Author:
Tang Jian,Yu Wenxiu,Zhao Guoxin,Jiao Xiangdong,Ding Xuepeng, , ,
Abstract
Processing ultrasonic echo signals to obtain high-precision residual thickness information of the pipeline wall is the key to nondestructive testing of corrosion of a long-distance pipeline. The traditional power spectrum estimation method assumes that an analyzed echo signal is Gaussian, and the useful information is insufficiently extracted, which leads to errors in the processing results. In this paper, to solve this problem, the bispectrum, which requires the least amount of computation in higher-order spectral estimation, is proposed to process an echo signal with a non-minimum phase and non-Gaussian characteristics. The bispectrum is projected onto a one-dimensional frequency space using the dimensionality reduction method, and one-dimensional diagonal slices of the bispectrum are extracted to analyze the characteristics of the echo signal, which significantly improves the intuitiveness of data processing. The experimental results show that the bispectrum dimensionality reduction method has high accuracy in processing ultrasonic echo signals, and the relative error of the residua wall thickness is below 2%. A C-scan image displaying the shape, size, depth, and other characteristics of pipeline corrosion obtained by the proposed method is much better than that using the traditional power spectrum estimation method. Therefore, the proposed method is suitable for nondestructive testing of corrosion of long-distance pipelines.
Funder
Beijing Municipal Commission of Education
Publisher
Fuji Technology Press Ltd.
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction
Reference21 articles.
1. N. M. H. Basri, K. S. M. Sahari, and A. Anuar, “Development of a Robotic Boiler Header Inspection Device with Redundant Localization System,” J. Adv. Comput. Intell. Intell. Inform., Vol.18, pp. 451-458, 2014.
2. A. Lanjile, M. Younis, S.-J. Kim, and S. Lee, “Exploiting Multi-Modal Sensing for Increased Detection Fidelity of Pipeline Leakage,” ASME 2019 Int. Design Engineering Technical Conf. and Computers and Information in Engineering Conf., Vol.2B, doi: 10.1115/DETC2019-97553, 2019.
3. M. S. M. Naqiuddin, M. S. Leong, L. M. Hee, and M. A. M. Azrieasrie, “Ultrasonic signal processing techniques for Pipeline: A review,” Engineering Application of Artificial Intelligence Conf. 2018, Vol.255, Article No.06006, 2019.
4. J. Tang, X.-D. Jiao, and B. Dai, “Application of improved secondary 1.5-D spectrum estimation in pipeline inner inspection,” J. of Shanghai Jiaotong University, Vol.49, No.3, pp. 406-410, 2015 (in Chinese).
5. R. Demirli and J. Saniie, “Model-based estimation of ultrasonic echoes. Part I: Analysis and algorithms,” IEEE Trans. on Ultrasonics, Ferroelectrics, and Frequency Control, Vol.48, No.3, pp. 787-802, 2001.