Title: Wear life prediction of vehicle mechanical parts based on Gray Markov chain

Authors: Haoge Peng; Ming Zhang

Addresses: Hunan Provincial Key Laboratory of Vehicle Power and Transmission System, Hunan Institution of Engineering, 88 Fuxing East Road, Xiangtan, 411104, China ' Xiangtan Nanfang Electric Locomotive Manufacturing Co., Ltd., Hekou Town, Xiangtan, 411214, China

Abstract: In order to overcome the high prediction error rate of traditional methods, a wear life prediction method of vehicle mechanical parts based on Gray Markov chain is proposed. The wear type, wear mechanism of vehicle mechanical parts and the relationship between wear type and surface damage form are analysed, and the wear amount of vehicle mechanical parts is calculated. Based on the calculation results of wear amount, the relative error and residual error of wear life prediction results based on GM (1,1) model are obtained by using Markov chain, and the wear life prediction results of vehicle mechanical parts are obtained under the condition of minimising the two. The experimental results show that the accuracy of this method is 58-92%, the maximum error rate is 4.5%, the minimum error rate is 0.9%, and the average output time is 1.16 s.

Keywords: Gray Markov chain; vehicle; mechanical parts; wear life prediction; relative error; predicting residual.

DOI: 10.1504/IJVD.2022.128027

International Journal of Vehicle Design, 2022 Vol.89 No.1/2, pp.160 - 173

Received: 22 Feb 2021
Accepted: 07 Jan 2022
Published online: 04 Jan 2023 *

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