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Pipeline defect detection with depth identification using PZT array and time-reversal method

  • Yang Xu (Department of Automation, School of Electronic Information and Electrical Engineering, Yangtze University) ;
  • Mingzhang Luo (Department of Automation, School of Electronic Information and Electrical Engineering, Yangtze University) ;
  • Guofeng Du (Department of Civil and Engineering Management, School of Urban Construction, Yangtze University)
  • Received : 2022.06.13
  • Accepted : 2023.10.12
  • Published : 2023.10.25

Abstract

The time-reversal method is employed to improve the ability of pipeline defect detection, and a new approach of identifying the pipeline defect depth is proposed in this research. When the L(0,2) mode ultrasonic guided wave excited through a lead zirconate titinate (PZT) transduce array propagates along the pipeline with a defect, it will interact with the defect and be partially converted to flexural F(n, m) modes and longitudinal L(0,1) mode. Using a receiving PZT array attached axisymmetrically around the pipeline, the L(0,2) reflection signal as well as the mode conversion signals at the defect are obtained. An appropriate rectangle window is used to intercept the L(0,2) reflection signal and the mode conversion signals from the obtained direct detection signals. The intercepted signals are time reversed and re-excited in the pipeline again, result in the guided wave energy focusing on the pipeline defect, the L(0,2) reflection and the L(0,1) mode conversion signals being enhanced to a higher level, especially for the small defect in the early crack stage. Besides the L(0,2) reflection signal, the L(0,1) mode conversion signal also contains useful pipeline defect information. It is possible to identify the pipeline defect depth by monitoring the variation trend of L(0,2) and L(0,1) reflection coefficients. The finite element method (FEM) simulation and experiment results are given in the paper, the enhancement of pipeline defect reflection signals by time-reversal method is obvious, and the way to identify pipeline defect depth is demonstrated to be effective.

Keywords

Acknowledgement

The research described in this paper was financially supported by the National Natural Science Foundation of China (grant number 52078052), and the China National Petroleum Corporation Essential Research and Strategic Reserve Technology Research Fund Project (grant number 2017Z-05).

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