| 摘要: |
| 提出了一种基于模拟电路故障诊断的神经网络方法。这种方法利用小波分解、数据标准化、主成分分析对输入数据进行预处理，采用k个神经元输出的前馈神经网络结构进行有效训练。该方法检测和识别故障准确率高，系统的鲁棒性和稳定性强。 |
| 关键词: 模拟电路 故障诊断 神经网络结构 主成分分析 |
| DOI：10.3969/j.issn.1001-893X. |
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| 基金项目:吉林省自然科学基金项目"集成电路及器件故障诊断方法及应用研究"(20010582) |
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| An Analog Circuit Fault Diagnosis Method Based on Neural-Network |
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| Abstract: |
| An analog circuit fault diagnosis method based on neural-network is presented. The method uses wavelet decomposition and principle component analysis to preprecess input data. The fault diagnosis system is based on 1-k neural network architecture using bavk-propagation algorithm for training. The system has capability to accurately detect and identify fault components in an experiment circuit. And it provides a more robust and stable fault diagnosis. |
| Key words: Analog circuit,Fault diagnosis,Neural-network architectures,Principle component analysis, |
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