监测电源电流并利用神经网络程序诊断电路故障

L. Kirkland, J. Dean
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引用次数: 5

摘要

当测试电路时,从电源中提取的电流会随着测试调用的不同功能而变化。电流绘制可以随时间绘制,显示所执行测试的特征轨迹。ATS电源中的传感器可用于监测测试执行过程中的电流流动。根据一张好卡片的“痕迹”的变化模式,可以使用神经网络对缺陷部件进行分类。这可以作为一个后台函数来执行,随着时间的推移,网络的准确性会提高。本文讨论了利用监测电源电流诊断电路故障的神经网络程序
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Monitoring power supply current and using a neural network routine to diagnose circuit faults
As a circuit is tested, the current drawn from a power supply can vary as different functions are invoked by the test. The current draw can be plotted against time, showing a characteristic trace for the test performed. Sensors in the ATS power supply can be used to monitor the current flow during test execution. Defective components can be classified using a neural network according to the pattern of variation from the "trace" of a good card. This can be performed as a background function, with the network gaining in accuracy over time. This paper discusses the neural network routine for diagnosing circuit faults using monitored power supply current.<>
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