Fault Diagnosis of Aero-engine Based on Support Vector Machines

摘要：

The aero-engine has a complex structure, with little and nonlinear fault data, in this paper, it shows a type of fault diagnosis approach based on Support Vector Machine (SVM) combining the characteristic of aero-engine fault data. In addition, during the Directed Acyclic Grap~(1) multiclass classify algorithm, firstly computing the Class Mean Value21 of example data, then get the classify priority level of fault type, construct the multiclass classify machine with the type of binary tree according to priority level. Under test, the approach is reasonable, and has better diagnosis speed and accuracy comparing with other classifying methods.

关键词： fault diagnosis support vector machine multiclass classify

作者: CHEN Mingzhu HUANG Min

作者单位: School of Reliability and Systems Engineering, Beijing University of Aeronautics and Astronautics, P.R.China, 100191

会议类型: 国际会议

会议名称: The 3rd International Institute of Statistics & Management Engineering Symposium(2010 国际统计与管理工程研讨会 IISMES)

会议地点: 威海

会议语种:英文

页码: 201-204

在线出版日期: 2010-07-24（万方平台首次上网日期，不代表论文的发表时间）