{"title":"Health Condition Monitoring of Aero-engine Based on Ant Colony Algorithm","authors":"Zhang Chuan-chao","doi":"10.1109/ICICTA.2011.43","DOIUrl":null,"url":null,"abstract":"An algorithm based on ant colony algorithm for health condition monitoring of aero-engine was put forward. The algorithm conversed the health status classification of aero-engine into solving the clustering-based optimization problem with constrain. Ant colony algorithm based on colony collaboration and learning could solve this clustering problem. The proposed algorithm was applied to monitor health condition of aero-engine. The emulation result shows that the algorithm has the merits of simple realization, fast convergence, strong parallelism and robustness, high identification accuracy and high reliability, and is fit for health condition monitoring of aero-engine with low demands on fault samples.","PeriodicalId":368130,"journal":{"name":"2011 Fourth International Conference on Intelligent Computation Technology and Automation","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Fourth International Conference on Intelligent Computation Technology and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICTA.2011.43","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
An algorithm based on ant colony algorithm for health condition monitoring of aero-engine was put forward. The algorithm conversed the health status classification of aero-engine into solving the clustering-based optimization problem with constrain. Ant colony algorithm based on colony collaboration and learning could solve this clustering problem. The proposed algorithm was applied to monitor health condition of aero-engine. The emulation result shows that the algorithm has the merits of simple realization, fast convergence, strong parallelism and robustness, high identification accuracy and high reliability, and is fit for health condition monitoring of aero-engine with low demands on fault samples.