Defect recognition of buried pipeline based on approximate entropy and variational mode decomposition

• Autorzy: Ju Haiyang , Wang Xinhua , Zhang Tao , Zhao Yizhen , Ullah Zia

Identyfikatory

DOI

10.24425/mms.2019.129587

• Języki publikacji: EN

Abstrakty

EN

The study aimed to examine the use of Geomagnetic Anomaly Detection (GAD) to locate the buried ferromagnetic pipeline defects without exposing them. However, the accuracy of GAD is limited by the background noise. In the present work, we propose an approximate entropy noise suppression (AENS) method based on Variational Mode Decomposition (VMD) for detection of pipeline defects. The proposed method is capable of reconstructing the magnetic field signals and extracting weak anomaly signals that are submerged in the background noise, which was employed to construct an effective detector of anomalous signals. The internal parameters of VMD were optimized by the Scale–Space algorithm, and their anti-noise performance was compared. The results show that the proposed method can remove the background noise in high-noise background geomagnetic field environments. Experiments were carried out in our laboratory and evaluation results of inspection data were analysed; the feasibility of GAD is validated when used in the application to detection of buried pipeline defects.

Słowa kluczowe

EN

Buried Pipeline; Defect Recognition; Geomagnetic Anomaly Detection; Variational Mode Decomposition; Approximate Entropy

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2019
• Tom: Vol. 26, nr 4
• Strony: 739--755
• Opis fizyczny: Bibliogr. 45 poz., fot., rys., tab., wzory

Twórcy

autor

Ju Haiyang

• Beijing University of Technology, College of Mechanical Engineering and Applied Electronics Technology, 100 Ping Le Yuan, Chaoyang District, Beijing 100124, China

autor

Wang Xinhua

• Beijing University of Technology, College of Mechanical Engineering and Applied Electronics Technology, 100 Ping Le Yuan, Chaoyang District, Beijing 100124, China

autor

Zhang Tao

• Beijing University of Technology, College of Mechanical Engineering and Applied Electronics Technology, 100 Ping Le Yuan, Chaoyang District, Beijing 100124, China

autor

Zhao Yizhen

• Beijing University of Technology, College of Mechanical Engineering and Applied Electronics Technology, 100 Ping Le Yuan, Chaoyang District, Beijing 100124, China

autor

Ullah Zia

• Beijing University of Technology, College of Mechanical Engineering and Applied Electronics Technology, 100 Ping Le Yuan, Chaoyang District, Beijing 100124, China

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Uwagi

EN

This work is supported by the National Key Research and Development Program of China (project number: 2017YFC0805005-1), the Collaborative Innovation Project of Chaoyang District Beijing China (project number: CYXC1709), and the Science and Technology Program of Beijing Municipal Education Commission (project number: KZ201810005009).