Name: Detection method of asynchronous motor bearing fault?
Application number: CN2007 1006 1633.3? Date of application: March 28th, 2007?
Gong (Announcement)No.: CN 10 1034038? Publication date (announcement): September 2007 12?
Main classification number: G 01M13/04 (2006+38+0)? Category classification:?
Classification number: G 01M13/04 (2006438+0); g 0 1r 3 1/34(2006.0 1)？
Priority:?
Applicant (patent right): North China Electric Power University; ?
Address: 07 1003 No.619, Yonghua North Street, Beishi District, Baoding City, Hebei Province?
Country and province code: Hebei; 13?
Inventor (Designer): Xu; Sun Yuling?
International application:
International announcement:?
Date of entry:?
Patent agency: Shijiazhuang Jike Patent and Trademark Office Co., Ltd.?
Agent: Li Xianmin; How about tall?
Division application number:?
Certification date:?
Abstract:?
The invention relates to an asynchronous motor bearing fault detection method, which belongs to the technical field of detection and is used for solving the problem of online detection of early faults of asynchronous motor bearings. The technical scheme is as follows: the acquired instantaneous stator current signal is is subjected to continuous thinning Fourier transform to obtain its fundamental wave, namely the reference signal us; then the instantaneous stator current signal IS is adaptively filtered according to the reference signal us and its frequency f 1; then the filtered output signal eT is subjected to continuous thinning Fourier transform to determine the ratio of the amplitude of the side frequency component of the current | F 1 MFV | to the fundamental wave component as the fault feature; and finally, the fault characteristic is obtained. The invention can detect early faults of bearings of various asynchronous motors online with high sensitivity and high reliability.
Sovereignty:
1, an asynchronous motor bearing fault detection method, which is characterized in that the instantaneous signal of stator current collected by connection is.
Fourier transform is continuously refined to get its fundamental wave, that is, the reference signal us, and then the instantaneous signal of stator current is analyzed according to the reference signal uS and its frequency f 1.
The signal is is adaptively filtered, and then the filtered output signal eT is subjected to continuous fine Fourier transform to determine the current | F 1 MFV | side frequency component.
And take it as a fault feature, and finally determine the fault index according to the detection threshold, and judge the axis according to the fault index.
Take the blame.
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Please look at the picture of the second patent: