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Upgrading In-Circuit Test of High Density PCBAs Using Electromagnetic Measurement and Principal Component Analysis

机译:使用电磁测量和主成分分析升级高密度PCBA的电路测试

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摘要

With the density increase of today’s printed circuit board assemblies (PCBA), electronic test methods such as in-circuit test (ICT) reached their limits. In the same time the requirements of high reliability and robustness are greater. Original equipment manufacturers are obliged to reduce the number of physical test points and to find better-adapted test methods to keep adequate test coverage. Current test methods must be rethought to include a large panel of physical phenomena that can be used to detect- electrical defects, absence, wrong value of components, absence and shorts without using test points on the board under test (BUT). In this paper, a test set-up based on the measurement of electromagnetic signature to diagnose faulty components contactlessly is presented. The technique consists in using magnetic field probes, which detect the field distribution over powered sensitive components. To evaluate the relevance of the method, reference EM signatures are extracted from fault-free circuits, which are compared to those extracted from a sample PCBA in which we introduced a component level defect by removing or changing the value of critical components. For more robust detection of multiple defect scenarios, the principal component analysis (PCA) method is used as an outlier detection algorithm.
机译:随着当今印刷电路板组件(PCBA)的密度增加,电子测试方法如在线测试(ICT)达到了限制。同时,高可靠性和鲁棒性的要求更大。原始设备制造商有义务减少物理测试点数,并找到更好的测试方法以保持足够的测试覆盖范围。必须备受当前的测试方法,以包括一个大块物理现象,可用于检测电气缺陷,不存在,缺少的组件,缺席和短路的错误值,而不使用被测电路板上的测试点(但是)。本文介绍了基于电磁签名测量以无接触地诊断故障组分的测试设置。该技术在使用磁场探针中,该探测器检测到电源敏感组件的场分布。为了评估该方法的相关性,从无故障电路提取参考EM签名,与从样品PCB中提取的那些通过去除或改变关键组分的值来进行比较。为了更强大地检测多个缺陷方案,主要成分分析(PCA)方法用作异常检测算法。

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