Vibration fault diagnosis based on multivariate state evaluation and correlation analysis

HUANG Yangsen, WANG Yong, LIU Yunping, FENG Xiaojian

Journal of Vibration and Shock ›› 2024, Vol. 43 ›› Issue (17) : 269-277.

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PDF(4208 KB)
Journal of Vibration and Shock ›› 2024, Vol. 43 ›› Issue (17) : 269-277.

Vibration fault diagnosis based on multivariate state evaluation and correlation analysis

  • HUANG Yangsen, WANG Yong, LIU Yunping, FENG Xiaojian
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Abstract

A fault diagnosis method based on Multivariate State Evaluation Technology (MSET) and Correlation Analysis (CA) is proposed to address the issue of abnormal vibration warning and cause diagnosis for turbogenerator rotor in running state. Firstly, the residual error is calculated between the predicted value and the operating value in the current evaluation window based on MSET and Sliding Window Principle. Secondly, the residual error of the correlation coefficient between in the state matrix and in the current evaluation window is calculated. Thirdly, thresholds are set for the relative deviation mean or residual error of each parameter and the residual error of each correlation coefficient to extract the abnormal features. Finally, vibration warning and abnormal diagnosis are based on Euclidean Distance and the anomalous features. The fault diagnosis method is validated by the operation data of turbogenerators. The results show that the proposed diagnosis method is feasible and can extract more abnormal or fault features compared with the single parameter self-change evaluation or parameter correlation analysis. It has the ability to diagnose multiple faults, which is beneficial for anormal warning and improving the accuracy of diagnosis. 

Key words

MSET / CA / abnormal warning / fault diagnosis

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HUANG Yangsen, WANG Yong, LIU Yunping, FENG Xiaojian. Vibration fault diagnosis based on multivariate state evaluation and correlation analysis[J]. Journal of Vibration and Shock, 2024, 43(17): 269-277

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