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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。
Aiming at the demand of the health monitoring and fault diagnosis of the automatic tiller bearings of the important load-bearing parts of the helicopter control system, the corresponding health monitoring technology and its fault diagnosis method are studied, which can provide the basis for the status assessment and usage management of helicopter structural health monitoring. As an adaptive time-frequency analysis method, empirical mode decomposition method is very suitable for dealing with complex non-stationary signals. A fault diagnosis method of helicopter automatic recliner bearings based on local Hilbert marginal spectrum is proposed. Firstly, the vibration signal is decomposed by wavelet packet. Then, the envelope signal is obtained by Hilbert transform of the reconstructed noise reduction signal. Finally, the envelope signal is decomposed by EMD. Local Hilbert marginal spectrum is selected by the effective IMF set to extract Fault characteristics. On this basis, a fault diagnosis test system for a helicopter automatic tilter is constructed. Research shows that the diagnostic method is reasonable and feasible.