基于EMD的联合收获机籽粒损失监测传感器设计与试验

Design and Experiment of Corn Combine Harvester Grain Loss Monitoring Sensor Based on EMD

玉米清选损失监测受清选脱出物种类多样、环境噪声复杂等影响严重,为了解决清选损失监测精度差、效率低的问题,设计了一款基于最小能量准则EMD(Empirical mode decomposition)去噪方法的清选损失监测传感器,实现了对采集信号中的振动、工噪和杂余等信号分离。利用Matlab仿真对模拟信号进行去噪,与小波去噪、低通滤波法和移动平均法3种去噪方法相比,基于最小能量准则EMD去噪方法在不同信噪比下均方根误差(RMSE)最小,为0.1698,信噪比(SNR)最高,为12.7453,处理后的信号最接近原始信号。为验证该方法的实用性,以籽粒损失率分别为0、5%、10%、15%和20%的冲击样本开展损失率监测传感器台架试验,结果表明:该传感器最小检测误差为1.8%,最大检测误差为3.9%,对比小波去噪、低通滤波法和移动平均法3种去噪方法所得试验数据,最小能量准则EMD去噪方法的平均误差分别减小了2.12、4.40、6.52个百分点,与仿真试验结果一致。该研究对于提高玉米清选损失率检测精度特别是信号处理过程中去噪方法的研究具有重要意义。

The current corn cleaning loss monitoring sensors are affected by various problems such as the variety of cleaning products and the complex environmental noise,and the monitoring accuracy is difficult to meet the actual needs.In order to solve this problem,a clearing loss monitoring sensor based on PVDF piezoelectric sensitive element was designed to separate the vibration,industrial noise and stray signals in the collected signal.A minimum energy criterion based on DSP electronic signal processing was proposed.The EMD denoising method used the decomposition order corresponding to the minimum energy point of the IMF component as the signal-to-noise boundary point.The amplitude discrimination circuit identified the impact signal and calculated the loss rate.In order to verify the feasibility of this method,the signal with Gaussian white noise was simulated for denoising.Compared with wavelet denoising,low-pass filtering and moving average,the Matlab simulation results showed that the EMD denoising method based on the minimum energy criterion had the smallest root mean square error(RMSE),the highest signal-to-noise ratio(SNR),and the processed signal was the closest to the original signal.Changing the signal-to-noise ratio of the original simulation signal further verified that the results obtained by this method were always optimal.In order to verify the accuracy of the method,the corn kernels and miscellaneous mixtures with loss rates of 0,5%,10%,15%and 20%were used as impact samples.Compared with the experimental data obtained by three denoising methods,wavelet denoising,low-pass filtering and moving average method,the average error of the minimum energy criterion EMD denoising method was reduced by 2.12 percentage points,4.40 percentage points and 6.52 percentage points,respectively.The research result was of great significance for improving the detection accuracy of corn cleaning loss rate,especially the research on denoising methods in the process of signal processing.