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Volume 45 Issue 3
Mar.  2023
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WANG Li, XIE Xiaohuai, ZHANG Yichi. Infrared Image-based ISSA-BP Neural Network for Airborne Circuit Board Chip Fault Diagnosis[J]. Infrared Technology , 2023, 45(3): 241-248.
Citation: WANG Li, XIE Xiaohuai, ZHANG Yichi. Infrared Image-based ISSA-BP Neural Network for Airborne Circuit Board Chip Fault Diagnosis[J]. Infrared Technology , 2023, 45(3): 241-248.
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Infrared Image-based ISSA-BP Neural Network for Airborne Circuit Board Chip Fault Diagnosis

  • Airborne Electronic Systems Deep Maintenance Laboratory, College of Vocational Technology, Civil Aviation University of China, Tianjin 300300, China

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  • Received Date: November 14, 2021
  • Revised Date: January 17, 2022
    Graphical Abstract
    • Abstract
  • This study proposes an improved sparrow search algorithm based on an infrared temperature-data-optimized back propagation neural network (ISSA-BPNN) for an airborne circuit board chip fault diagnosis method that cannot diagnose dynamic failures. First, an infrared thermal imaging camera collected circuit board chip temperature data to establish a feature model of static, dynamic, and statistical characteristics of the circuit board chip warming process. We used sine chaos mapping to initialize the sparrow population distribution, the levy flight improvement finder sparrow location update, and an improved sparrow search algorithm to optimize the weight parameters of the BP neural network. Finally, the temperature feature model was input to the ISSA-BP neural network for training and testing to complete the circuit board chip fault diagnosis. The experiments used an avionics system power supply circuit board for reliability analysis, and the results revealed that the method achieved a comprehensive fault diagnosis rate of 97.84% under different circuit board operating conditions.
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    • References (15)
  • [1]
    SHI L, ZHOU Z, JIA H, et al. Fault diagnosis of functional circuit in avionics system based on BPNN[C]//Prognostics and System Health Management Conference, IEEE, 2019: 1-5.
    [2]
    DONG Z, CHEN L. Image registration in PCB fault detection based on infrared thermal imaging[C]//Chinese Control Conference (CCC). IEEE, 2019: 4819-4823.
    [3]
    Sarawade A A, Charniya N N. Detection of faulty integrated circuits in PCB with thermal image processing[C]//International Conference on Nascent Technologies in Engineering (ICNTE). IEEE, 2019: 1-6.
    [4]
    孙东旭, 贾世伟, 孟玉慈, 等. 综合模块化航电系统FC网络的机内测试设计[J]. 航空计算技术, 2016, 46(6): 108-112. https://www.cnki.com.cn/Article/CJFDTOTAL-HKJJ201606028.htm

    SUN Dongxu, JIA Shiwei, MENG Yuci, et al. Built-in-test design for integrated module avionics fibre channel networks[J]. Aeronautical Computing Technique, 2016, 46(6): 108-112. https://www.cnki.com.cn/Article/CJFDTOTAL-HKJJ201606028.htm
    [5]
    ZHENG T, WANG Z, TAN C, et al. Research on fault prediction and diagnosis method of PCB circuit[C]//International Conference on Artificial Intelligence and Computer Engineering (ICAICE). IEEE, 2020: 387-390.
    [6]
    徐奇伟, 黄宏, 张雪锋, 等. 基于改进区域全卷积网络的高压引线接头红外图像特征分析的在线故障诊断方法[J]. 电工技术学报, 2021, 36(7): 1380-1388. https://www.cnki.com.cn/Article/CJFDTOTAL-DGJS202107008.htm

    XU Qiwei, HUANG Hong, ZHANG Xuefeng, et al. Online fault diagnosis method for infrared image feature analysis of high-voltage lead connectors based on improved R-FCN[J]. Transactions of China Electrotechnical Society, 2021, 36(7): 1380-1388. https://www.cnki.com.cn/Article/CJFDTOTAL-DGJS202107008.htm
    [7]
    张博. 基于红外图像电路板故障检测技术研究[D]. 沈阳: 沈阳航空航天大学, 2018.

    ZHANG Bo. Research on Circuit Board Fault Detection Technology Based on Infrared Image[D]. Shenyang: Shenyang Aerospace University, 2018.
    [8]
    Salvi S S, Jain A. Detection of unusual thermal activities in a semiconductor chip using backside infrared thermal imaging[J]. Journal of Electronic Packaging, 2021, 143(2): 020901. DOI: 10.1115/1.4049291
    [9]
    Al Obaidy F, Yazdani F, Mohammadi F A. Intelligent testing for Arduino UNO based on thermal image[J]. Computers & Electrical Engineering, 2017, 58: 88-100.
    [10]
    王力, 李硕, 武会杰, 等. 基于红外技术的机载电路板故障诊断研究[J]. 计算机仿真, 2017, 34(7): 89-93. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJZ201707019.htm

    WANG Li, LI Shuo, WU Huijie, et al. Research of aviation circuit board fault diagnosis and prediction based on infrared technology[J]. Computer Simulation, 2017, 34(7): 89-93. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJZ201707019.htm
    [11]
    郝建新, 贾春宇. 基于红外热图的机载电路板故障模式诊断研究[J]. 红外技术, 2019, 41(3): 273-278. http://hwjs.nvir.cn/article/id/hwjs201903013

    HAO Jianxin, JIA Chunyu. Research on fault mode diagnosis of airborne circuit board based on infrared images[J]. Infrared Technology, 2019, 41(3): 273-278. http://hwjs.nvir.cn/article/id/hwjs201903013
    [12]
    王力, 刘子奇. WPA-IGA-BP神经网络的模拟电路故障诊断[J]. 系统工程与电子技术, 2021, 43(4): 1133-1143. https://www.cnki.com.cn/Article/CJFDTOTAL-XTYD202104034.htm

    WANG Li, LIU Ziqi. Fault diagnosis of analog circuit for WPA-IGA-BP neural network[J]. System Engineering and Electronics, 2021, 43(4): 1133-1143. https://www.cnki.com.cn/Article/CJFDTOTAL-XTYD202104034.htm
    [13]
    GUO Y, RAN C, JI X, et al. Fault diagnosis in analog circuits based on combined-optimization BP neural networks[J]. Journal of Northwestern Polytechnical University, 2013, 1: 44-48.
    [14]
    XUE J, SHEN B. A novel swarm intelligence optimization approach: sparrow search algorithm[J]. Systems Science & Control Engineering An Open Access Journal, 2020, 8(1): 22-34.
    [15]
    Reynolds Andy. Liberating Lévy walk research from the shackles of optimal foraging[J]. Physics of Life Reviews, 2015, 14: 59-83.
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