基于人工神经网络的飞机发动机故障诊断模型构建研究

Research on Construction of Aircraft Engine Fault Diagnosis Model Based on Artificial Neural Network

发动机属于飞机中的核心结构,其维修费用占比较高,为了降低飞机安全事故的发生和节约成本的目的,对飞机发动机的故障进行诊断和检测属于重要任务。由于人工神经网络功能强度,能够处理复杂的发动机故障诊断问题,于是文章研究了基于人工神经网络的飞机发动机故障诊断模型构建,并将模型应用于发动机故障诊断中发现,相比于BP神经网络模型,人工神经网络模型具有更好的应用效果,能够提高故障诊断的效率和准确性。

The engine belongs to the core structure of the aircraft,and its maintenance costs are relatively high.In order to reduce the occurrence of aircraft safety accidents and save costs,it is an important task to diagnose and detect the failure of the aircraft engine.Due to the artificial neural network's functional strength,it can handle complex engine fault diagnosis problems,so the paper studies the construction of aircraft engine fault diagnosis model based on artificial neural network,and applies the model to engine fault diagnosis,compared with BP neural network model,the artificial neural network model has better application effect and can improve the efficiency and accuracy of fault diagnosis.