An SFA-HMM performance evaluation method using state difference optimization for running gear systems in high-speed trains

• Autorzy: Cheng Chao , Wang Meng , Wang Jiuhe , Shao Junjie , Chen Hongtian

Identyfikatory

DOI

10.34768/amcs-2022-0028

• Języki publikacji: EN

Abstrakty

EN

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. In addition to directly classical performance evaluation for running gear systems of high-speed trains, the slow feature statistic is proposed to detect the difference in the system state through test data, and then eliminate the error evaluation of the HMM in the stable state. In addition, indicator planning and status classification of the data are performed through historical information and expert knowledge. Finally, a case study of the running gear system in high-speed trains is discussed. After comparison, the result shows that the proposed method can enhance evaluation performance.

Słowa kluczowe

EN

slow feature analysis; SFA; performance evaluation; hidden Markov model; HMM; running gear system

PL

analiza cech; SFA; ocena efektywności; ukryty model Markowa; HMM; układ biegowy

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2022
• Tom: Vol. 32, no. 3
• Strony: 389--402
• Opis fizyczny: Bibliogr 36 poz., rys., tab., wykr.

Twórcy

autor

Cheng Chao

• Institute of Computer Science and Engineering, Changchun University of Technology, No. 2055, Yanan Ave., Chaoyang District, Changchun 130012, China
• National Railway Passenger Car System Integration Engineering Technology Research Center, CRRC Changchun Railway Vehicles Co., Ltd., No. 2001, Changke Ave., Green Park Economic Development District, Changchun 130062, China

autor

Wang Meng

• Institute of Computer Science and Engineering, Changchun University of Technology, No. 2055, Yanan Ave., Chaoyang District, Changchun 130012, China

autor

Wang Jiuhe

• Institute of Computer Science and Engineering, Changchun University of Technology, No. 2055, Yanan Ave., Chaoyang District, Changchun 130012, China

autor

Shao Junjie

• National Railway Passenger Car System Integration Engineering Technology Research Center, CRRC Changchun Railway Vehicles Co., Ltd., No. 2001, Changke Ave., Green Park Economic Development District, Changchun 130062, China

autor

Chen Hongtian

• Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB T6G 2V4, Canada

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Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)