|A Multi-mode Incipient Sensor Fault Detection and Diagnosis Method for Electrical Traction Systems
Hongtian Chen, Bin Jiang*, and Ningyun Lu
International Journal of Control, Automation, and Systems, vol. 16, no. 4, pp.1783-1793, 2018
Abstract : "This paper proposes a data-driven sensor fault detection and diagnosis (FDD) method for electrical
traction systems. Considering their switched characteristics, electrical traction systems can be regarded as switched
systems. A mixture non-Gaussian data set will be formed, which can be firstly divided into six different operation
modes, and principal component analysis (PCA) is then used for feature extraction in each mode. For two fault
indicators in principal and residual subspaces, their probability density functions (PDFs) are estimated and used
to determine reasonable thresholds for FDD. The proposed methodology extends the application of multivariate
statistical technology to electrical traction systems. It can be applied easily and effectively without requirements on
system parameters, and can deal with incipient sensor faults in traction system. Experiments with several different
types of incipient sensor faults are conducted, which can demonstrate the effectiveness of the proposed method."
"Electrical traction system, fault detection and diagnosis (FDD), incipient sensor fault, multi-mode, non-Gaussian signal."