Pipeline Flange Loose Bolt Localization Technology Based on Waveform Correlation Coefficient

DOI: https://doi.org/10.62517/jes.202602202

Author(s)

Cong Yu1,2, Peng Cheng1,2,*, Chenxi Shao1,2

Affiliation(s)

1China Academy of Machinery Science and Technology. Beijing, China 2Yanqi Lake Institute of Basic Manufacturing Technology Research (Beijing) Co., Ltd., Beijing, China *Corresponding Author

Abstract

To address the challenge of locating bolt looseness in pipeline flanges equipped with sealing gaskets, this paper proposes a detection method based on stress wave principles combined with deep learning. Vibration signals were collected under various bolt loosening conditions at different excitation points on the flange. The overall waveform correlation coefficient and segmental waveform correlation coefficients of the signals were calculated to construct a feature dataset, and a Support Vector Machine (SVM) model was employed to identify the positions of loosened bolts. Experimental results demonstrate that when excitation points are selected near the sensor or far from the sensor, the waveform correlation coefficients across different time domains effectively reflect variations in the location of loosened bolts, achieving high recognition accuracy. This method provides a feasible technical approach for accurately locating bolt looseness in pipeline flanges.

Keywords

Flange Bolt Looseness; Stress Wave; Waveform Correlation Coefficient; Support Vector Machine; Structural Health Monitoring

References

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