Geomagnetic detection method for pipeline defects based on ceemdan and WEP-TEO

• Autorzy: Zhang Tao , Wang Xinhua , Chen Yingchun , Shuai Yi , Ullah Zia , Ju Haiyang , Zhao Yizhen

Identyfikatory

DOI

10.24425/mms.2019.128363

• Języki publikacji: EN

Abstrakty

EN

This paper presents a geomagnetic detection method for pipeline defects using complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and wavelet energy product (WEP) - Teager energy operator (TEO), which improves detection accuracy and defect identification ability as encountering strong inference noise. The measured signal is first subtly decomposed via CEEMDAN into a series of intrinsic mode functions (IMFs), which are then distinguished by the Hurst exponent to reconstruct the filtered signal. Subsequently, the scale signals are obtained by using gradient calculation and discrete wavelet transform and are then fused by using WEP. Finally, TEO is implemented to enhance defect signal amplitude, completing geomagnetic detection of pipeline defects. The simulation results created by magnetic dipole in a noisy environment, indoor experiment results and field testing results certify that the proposed method outperforms ensemble empirical mode decomposition (EEMD)-gradient, EEMD-WEP-TEO, CEEMDAN-gradient in terms of detection deviation, peak side-lobe ratio (PSLR) and integrated side-lobe ratio (ISLR).

Słowa kluczowe

EN

geomagnetic detection; pipeline defects; magnetic field; filtering; data processing

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2019
• Tom: Vol. 26, nr 2
• Strony: 345--361
• Opis fizyczny: Bibliogr. 29 poz., fot., rys., tab., wykr., wzory

Twórcy

autor

Zhang Tao

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

autor

Wang Xinhua

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

autor

Chen Yingchun

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

autor

Shuai Yi

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

autor

Ullah Zia

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

autor

Ju Haiyang

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

autor

Zhao Yizhen

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

Bibliografia

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Uwagi

EN

1. This work was supported by the National Key Research and Development Program of China (2017YFC 0805005-1), Science and Technology Program of Beijing Municipal Education Commission (KZ2018 10005009), Collaborative Innovation Project of Chaoyang District Beijing China (CYXC1709), China Postdoctoral Science Foundation (2018T110018), and “Rixin Scientist” of Beijing University of Technology.

PL

2. Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).