DOAJ Open Access 2024

An accurate localization method for underground pipeline leakage points in chemical parks based on ultrasonic creep wave flaw detection and data integration

Wang Kangxi Li Peiwang Sun Guanghui Zhao Zhuyi Luo Wei

Abstrak

To ensure the reliable management of the safe operation of an underground pipeline in a chemical industrial park and accurately determine the location of the pipeline leakage point, a precise location method for the leakage point of an underground pipeline in a chemical industrial park based on ultrasonic creeping wave flaw detection and data integration is proposed. In this method, the ultrasonic creeping wave flaw detector is used to detect the underground pipelines in the chemical industry park and obtain the status signals of the underground pipelines in the chemical industry park. The improved K-means algorithm is used to fuse the signals collected by clustering to obtain abnormal signals in the signals; The wavelet transform is used to process the ultrasonic abnormal signals obtained by clustering, extract the local time energy density characteristics of the frequency band, and superimpose the image. By introducing image enhancement factors, the leakage area can be centrally located, the coordinates of the pipeline leakage points can be determined, and the leakage degree can be determined by calculating the sum of the damage probability of each leakage point. The test results show that the clustering effect of this method is good, and the separability measurement indexes are all above 0.925, which can complete the location of single point and multi-point leakage points, and the maximum location error is 11.55 mm. The reliability of the location of the leakage point is high.

Penulis (5)

W

Wang Kangxi

L

Li Peiwang

S

Sun Guanghui

Z

Zhao Zhuyi

L

Luo Wei

Format Sitasi

Kangxi, W., Peiwang, L., Guanghui, S., Zhuyi, Z., Wei, L. (2024). An accurate localization method for underground pipeline leakage points in chemical parks based on ultrasonic creep wave flaw detection and data integration. https://doi.org/10.1051/aacus/2024072

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Informasi Jurnal
Tahun Terbit
2024
Sumber Database
DOAJ
DOI
10.1051/aacus/2024072
Akses
Open Access ✓