Wear fault analysis of centrifugal pump impeller based on multi-source signal fusio
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摘要: 针对离心泵故障信号易被噪声淹没、数据分析困难的问题,提出了一种基于多源信号融合的离心泵叶轮磨损故障分析方法。采集离心泵叶轮正常状态和磨损状态下蜗壳、出水口和底座3处的振动信号及原动机接线端的电信号;采用小波包分解提取振动信号的特征频段,通过横向比较各频段能量值确定底座可作为最佳检测点,通过纵向比较各频段能量值以缩小频率分析范围;在缩小频率分析范围的基础上,采用线性调频Z变换对原动机接线端的电信号进行频谱分析,将故障特征频率与3次谐波频率分离,从而精确提取到故障特征频率。试验结果验证了该方法的有效性。Abstract: In view of problems that fault signal of centrifugal pump is easily submerged by noise and data analysis is difficult, a wear fault analysis method of centrifugal pump impeller based on multi-source signal fusion was proposed. Three vibration signals of volute, outlet and base of centrifugal pump, and electrical signals of prime mover terminal are collected when centrifugal pump impeller is in normal condition and wear state. Wavelet packet decomposition is used to extract characteristic frequency bands of the vibration signals, it is determined that the base can be used as the best detection point by laterally comparing energy values of each frequency band, and frequency analysis range is narrowed by longitudinally comparing the energy values of each frequency band. Based on narrowed frequency analysis range, chirp Z transform is used to analyze electrical signals of prime mover terminal and separate fault characteristics frequency and the third harmonic frequency, so as to extract fault characteristic frequency accurately. Test result verifies effectiveness of the method.
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