Fault Diagnosis System for Reciprocating Air Compressor Based on Support Vector Machine

摘要：

Reciprocating air compressors structure is complex, and it has various exaltation sources when running, moreover, there are a few fault samples in actual fault diagnosis, so it is difficult to implement intelligent diagnosis. Support Vector Machine based on Statistical Learning Theory just overcomes this deficiency, and it provides a new approach for diagnosis technology to develop into intelligent diagnosis. The application of Support Vector Machine on fault diagnosis for reciprocating air compressor and a concrete implementation scheme are discussed in this paper. A fault diagnosis system for reciprocating air compressor is established, and the vibration signals of rolling bear in reciprocating air compressors crankcase are simulated in a test-bed. The test result shows that this system has strong adaptability for reciprocating air compressor diagnosis of a few samples and could recognize fault rapidly and accurately.

关键词： reciprocating air compressor Support Vector Machine fault diagnosis

作者: Fu Sheng Li Jing Zhang Yabin

作者单位: College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technolo Beijing Wellincontrol Technology Development Co,.Ltd Technology Department Beijing 100086

会议类型: 国际会议

会议名称: 2009 International Workshop on Information Security and Application(2009 信息安全与应用国际研讨会)

会议地点: 青岛

会议语种:英文

页码: 546-549

在线出版日期: 2009-11-21（万方平台首次上网日期，不代表论文的发表时间）