The Analysis of Fault Diagnosis for Rolling Bearings Based on Genetic Algorithm,Wavelet Transform and Neural Network

摘要：

Genetic algorithms-based global optimization, Wavelet analysis with data compression and feature extraction of features, Neural networks has the nonlinearity mapping and learning the advantages of reasoning, genetic algorithm (GA), wavelet (WA) and neural network (BP) algorithm combined, Used for rolling bearing fault . Examples show, using GA-WANN model fault diagnosis. The model has comparably fast, good robustness and accurate diagnosing abilities.

关键词： rolling bearing wavelet transform artificial neural network genetic algorithm fault diagnosis genetic algorithm - wavelet neural network

作者: Li Tian Ming-long Zhou Ling-chun Li Jing Wang

作者单位: AnHui Polytechnic University,Wuhu24100, Anhui Province, China AnHui Polytechnic University,Wuhu241000, Anhui Province, China

会议类型: 国际会议

会议名称: The 13th IEEE Joint International Computer Science and Information Technology Conference(2011年第13届IEEE联合国际计算机科学与信息技术会议 JICSIT 2011)

会议地点: 重庆

会议语种:英文

页码: 773-776

在线出版日期: 2011-08-20（万方平台首次上网日期，不代表论文的发表时间）