Fault diagnosis based on Walsh transform and rough sets
An accurate and fast method for fault diagnosis is an important issue most techniques have sought to. For this reason, a fast fault diagnosis method based on Walsh transform and rough sets is proposed in this paper. Firstly, fault signals are fast transformed by Walsh matrix, and the Walsh spectrums are obtained, whose statistical characteristics constitute feature vectors. Secondly, the feature vectors are discretized and reduced by the rough sets theory, as a result, key features are retained and diagnosis rules are provided. Finally, utilized these diagnosis rules, fault diagnosis is carried out experimentally in the spectrum domain and its performance is compared with that of other methods, the higher accuracy is achieved and much time is saved, which fully validates the effectiveness of our approach.
fault diagnosis walsh transform rough sets discernable matrix attribution reduction