238 / 2021-11-03 20:53:33
Hierarchical Diagnosis of Analog Circuit Fault Based on Neural Network Group
Analog circuits, Fourier Transform, Hierarch-ical diagnosis, Neural network group.
终稿
Xin Zhou / Sichuan Normal University
Xiaolian Zhang / Neijiang Normal University
Yintao Ou / Sichuan Normal University
Wenhai Liang / Sichuan Normal University

     This paper presents a new hierarchical fault diagnosis method of analog circuit based on back propagation (BP) neural network group. This method realizes soft fault and hard fault diagnosis of analog circuit. To improve the accuracy of automatic diagnosis of this method, a multi-feature parameter fusion preprocessing scheme is presented. The Fast Fourier Transform (FFT) is used to calculate the DC component, fundamental amplitude, fundamental phase angle, amplitude of second harmonic, phase angle of second harmonic and distortion of the time domain output signal,these feature data are used as the input of BP neural network group. The fault diagnosis performance of this method is verified by the simulation and test of the triode single-stage amplifier circuit. The results show that this method performs well on fault diagnose. The accuracy of simulation diagnosis is up to 95%, and the accuracy of test is up to 90%.

重要日期
  • 会议日期

    07月11日

    2023

    08月18日

    2023

  • 11月10日 2021

    初稿截稿日期

  • 12月10日 2021

    注册截止日期

  • 12月11日 2021

    报告提交截止日期

主办单位
IEEE IAS
承办单位
IEEE IAS Student Chapter of Southwest Jiaotong University (SWJTU)
IEEE IAS Student Chapter of Huazhong University of Science and Technology (HUST)
IEEE PELS (Power Electronics Society) Student Chapter of HUST
移动端
在手机上打开
小程序
打开微信小程序
客服
扫码或点此咨询