基于自适应阈值函数的铡草机振动信号去噪  

Wavelet Threshold De-noising Algorithm Based on Adaptive Threshold Function

作　　者：王晓蓉[1] 王海超 王春光[1] Wang Xiaorong;Wang Haichao;Wang Chunguang(College of Mechanical and Electrical Engineering,Inner Mongolia Agricultural University,Hohhot 010018,China)

机构地区：[1]内蒙古农业大学机电工程学院,呼和浩特010018 [2]内蒙古农业大学能源与交通工程学院,呼和浩特010018

出　　处：《农机化研究》2021年第11期14-18,23,共6页Journal of Agricultural Mechanization Research

基　　金：国家自然科学基金项目(50865005);国家重点研发计划重点专项(2016YFD0701704)。

摘　　要：针对传统小波软、硬阈值函数对铡草机振动信号去噪的不足,采用一种自适应阈值函数去噪算法,实现铡草机振动信号降噪。该方法根据小波分解原理,采用分层阈值,同时通过参数调整阈值函数,在信号分解小尺度上滤除大量噪声分量,而在大尺度上去除噪声分量的同时尽量保留有用信号分量。为验证本文算法有效性,采用软、硬阈值函数法与本文算法对模拟信号和铡草机振动信号进行对比试验,结果表明:本文算法优于2种传统算法,在滤除噪声的同时很好地保留了原信号特征。Aiming at the shortcomings of traditional wavelet soft and hard threshold functions to de-noise the vibration signal of chaff cutters, the paper adopted an adaptive threshold function de-noising algorithm to achieve noise reduction of the vibration signal of chaff cutters.According to the principle of wavelet decomposition, this method used layered thresholds and adjusted the threshold function through parameters to filter out a large number of noise components on the small scale of signal decomposition,while removing the noise components on a large scale while trying to retain useful signal components. In order to verify the effectiveness of the algorithm in this paper,the soft and hard threshold function method and the algorithm in this paper were used to compare the analog signal and the vibration signal of the guillotine machine. The experimental results showed that the algorithm in this paper was superior to the two traditional algorithms,and it retained the original signal characteristics while filtering noise.

关 键 词：铡草机 小波去噪 阈值函数 分层阈值 

分 类 号：S817.121[农业科学—畜牧学]