for combine harvesters. Craessaerts, Saeys, Missotten, & De Baerdemaeker (2010, Craessaerts, De Baerdemaeker, Missotten, & Saeys, 2010) identified optimum working conditions of a combine harvester based on experimental data and fuzzy modelling techniques. Grain detection sensors mounted at the rear section of the sieve were used to predict sieve losses, and a fuzzy-control system which combines the knowledge of experienced operators with databased models was developed. Omid et al. (2010) found that the grain harvesting was a non-linear process, and they designed a fuzzy logic controller incorporating human expert knowledge for automatic adjustment and control of combine harvesters to achieve minimal grain losses. The controller could automatically adjust cylinder speed, concave clearance, fan speed and forward speed based on the measured losses at straw walker and sieve sections. Maertens, Ramon, and De Baerdemaeker (2004) installed two impact-type sensors under the separation drum and proposed an on-the-go monitoring algorithm for separation processes in combine harvesters. With the algorithm it was possible to accurately estimate a local thresh-ability index by tracking the exponential relationship between both throughput and grain loss signals. The stabilities of these automatic control systems greatly depended on the measurement accuracy of grain losses. Piezoelectric ceramic is the most widely used material to develop grain impact sensors (Leonard & Larson, 1989; Liu & Leonard, 1993; Mao & Ni, 2008). Currently, both the crop feed rate of combine harvesters and the yield of grain are increasing. Because of the wide difference in grain properties, current sensors do not well satisfy requirements, especially in detection speed and sensitivity. There is a need to develop
displacement of floating raft, m displacement of the upper panel which F acting on, m x3, x4, x5 displacements of other upper panels excited by x0 and F, (x3 ¼ x4 ¼ x5), m deformation of lower isolator, m xr1 deformation of upper isolator, m xr2 z damping ratio l frequency ratio m mass ratio n Poison’s Ratio of upper panel r density of upper panel, kg m3 ɷ driving frequency, rad s1 ɷ0, ɷ1 natural frequencies of sensor, rad s1 ɷ01, ɷ02 natural frequencies excited by x0, rad s1 ɷ11, ɷ12, ɷ13 natural frequencies excited by F, rad s1 x1 x2
a new sensor which can accurately monitor the grain loss real-time. Polyvinylidene fluoride (PVDF) film is a new polymeric piezoelectric material. It became a research topic in recent years because of its advantages such as high sensitivity to weak impacts and acceleration, higher thermal, chemical stability, and flexible structures (Daku, Mohamed, & Prugger, 2004; Grinspan & Gnanamoorthy, 2010; Shirinov & Schomburg, 2008). Vibration is a major interference factor affecting sensor accuracy. In field situation, a combine harvester generally undergoes time-varying multiple frequency disturbances generated by the cleaning sieve, threshing drums, header and engine et al. It is therefore a difficult task to identify a grain impact signal from vibration noise. The objective was to develop a new grain impact sensor with higher detection speed and sensitivity. Piezoelectric PVDF films were selected as sensitive material. In order to attenuate the vibration interference, a floating raft damping structure, which is composed of double-layer isolators, was used to construct the sensor. Through the analysis of a mathematical model of the sensor and the vibration characteristics of installation position, resonances of the sensor under the field condition were calculated, and the optimum parameters for the isolators were derived. The performance of the sensor was verified by field experiments.
Fig. 1 e Structure of sensor.
