基于免疫理论的航空发动机磨损故障智能诊断

doi:10.7527/S1000-6893.2014.0357

Abstract

Abstract:

To meet the development requirements of intelligentization and accuracy for the aircraft engine wear fault diagnosis technology, an intelligent diagnosis method for aircraft engine wear fault is proposed based on the traditional oil monitoring technology, and this method is combined with the artificial immune system's (AIS) advantages, such as adaptive characteristic, learning and memory characteristic and recognition characteristics. Firstly, the method uses negative selection principle of artificial immune theory to build detectors. The optimized immune algorithm improves the initial detectors' representativeness and coverage. And then fault samples are used to train and generate mature detectors. So the typical information of aircraft engine wear fault is stored in the mature detectors, implementing effective learning and memory of the failure modes. Finally, wear fault of the aircraft engine can be found through the activated detectors. The case analytical results of the sample data demonstrate that the method has strong ability to recognize aircraft engine wear faults and it has very good monitoring effect to wear condition.

Key words: aircraft engine, fault diagnosis, immune system, oil analysis, wear

CLC Number:

V263.6
TK418

MA Anxiang, LI Yanjun, CAO Yuyuan, WANG Zhenyu, AN Gang. Intelligent diagnosis for aircraft engine wear fault based on immune theory[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2015, 36(6): 1896-1904.

References

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Intelligent diagnosis for aircraft engine wear fault based on immune theory

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