Short-circuit Fault Diagnosis Method Based on Wavelet Neural Network
In response to the problem of poor diagnostic performance of traditional methods for short-circuit faults,this paper proposes a simulation integrated circuit short-circuit fault diagnosis method based on wavelet neural network.Firstly,reconstruct the original signal of the simulated integrated circuit,extract the characteristics of the short-circuit fault signal,then use the determined fault location to identify the fault type through wavelet neural network,and finally judge the severity of the short-circuit fault to achieve the diagnosis of the simulated integrated circuit short-circuit fault.The experimental results show that the degree of short-circuit fault identified by the proposed design method is very close to the target value,and has practical application value.
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