Rotor rubbing diagnosis method based on fusion of time-frequency features of blade tip clearance

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Journal of Vibration and Shock ›› 2024, Vol. 43 ›› Issue (23) : 94-101.

GU Zhaopeng1,2, WAGN Weimin1,2, LIU Bingcheng2, MI Kejia2

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Abstract

High-end turbomachinery represented by aero-engine and shipboard gas turbine in high efficiency, large maneuvering flight and other working conditions, the internal structure tends to be compact and complex, so that the probability of internal rotor stator rubbing increases, due to the internal less measurement points, difficult to monitor, often difficult to accurately find rubbing faults in a timely manner. In this paper, we propose a rotor rubbing fault diagnosis method by fusing the time-frequency characteristics of the blade tip clearance. Firstly, we obtain the Blade Tip Clearance (BTC) sequence through the blade tip vibration-clearance composite sensor, and then we evaluate the abnormality of the BTC sequence through the machine learning algorithm; if there is an abnormal alarm, we carry out Fourier decomposition of the abnormal signals and summarize the time-frequency energy spectrum of the components. Finally, the occurrence of faults is determined by the rubbing bands in the time-frequency energy spectrum. The experimental results show that the machine learning model is able to diagnose the rotor in real time after applying short-time and continuous rubbing conditions, and the proposed method can completely separate the occurrence of the two types of rubbing and the process of continuous rubbing that is applied slowly and ends quickly after the alarm. Comparison with the rotor vibration signal shows that the method can obtain the BTC and sense rotor rubbing faults through the magazine measuring point, realizing "one sensor and many messages", which provides a new method for the condition monitoring and health management of turbomachinery.

Key words

blade tip sensing / rubbing faults / machine learning / Fourier decomposition / blade tip clearance (BTC)

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GU Zhaopeng1, 2, WAGN Weimin1, 2, LIU Bingcheng2, MI Kejia2. Rotor rubbing diagnosis method based on fusion of time-frequency features of blade tip clearance[J]. Journal of Vibration and Shock, 2024, 43(23): 94-101

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