J. Folmer, B. Weißenberger, B. Vogel‐Heuser, Heiko Meyer
{"title":"基于工程和历史数据的自动化设备诊断","authors":"J. Folmer, B. Weißenberger, B. Vogel‐Heuser, Heiko Meyer","doi":"10.1109/ETFA.2012.6489688","DOIUrl":null,"url":null,"abstract":"In automation, the suited scheduled maintenance is one of the keys for plants' operation in order to minimize plants' shutdown. Usually, maintenance is time-interval based or operation-time based to prevent plant shutdowns by means of displacing aged automation devices early. This causes an increasing expenditure due to the fact that the replaced automation devices could be in operation longer and the plant has to be stopped for replacing the device. In this paper we present an approach focusing on combining engineering data and historical process data to extract additional information and applying analysis methods for diagnosis. We introduce how to find cause-effect dependencies of failures during abnormal plant situations to forecast abnormal and critical plant situations.","PeriodicalId":222799,"journal":{"name":"Proceedings of 2012 IEEE 17th International Conference on Emerging Technologies & Factory Automation (ETFA 2012)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Diagnosis of automation devices based on engineering and historical data\",\"authors\":\"J. Folmer, B. Weißenberger, B. Vogel‐Heuser, Heiko Meyer\",\"doi\":\"10.1109/ETFA.2012.6489688\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In automation, the suited scheduled maintenance is one of the keys for plants' operation in order to minimize plants' shutdown. Usually, maintenance is time-interval based or operation-time based to prevent plant shutdowns by means of displacing aged automation devices early. This causes an increasing expenditure due to the fact that the replaced automation devices could be in operation longer and the plant has to be stopped for replacing the device. In this paper we present an approach focusing on combining engineering data and historical process data to extract additional information and applying analysis methods for diagnosis. We introduce how to find cause-effect dependencies of failures during abnormal plant situations to forecast abnormal and critical plant situations.\",\"PeriodicalId\":222799,\"journal\":{\"name\":\"Proceedings of 2012 IEEE 17th International Conference on Emerging Technologies & Factory Automation (ETFA 2012)\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 2012 IEEE 17th International Conference on Emerging Technologies & Factory Automation (ETFA 2012)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ETFA.2012.6489688\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2012 IEEE 17th International Conference on Emerging Technologies & Factory Automation (ETFA 2012)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETFA.2012.6489688","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Diagnosis of automation devices based on engineering and historical data
In automation, the suited scheduled maintenance is one of the keys for plants' operation in order to minimize plants' shutdown. Usually, maintenance is time-interval based or operation-time based to prevent plant shutdowns by means of displacing aged automation devices early. This causes an increasing expenditure due to the fact that the replaced automation devices could be in operation longer and the plant has to be stopped for replacing the device. In this paper we present an approach focusing on combining engineering data and historical process data to extract additional information and applying analysis methods for diagnosis. We introduce how to find cause-effect dependencies of failures during abnormal plant situations to forecast abnormal and critical plant situations.