A Reliable Pipeline Leak Detection Method Using Acoustic Emission with Time Difference of Arrival and Kolmogorov–Smirnov Test
This paper proposes a novel and reliable leak-detection method for pipeline systems based on acoustic emission (AE) signals. The proposed method analyzes signals from two AE sensors installed on the pipeline to detect leaks located between these two sensors. Firstly, the raw AE signals are preproces...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/23/9296 |
| _version_ | 1797399650761703424 |
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| author | Duc-Thuan Nguyen Tuan-Khai Nguyen Zahoor Ahmad Jong-Myon Kim |
| author_facet | Duc-Thuan Nguyen Tuan-Khai Nguyen Zahoor Ahmad Jong-Myon Kim |
| author_sort | Duc-Thuan Nguyen |
| collection | DOAJ |
| description | This paper proposes a novel and reliable leak-detection method for pipeline systems based on acoustic emission (AE) signals. The proposed method analyzes signals from two AE sensors installed on the pipeline to detect leaks located between these two sensors. Firstly, the raw AE signals are preprocessed using empirical mode decomposition. The time difference of arrival (TDOA) is then extracted as a statistical feature of the two AE signals. The state of the pipeline (leakage/normal) is determined through comparing the statistical distribution of the TDOA of the current state with the prior normal state. Specifically, the two-sample Kolmogorov–Smirnov (K–S) test is applied to compare the statistical distribution of the TDOA feature for leak and non-leak scenarios. The K–S test statistic value in this context functions as a leakage indicator. A new criterion called leak sensitivity is introduced to evaluate and compare the performance of leak detection methods. Extensive experiments were conducted using an industrial pipeline system, and the results demonstrate the excellence of the proposed method in leak detection. Compared to traditional feature-based indicators, our approach achieves a significantly higher performance in leak detection. |
| first_indexed | 2024-03-09T01:43:12Z |
| format | Article |
| id | doaj.art-94d99df03acc4abea4bf4c6d37fe8233 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T01:43:12Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-94d99df03acc4abea4bf4c6d37fe82332023-12-08T15:25:17ZengMDPI AGSensors1424-82202023-11-012323929610.3390/s23239296A Reliable Pipeline Leak Detection Method Using Acoustic Emission with Time Difference of Arrival and Kolmogorov–Smirnov TestDuc-Thuan Nguyen0Tuan-Khai Nguyen1Zahoor Ahmad2Jong-Myon Kim3Department of Electrical, Electronic and Computer Engineering, University of Ulsan, Ulsan 44610, Republic of KoreaDepartment of Electrical, Electronic and Computer Engineering, University of Ulsan, Ulsan 44610, Republic of KoreaDepartment of Electrical, Electronic and Computer Engineering, University of Ulsan, Ulsan 44610, Republic of KoreaDepartment of Electrical, Electronic and Computer Engineering, University of Ulsan, Ulsan 44610, Republic of KoreaThis paper proposes a novel and reliable leak-detection method for pipeline systems based on acoustic emission (AE) signals. The proposed method analyzes signals from two AE sensors installed on the pipeline to detect leaks located between these two sensors. Firstly, the raw AE signals are preprocessed using empirical mode decomposition. The time difference of arrival (TDOA) is then extracted as a statistical feature of the two AE signals. The state of the pipeline (leakage/normal) is determined through comparing the statistical distribution of the TDOA of the current state with the prior normal state. Specifically, the two-sample Kolmogorov–Smirnov (K–S) test is applied to compare the statistical distribution of the TDOA feature for leak and non-leak scenarios. The K–S test statistic value in this context functions as a leakage indicator. A new criterion called leak sensitivity is introduced to evaluate and compare the performance of leak detection methods. Extensive experiments were conducted using an industrial pipeline system, and the results demonstrate the excellence of the proposed method in leak detection. Compared to traditional feature-based indicators, our approach achieves a significantly higher performance in leak detection.https://www.mdpi.com/1424-8220/23/23/9296leak detectionpipeline systemsacoustic emissiontime difference of arrivalcross-correlationKolmogorov–Smirnov test |
| spellingShingle | Duc-Thuan Nguyen Tuan-Khai Nguyen Zahoor Ahmad Jong-Myon Kim A Reliable Pipeline Leak Detection Method Using Acoustic Emission with Time Difference of Arrival and Kolmogorov–Smirnov Test Sensors leak detection pipeline systems acoustic emission time difference of arrival cross-correlation Kolmogorov–Smirnov test |
| title | A Reliable Pipeline Leak Detection Method Using Acoustic Emission with Time Difference of Arrival and Kolmogorov–Smirnov Test |
| title_full | A Reliable Pipeline Leak Detection Method Using Acoustic Emission with Time Difference of Arrival and Kolmogorov–Smirnov Test |
| title_fullStr | A Reliable Pipeline Leak Detection Method Using Acoustic Emission with Time Difference of Arrival and Kolmogorov–Smirnov Test |
| title_full_unstemmed | A Reliable Pipeline Leak Detection Method Using Acoustic Emission with Time Difference of Arrival and Kolmogorov–Smirnov Test |
| title_short | A Reliable Pipeline Leak Detection Method Using Acoustic Emission with Time Difference of Arrival and Kolmogorov–Smirnov Test |
| title_sort | reliable pipeline leak detection method using acoustic emission with time difference of arrival and kolmogorov smirnov test |
| topic | leak detection pipeline systems acoustic emission time difference of arrival cross-correlation Kolmogorov–Smirnov test |
| url | https://www.mdpi.com/1424-8220/23/23/9296 |
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