基于BP神经网络与瞬态响应分析的电路故障诊断技术

Circuit Fault Diagnosis Based on Pattern Recognition and Transient Response Analysis

论文研究了基于模式识别原理的人工神经网络电路故障诊断方法,结合仿真技术,应用瞬态响应分析把数模混合信号电路中数字电路部分与模拟电路部分统一进行诊断,探讨了模拟电路和数字电路特性相差太大难于诊断的问题。针对具体电路,利用MATLAB神经网络工具箱对电路进行仿真,结果表明,利用所提出的实现方法对模拟及数模混合电路进行了较准确的诊断,达到了预期的目的。

This paper studies the circuit fault diagnosis approach based on artificial neural networks.Combined with simulation technology,a new unified method to test mixed-signal circuits is presented.Using Transient Response Analysis, the method needn’t partition the mixed-signal circuits into digital units and analog units and solves the difficulty that the characteristics between analog circuits and digital circuits are too different to test.Simulating for the real circuit fault diagnosis example by the neural network toolbox of MATLAB,the obtained results showed that the proposed method in the paper is feasible.