A Novel Fault Detection Method for Running Gear Systems Based on Dynamic Inner Slow Feature Analysis

Abstract

Process and sensor noise often affect the monitoring of slowly changing faults in highspeed trains, which seriously increases the difficulty of slow-change fault detection (FD). By introducing the idea of dynamic inner into the framework of multiple statistics, a novel dynamic inner slowness feature analysis (DISFA) is proposed in this article. This method considers both dynamic and static conditions and improves the detection speed of slow-change faults of running gears, and improves the detection rate of slow-change faults. Compared with other traditional methods, this method is more sensitive to slow changes, can effectively analyze fault-related data, and improve the detection efficiency of slow-changing faults. First, the validity of the method proposed in this paper is proved by mathematical deduction, then it is verified by actual operation devices. INDEX TERMS slow-change fault, fault detection (FD), dynamic inner slow feature analysis (DISFA), high-speed trains.

Dynamics and Fault Diagnosis of Railway Vehicle Gearboxes: A Review

“…The proposed method not only has a good fault detection ability but also exhibits strong robustness to high-level noise. Song et al [75] introduced the dynamic inner into the framework of multiple statistics and proposed a dynamic inner slowness feature analysis method for the fault detection of running gear systems. This method improves the detection speed and the detection rate of slow-change faults.…”

“…Existing studies, such as [69], [74], [75], [76], [77], [78], [79], primarily focused on monitoring the overall health status of gearboxes rather than specifically identifying the faulty components. Future research on diagnosing the specific fault types and degrees in gearboxes is needed.…”

A Data-Driven Scheme for Fault Detection of Discrete-Time Switched Systems

“…As is well known, fault detection has served as an effective tool to guarantee the safety and reliability of dynamic systems. Nowadays, the study on fault detection has drawn considerable attention from the literature [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 ]. The model-based fault detection takes up an important role in the fault detection field.…”