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作者:

Wang, Xinhua (Wang, Xinhua.) | Gu, Yaping (Gu, Yaping.) | Chen, Yingchun (Chen, Yingchun.) | Ullah, Zia (Ullah, Zia.) | Zhao, Yizhen (Zhao, Yizhen.)

收录:

EI SCIE

摘要:

This paper presents a harmonic magnetic field detection technology for damage identification of an in-service coated steel pipeline. Based on the principles of electromagnetic theory and magnetic field detection combined with magnetic focusing technology, an array consisting of a focusing detection probe and a harmonic magnetic field detection system were designed. However, the acquired detection signal includes an excitation signal in addition to the defect information. In order to make the defect information more obvious, the excitation signal needs to be removed to extract the defect feature. Local mean decomposition (LMD) is a new time-frequency analysis method that adaptively decomposes a signal into a set of product function (PF) combinations. The envelope of the PF is the instantaneous amplitude and the instantaneous frequency can be calculated by demodulating the derivative of the phase with a uniform amplitude-modulated signal. This method completely bypasses the Hilbert transform. Therefore, it does not involve the problem of negative frequencies without physical meaning. The effectiveness of LMD is demonstrated by a successful example of damage detection. Combining the data characteristics obtained by the experiment, the data processing algorithm suitable for the test data is written by improving the LMD. The algorithm is easy to use and has high engineering practicability.

关键词:

damage detection data processing harmonic magnetic field local mean decomposition

作者机构:

  • [ 1 ] [Wang, Xinhua]Beijing Univ Technol, Dept Mech Engn & Appl Elect Technol, Beijing, Peoples R China
  • [ 2 ] [Gu, Yaping]Beijing Univ Technol, Dept Mech Engn & Appl Elect Technol, Beijing, Peoples R China
  • [ 3 ] [Chen, Yingchun]Beijing Univ Technol, Dept Mech Engn & Appl Elect Technol, Beijing, Peoples R China
  • [ 4 ] [Ullah, Zia]Beijing Univ Technol, Dept Mech Engn & Appl Elect Technol, Beijing, Peoples R China
  • [ 5 ] [Zhao, Yizhen]Beijing Univ Technol, Dept Mech Engn & Appl Elect Technol, Beijing, Peoples R China

通讯作者信息:

  • [Chen, Yingchun]Beijing Univ Technol, Dept Mech Engn & Appl Elect Technol, Beijing, Peoples R China

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来源 :

INSIGHT

ISSN: 1354-2575

年份: 2020

期: 9

卷: 62

页码: 533-539

1 . 1 0 0

JCR@2022

ESI学科: ENGINEERING;

ESI高被引阀值:28

JCR分区:4

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WoS核心集被引频次: 2

SCOPUS被引频次: 2

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