Pipeline Leakage Detection and Localization Using a Reliable Pipeline-Mechanism Model Incorporating a Bayesian Model Updating Approach
Pipeline transportation is widely used in industrial production and daily life. In order to reduce the waste of resources and economic losses caused by pipeline leakage, effective pipeline leakage detection and localization technology is particularly important. Among the many leakage detection metho...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-04-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/14/8/1255 |
| _version_ | 1797434167216046080 |
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| author | Mengfei Zhou Yinze Xu Baihui Cui Yinchao Hu Tian Guo Yijun Cai Xiaofang Sun |
| author_facet | Mengfei Zhou Yinze Xu Baihui Cui Yinchao Hu Tian Guo Yijun Cai Xiaofang Sun |
| author_sort | Mengfei Zhou |
| collection | DOAJ |
| description | Pipeline transportation is widely used in industrial production and daily life. In order to reduce the waste of resources and economic losses caused by pipeline leakage, effective pipeline leakage detection and localization technology is particularly important. Among the many leakage detection methods, the model-based method for pipeline leakage detection and localization is widely used. However, the key to the method is how to obtain an accurate and reliable pipeline model to ensure and improve the detection accuracy. This paper proposes a novel method to obtain a reliable pipeline-mechanism model that fused data and mechanism models based on Bayesian theory. Moreover, in the process of Bayesian fusion, the complexity and calculations in the mechanism models were greatly reduced by establishing a surrogate model. After that, the multidimensional posterior distribution was sampled by the Markov chain Monte Carlo-differential evolution adaptive metropolis (ZS) (MCMC-DREAM (ZS)) algorithm, and the uncertainty in the model was updated to obtain a reliable pipeline-mechanism model. Subsequently, the pipeline resistance coefficient, which could be calculated based on the reliable pipeline-mechanism model, was proposed as an indicator for detecting whether the pipeline leaked or not. Finally, the pipeline leak model was used to determine the location of the leak. The reliable pipeline-mechanism model was applied in an experimental device to validate its performance. The results showed that the proposed method improved the accuracy and reliability of the mechanism model, and, in addition, the leakage could be accurately located. |
| first_indexed | 2024-03-09T10:27:21Z |
| format | Article |
| id | doaj.art-8ccfd0a57f3f4325b64456af34b42c09 |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-09T10:27:21Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-8ccfd0a57f3f4325b64456af34b42c092023-12-01T21:31:49ZengMDPI AGWater2073-44412022-04-01148125510.3390/w14081255Pipeline Leakage Detection and Localization Using a Reliable Pipeline-Mechanism Model Incorporating a Bayesian Model Updating ApproachMengfei Zhou0Yinze Xu1Baihui Cui2Yinchao Hu3Tian Guo4Yijun Cai5Xiaofang Sun6College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, ChinaCollege of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, ChinaCollege of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, ChinaCollege of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, ChinaCollege of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, ChinaCollege of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, ChinaCollege of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310014, ChinaPipeline transportation is widely used in industrial production and daily life. In order to reduce the waste of resources and economic losses caused by pipeline leakage, effective pipeline leakage detection and localization technology is particularly important. Among the many leakage detection methods, the model-based method for pipeline leakage detection and localization is widely used. However, the key to the method is how to obtain an accurate and reliable pipeline model to ensure and improve the detection accuracy. This paper proposes a novel method to obtain a reliable pipeline-mechanism model that fused data and mechanism models based on Bayesian theory. Moreover, in the process of Bayesian fusion, the complexity and calculations in the mechanism models were greatly reduced by establishing a surrogate model. After that, the multidimensional posterior distribution was sampled by the Markov chain Monte Carlo-differential evolution adaptive metropolis (ZS) (MCMC-DREAM (ZS)) algorithm, and the uncertainty in the model was updated to obtain a reliable pipeline-mechanism model. Subsequently, the pipeline resistance coefficient, which could be calculated based on the reliable pipeline-mechanism model, was proposed as an indicator for detecting whether the pipeline leaked or not. Finally, the pipeline leak model was used to determine the location of the leak. The reliable pipeline-mechanism model was applied in an experimental device to validate its performance. The results showed that the proposed method improved the accuracy and reliability of the mechanism model, and, in addition, the leakage could be accurately located.https://www.mdpi.com/2073-4441/14/8/1255pipeline leakage detection and localizationmechanism modelmodel reliabilityBayesian theorypipeline resistance coefficientuncertainty quantification |
| spellingShingle | Mengfei Zhou Yinze Xu Baihui Cui Yinchao Hu Tian Guo Yijun Cai Xiaofang Sun Pipeline Leakage Detection and Localization Using a Reliable Pipeline-Mechanism Model Incorporating a Bayesian Model Updating Approach Water pipeline leakage detection and localization mechanism model model reliability Bayesian theory pipeline resistance coefficient uncertainty quantification |
| title | Pipeline Leakage Detection and Localization Using a Reliable Pipeline-Mechanism Model Incorporating a Bayesian Model Updating Approach |
| title_full | Pipeline Leakage Detection and Localization Using a Reliable Pipeline-Mechanism Model Incorporating a Bayesian Model Updating Approach |
| title_fullStr | Pipeline Leakage Detection and Localization Using a Reliable Pipeline-Mechanism Model Incorporating a Bayesian Model Updating Approach |
| title_full_unstemmed | Pipeline Leakage Detection and Localization Using a Reliable Pipeline-Mechanism Model Incorporating a Bayesian Model Updating Approach |
| title_short | Pipeline Leakage Detection and Localization Using a Reliable Pipeline-Mechanism Model Incorporating a Bayesian Model Updating Approach |
| title_sort | pipeline leakage detection and localization using a reliable pipeline mechanism model incorporating a bayesian model updating approach |
| topic | pipeline leakage detection and localization mechanism model model reliability Bayesian theory pipeline resistance coefficient uncertainty quantification |
| url | https://www.mdpi.com/2073-4441/14/8/1255 |
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