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A New Fault Diagnosis Method of Adaptive Demodulated Resonance Technique Based On Wavelet Packet in Multi-Information Domains

机译:基于小波包在多信息域中的自适应解调谐振技术的新故障诊断方法

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Fault information is incomplete while using a single information domain fault feature parameters to construct fault feature vector, and demodulated resonance technique have to predetermine resonant frequency and fixed center frequency also has its shortcomings, in order to solve these problems, a new fault diagnosis method is proposed of adaptive demodulated resonance technique based on wavelet packet in multi-information domains. The fault feature vector extracted from multi- information domains is described, signal processing flow of envelope demodulation based on denoising and filtering of wavelet packet is analyzed, the fault diagnosis method of adaptive demodulated resonance technique based on wavelet packet is given, and the method is applied to fault diagnosis of axial piston hydraulic pump. Experiment results show that multi-domain feature vector increases the completeness of the fault information, it is able to obtain good diagnosis effect, and the new fault diagnosis method is able to identify known and unknown faults resonance frequency automatically, the frequency range is narrow, the rate of diagnosis is high.
机译:使用单个信息域故障特征参数的故障信息是不完整的构建故障特征向量,并解调的谐振技术必须具有预定谐振频率和固定中心频率也具有其缺点,以解决这些问题,一个新的故障诊断方法是基于多信息域中小波包的自适应解调谐振技术提出。描述了从多信息域中提取的故障特征向量,分析了基于小波包的去噪和过滤的包络解调的信号处理流,给出了基于小波包的自适应解调谐振技术的故障诊断方法,方法是应用于轴向活塞液泵的故障诊断。实验结果表明,多域特征向量增加了故障信息的完整性,它能够获得良好的诊断效果,并且新的故障诊断方法能够自动识别已知和未知的故障共振频率,频率范围窄,诊断率很高。

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