A fault diagnosis method based on AWA-SVM of complicated equipment

Owing to the diversity and uncertainty of the faults of complicated equipment, applying the Adaptive Wavelet Analysis to pick up the characteristics of the circuit measured and to get the feature vector of the signal is a effective way to match the characteristics of the wavelet´s time frequency and the circuit´s response time frequency. Combined with fault diagnosis of the support vector machine, it´s feasible to overcome the difficulty caused by small-scaled samples, nonlinearity and multi dimension. It has been testify effective and accurate in fault diagnosis of complicated equipment.