基于集合经验模态分解与样本熵联合小波的固肥流量微波信号去噪方法  

Microwave signal denoising method for solid fertilizer flow based on combined empirical mode decomposition and sample entropy joint wavelet

作　　者：张俊宁 赵礼豪 陈宁波 杨立伟[2] 刘刚[2] 吕树盛[3] Zhang Junning;Zhao Lihao;Chen Ningbo;Yang Liwei;Liu Gang;Lyu Shusheng(School of Mechanical and Electrical Engineering,Beijing Information Science&Technology University,Beijing 100192,China;Key Laboratory of Smart Agriculture System Integration of China Agricultural University,Beijing 100083,China;Chinese Academy of Agricultural Machinery Industry Technology Service Center,Beijing 100083,China)

机构地区：[1]北京信息科技大学机电工程学院,北京100192 [2]中国农业大学智慧农业系统集成研究教育部重点实验室,北京100083 [3]中国农业机械化科学研究院集团有限公司行业技术服务中心,北京100083

出　　处：《电子测量与仪器学报》2024年第11期118-125,共8页Journal of Electronic Measurement and Instrumentation

基　　金：国家自然科学基金(32371989);国家农业重大科技项目子课题(NK2022180603-01)项目资助。

摘　　要：针对使用多普勒微波传感器测量颗粒肥料流量时,施肥机运作产生的振动和外部多种干扰导致采集到的信号失真的问题,首先对小波分析与卡尔曼滤波算法进行寻找最优参数。通过对比两种算法的去噪效果,提出一种基于集成经验模态与样本熵联合小波的去噪算法。并以史丹利15-15-15颗粒肥为实验对象,将多普勒微波传感器等检测系统部署在施肥机上,采集颗粒肥料质量流量信号进行算法效果实验验证。结果表明:与原始信号相比,优化增益系数后的卡尔曼滤波算法,平均信号信噪比提升了3.548 dB。优化小波去噪参数后的小波分析算法,平均信噪比提高了7.184 dB。结合优化去噪参数后的小波分析联合集合经验模态与样本熵的去噪算法,去噪后的信号平均信噪比提高了7.899 dB,平均均方根误差降低了0.184,该算法对用多普勒微波传感器测量颗粒肥料质量流量信号的去噪处理上具有显著的优势。When using a Doppler microwave sensor to measure the flow of granular fertilizer,the vibration generated by the operation of the fertilizer applicator and various external disturbances can cause the collected signal to be distorted.This article first explores the optimal parameters for wavelet analysis and Kalman filtering algorithms.By comparing the denoising effects of the two algorithms,a denoising algorithm based on the combination of empirical mode decomposition and sample entropy combined with wavelet is proposed.Taking Stanley 15-15-15 granular fertilizer as the experimental object,the detection system such as Doppler microwave sensor is deployed on the fertilizer applicator to collect the mass flow signal of granular fertilizer for algorithm effect experimental verification.The results indicate that,compared to the original signal,the average signal-to-noise ratio of the Kalman filtering algorithm improved by 3.548 dB after optimizing the gain coefficient.After optimizing the wavelet denoising parameters,the average SNR of the wavelet analysis algorithm increased by 7.184 dB.When combining the optimized wavelet analysis with the denoising algorithm of integrated empirical mode decomposition and sample entropy,the average SNR of the denoised signal increased by 7.899 dB,while the average root mean square error decreased by 0.184,this algorithm demonstrates significant advantages in denoising the mass flow rate signals of granular fertilizers.

关 键 词：固肥 多普勒微波 去噪 小波分析 集合经验模态 样本熵 

分 类 号：TN713[电子电信—电路与系统] S237[农业科学—农业机械化工程]