| 基于红外图像的ISSA-BP神经网络机载电路板芯片故障诊断 |
| |
| 引用本文： | 王力,谢晓怀,张亦弛.基于红外图像的ISSA-BP神经网络机载电路板芯片故障诊断[J].红外技术,2023,45(3):241-248. |
| |
| 作者姓名： | 王力 谢晓怀 张亦弛 |
| |
| 作者单位： | 中国民航大学 电子信息与自动化学院 机载电子系统深度维修实验室, 天津 300300 |
| |
| 基金项目： | 国家自然科学基金委员会与中国民用航空局联合资助基金U1733119中央高校基本业务费项目3122017107基于红外技术与数据驱动的机载电路板卡故障诊断与预测研究2021YJS018 |
| |
| 摘 要： | 针对传统红外图像的机载电路板芯片故障诊断法诊断率低且无法诊断动态故障的问题，本文提出了一种基于红外温度数据的改进麻雀搜索算法优化BP神经网络（Improved sparrow search algorithm-Back propagation neural networks, ISSA-BPNN）机载电路板芯片故障诊断方法。首先，提取红外热像仪采集的电路板芯片温度数据，建立电路板芯片升温过程中静态、动态、统计特征的特征模型；然后，利用Sine混沌映射初始化麻雀种群分布，利用Levy飞行策略改进发现者种群位置更新公式，将改进后的麻雀搜索算法优化BP神经网络的权值参数；最后，将温度特征模型输入到ISSA-BP神经网络进行训练和测试，从而完成电路板芯片故障诊断。实验采用航电系统电源电路板进行可靠性分析，实验结果表明，该方法在电路板不同工况下综合故障诊断率达到97.84%。
|
| 关 键 词： | 红外温度 改进麻雀搜索算法 BP神经网络 电路板芯片 故障诊断 |
| 收稿时间： | 2021-11-15 |
Infrared Image-based ISSA-BP Neural Network for Airborne Circuit Board Chip Fault Diagnosis |
| |
| Affiliation: | Airborne Electronic Systems Deep Maintenance Laboratory, College of Vocational Technology, Civil Aviation University of China, Tianjin 300300, China |
| |
| 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. |
| |
| Keywords: | |
|
| 点击此处可从《红外技术》浏览原始摘要信息 |
|
点击此处可从《红外技术》下载全文 |
