Intelligent Diagnosis for Aero-engine Wear Condition Based on Immune Theory

被引：0

作者：

Ma, Anxiang ^{[1
]}

Li, Yanjun ^{[1
]}

Cao, Yuyuan ^{[1
]}

An, Gang ^{[1
]}

Wang, Zhenyu ^{[1
]}

机构：

[1] Nanjing Univ Aeronaut & Astronaut, Coll Civil Aviat, Nanjing, Jiangsu, Peoples R China

来源：

PROCEEDINGS OF 2014 PROGNOSTICS AND SYSTEM HEALTH MANAGEMENT CONFERENCE (PHM-2014 HUNAN) | 2014年

关键词：

aero-engine; fault diagnosis; artificial immune theory; oil analysis; wear; SYSTEM;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Based on the traditional oil monitoring technology and combined with the artificial immune system's advantages, such as adaptive characteristic, learning and memory characteristic and recognition characteristics, an intelligent diagnosis method for aero-engine wear condition is proposed. The method uses negative selection principle of artificial immune theory to build detectors, and then uses fault samples to train and evolve mature detectors. So the typical information of aero-engine wear conditions is stored in the detectors. Wear failure of the system can be found through the activated detectors. The results of sample data analysis demonstrate that the method has strong ability to recognize aero-engine wear faults.

引用

页码：678 / 682

页数：5

共 7 条

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