{"title":"流体输送管道泄漏尺寸估计的声学方法","authors":"Georgios-Panagiotis Kousiopoulos, S. Nikolaidis","doi":"10.1109/mocast54814.2022.9837751","DOIUrl":null,"url":null,"abstract":"Pipeline networks are frequently used in a vast number of applications and their secure and undisturbed operation is very important. However, leaks can occur at any time and cause serious problems. For this reason, extensive research has been conducted over the years on the development of effective leak detection and localization methods. On the other hand, very few papers concerning the estimation of the leak size in a pipeline have been published in the literature. This was a main incentive for the development of the leak size estimation method proposed in the present paper. This non-intrusive method uses the acoustic signals produced in the leak point and propagating in the pipeline and it relies on the energy of the signals, which is reflected in the RMS value, and also on proper filtering. Specifically, by the help of some initial measurements, certain position-dependent threshold values are extracted which separate the different leak categories. This way, by the RMS value of a certain acoustic signal, the corresponding leak can be classified into one of the available categories, which differ from each other on the range of the included leak orifice diameters. The proposed method was tested experimentally in a laboratory setup, which contains a water-filled steel pipeline, and its success rate was examined under different ambient noise conditions.","PeriodicalId":122414,"journal":{"name":"2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Acoustic method for leak size estimation in fluid-carrying pipelines\",\"authors\":\"Georgios-Panagiotis Kousiopoulos, S. Nikolaidis\",\"doi\":\"10.1109/mocast54814.2022.9837751\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Pipeline networks are frequently used in a vast number of applications and their secure and undisturbed operation is very important. However, leaks can occur at any time and cause serious problems. For this reason, extensive research has been conducted over the years on the development of effective leak detection and localization methods. On the other hand, very few papers concerning the estimation of the leak size in a pipeline have been published in the literature. This was a main incentive for the development of the leak size estimation method proposed in the present paper. This non-intrusive method uses the acoustic signals produced in the leak point and propagating in the pipeline and it relies on the energy of the signals, which is reflected in the RMS value, and also on proper filtering. Specifically, by the help of some initial measurements, certain position-dependent threshold values are extracted which separate the different leak categories. This way, by the RMS value of a certain acoustic signal, the corresponding leak can be classified into one of the available categories, which differ from each other on the range of the included leak orifice diameters. The proposed method was tested experimentally in a laboratory setup, which contains a water-filled steel pipeline, and its success rate was examined under different ambient noise conditions.\",\"PeriodicalId\":122414,\"journal\":{\"name\":\"2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)\",\"volume\":\"108 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/mocast54814.2022.9837751\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/mocast54814.2022.9837751","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Acoustic method for leak size estimation in fluid-carrying pipelines
Pipeline networks are frequently used in a vast number of applications and their secure and undisturbed operation is very important. However, leaks can occur at any time and cause serious problems. For this reason, extensive research has been conducted over the years on the development of effective leak detection and localization methods. On the other hand, very few papers concerning the estimation of the leak size in a pipeline have been published in the literature. This was a main incentive for the development of the leak size estimation method proposed in the present paper. This non-intrusive method uses the acoustic signals produced in the leak point and propagating in the pipeline and it relies on the energy of the signals, which is reflected in the RMS value, and also on proper filtering. Specifically, by the help of some initial measurements, certain position-dependent threshold values are extracted which separate the different leak categories. This way, by the RMS value of a certain acoustic signal, the corresponding leak can be classified into one of the available categories, which differ from each other on the range of the included leak orifice diameters. The proposed method was tested experimentally in a laboratory setup, which contains a water-filled steel pipeline, and its success rate was examined under different ambient noise conditions.