{"title":"基于贝叶斯网络和故障树的涡轮压气机故障诊断决策工具的开发与应用","authors":"Abdelaziz Lakehal, mourad nahal, Riad Harouz","doi":"10.24425/mper.2019.129565","DOIUrl":null,"url":null,"abstract":"Fault Tree is one of the traditional and conventional approaches used in fault diagnosis. By identifying combinations of faults in a logical framework it’s possible to define the structure of the fault tree. The same go with Bayesian networks, but the difference of these probabilis- tic tools is in their ability to reasoning under uncertainty. Some typical constraints to the fault diagnosis have been eliminated by the conversion to a Bayesian network. This paper shows that information processing has become simple and easy through the use of Bayesian networks. The study presented showed that updating knowledge and exploiting new knowl- edge does not complicate calculations. The contribution is the structural approach of faults diagnosis of turbo compressor qualitatively and quantitatively, the most likely faults are defined in descending order. The approach presented in this paper has been successfully applied to turbo compressor, which represent vital equipment in petrochemical plant.","PeriodicalId":45454,"journal":{"name":"Management and Production Engineering Review","volume":"7 8","pages":"0"},"PeriodicalIF":0.9000,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Development and application of a decision making tool for fault diagnosis of turbocompressor basedon Bayesian network and fault tree\",\"authors\":\"Abdelaziz Lakehal, mourad nahal, Riad Harouz\",\"doi\":\"10.24425/mper.2019.129565\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fault Tree is one of the traditional and conventional approaches used in fault diagnosis. By identifying combinations of faults in a logical framework it’s possible to define the structure of the fault tree. The same go with Bayesian networks, but the difference of these probabilis- tic tools is in their ability to reasoning under uncertainty. Some typical constraints to the fault diagnosis have been eliminated by the conversion to a Bayesian network. This paper shows that information processing has become simple and easy through the use of Bayesian networks. The study presented showed that updating knowledge and exploiting new knowl- edge does not complicate calculations. The contribution is the structural approach of faults diagnosis of turbo compressor qualitatively and quantitatively, the most likely faults are defined in descending order. The approach presented in this paper has been successfully applied to turbo compressor, which represent vital equipment in petrochemical plant.\",\"PeriodicalId\":45454,\"journal\":{\"name\":\"Management and Production Engineering Review\",\"volume\":\"7 8\",\"pages\":\"0\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2023-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Management and Production Engineering Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24425/mper.2019.129565\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Management and Production Engineering Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24425/mper.2019.129565","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
Development and application of a decision making tool for fault diagnosis of turbocompressor basedon Bayesian network and fault tree
Fault Tree is one of the traditional and conventional approaches used in fault diagnosis. By identifying combinations of faults in a logical framework it’s possible to define the structure of the fault tree. The same go with Bayesian networks, but the difference of these probabilis- tic tools is in their ability to reasoning under uncertainty. Some typical constraints to the fault diagnosis have been eliminated by the conversion to a Bayesian network. This paper shows that information processing has become simple and easy through the use of Bayesian networks. The study presented showed that updating knowledge and exploiting new knowl- edge does not complicate calculations. The contribution is the structural approach of faults diagnosis of turbo compressor qualitatively and quantitatively, the most likely faults are defined in descending order. The approach presented in this paper has been successfully applied to turbo compressor, which represent vital equipment in petrochemical plant.
期刊介绍:
Management and Production Engineering Review (MPER) is a peer-refereed, international, multidisciplinary journal covering a broad spectrum of topics in production engineering and management. Production engineering is a currently developing stream of science encompassing planning, design, implementation and management of production and logistic systems. Orientation towards human resources factor differentiates production engineering from other technical disciplines. The journal aims to advance the theoretical and applied knowledge of this rapidly evolving field, with a special focus on production management, organisation of production processes, management of production knowledge, computer integrated management of production flow, enterprise effectiveness, maintainability and sustainable manufacturing, productivity and organisation, forecasting, modelling and simulation, decision making systems, project management, innovation management and technology transfer, quality engineering and safety at work, supply chain optimization and logistics. Management and Production Engineering Review is published under the auspices of the Polish Academy of Sciences Committee on Production Engineering and Polish Association for Production Management.