计算机工程与应用 ›› 2015, Vol. 51 ›› Issue (22): 22-27.

• 博士论坛 • 上一篇    下一篇

基于果蝇-构造小波神经网络模拟电路诊断方法

于文新1,何怡刚2,吴先明3,高  坤3   

  1. 1.湖南科技大学 信息与电气工程学院,湖南 湘潭 411201
    2.合肥工业大学 电气与自动化工程学院,合肥 230009
    3.湖南大学 电气与信息工程学院,长沙 410088
  • 出版日期:2015-11-15 发布日期:2015-11-16

Method of analog circuit fault diagnosis based on FOA-neural network

YU Wenxin1, HE Yigang2, WU Xianming3, GAO Kun3   

  1. 1.School of Information & Electrical Engineering, Hunan University of Science and Technology, Xiangtan, Hunan 411201, China
    2.School of Electrical and Automation Engineering, Hefei University of Technology, Hefei 230009, China
    3.College of Electrical and Information Engineering, Hunan University, Changsha 410088, China
  • Online:2015-11-15 Published:2015-11-16

摘要: 利用果蝇算法优化构造小波神经网络,建立FOA-构造小波神经网络模型,并将模型应用于模拟电路故障分析当中,通过仿真试验可发现该方法在故障诊断中有较高的准确性。

关键词: 果蝇算法, 小波神经网络, 模拟电路, 故障诊断

Abstract: In the paper, FOA and wavelet-neural network are applied to establish a FOA-structure wavelet neural network algorithm. The model is applied to an analog circuit fault analysis by simulation. The method has higher accuracy in fault diagnosis.

Key words: Fruit fly Optimization Algorithm(FOA), neural network, analog circuit, fault diagnosis