Fault Diagnosis of Elevator Braking System Based On Wavelet packet algorithm and Fuzzy Neural Network

摘要：

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 Bspline 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.

关键词： wavelet packet fuzzy neural network fault diagnosis elevator braking system.

作者: Peiliang Wang Wuming He Wenjun Yan

作者单位: School of Information Engineering,Huzhou Teachers College,Huzhou 313000,Zhejiang,China Institute of School of Information Engineering,Huzhou Teachers College,Huzhou 313000,Zhejiang,China Institute of Electrical Automatic Control,Zhejiang University,Hangzhou 310027,Zhejiang,China

会议类型: 国际会议

会议名称: 2009 9th International Conference on Electronic Measurement & Instruments(第九届电子测量与仪器国际会议 ICEMI2009)

会议地点: 北京

会议语种:英文

页码: 4256-4259

在线出版日期: 2009-08-16（万方平台首次上网日期，不代表论文的发表时间）