An Improved Time-frequency Identification Method for Pipeline Weld EMAE Aliasing Modes with a Focused Electromagnetic Excitation Device | Zendy

Houshi Ding | Zendy; Pan Hu | Zendy; Tongyu Zhao | Zendy; Yuchao Jin | Zendy; Xu Gui | Zendy

Open Access

An Improved Time-frequency Identification Method for Pipeline Weld EMAE Aliasing Modes with a Focused Electromagnetic Excitation Device

Author(s) -

Houshi Ding,

Pan Hu,

Tongyu Zhao,

Yuchao Jin,

Xu Gui

Publication year - 2025

Publication title -

ieee access

Language(s) - English

Resource type - Magazines

SCImago Journal Rank - 0.587

H-Index - 127

eISSN - 2169-3536

DOI - 10.1109/access.2025.3575797

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

The detection of circumferential cracks in pipeline welds is crucial for ensuring pipeline safety. Electromagnetic acoustic emission (EMAE) is favored for its controllable inspection process and its sensitivity to small defects, making it particularly effective for detecting pipeline weld cracks. However, the complex nature of EMAE signals, which consist of both guided wave and acoustic emission (AE) components, presents challenges in the design of excitation devices and mode identification. This paper presents an improved time-frequency identification method for pipeline weld EMAE aliasing modes with a focused electromagnetic excitation device. The focused electromagnetic excitation device generates eddy currents and magnetic fields that focus on the crack, enhancing the Lorentz force and concentrating the AE source at the crack tip. The Group Sparse Wavelet Transform with a Tunable Q-factor (GS-TQWT) algorithm is applied to reconstruct the EMAE signal, separating the signal wave packets and improving the signal-to-noise ratio (SNR). Mode identification is performed by combining the pipeline’s guided wave conversion dispersion curves with Discrete Wavelet Transform (DWT) plots. The results show that EMAE signals from circumferential cracks contain multiple modes, with the first three wave packets containing the F(1,1), F(1,2), F(1,3), and L(0,1) modes. Additionally, as the crack width increases, the arrival time of the first three wave packets is delayed, the end time is advanced, and the overall duration is shortened. This method offers a promising approach for EMAE monitoring and multi-mode analysis of pipeline welds.

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