Fault diagnosis based on orthogonal semi-supervised LLTSA for feature extraction and Transductive SVM for fault identification

• Published in: Journal of intelligent & fuzzy systems Vol. 34; no. 6; pp. 3499 - 3511
• Main Authors: Luo, Jiufei, Xu, Haitao, Su, Zuqiang, Xiao, Hong, Zheng, Kai, Zhang, Yi
• Format: Journal Article
• Language: English
• Published: Amsterdam IOS Press BV 01.01.2018
• Subjects: Clustering; Decomposition; Fault diagnosis; Feature extraction; Gearboxes; Machine learning; Manifolds (mathematics); Statistical analysis; Statistical methods; Support vector machines; Wavelet transforms

To overcome the low diagnosis accuracy caused by the scarcity of labeled training samples, a fault diagnosis method was proposed using orthogonal Semi-supervised linear local tangent space alignment (OSSLLTSA) for feature extraction and transductive support vector machine (TSVM) for fault identifica...