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基于Pspice的混合信号电路故障检测
资料介绍
针对混合信号电路故障检测难、检测准确率低的问题，采用神经网络与故障字典相结合的混合信号电路故障检测方法。运用Pspice对混合信号电路进行仿真，用蒙特卡罗算法对电路进行分析。提取电路中具有代表性的电流信息，建立正常状态下的故障字典。用Matlab进行神经网络的设计，通过训练、测试证明了该方法故障覆盖率可达到90％，准确率达到96％。
Currently, it＇s hard to detect faults and the detection accuracy is low in mixed-signal circuit. To solve these problems, the paper introduced a faults detection method, which combined neural network and fault-dictionary, for mixedsignal circuit. Fully emulating mixed-signal circuits hy Pspiee software and using Monte-Carlo method to analyze it. Then distilling the representative current-information of the circuit and establishing the fault-dictionary in the order. It used Matlab to design neural network, the experimental results from training and testing proved that coverage of the method can reach to 90% and accuracy 96%.
部分文件列表
| 文件名 | 大小 |
| 基于Pspice的混合信号电路故障检测.pdf | 228K |
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