Generalized Multi-fractal Method for Soft Fault Feature Extraction of Non-linear Analog Circuits Based on EMD

Abstract

The soft fault signal of non-linear analog circuits is non-linear and unstable. Its inherent characteristics cannot be analyzed by the traditional linear method. Therefore, a new method based on the empirical mode decomposition (EMD) and a generalized multi-fractal dimension algorithm is proposed for soft fault signal feature extraction of non-linear analog circuits. The EMD decomposed the circuits soft fault signal into several intrinsic mode functions (IMF). The EMD then modified a traditional G-P correlation dimension algorithm to simply and reliably use it for calculating the generalized multi-fractal dimensions of the fault signals. According to fractal theory, the generalized fractal dimensions of the original fault signals and IMF can be obtained for an appropriate weight factor q. The principle IMF component can then be filtered using the cross-correlation coefficient criterion. The obtained generalized multi-fractal dimension of the principle IMF component was continually input in the supporting vector machine as a characteristic vector to diagnose the soft fault of the non-linear analog circuits. The feasibility and validity of this proposed method were demonstrated by experiments.