基于局部Hilbert边际谱的自动倾斜器轴承故障诊断

Fault Diagnosis Method of Swash-plate Bearing Based on Local Hilbert Marginal Spectrum

针对直升机操纵系统重要承力部件自动倾斜器轴承健康监测与故障诊断的需求,研究相应健康监测技术及其故障诊断方法,从而为直升机结构健康监测状态评估与使用管理提供依据。经验模态分解方法作为一种自适应时频分析方法,非常适用于处理复杂非平稳信号,提出了一种基于局部Hilbert边际谱的直升机自动倾斜器轴承故障诊断方法。该方法首先将振动信号进行小波包分解;然后对重构降噪信号采用Hilbert变换进行包络分析得到包络信号;最后对包络信号进行EMD分解,选取有效IMF集计算局部Hilbert边际谱,提取故障特征。在此基础上,构建了某型直升机自动倾斜器故障诊断试验系统。研究表明,该诊断方法合理、可行。

According to the demand of health monitoring and fault diagnosis on the important load bearing components swash plate bearing of the helicopter handing system, it is necessary to study the corresponding health monitoring technolo- gy and its fault diagnosis method, to provide the assessment reference for structure health state and the usage management of the helicopter. Empirical Mode Decomposition （EMD） method as an adaptive time-frequency analysis method which is very suitable for dealing with non-stationary signal, and a fault diagnosis method is given for the helicopter swash plate bear- ing based on the local Hilbert marginal spectrum. Firstly, wavelet packet is used for decomposition of the vibration signal. Then, the Hilbert transform is used for envelope analysis to obtain the envelope signal of the de-noised reduction signal. Fi- nally, the result is decomposed by EMD, and the effective IMF is selected to calculation the local Hilbert marginal spectrum and extract the fault feature. On this basis, a fault diagnosis test system for a type of helicopter swash plate bearing is con- structed. Research results show that the method is reliable and applicable.