{"title":"航空发动机排气测量通道的神经网络建模","authors":"F. Adamčík, R. Andoga, P. Krajňák, L. Madarász","doi":"10.1109/INES.2011.5954756","DOIUrl":null,"url":null,"abstract":"The article is focused on diagnostics in the field of aviation turbo-jet engines. Evaluation of their technical status, and potential failures and pre-failure processes can be improved by monitoring their thermally loaded components. Part of the research in the given area also involves mathematical modeling of the channel measuring the exhaust gases temperature, using neural networks to compensate for dynamic errors of slow thermocouples used in such measurements.","PeriodicalId":414812,"journal":{"name":"2011 15th IEEE International Conference on Intelligent Engineering Systems","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling of the measurement channel of outlet gases of the aviation engine using neural networks\",\"authors\":\"F. Adamčík, R. Andoga, P. Krajňák, L. Madarász\",\"doi\":\"10.1109/INES.2011.5954756\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The article is focused on diagnostics in the field of aviation turbo-jet engines. Evaluation of their technical status, and potential failures and pre-failure processes can be improved by monitoring their thermally loaded components. Part of the research in the given area also involves mathematical modeling of the channel measuring the exhaust gases temperature, using neural networks to compensate for dynamic errors of slow thermocouples used in such measurements.\",\"PeriodicalId\":414812,\"journal\":{\"name\":\"2011 15th IEEE International Conference on Intelligent Engineering Systems\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 15th IEEE International Conference on Intelligent Engineering Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INES.2011.5954756\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 15th IEEE International Conference on Intelligent Engineering Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INES.2011.5954756","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling of the measurement channel of outlet gases of the aviation engine using neural networks
The article is focused on diagnostics in the field of aviation turbo-jet engines. Evaluation of their technical status, and potential failures and pre-failure processes can be improved by monitoring their thermally loaded components. Part of the research in the given area also involves mathematical modeling of the channel measuring the exhaust gases temperature, using neural networks to compensate for dynamic errors of slow thermocouples used in such measurements.
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