b i o s y s t e m s e n g i n e e r i n g 1 1 2 ( 2 0 1 2 ) 2 2 7 e2 3 5
229
2. Structural design and theoretical consideration 2.1.
Structure of sensor
Floating raft is a special double-layer isolation system that reduces the level of noise and vibration. It provides much better damping performance than a single dynamic vibration absorber (Krenk & Høgsberg, 2008; Niu, Song, & Lim, 2005; Sun, Zhang, Zhang, & Chen, 2010). Fig. 1 gives the structure model of sensor which can be divided into six subsystems: (1) PVDF films, (2) upper rigid panels, (3) upper isolators, (4) rigid floating raft, (5) lower isolators and (6) bases. The size of the PVDF film was 25 mm 120 mm, its thickness was 50 mm, and the piezoelectric constant was 25 pC N1. Two electrodes were deposited on both sides of PVDF film. To avoid the scratching of electrode surfaces due to grain impact, two PET protective films (0.08 mm thickness) were adhered outside the electrodes. Then, a multi-layer film was pasted onto an upper rigid panel to construct an individual detection unit. When a grain impacts onto the film, due to its piezoelectric properties, an electric charge and voltage is generated at the electrodes. The film is flexible and lightweight enabling the vibration characteristics of the sensor to be neglected. The sensor has a high sensitivity because the grain impacts directly on the PVDF film. In order to increase the detection speed, four similar detection units were arranged as an array on a rigid floating raft with each unit designed an individual signal processing circuit. In order to avoid mutual vibrational interference between array units and the bases, upper isolators were added between the upper panels and the floating raft, and the floating raft was supported on the base by lower isolators.
2.2.
G1 ¼
G2 ¼
affect the output of the PVDF film, so only the vertical forces and the resulting motions of the sensor were involved in the presented model. Vibration performance of the sensor under two situations will be investigated: (a) motion due to displacement x0 of the base, and (b) excitation due to a grain impact force F acting on an upper panel. Considering that the displacements of others upper panels x3, x4 and x5 excited by x0 and F are same, x3 ¼ x4 ¼ x5, the equations of motion governing the sensor can be expressed as 8 < m1 x€1 þðc1 þ4cÞx_ 1 cx_ 2 3cx_ 3 þðk1 þ4kÞx1 kx2 3kx3 ¼c1 x_ 0 þk1 x0 mx€2 cx_ 1 þcx_ 2 kx1 þkx2 ¼F : 3mx€3 cx_ 1 þ3cx_ 3 kx1 þkx3 ¼0 (1)
Using Laplace Transformation and Cramer’s Rule, the displacement of upper panel and floating raft can be solved for as; x3 ¼ G0 x0 þ G1 F
(2)
x1 ¼ G2 x0 þ G3 F
(3)
Equations of motion
Figure 2 shows an analytical model of the sensor. The vertical vibration was more significant than other directions which
G0 ¼
Fig. 2 e Analytical model of floating raft structure.
where, the transmissibility equations are;
m1 l
u20
cc1 l2 u20 þ jlu0 ðkc1 þ k1 cÞ þ kk1 2 þ jlu0 ðc1 þ 4cÞ þ k1 þ 4k ml2 u20 þ jclu0 þ k 4ðjclu0 þ kÞ
(4)
m1 l
u20
jl3 u30 3c2 kl2 u20 þ 3jck2 lu0 þ k3 2 þ jlu0 ðc1 þ 4cÞ þ k1 þ 4k ml2 u20 þ jclu0 þ k 4ðjclu0 þ kÞ ml2 u20 þ jclu0 þ k
(5)
2
2
jmc1 l3 u30 ðcc1 þ mk1 Þl2 u20 þ jlu0 ck1 þ c1 k þ kk1 2 m1 l2 u20 þ jlu0 ðc1 þ 4cÞ þ k1 þ 4k ml2 u20 þ jclu0 þ k 4ðjclu0 þ kÞ
(6)
230
G3 ¼
b i o s y s t e m s e n g i n e e r i n g 1 1 2 ( 2 0 1 2 ) 2 2 7 e2 3 5
m1 l
2
u20
c2 l2 u20 þ 2jcklu0 þ k2 2 þ jlu0 ðc1 þ 4cÞ þ k1 þ 4k ml2 u20 þ jclu0 þ k 4ðjclu0 þ kÞ
pffiffiffiffiffiffiffiffiffiffi pffiffiffiffiffiffiffi where, j ¼ 1, u0 ¼ k=m and frequency ratio l ¼ ɷ/ɷ0. The deformation of the lower isolator xr1 and upper isolator xr2 are; xr1 ¼ x1 x0
(8)
xr2 ¼ x3 x1
(9)
The material of upper panels and the floating raft was stainless steel 304, its elastic modulus E was 190 GPa, Poison’s ratio n was 0.29, density r was 8000 kg m3, thickness h was 1 mm, and m was 25 g, m1 was 100 g and mass ratio m ¼ m/m1 was 0.25. Using the above transmissibility equations, the responses of sensor under different vibration loads can be calculated. The sensor was loaded via x0, Eq. (4) was calculated at different damping ratios z and the results of magnification ratio jG0j as a function of the frequency ratio l are plotted in Fig. 3. It can be seen that two natural frequencies ɷ01, ɷ02 are generated. Similarly, assuming a grain impact force F acts on the upper panel, Eq. (5) was calculated and the results of magnification ratio jG1j are shown in Fig. 4. It had three natural frequencies, ɷ11, ɷ12 and ɷ13.
