Reliability Assessment Model and Simulation of Journal Bearing of Railway Freight Cars Based on Bayesian Method under Small Sample Sizes
Generally, the box bearing of railway freight cars has no bearing sample failure data at the end of the time-terminated reliability test. However, it is expensive and has high service reliability requirements. Given a small sample size and zero-failure data, the traditional failure probability calcu...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2022/5275843 |
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| author | Juping Yang Haijun Len Junguo Wang Yongxiang Zhao |
| author_facet | Juping Yang Haijun Len Junguo Wang Yongxiang Zhao |
| author_sort | Juping Yang |
| collection | DOAJ |
| description | Generally, the box bearing of railway freight cars has no bearing sample failure data at the end of the time-terminated reliability test. However, it is expensive and has high service reliability requirements. Given a small sample size and zero-failure data, the traditional failure probability calculation formula based on a large sample size and the reliability modeling technique cannot easily assess the reliability of rolling bearings accurately. Considering the applicability of the bearing of railway freight cars, this study integrated the prior information of samples and the simulation test information according to Bayes statistical theory, deduced the mathematical model of cumulative failure probability under failure-free data, calculated the distribution parameters using the least square method, and established the reliability estimation model of rolling bearings on the basis of Weibull distribution. The failure-free simulation data of rolling bearings were produced according to the Monte Carlo simulation, and the reliability of the journal bearing of railway freight cars was simulated and assessed by three methods. Simulation results demonstrate that the proposed reliable Bayes multilayer estimation method could not only meet the design requirements of the ISO 281 rolling bearing standards on that basis of the failure-free data and small sample size of the time-terminated simulation, but also assess the reliability of the rolling bearing of railway freight cars. |
| format | Article |
| id | doaj-art-9a3e79211e394312b7b44e65aa99e822 |
| institution | Kabale University |
| issn | 2042-3195 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-9a3e79211e394312b7b44e65aa99e8222025-08-20T03:36:54ZengWileyJournal of Advanced Transportation2042-31952022-01-01202210.1155/2022/5275843Reliability Assessment Model and Simulation of Journal Bearing of Railway Freight Cars Based on Bayesian Method under Small Sample SizesJuping Yang0Haijun Len1Junguo Wang2Yongxiang Zhao3Traction Power State Key LaboratorySchool of Mechanical EngineeringSchool of Mechanical EngineeringSchool of Mechanical EngineeringGenerally, the box bearing of railway freight cars has no bearing sample failure data at the end of the time-terminated reliability test. However, it is expensive and has high service reliability requirements. Given a small sample size and zero-failure data, the traditional failure probability calculation formula based on a large sample size and the reliability modeling technique cannot easily assess the reliability of rolling bearings accurately. Considering the applicability of the bearing of railway freight cars, this study integrated the prior information of samples and the simulation test information according to Bayes statistical theory, deduced the mathematical model of cumulative failure probability under failure-free data, calculated the distribution parameters using the least square method, and established the reliability estimation model of rolling bearings on the basis of Weibull distribution. The failure-free simulation data of rolling bearings were produced according to the Monte Carlo simulation, and the reliability of the journal bearing of railway freight cars was simulated and assessed by three methods. Simulation results demonstrate that the proposed reliable Bayes multilayer estimation method could not only meet the design requirements of the ISO 281 rolling bearing standards on that basis of the failure-free data and small sample size of the time-terminated simulation, but also assess the reliability of the rolling bearing of railway freight cars.http://dx.doi.org/10.1155/2022/5275843 |
| spellingShingle | Juping Yang Haijun Len Junguo Wang Yongxiang Zhao Reliability Assessment Model and Simulation of Journal Bearing of Railway Freight Cars Based on Bayesian Method under Small Sample Sizes Journal of Advanced Transportation |
| title | Reliability Assessment Model and Simulation of Journal Bearing of Railway Freight Cars Based on Bayesian Method under Small Sample Sizes |
| title_full | Reliability Assessment Model and Simulation of Journal Bearing of Railway Freight Cars Based on Bayesian Method under Small Sample Sizes |
| title_fullStr | Reliability Assessment Model and Simulation of Journal Bearing of Railway Freight Cars Based on Bayesian Method under Small Sample Sizes |
| title_full_unstemmed | Reliability Assessment Model and Simulation of Journal Bearing of Railway Freight Cars Based on Bayesian Method under Small Sample Sizes |
| title_short | Reliability Assessment Model and Simulation of Journal Bearing of Railway Freight Cars Based on Bayesian Method under Small Sample Sizes |
| title_sort | reliability assessment model and simulation of journal bearing of railway freight cars based on bayesian method under small sample sizes |
| url | http://dx.doi.org/10.1155/2022/5275843 |
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