关键词: 涡轮风扇发动机;发动机空气系统部件;故障诊断;人工神经元网络

Abstract: In order to overcome the convergent difficulty of BP algorithm, a new learning rule of BP algorithm named hybrid rule is proposed.Normalizing the neural net input by its modulus, a fault library with fault magnitude and a BPN which can diagnosis the turbofan gas path component faults quantitatively are built successfully. A validation of the data of noisy measurements and the real engine ground test is made. The diagnostic results show that the BPN can quantify the magnitude of deterioration of the various engine components, detect the multiple faults and has robust adaptation of random error in measurement system.

Key words: Turbofan engine;Engine air system component;Fault diagnosis;Artificial neural network