u01;02 ¼ u11;12
sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 4u40 þ u41 u21 2 ; ɷ13 ¼ ɷ0 ¼ u0 þ 2 2
(7)
the frequencies of vibration interference and the grain impact signal. It is found that the natural frequencies were determined by the stiffness of the isolators, and decreasing the natural frequencies could be achieved by using isolators with lower stiffness. The frequency of grain impact signal mainly depended on the grain mass and stiffness. The frequencies for rice and wheat seeds are generally higher than 1 kHz (Ni, Mao, Zhang, & Chen, 2010; Wojtkowski, Pecen, Horabik, & Molenda, 2010; Zhao, Li, Chen, & Xu, 2011). While vibration interference due to base displacement (x0) is more complex, the floating raft structure generally needs to undergo time-varying multiple frequency disturbances. Although using isolators with lower stiffness is beneficial to reduce high frequency vibration, the deformation of isolators is increased by reducing the isolator’s stiffness at excitation of lower frequency. The greater deformation of isolators increases the size of the sensor, so the stiffness of isolators needs to be identified according to the spectral characteristics of actual conditions. Furthermore, it also can be seen from Figs. 3 and 4 that the introduction of damping ratio z into the isolators modifies the magnification ratio. The magnitude of resonance is greatly reduced if the damping ratio of isolator is increased. Therefore, the reduction of the magnification ratios jG0j and jG1j can be achieved by tuning the natural frequencies and by using isolators with larger damping ratios.
pffiffiffiffiffiffiffi pffiffiffiffiffiffiffiffiffiffiffiffiffiffi where, u1 ¼ k1 =m1 and damping ratio z ¼ c=2 mk. In order to improve the damping performance of sensor, its natural frequencies should be designed to be far lower than
2.3.
Grain impact resonance
Fig. 3 e Resonance amplitude response of the upper rigid panel jG0j under the exciting of base displacement x0.
Fig. 4 e Resonance amplitude response of the upper rigid panel jG0j under the exciting of impact force F.
Detection speed is an important index of a sensor. The upper panel fixed with a PVDF film is an elastic system, so
b i o s y s t e m s e n g i n e e r i n g 1 1 2 ( 2 0 1 2 ) 2 2 7 e2 3 5
231
Fig. 5 e Effect of upper isolator stiffness on grain impact resonance: (a) k [ 4000 N mL1; (b) k [ 15,000 N mL1; (c) k [ 30,000 N mL1.
the resonance wave will be generated when a grain impacts on it. It has been shown that the attenuation speed of a resonance wave is significantly affected by its supporting stiffness (Yang, Zhao, & Xi, 2005; Zhong, Sun, & Liu, 2006). A higher attenuation speed can shorten the detection time of a grain impact, and improve the sensor detection speed. In order to analyse the detection speed of the sensor, grain impact tests were carried out. Impact speeds between grain and the PVDF film were about 2 m s1. After charge amplifier, the output voltage of PVDF film was recorded through a highspeed data acquisition system. With upper isolator stiffness k in the range 4000 to 30,000 N m1, comparisons of grain impact resonance signals are shown in Fig. 5. No significant difference was found between peak amplitudes of the output voltage, but the attenuation speed of resonance wave increased as the stiffness of the upper isolator increased. It was also found that because of the isolation of floating raft, the stiffness of lower isolator has almost no effect on the sensor response of grain impact. Results from repeated experiments showed that the attenuation time was in the range of 15e20 ms when the stiffness of the upper isolator k was 4000 N m1, but the values were be reduced to the range
Fig. 6 e Installation position of the sensor on a combine harvester.
