Fault condition prognostic for rotating machinery based on new WEEMD and adaptive boosting regression algorithm

Pei Yao, Zhongsheng Wang, Hongkai Jiang, Zhenbao Liu

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

This paper addresses a fault condition prognostic for sudden failure of rotating machinery. The proposed method is based on the utilization of feature extraction by using signal processing technique, and adaptive boosting (adaboost) regression algorithm. In this paper, we decompose vibration signal using wavelet packet decomposition and ensemble empirical mode decomposition (WEEMD), and successively we utilize the high order spectrum slice to describe the process of a fault evolution, and finally adaptive boosting regression algorithm is adopted for predicting the fault conditions. Experimental results of rotating machinery show that adaboost regression is pronounced comparing with other regression methods for fault condition prognostics.

源语言英语
主期刊名Proceedings of the 3rd IASTED Asian Conference on Modelling, Identification, and Control, AsiaMIC 2013
58-62
页数5
DOI
出版状态已出版 - 2013
活动3rd IASTED Asian Conference on Modelling, Identification, and Control, AsiaMIC 2013 - Phuket, 泰国
期限: 10 4月 201312 4月 2013

出版系列

姓名Proceedings of the 3rd IASTED Asian Conference on Modelling, Identification, and Control, AsiaMIC 2013

会议

会议3rd IASTED Asian Conference on Modelling, Identification, and Control, AsiaMIC 2013
国家/地区泰国
Phuket
时期10/04/1312/04/13

指纹

探究 'Fault condition prognostic for rotating machinery based on new WEEMD and adaptive boosting regression algorithm' 的科研主题。它们共同构成独一无二的指纹。

引用此