Applying blind signal separation theory to diagnose heavy-duty vehicle

Abstract

It is common to see difficult feature extraction in heavy-duty vehicles fault diagnosis due to strong interference. Blind signal separation(BSS) technology proves to be effective to extract the principal component out of the multi-sources signals. Therefore, it is used to extract the fault information for heavy-duty vehicle in this paper. A bispectrum of the data after BSS is obtained and scanned in frequency field. The result indicates that BSS can reduce the interference out of the engine vibration and extract the wanted fault features more effectively.