基于故障字典和神经网络理论的故障诊断方法

鉴于传统的故障诊断方法对复杂系统或设备进行故障诊断时,有诊断速度慢、对多故障同时发生的情况难以准确定位等缺点,提出了基于故障字典法和神经网络理论的综合故障诊断方法;在叙述该综合诊断方法的基础上,以某型飞机自动驾驶仪飞控盒的主要故障为例,分析说明了运用该方法进行设备故障诊断的具体过程,并进行了仿真研究;实现了对此设备单故障和多故障的快速准确定位;结果表明该综合故障诊断方法解决此类故障诊断问题是有效的.

Fault Diagnosis Method Based on Trouble Dictionary Method and Artificial Neural Network Theory

The traditional fault diagnosis methods had the shortcomings that the diagnosis speed was slow and it was hard to accurately fix the faults taking place at one time when it was diagnosing the complicated system or equipment.The integrated fault diagnosis technology based on trouble dictionary method and the artificial neural network theory are introduced here.Then,with the major failure of certain mould aircraft autopilot's flying-controlled box as the example,the real diagnosis course and method are analyzed and explained,and so on,the simulation research is made.The high-speed diagnosis for one fault and some faults taking place at one time is realized.The results show that this failure diagnosis method is effective to solve the issue.