Feature Selection Method for Hydraulic System Faults Diagnosis Based on GA-PLS

摘要：

　　Feature selection is a key step in hydraulic system fault diagnosis.Some of the collected features are unrelated to classification model,and some are high correlated to other features.These features are harmful for establishing classification model.In order to solve this problem,genetic algorithm-partial least squares (GA-PLS) is proposed for selecting the representative and optimal features.K nearest neighbor algorithm (KNN) is used for diagnosing and classifying hydraulic system faults.For expressing better performance of GA-PLS,the original data of a model engineering hydraulic system is used,and the results of GA-PLS are compared with all feature used and GA.The experimental results show that,the proposed feature method can diagnose and classify hydraulic system faults more efficiently with using fewer features.

关键词： hydraulic system fault diagnosis feature selection genetic algorithm-partial least squares (GA-PLS)

作者: Sheng Li Peilin Zhang Bing Li

作者单位: Department 1st, Ordnance Engineering College Shijiazhuang 050003, China

会议类型: 国际会议

会议名称: the 2010 International Conference on Frontiers of Manufacturing and Design Science(第一届制造与设计科学国际会议(ICFMD 2010))

会议地点: 重庆

会议语种:英文

页码: 1130-1134

在线出版日期: 2010-12-11（万方平台首次上网日期，不代表论文的发表时间）