Title :
Fault diagnosis of elevator braking system based on wavelet packet algorithm and fuzzy neural network
Author :
Wang, Peiliang ; He, Wuming ; Yan, Wenjun
Author_Institution :
Sch. of Inf. Eng., Huzhou Teachers´´ Coll., Huzhou, China
Abstract :
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.
Keywords :
braking; eigenvalues and eigenfunctions; fault diagnosis; fuzzy neural nets; lifts; wavelet transforms; B-spline; brake shoe gap-time signals; eigenvalue; elevator braking system; fault diagnosis model; fuzzy neural network; wavelet packet algorithm; Eigenvalues and eigenfunctions; Elevators; Fault detection; Fault diagnosis; Footwear; Frequency; Fuzzy neural networks; Signal processing; Spline; Wavelet packets; elevator braking system; fault diagnosis; fuzzy neural network; wavelet packet;
Conference_Titel :
Electronic Measurement & Instruments, 2009. ICEMI '09. 9th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-3863-1
Electronic_ISBN :
978-1-4244-3864-8
DOI :
10.1109/ICEMI.2009.5274152