Measurement method and mathematical model for the seeding downforce of planter row unit
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Abstract
Appropriate and consistent seeding downforce can reduce the vibration of row units and improve the stability of sowing depth. Studies have shown that the existing real-time measurement methods are not suitable for precise control of downforce due to the poor universality of methods, inadequate stability and low accuracy of output. To solve these problems and promote the development and application of downforce control technology, a universal measurement method was adopted by replacing the pin shaft of the limit block with the axle pin sensor. The mechanical analysis and design selection methods of the axle pin sensor were studied, which could provide a reference for the design of pin sensor with similar structure in the future. Based on the analysis of the motion of a gauge wheel, a relationship model between the seeding downforce and the sowing depth was established, which pointed out that the angle of limit shank was an important factor affecting the accuracy of downforce measurement. Then a sowing depth measurement device based on the angle of limit shank was designed and the corresponding depth measuring model was established to reduce the measurement error of single variable model with different sowing depth settings. Equipped with the sowing depth measurement device and the axle pin sensor, an indoor test platform was built and a modeling experiment with six kinds of sowing depth and seven levels of downforce was conducted. By using the polynomial approximation fitting method with Matlab, the sensor data was analyzed and a bivariate correction downforce measurement model was established with determination coefficient (R2) of 0.991 6 and root mean square error (RMSE) of 28.88 N. To accurately evaluate the predictive performance of the model, a validation test with another three sowing depth settings and six downforce values was designed and carried out. The results showed that the maximum absolute value of prediction error was 44.13 N and the maximum relative prediction error was 3.28% with different sowing depth settings, which indicated that the downforce measurement model had good universality and accuracy. Furthermore, to analyze the frequency composition of dynamic change of seeding downforce caused by collision and impact during seeding operation, a field experiment of two-factor split plot was carried out with tillage mode and speed as experimental factors, and the data was collected by an electronic control unit (ECU) with the sample frequency of 200 Hz. Spectrum analysis of the data by discrete Fourier transform (DFT) showed that the time-domain variation of downforce was sharper at higher planting speed and a larger margin of downforce occurred in no-tillage field, which led to the increase of high-frequency components. Besides that, the main frequency amplitude of downforce vibration decreased with the increase of planting speed, whose maximum value was at 4 km/h, corresponding to 219.1 N and 161.4 N for the no-tillage field and the rotary tillage field respectively. The results of power spectral density (PSD) analysis of downforce signal showed that the main frequency amplitude and peak value of PSD in the no-tillage field were larger than that in the rotary tillage field. Moreover, the vibration frequency was less affected by tillage mode and planting speed, mainly concentrated in 0-1 Hz, which could provide a reference for low-pass filtering of signals in downforce control. The study can lay a foundation for precise control of seeding downforce.
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