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基于MED和LMD的自动倾斜器轴承广义Shannon熵谱分析
引用本文:张先辉,李新民,金小强.基于MED和LMD的自动倾斜器轴承广义Shannon熵谱分析[J].航空动力学报,2019,34(4):764-771.
作者姓名:张先辉  李新民  金小强
作者单位:中国航空工业集团有限公司中国直升机设计研究所直升机旋翼动力学重点实验室,江西景德镇,333001;中国航空工业集团有限公司中国直升机设计研究所直升机旋翼动力学重点实验室,江西景德镇,333001;中国航空工业集团有限公司中国直升机设计研究所直升机旋翼动力学重点实验室,江西景德镇,333001
基金项目:航空科学基金(2013ZD02001)
摘    要:针对轴承信号微弱故障特征易被强背景噪声淹没的问题,提出采用最小熵反褶积,通过逆滤波器最优化设计,对目标信号进行降噪处理,其峭度值提高了约3.8倍,增强了信号的微弱故障特征;针对非平稳非线性信号频率成分复杂难以解调的问题,提出采用局部均值分解(LMD)和峭度-相关系数筛选准则,其可对非平稳非线性信号进行自适应分解和最优重构,提高了信号的信噪比;针对信号耦合调制及边频突出的问题,通过引入广义Shannon熵进行包络谱带内降噪处理,信号一阶故障特征调制频率与故障特征频率的幅度比降低了24%~43%。通过实验室信号及某型直升机自动倾斜器轴承故障诊断地面试验的分析结果验证了该方法的合理性和可行性。 

关 键 词:自动倾斜器轴承  故障诊断  最小熵反褶积(MED)  局部均值分解(LMD)  广义Shannon熵谱
收稿时间:2018/1/10 0:00:00

General Shannon entropy spectrum of swash-platebearing based on MED and LMD
Abstract:To overcome the difficulty of swash-plate bearing early fault features of the helicopter easily immerged in strong background noise, a method based on the minimum entropy deconvolution was proposed through the optimization design of the inverse filter, its kurtosis value was increased by about 3.8 times, the vibration signal was denoised and the weak fault characteristics of vibration signal were enhanced. By using local mean decomposition (LMD) and kurtosis-correlation coefficient criterion to settle the issue of non-stationary and nonlinear signal frequency components of complex demodulation, it can adaptively decompose and optimally reconstruct the non-stationary and nonlinear signal, and improve the signal-to-noise ratio of vibration signal. To settle the issue of coupling modulation and sideband highlighting, through noise reduction in envelope spectrum by introducing the general Shannon entropy, the amplitude ratio of the first-order fault characteristic modulation frequency to the fault characteristic frequency was reduced by about 24%-43%. The diagnosis research results of laboratory signal and the fault diagnosis test system for a type of helicopter swash plate bearing verify that the method is reliable and applicable.
Keywords:swash-plate bearing  fault diagnosis  minimum entropy deconvolution(MED)  local mean decomposition(LMD)  general Shannon entropy spectrum
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