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Fault diagnosis of elevator braking system based on wavelet packet algorithm and fuzzy neural network

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3 Author(s)
Peiliang Wang ; Sch. of Inf. Eng., Huzhou Teachers'' Coll., Huzhou, China ; Wuming He ; Wenjun Yan

Aiming at the fault features of the elevator braking system, the basic characteristics of three faults types are analysised. By detecting the brake shoe gap-time signals in the process of braking, the fault signals are decomposed using wavelet packet, and the signal characteristics of 8 frequency components from the low-frequency to high-frequency in the third layer are extracted. Then taking advantages of B-spline and fuzzy neural networks to set up the elevator braking system fault diagnosis model, the 8 obtained eigenvalue are used as the model inputs for fault diagnosis. The result shows that this method is effectual and applied.

Published in:

Electronic Measurement & Instruments, 2009. ICEMI '09. 9th International Conference on

Date of Conference:

16-19 Aug. 2009

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