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Rotating machinery fault source location method based on sensitive characteristic frequency band
Published:2022-10-20 author:TAN Yi, MA Bo, ZHANG Qiang-sheng. Browse: 1152 Check PDF documents

Rotating machinery fault source location method based on 
sensitive characteristic frequency band


TAN Yi1, MA Bo1,2, ZHANG Qiang-sheng3*

(1.College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing 100029, 

China; 2.Beijing Key Laboratory of High End Mechanical Equipment Health Monitoring and Self Recovery, Beijing University 

of Chemical Technology, Beijing 100029, China; 3.Nuclear and Radiation Safety Center, MEE, Beijing 100082, China)


Abstract: In the application of rotating machinery fault monitoring based on acoustic array, aiming at the problem of inaccurate fault source location caused by artificially determining the frequency range of acoustic array signal only based on expert experience, a fault source location method of rotating machinery based on sensitive feature frequency band was proposed. Firstly, according to the obvious periodic impact characteristics of the rotating machinery fault acoustic signal, the Protrugram method was used to determine the sensitive characteristic frequency band range of the acoustic array signal,and the sensitive characteristic frequency band signal was extracted. Then, the minimum variance distortionless response method was used to analyze the sensitive characteristic frequency band signal, calculating the sound field distribution of the plane where the rotating machinery was located, and make the sound field distribution map. The camera monitoring picture was combined with the sound field distribution map to identify the maximum sound source location, which was the fault source location. Finally, a fault simulation test was designed to verify the feasibility of the method. The research results show that the positioning error of this method for bearing faults and unbalance faults is not more than 0.10m, which can effectively determine the location of the fault source and realize the visualization of the fault source location of rotating machinery.

Key words:  mechanical operation and maintenance; acoustic signal monitoring; rotor unbalance fault; bearing fault; acoustic array signal frequency; sound field distribution map; minimum variance distortionless response(MVDR); signal impulse characteristics
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