Intelligent diagnosis for aero-engine wear condition based on immune theory

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 aeroengine 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.