8e12 ms and 6e10 ms when k increased to 15,000 N m1 and 30,000 N m1, respectively.
2.4.
Base excitation resonance
To measure grain cleaning loss, a bracket was fixed to the rear of a cleaning sieve, and the sensors were mounted on the bracket (Fig. 6). The axial and radial installation position of the sensors was adjustable. When the combine harvester operated, the sensors vibrated at a same frequency as the sieve. Preliminary analysis of the vibration interference signals is essential to optimise the sensor design. When the sieve vibrated at a working frequency of 340 rpm, an accelerometer, rigidly mounted on the base, was used to sense the vibration signal. Figure 7 gives the magnitude of acceleration in the vertical direction. Besides the reciprocating vibration with
Fig. 7 e Vertical acceleration of base.
232
b i o s y s t e m s e n g i n e e r i n g 1 1 2 ( 2 0 1 2 ) 2 2 7 e2 3 5
Fig. 8 e Frequency spectrum of base vertical acceleration.
cleaning sieve, the sensor was also affected by the instantaneous impact. Although the displacement of such impact was generally <2 mm, the generated acceleration amplitude could be >1500 m s2, and its frequency spectrum distributed over a wide range (Fig. 8). It is almost impossible to identify a grain impact force from the vibration noise just using a signal processing circuit, so the damping structure of sensor had to be optimised for suppression of this noise. A low-density sponge was selected to make the isolators. Its damping ratio z was about 0.1. The dynamic properties of sensor were calculated by substituting the acquired vibration signals of base into the transmissibility equations, Eqs. (4)e(7).
With the stiffness of the upper isolator k of 15,000 N m1, and the stiffness of lower isolator k1 in the range of 2000e40,000 N m1, the calculated results showed that the acceleration magnitude of upper panel due to the base excitation deceased with decreasing k1. The values were <150 m s2 for k1 < 5000 N m1, and >450 m s2 for k1 > 15,000 N m1. However, the maximum deformation of the isolators increased with decreasing k1. When k1 < 5000 N m1, the maximum deformation of the lower isolator xr1 was >10 mm. Using a lower stiffness isolator could improve the damping effect, but it will increase the geometrical size of sensor. So, taking the two effects into a comprehensive analysis, the optimum stiffness of the lower isolator was predicted to be w8000 N m1. Figures 9(a)e(d) give the calculated values and the frequency spectrum of acceleration of upper panel and deformation of the lower and upper isolators with k ¼ 15,000 N m1 and k1 ¼ 8000 N m1. It can be seen that the amplitude of acceleration after damping is suppressed below 200 m s2, and its peak frequencies were <250 Hz. So, by signal frequency analysis, the grain impact signal can be identified from the vibration noise. According to the calculation results of the deformations of lower isolators xr1 and upper isolator xr2 (Fig. 9(c) and (d)), their thicknesses were determined as 1 mm and 4 mm respectively. The natural frequencies of the sensor were ɷ01 ¼ ɷ11 ¼ 31.3 Hz, ɷ02 ¼ ɷ12 ¼ 177.3 Hz, ɷ13 ¼ 123.3 Hz.
2.5.
Design of signal process circuit
The electric charge output from PVDF film could not be measured directly. A charge amplifier was designed to convert the electric charge to a voltage signal. The output voltage of the charge amplifier included the impact signal of the grain,
Fig. 9 e Calculation results of dynamic properties of sensor with k [ 15,000 N mL1 and k1 [ 8000 N mL1: (a) Acceleration of PVDF film; (b) Frequency spectrum of PVDF film acceleration; (c) Deformation of lower isolator; (d) Deformation of upper isolator.
233
b i o s y s t e m s e n g i n e e r i n g 1 1 2 ( 2 0 1 2 ) 2 2 7 e2 3 5
PVDF film
charge amplifier
hgh-pass filter
absolute value amplifier
envelope detector
voltage comparator
square voltage signal
Fig. 10 e Schematic diagram of signal processing circuit.
