Research and Application of Fault Prediction Method for High-speed EMU Based on PHM Technology

Haitao Wang (왕해도); Min, Byung-Won (민병원)

doi:10.20465/KIOTS.2022.8.6.055

Research and Application of Fault Prediction Method for High-speed EMU Based on PHM Technology

Journal of Internet of Things and Convergence
Abbr : JKIOTS
2022, 8(6), pp.55-63
DOI : 10.20465/KIOTS.2022.8.6.055
Publisher : The Korea Internet of Things Society
Research Area : Engineering > Computer Science > Internet Information Processing
Received : September 12, 2022
Accepted : November 8, 2022
Published : December 31, 2022

Haitao Wang ¹, Min, Byung-Won ¹

¹목원대학교

Accredited

ABSTRACT

In recent years, with the rapid development of large and medium-sized urban rail transit in China, the total operating mileage of high-speed railway and the total number of EMUs(Electric Multiple Units) are rising. The system complexity of high-speed EMU is constantly increasing, which puts forward higher requirements for the safety of equipment and the efficiency of maintenance.At present, the maintenance mode of high-speed EMU in China still adopts the post maintenance method based on planned maintenance and fault maintenance, which leads to insufficient or excessive maintenance, reduces the efficiency of equipment fault handling, and increases the maintenance cost. Based on the intelligent operation and maintenance technology of PHM(prognostics and health management). This thesis builds an integrated PHM platform of "vehicle system-communication system-ground system" by integrating multi-source heterogeneous data of different scenarios of high-speed EMU, and combines the equipment fault mechanism with artificial intelligence algorithms to build a fault prediction model for traction motors of high-speed EMU.Reliable fault prediction and accurate maintenance shall be carried out in advance to ensure safe and efficient operation of high-speed EMU.

KEYWORDS

High speed EMU, Prognostics, Model, Neural Network, Intelligence

Citation status

* References for papers published after 2023 are currently being built.

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Journal of Internet of Things and Convergence 2023 KCI Impact Factor : 0.89

Research and Application of Fault Prediction Method for High-speed EMU Based on PHM Technology

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Citation status

* References for papers published after 2023 are currently being built.

Journal of Internet of Things and Convergence 2023 KCI Impact Factor : 0.89

Research and Application of Fault Prediction Method for High-speed EMU Based on PHM Technology

ABSTRACT

KEYWORDS

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* References for papers published after 2023 are currently being built.