An SFA-HMM performance evaluation method using state difference optimization for running gear systems in high-speed trains - Cheng, Chao; Wang, Meng; Wang, Jiuhe; Shao, Junjie; Chen, Hongtian (Zielona Góra: Uniwersytet Zielonogórski)
The evaluation of system performance plays an increasingly important role in the reliability analysis of cyber-physical systems. Factors of external instability affect the evaluation results in complex systems. Taking the running gear in high-speed trains as an example, its complex operating environment is the most critical factor affecting the performance evaluation design. In order to optimize the evaluation while improving accuracy, this paper develops a performance evaluation method based on slow feature analysis and a hidden Markov model (SFA-HMM). The utilization of SFA can screen out the slowest features as HMM inputs, based on which a new HMM is established for performance evaluation of running gear systems.
Keywords: slow feature analysis (SFA); performance evaluation; hidden Markov model (HMM); running gear systems