LAUSR

Abstract A novel symmetric single-valued neutrosophic cross entropy (SVNCE) measure based upon a newly developed symmetric measure of fuzzy cross entropy is established and then applied it for identifying defects of bearings installed in a test rig and axial piston pump. A 3-level wavelet packet transformation (WPT) is used for extracting and decomposing the fault features associated with the vibrational signals. The new evaluated SVNCE values between knowledge of various faults types and real testing samples provide useful evaluation information of fault types. The concluded results reveal that the proposed SVNCE measure furnishes better fault identification accuracy when compared with the existing model based upon correlation coefficient of simplified neutrosophic sets (SNSs). Furthermore, the proposed SVNCE measure offers consistent and feasible results and is capable for holding the optimal fault type selection under sensitive analysis.