Fig. 11 e Output voltage of sensor: (a) without the damping structure; (b) damping structure k [ 30,000 N mL1 and k1 [ 80,000 N mL1; (c) damping structure k [ 15,000 N mL1 and k1 [ 8000 N mL1.
materials other than grain (MOG) and vibration interference. According to their different frequency characteristics, the grain impact signal is distinguished by using a high-pass filter, with a critical frequency of 1 kHz. Peak voltage is another crucial index for identifying grain impact signal. Due to the stochastic attitude of grains impacting on the PVDF film, the generated peak voltage may be a positive or negative value (Fig. 5). In order to acquire the peak voltage accurately, an absolute value amplifier consisting of a precision detector and an adder is designed. Then, to avoid the influence of impact resonance wave, an envelope detector is added to extract signal envelop curve. Finally, the signal is transmitted to a voltage comparator to shape the wave. Therefore, the signal process circuit will output a square voltage signal while a grain impact occurs. Figure 10 shows the schematic diagram of signal processing circuit.
2.6.
Grain detection
Figure 11(a) shows the output voltage signal of the sensor without the use of isolators. Because of the interference of vibration noise at high frequency, the voltage value was
fluctuated in the range of 0e4 V. Grain impact signals were submerged in the noise. In order to analyse the effect of the physical properties of the isolators on the damping properties of sensor, two sets of isolators were manufactured using lowdensity sponge and rubber. The contrasting test results are shown in Fig. 11(b) and (c). When using the rubber isolators with greater stiffness (k ¼ 30,000 N m1 and k 1 1 ¼ 80,000 N m ), the output voltage of the sensor contained periodic vibration impact signal originated from the sieve, and the peak value is higher than 3 V. When using the low-density sponge isolators with stiffness (k ¼ 1500 N m1 and k1 ¼ 8000 N m1), this impact signal was suppressed effectively. Grain detection performance tests were carried out with the vertical impact velocity of 1.5e3 m s1 (Li et al., 2011). It was found that the output voltage increased monotonically with increasing vertical impact velocity, the voltage amplitudes of MOG were general below 1.0 V, and the voltage amplitudes of rice and wheat (Thousand seed mass 30e40 g) were mainly in the range of 2e5 V. Hence, the threshold value of comparator was set to 1.5 V, and the grain impact signals were successfully identified. The mean time width generated square voltage was generally <2.5 ms.
Table 1 e Properties of grains.
Grain moisture content, % MOG moisture content, % Average length of the stems, m MOG/Grain mass ratio Thousand seed mass, g Grain yield, t ha1
Rice # 1 Long Jing 29
Rice # 2 Wu 2645
Wheat # 1 Yang Mai 158
Wheat # 2 Yang Mai 16
18.6 50.4 0.84 1.78 37.7 8.2
24.1 68.0 1.03 1.92 30.6 9.8
14.7 40.8 0.91 1.32 41.0 6.6
12.8 44.1 0.95 1.43 35.8 5.9
234
b i o s y s t e m s e n g i n e e r i n g 1 1 2 ( 2 0 1 2 ) 2 2 7 e2 3 5
Table 2 e Error analysis of cleaning losses obtain using the sensor compared to manual measurement. Variety
Forward velocity, m s1 Sensor
Manual a
Total mass, g Ratio, % Rice # 1 Rice # 2 Wheat # 1 Wheat # 2
1.0 1.2 1.0 1.2 1.0 1.2 1.0 1.2
Absolute error, %b Relative error, %c
Cleaning loss
607.3 653.2 1264.0 1203.8 233.4 247.6 121.6 136.3
0.99 1.06 1.72 1.64 0.47 0.50 0.27 0.31
Total mass, g Ratio, %a 651.9 719.6 1227.5 1117.2 257.4 227.7 141.6 154.9
1.06 1.17 1.67 1.52 0.52 0.46 0.32 0.35
0.073 0.108 0.050 0.118 0.049 0.040 0.045 0.042
6.84 9.23 2.98 7.75 9.33 8.73 14.09 12.01
a Grain mass ratio at the exit. b Absolute dispersion of grain mass ratio at the exit obtained by the sensor and by manual. c The ratio of absolute error and grain mass ratio at the exit obtained by manual.
3.
Field experiment
3.1.
