The method uses wavelet transform and principle component analysis to preprocess fault signal, afterward training and testing wavelet neural network with the preprocessed fault characteristic data.
该方法首先利用小波变换和主成分分析对故障信号进行预处理，然后用处理后的故障特征数据对小波神经网络进行训练和测试。
The core of this method is to find the mapping relations between fault component and load-shedding buses or the system.
该方法核心是找到故障元件与削减负荷节点和系统的映射关系。
Be aimed at the characteristic of the fault influencing to exhaust, building the fault diagnosis expert system through idea and method of the analyzing exhaust gas emission component is researched.
并针对影响汽车排放的故障的特点，通过废气排放成分分析的诊断思路及方法，对构建尾气分析专家系统进行了研究。
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