Xiugang Chen , Cuiwei Liu , Kang Xiao , Wenjie Liu , Tao Gu , Yuxing Li
{"title":"基于振动信号的埋地输气管道泄漏识别实验研究","authors":"Xiugang Chen , Cuiwei Liu , Kang Xiao , Wenjie Liu , Tao Gu , Yuxing Li","doi":"10.1016/j.jpse.2024.100230","DOIUrl":null,"url":null,"abstract":"<div><div>It is difficult to detect and locate small leakages, especially for buried pipelines. Therefore, a non-intrusive leakage identification method for buried gas pipelines is proposed in this study. Accelerometers were arranged in the soil at a certain distance from the leakage orifice to capture the acceleration signals caused by leakage. A 7-layer wavelet transform was applied to extract the leakage characteristic frequency band. Meanwhile, the attenuation characteristics of vibration signals were analyzed and the signal amplitude attenuation patterns in the axial, radial, and circumferential directions were analyzed. The results show that the leakage recognition rate is nearly 100% by selecting a peak signal-to-noise ratio (P-SNR) threshold of 7.26. Thus, the non-intrusive method based on accelerometers can be successfully applied for the leakage monitoring of buried gas pipelines.</div></div>","PeriodicalId":100824,"journal":{"name":"Journal of Pipeline Science and Engineering","volume":"5 2","pages":"Article 100230"},"PeriodicalIF":4.8000,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Experimental study on the leakage identification for the buried gas pipeline via vibration signals\",\"authors\":\"Xiugang Chen , Cuiwei Liu , Kang Xiao , Wenjie Liu , Tao Gu , Yuxing Li\",\"doi\":\"10.1016/j.jpse.2024.100230\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>It is difficult to detect and locate small leakages, especially for buried pipelines. Therefore, a non-intrusive leakage identification method for buried gas pipelines is proposed in this study. Accelerometers were arranged in the soil at a certain distance from the leakage orifice to capture the acceleration signals caused by leakage. A 7-layer wavelet transform was applied to extract the leakage characteristic frequency band. Meanwhile, the attenuation characteristics of vibration signals were analyzed and the signal amplitude attenuation patterns in the axial, radial, and circumferential directions were analyzed. The results show that the leakage recognition rate is nearly 100% by selecting a peak signal-to-noise ratio (P-SNR) threshold of 7.26. Thus, the non-intrusive method based on accelerometers can be successfully applied for the leakage monitoring of buried gas pipelines.</div></div>\",\"PeriodicalId\":100824,\"journal\":{\"name\":\"Journal of Pipeline Science and Engineering\",\"volume\":\"5 2\",\"pages\":\"Article 100230\"},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2024-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Pipeline Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S266714332400057X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Pipeline Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S266714332400057X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Experimental study on the leakage identification for the buried gas pipeline via vibration signals
It is difficult to detect and locate small leakages, especially for buried pipelines. Therefore, a non-intrusive leakage identification method for buried gas pipelines is proposed in this study. Accelerometers were arranged in the soil at a certain distance from the leakage orifice to capture the acceleration signals caused by leakage. A 7-layer wavelet transform was applied to extract the leakage characteristic frequency band. Meanwhile, the attenuation characteristics of vibration signals were analyzed and the signal amplitude attenuation patterns in the axial, radial, and circumferential directions were analyzed. The results show that the leakage recognition rate is nearly 100% by selecting a peak signal-to-noise ratio (P-SNR) threshold of 7.26. Thus, the non-intrusive method based on accelerometers can be successfully applied for the leakage monitoring of buried gas pipelines.