Method
To test the performance of the sensor, cleaning loss monitoring experiments were carried out in different rice and wheat fields. Table 1 gives the cultivars and the major properties of grains. Three similar sensors were assembled on a conventional 4LQZ combine harvester (Fig. 6, Foton Lovol International Heavy Industry Co., Ltd, China), and a secondary instrument based on AT89C52 (Atmel Co., USA) single chip microcomputer was designed to count the total number of square voltage outputted from the three sensors. The width of header was 4.5 m and the width of the cleaning sieve was 1 m. Because the grain detected by the sensor was only a part of the total loss of grain, the proportional relationship between the counting result of sensor and the total loss grain needed to be identified. The forward velocities of combine harvester were 1.0 and 1.2 m s1, the harvesting distance was 15 m, and the corresponding feeding rates were 8e10 kg s1 for rice and 7e8.5 kg s1 for wheat. An oil skin was used to collect the total material escaping from the end of the cleaning sieve, and the entrained free grains were cleaned out by hand (cleaning loss). The tests were repeated twice for each parameter. It was found that the proportional relationship mainly depended on the grain physical characteristics and the cleaning operating parameters; the effect of forward velocity on the proportional relationship was not significant. Because the rice grain was lighter and the MOG/Grain mass ratio was larger, the proportional relationship of rice was slightly less than for wheat. From comprehensive analysis of the tests results, the average values of proportional relationships were about 0.11 for rice and 0.14 for wheat.
3.2.
Results and discussion
Based on the number of seeds counted by the sensor and the average proportional relationship, total grain cleaning losses were calculated. For the same operating parameters, Table 2 gives the error analysis results of grain cleaning losses obtained by the sensor and by manual. It was found that the
relative measurement error of rice cleaning loss was <10%, and the relative measurement error of wheat cleaning loss was a little higher. It was known that the moisture content and the MOG/ Grain mass ratio of the wheat were lower and the grain surface was smoother; these factors were beneficial to improve the cleaning performance, so the wheat cleaning loss ratio was <0.5% in general. The process of grain cleaning is complex and it is affected by the vibration parameters of the cleaning sieve, cleaning flow field and the grain physical characteristics. The motion of grain escaping from the outlet of the cleaning sieve is a stochastic process, and there are some variations in the proportional relationship between the counted grains and the total cleaning loss. For wheat # 2 tests, the total number of lost grains in the harvesting area 4.6 m 15 m was in the range 3000e4000, and only 500e600 grains were detected by sensors. Small variations in the number of detected grains will lead to a larger relative error, this is why the relative measurement error increased to 14.09%, and the absolute measurement error was limited to 0.05%. In addition, small stones, or MOG, ejected from sieve at high speed and impacting on the PVDF films can all possibly influence the measurement results. They will lead to a reduction in monitoring accuracy in the field.
4.
Conclusions
A grain impact sensor, utilising PVDF films and floating raft damping structure, was designed to monitor grain losses in the field. Based on the dynamic analysis of the sensor and the analysis of the vibration interferences, the sensor resonances were calculated. It was found that the amplitude of acceleration generated by the vibration of the combine harvester could be >1500 m s2. Therefore, machine vibration was an important interference factor that reduced sensor accuracy. By using a floating raft damping structure, the acceleration amplitude and corresponding frequency spectrum of the PVDF films could be suppressed. An appropriate increase in the stiffness of the upper isolator can increase the attenuation speed of resonance wave. A signal processing circuit composed of
b i o s y s t e m s e n g i n e e r i n g 1 1 2 ( 2 0 1 2 ) 2 2 7 e2 3 5
charge amplifier, low-pass filter, absolute value amplifier, envelope detector and voltage comparator in series was used to detect grain impact signals. The detection time of a grain impact was <2.5 ms. Sensors were installed at the end of the sieve of a combine harvester and cleaning loss monitoring tests were carried out in rice and wheat fields. The results indicated that the relative measurement error was <15%.
Acknowledgements This research was supported by the National HighTechnology Research and Development Program of China (863Program) (No. 2010AA101402), China Postdoctoral Science Foundation (No. 20110490124), Postdoctoral Science Foundation of Jiangsu Province (No. 1102131C) and Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PADP).
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