A System for Detecting Failed Electronics Using Acoustics

R. Shannon, Gregory Zucaro, J. Tallent, Vontrelle Collins, John Carswell
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引用次数: 2

Abstract

Industry-produced printed circuit boards (PCBs) used by the United States Navy and Marine Corps are typically coated with a layer of “conformal coating” made of silicone or polyurethane in order to protect electrical and electronic components on the board. Conformal coating has to be removed every time board troubleshooting and maintenance are performed, and must be reapplied after board maintenance is complete. This can be an expensive and time-consuming process. This paper describes an effort to develop a non-contact solution to detect failed components on a PCB without having first to remove the conformal coating. This patent-pending technique detects density changes in the physical makeup of circuit board components due to failure. By analyzing ultrasonic reflections from the components at 2MHz, the authors were able to distinguish between working components and failed components with varying degrees of accuracy. The authors applied this technique to $1K\Omega$ resistors and three types of transistor-to-transistor logic (TTL) integrated circuits (ICs). Overvoltage faults were induced in these components in order to generate observable density changes. To reduce human error, a measurement rig was built which incorporated an automated X-Y-Z plotter system, in order to process dozens of components at a time without human interaction. The data gathered by this system was processed to isolate only the acoustic reflections of components on a circuit board. Time-domain and frequency-domain features were then extracted. These features were used to train neural networks to distinguish between working components and components with over-voltage faults that were not readily observable by eye. Each type of component or chip needed to have its own associated trained neural network. For $1K\Omega$ resistors, the system has demonstrated seventy to eighty percent accuracy in distinguishing components with over-voltage faults. For two of the TTL ICs, eighty to eighty-five percent accuracy has been achieved. For one IC type, a fifty-five percent accuracy was measured. The authors have demonstrated that low-cost acoustic measurements in the megahertz range can be used to detect failures in ICs and other common circuit board components.
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一种利用声学检测故障电子设备的系统
美国海军和海军陆战队使用的工业生产印刷电路板(pcb)通常涂有一层由硅树脂或聚氨酯制成的“保形涂层”,以保护电路板上的电气和电子元件。每次进行单板故障排除和维护时,都必须清除保形涂层,单板维护完成后必须重新涂抹保形涂层。这可能是一个昂贵且耗时的过程。本文描述了开发一种非接触式解决方案来检测PCB上的失效组件而无需首先去除保形涂层的努力。这项正在申请专利的技术检测由于故障导致电路板组件物理组成的密度变化。通过分析组件在2MHz的超声波反射,作者能够以不同程度的精度区分工作组件和失效组件。作者将这种技术应用于$1K\Omega$电阻和三种类型的晶体管到晶体管逻辑(TTL)集成电路(ic)。在这些元件中诱发过电压故障,以产生可观察到的密度变化。为了减少人为误差,建造了一个测量平台,其中包括一个自动X-Y-Z绘图仪系统,以便在没有人工干预的情况下一次处理数十个组件。该系统收集的数据经过处理后,只隔离了电路板上组件的声反射。然后提取时域和频域特征。这些特征被用于训练神经网络,以区分工作部件和具有过电压故障的部件,这些部件不易被肉眼观察到。每种类型的组件或芯片都需要有自己相关的训练有素的神经网络。对于$1K\Omega$电阻器,该系统在区分过电压故障组件方面已经证明了70%到80%的准确率。对于其中两个TTL集成电路,已经达到了80%到85%的精度。对于一种IC类型,测量的准确率为55%。作者已经证明,在兆赫范围内的低成本声学测量可用于检测ic和其他常见电路板组件的故障。
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