{"title":"基于分布式主成分分析方法的污水处理厂故障检测","authors":"A. Sánchez-Fernández, M. J. Fuente, G. Palmero","doi":"10.1109/ETFA.2015.7301504","DOIUrl":null,"url":null,"abstract":"This paper proposes a distributed fault detection and diagnosis method based on Principal Component Analysis (PCA) in a whole plant monitoring scheme. The method is based on the decomposition of the plant into multiple blocks using plant topology. A local PCA based fault detection method is applied in each block and the results are sent to the central node to fuse the information and to detect and diagnose faults in the global plant. This method is compared with the centralized PCA method and some distributed principal component analysis (DPCA) methods in a wastewater treatment plant (WWTP). The objective is to check which of the distributed methods implemented is the best one in terms of detecting faults and minimizing the communication cost between the blocks. Empirical results on the WWTP show that the DPCA method based on local models has very good results.","PeriodicalId":6862,"journal":{"name":"2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA)","volume":"9 1","pages":"1-7"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"Fault detection in wastewater treatment plants using distributed PCA methods\",\"authors\":\"A. Sánchez-Fernández, M. J. Fuente, G. Palmero\",\"doi\":\"10.1109/ETFA.2015.7301504\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a distributed fault detection and diagnosis method based on Principal Component Analysis (PCA) in a whole plant monitoring scheme. The method is based on the decomposition of the plant into multiple blocks using plant topology. A local PCA based fault detection method is applied in each block and the results are sent to the central node to fuse the information and to detect and diagnose faults in the global plant. This method is compared with the centralized PCA method and some distributed principal component analysis (DPCA) methods in a wastewater treatment plant (WWTP). The objective is to check which of the distributed methods implemented is the best one in terms of detecting faults and minimizing the communication cost between the blocks. Empirical results on the WWTP show that the DPCA method based on local models has very good results.\",\"PeriodicalId\":6862,\"journal\":{\"name\":\"2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA)\",\"volume\":\"9 1\",\"pages\":\"1-7\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ETFA.2015.7301504\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETFA.2015.7301504","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fault detection in wastewater treatment plants using distributed PCA methods
This paper proposes a distributed fault detection and diagnosis method based on Principal Component Analysis (PCA) in a whole plant monitoring scheme. The method is based on the decomposition of the plant into multiple blocks using plant topology. A local PCA based fault detection method is applied in each block and the results are sent to the central node to fuse the information and to detect and diagnose faults in the global plant. This method is compared with the centralized PCA method and some distributed principal component analysis (DPCA) methods in a wastewater treatment plant (WWTP). The objective is to check which of the distributed methods implemented is the best one in terms of detecting faults and minimizing the communication cost between the blocks. Empirical results on the WWTP show that the DPCA method based on local models has very good results.