Dynamic Reliability Evaluation of High-Speed Train Gearbox Based on Copula Function

Abstract

As a key component of the high-speed train transmission system, the reliability of the gearbox directly affects the reliability and driving safety of the high-speed train. Taking the key parts in the gearbox: driving gear, driven gear, gearbox housing and bearing as the research object, the dynamic reliability of the gearbox is evaluated. First, combined with classical stress-strength interference theory, the number of stochastic loads is regarded as a Poisson process, and the strength degradation is described by the Gamma process, the Gamma strength degradation parameter of each part is determined from the part material or the part's P-S-N curve, and the reliability model of each key part of the gearbox is obtained. Second, the gearbox is regarded as a series system, and the Gumbel Copula function is introduced to deal with the nonlinear correlation between different parts and between different failure modes of the same part. The nesting relationship of the Copula function is determined, the parameter values of the Gumbel Copula function are determined based on the kernel density estimation and maximum likelihood estimation method, so as to establish the dynamic reliability model of the gearbox system and realize the evaluation of the dynamic reliability of the gearbox. The evaluation results show that the method for evaluating the reliability of high-speed train gearboxes is in line with engineering practice. The evaluation method has practical significance for the reliability check, optimization design and dynamic tracking of the gearbox reliability during the service period of the high-speed train gearbox.

A novel reliability analysis methodology based on IPSO-MCopula model for gears with multiple failure modes

“…To optimally determine the parameters appeared in the proposed MCopula function, we firstly use the Monte Carlo (MC) scheme to randomly generate the sample data and the MLE scheme to estimate the dependent parameters, where both schemes were quite successfully applied in reliability analysis problems. 3,33,34 Secondly, the weight coefficient is determined by the IPSO algorithm proposed by this study. Details are described as follows.…”

Wind turbine gear reliability analysis considering dependent competing failure

“…Therefore, the Gamma process is a suitable way to analyze the gear degradation process. 28 Considering the fluctuations and jumps of the load level under practical working conditions, the rate of degradation changes erratically over time. It is decided to use the nonlinear Gamma degradation process.…”

“…The Gamma process is a monotonically increasing random process, and its increment complies with the Gamma distribution of the same scale parameter β. Therefore, the Gamma process is a suitable way to analyze the gear degradation process 28 . Considering the fluctuations and jumps of the load level under practical working conditions, the rate of degradation changes erratically over time.…”

Reliability evaluation of a complex system that considers the influence of the fluctuation degree of the performance degradation trajectory

“…The performance degradation of complex systems is widespread in engineering, such as the precision degradation of computer numerical control (CNC) machine tools, the wear of gearboxes and the corrosion of offshore bridges. 7,[13][14][15] At present, reliability assessment based on performance degradation data is divided into three categories. The first category includes reliability assessment methods based on degradation trajectories.…”

“…Therefore, the reliability research of complex systems by using performance degradation data has been widely performed. The performance degradation of complex systems is widespread in engineering, such as the precision degradation of computer numerical control (CNC) machine tools, the wear of gearboxes and the corrosion of offshore bridges 7,13–15 …”