基于Mallat算法的谷物流量信号小波去噪方法  

Wavelet denoising method for grain flow signal based on Mallat algorithm

作　　者：陈进[1] 王坤[1] 李耀明[2] 

机构地区：[1]江苏大学机械工程学院,镇江212013 [2]江苏大学现代农业装备与技术教育部重点实验室,镇江212013

出　　处：《农业工程学报》2017年第3期190-197,共8页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家十三五重点研发计划(2016YFD0702001)

摘　　要：针对联合收获机在复杂噪声背景作业过程中难以获取可靠的谷物流量信息的难题,提出了利用小波变换(wavelet transform,WT)对谷物流量传感器输出信号去噪处理方法。根据流量原始信号和噪声的频谱特性确定小波函数和分解尺度,将采集的流量原始信号通过Mallat算法进行小波分解,滤除高频噪声分量重构流量有效信号,由单片机AD通道对流量有效信号进行标定,标定试验后的传感器在不同谷物流量下累积质量最大相对误差为1.68%。利用北斗定位模块进行差分定位提高定位精度,测产装置信息由8051F单片机存储用以绘制农田作业产量图,将设计的测产系统安装在联合收获机上进行模拟水稻作业试验,试验结果表明:对流量传感器输出信号进行小波分解后,谷物流量测量相对误差最大为6.18%,平均相对误差为5.37%。通过对流量传感器输出原始信息进行小波变换,对比小波去噪前后信号的频谱曲线,验证了基于Mallat算法的流量信号去噪和流量有效信息重构方法的可行性和准确性,该研究可为研究农业机械复杂作业环境下原始信息去噪与有效信息重构提供参考。Aiming at the problem that combine harvester cannot obtain reliable grain flow information in complex noisebackground, wavelet transform （WT） is proposed to denoise the output signal of grain flow sensor. The method is as follows：using the LabVIEW data acquisition card to acquire the output signal of the grain flow sensor and analyzing theamplitude-frequency characteristics of signal, in which the energy-dominant frequency band is set as the grain effective signal,and the chaotic and the frequency band with flat amplitude change are set as the noise signal. The spectrum of original signaland noise is used to determine how to choose the wavelet function and decomposition scale. By analyzing theamplitude-frequency characteristics of the original signal, the energy-dominant center frequency in the grain flow is 40 Hz, andthe noise is distributed in 2 frequency bands, of which the signal energy attenuation is faster, the bandwidth distribution isnarrower and the change trend is consistent with the original signal in 500-600 Hz band, so the bands are the vibration noise ofthe yield platform. Above 800 Hz the signal changes slowly in energy attenuation, the bandwidth distribution is wide and thechanges are random, so the bands are the high-frequency noise of the yield platform. In the research, the yield measuringsystem is designed to obtain the yield information. The Mallat algorithm is applied to decompose and remove the noisecomponents of grain flow signal, the DB4 wavelet is chosen as the wavelet function and the decomposition scale is 6. Theeffective data of grain flow are reconstructed by wavelet and calibrated by the analog to digital converter channel ofmicrocomputer. The maximum relative error of the grain mass is 1.68% under different grain flow after calibration. Theposition data are obtained by the Beidou Navigation Satellite System （BDS） with the pseudo-range differential positiontechnology. The yield measuring system is installed on the combine harvester to simulate the rice operation experinaen

关 键 词：小波变换 算法 谷物 联合收获机 产量图 误差分析 

分 类 号：S225[农业科学—农业机械化工程]