基于LSTM的航空发电机整流电路诊断技术

整流电路是航空发电机的重要组成部分，存在故障频发且维修困难等问题。为对电励磁双凸极发电机(DSEG)的整流电路进行故障诊断，研究了一种基于长短时记忆(LSTM)网络的故障诊断方法。首先，采集多种故障模式下发电机的三相电枢电流信号。其次，利用不同的信号处理方法处理故障信号以获取故障特征信息。然后，将获得的故障特征数据分为训练和测试样本输入LSTM网络进行故障分类。最后,计算并分析诊断结果。仿真与试验结果表明所提方法具有良好的故障诊断效果。

Diagnosis Technology of Aero-Generator Rectifier Circuit Based on LSTM

As an important part of aero-generator, rectifier circuit has many problems, such as frequent faults and difficult maintenance. In order to realize the fault diagnosis of doubly salient electro-magnetic generator (DSEG) rectifier circuit, a fault diagnosis method based on long short term memory (LSTM) network is studied. Firstly, the three-phase armature current signals of the generator under various fault modes are collected. Secondly, different signal processing methods are used to process fault signals to obtain fault characteristic information. Then, the obtained fault characteristic data are divided into training and test samples and input to LSTM network for fault classification. Finally, the diagnosis results are calculated and analyzed. The simulation and experimental results show that the proposed method has a good fault diagnosis effect.