国产欧美精品一区二区,中文字幕专区在线亚洲,国产精品美女网站在线观看,艾秋果冻传媒2021精品,在线免费一区二区,久久久久久青草大香综合精品,日韩美aaa特级毛片,欧美成人精品午夜免费影视

New methods and models for knowledge-based data analysis are brought by kernel method. It uses nonlinear mapping, the original data is embedded into a high dimensional feature space, then conduct the linear analysis and processing. The traditional methods cannot solve the problem of poor classification performance in the case of high dimensionality of fault feature data and serious overlap of fault samples, therefore in the circuit fault feature data pre-processing stage, we propose a method of extracting circuit fault feature.The method step by step, respectively, conduct wavelet packet analysis of Circuit Output Voltage Waveform in the time domain and measure amplitude-frequency characteristics of the circuit in the frequency domain; Preprocessed fault feature vectors is just eight-dimensional vector, thus reducing training time of SVM .When the method is applied in the fault diagnosis of the CTSV filter circuit in international standard circuit, the results have shown that this method can highlight the different characteristics of the fault, and the fault diagnostic correct rate of 98.57% is achieved.