{"title":"基于复杂网络方法的配水系统泄漏识别","authors":"M. Nicolini","doi":"10.1109/ICKII.2018.8569182","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce a new methodology based on Complex Network Theory aimed at the prompt identification of leakages occurring in a water distribution system. The underlying idea is a data mining algorithm which, starting from real-time measurements of pressure gages installed in the system, builds a virtual complex network in which the nodes are represented by the locations of instrumentation and links are created if the correlation coefficient between pressure signals is above a given threshold. For the system analyzed in the paper, we show that the node in which the leak forms is always characterized by the lowest degree centrality with respect to all the others, thus giving the possibility of its early identification.","PeriodicalId":170587,"journal":{"name":"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Leakage Identification in Water Distribution Systems with a Complex Networks Approach\",\"authors\":\"M. Nicolini\",\"doi\":\"10.1109/ICKII.2018.8569182\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we introduce a new methodology based on Complex Network Theory aimed at the prompt identification of leakages occurring in a water distribution system. The underlying idea is a data mining algorithm which, starting from real-time measurements of pressure gages installed in the system, builds a virtual complex network in which the nodes are represented by the locations of instrumentation and links are created if the correlation coefficient between pressure signals is above a given threshold. For the system analyzed in the paper, we show that the node in which the leak forms is always characterized by the lowest degree centrality with respect to all the others, thus giving the possibility of its early identification.\",\"PeriodicalId\":170587,\"journal\":{\"name\":\"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICKII.2018.8569182\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICKII.2018.8569182","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Leakage Identification in Water Distribution Systems with a Complex Networks Approach
In this paper, we introduce a new methodology based on Complex Network Theory aimed at the prompt identification of leakages occurring in a water distribution system. The underlying idea is a data mining algorithm which, starting from real-time measurements of pressure gages installed in the system, builds a virtual complex network in which the nodes are represented by the locations of instrumentation and links are created if the correlation coefficient between pressure signals is above a given threshold. For the system analyzed in the paper, we show that the node in which the leak forms is always characterized by the lowest degree centrality with respect to all the others, thus giving the possibility of its early identification.