Analysis of the reliability of a starter-generator using a dynamic Bayesian network. (March 2020)

• Record Type: Journal Article
• Authors: Lee, Dooyoul; Choi, Dongsu
• Is Part Of: Reliability engineering & system safety. Volume 195(2020)
• Publication Date: 2020-03
• Subjects: Bayesian Network -- Reliability-Centered Maintenance -- Starter-Generator -- Bearing; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2019.106628
• Languages: English
• ISSNs: 0951-8320

Abstract

Abstract: The reliability of a starter-generator in transport aircraft was assessed. Using the process of reliability-centered maintenance (RCM), necessary decisions were made not only to satisfy the reliability requirement but also to reduce the maintenance load. Failure data have indicated that the life of a starter-generator is limited by the reliability of a bearing. The degradation of the bearing was represented by a dynamic Bayesian network (DBN). Parameters were learned by using the EM algorithm given failure data. The DBN model yielded more conservative risk projection than traditional survival analysis due to the limited number of failure data. The DBN model can make up for the lack of data records by knowledge of experts. Using a calibrated model, the time for inspection was determined to maintain reliability over a prescribed amount of time.