{"title":"Source location and anomaly detection for damage identification of buried pipelines using kurtosis-based transfer function","authors":"Sun-Ho Lee, Choon-su Park, D. Yoon","doi":"10.1177/14759217231191080","DOIUrl":null,"url":null,"abstract":"The failure of buried pipelines can lead to serious consequences such as explosions, environmental pollution, settlement, as well as economic loss. To prevent these outcomes, it is crucial to identify the causes of failure and monitor their signs. One of the main causes of failure is unexpected third-party interference (TPI), which is particularly challenging to detect. Regarding to this issue, this study proposes a new algorithm for monitoring impact damage, which can be used for prompt response and damage prevention. The algorithm is integrated into the system using two approaches. The first approach focuses on detecting the location of the damage (referred to as source location). A kurtosis-based transfer function was newly proposed to selecting the optimal frequency band for time-difference-of-arrival based source location, resulting in accurate pinpointing of damage, even in a noisy environment. The second approach is used to determine whether impact damage has actually occurred by observing newly suggested features in both the time and frequency domains (referred to as anomaly detection). These features evaluate the presence of damage and the similarity between signals. As a result, it was evaluated that the field applicability was higher than that of conventional methods, and the superiority of the proposed method was also verified through field experiments. The method proposed in this study is expected to enable immediate response when the integrity of the buried pipelines is on the line of failure due to TPI.","PeriodicalId":51184,"journal":{"name":"Structural Health Monitoring-An International Journal","volume":null,"pages":null},"PeriodicalIF":5.7000,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Structural Health Monitoring-An International Journal","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1177/14759217231191080","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
The failure of buried pipelines can lead to serious consequences such as explosions, environmental pollution, settlement, as well as economic loss. To prevent these outcomes, it is crucial to identify the causes of failure and monitor their signs. One of the main causes of failure is unexpected third-party interference (TPI), which is particularly challenging to detect. Regarding to this issue, this study proposes a new algorithm for monitoring impact damage, which can be used for prompt response and damage prevention. The algorithm is integrated into the system using two approaches. The first approach focuses on detecting the location of the damage (referred to as source location). A kurtosis-based transfer function was newly proposed to selecting the optimal frequency band for time-difference-of-arrival based source location, resulting in accurate pinpointing of damage, even in a noisy environment. The second approach is used to determine whether impact damage has actually occurred by observing newly suggested features in both the time and frequency domains (referred to as anomaly detection). These features evaluate the presence of damage and the similarity between signals. As a result, it was evaluated that the field applicability was higher than that of conventional methods, and the superiority of the proposed method was also verified through field experiments. The method proposed in this study is expected to enable immediate response when the integrity of the buried pipelines is on the line of failure due to TPI.
期刊介绍:
Structural Health Monitoring is an international peer reviewed journal that publishes the highest quality original research that contain theoretical, analytical, and experimental investigations that advance the body of knowledge and its application in the discipline of structural health monitoring.