Cavitation induced vibration fault analysis of centrifugal pump based on MFDFA-BP under multi-sensor data

被引:0
作者
Liang X. [1 ]
Luo Y. [1 ]
Deng F. [1 ]
Gao G. [1 ]
Cao H. [1 ]
机构
[1] Jiangxi Provincial Key Lab of Precision Drive and Control, Nanchang Institute of Technology, Nanchang
来源
Zhendong yu Chongji/Journal of Vibration and Shock | 2022年 / 41卷 / 17期
关键词
BP neural network; centrifugal pump; detrended fluctuation analysis; fault diagnosis; multi-fractal; multi-sensor data;
D O I
10.13465/j.cnki.jvs.2022.17.029
中图分类号
学科分类号
摘要
Here, aiming at incompleteness of data measured by a single sensor and non-linearity and non-stationarity of centrifugal pump fault signals, a centrifugal pump cavitation induced vibration fault analysis method based on the multi-fractal detrended fluctuation analysis (MFDFA)and the back propagation (BP) neural network under multi-sensor data was proposed. Firstly, MFDFA method was used to analyze 8 types measured signals of centrifugal pump under 5 different working conditions, and extract multifractal spectrum feature parameters of Δf, α0, Δα, αminand αmaxfor forming fault characteristic vector. Combining with BP neural network, fault diagnosis of single sensor signalswas performed, and signals with better recognition rate were optimized to form the multi-sensor characteristic vector, and conduct the study on cavitation induced vibration faults of multi-sensor centrifugal pump. The results showed that the multifractal spectrum feature parameters extracted with MFDFA can correctly reflect operation state of centrifugal pump, andparameters of Δf, Δα and αmaxand have a better effect on fault classification; signals, such as, pump vibration, torque and motor vibration reflect fault essence more correctly; the accuracy rate of multi-sensor fault diagnosis model is more than 13% higher than that of a single sensor to provide a new method for state identification of different levels cavitation faultsof centrifugal pump. © 2022 Chinese Vibration Engineering Society. All rights reserved.
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页码:238 / 243and281
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