LAPSE:2023.9594v1
Published Article

LAPSE:2023.9594v1
A Fast Signal-Processing Method for Electromagnetic Ultrasonic Thickness Measurement of Pipelines Based on UKF and SMO
February 27, 2023
Abstract
Electromagnetic ultrasonic testing technology has advantages in measuring the thickness of pipelines in service. However, the ultrasonic signal is susceptible to corrosions on the internal and external surfaces of the pipeline. Since the electromagnetic ultrasonic signal is nonlinear, and a dynamic model is difficult to establish accurately, in this paper, a new unscented Kalman filter (UKF) method based on a sliding mode observer (SMO) is proposed. The experiments, conducted on five different testing samples, validate that the proposed method can effectively process the signals drowned in noise and accurately measure the wall thickness. Compared with FFT and UKF, the signal-to-noise ratio of the signals processed by SMO−UKF shows a maximum increase of 155% and 171%. Meanwhile, a random assignment method is proposed for the self-regulation of hyper parameters in the process of Kalman filtering. Experimental results show that the automatic adjustment of hyper parameters can be accomplished in finite cycle numbers and greatly shortens the overall filtering time.
Electromagnetic ultrasonic testing technology has advantages in measuring the thickness of pipelines in service. However, the ultrasonic signal is susceptible to corrosions on the internal and external surfaces of the pipeline. Since the electromagnetic ultrasonic signal is nonlinear, and a dynamic model is difficult to establish accurately, in this paper, a new unscented Kalman filter (UKF) method based on a sliding mode observer (SMO) is proposed. The experiments, conducted on five different testing samples, validate that the proposed method can effectively process the signals drowned in noise and accurately measure the wall thickness. Compared with FFT and UKF, the signal-to-noise ratio of the signals processed by SMO−UKF shows a maximum increase of 155% and 171%. Meanwhile, a random assignment method is proposed for the self-regulation of hyper parameters in the process of Kalman filtering. Experimental results show that the automatic adjustment of hyper parameters can be accomplished in finite cycle numbers and greatly shortens the overall filtering time.
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Keywords
electromagnetic acoustic transducer, pipeline, sliding mode observer, unscented Kalman filter
Subject
Suggested Citation
Zhu H, Tu J, Cai C, Deng Z, Wu Q, Song X. A Fast Signal-Processing Method for Electromagnetic Ultrasonic Thickness Measurement of Pipelines Based on UKF and SMO. (2023). LAPSE:2023.9594v1
Author Affiliations
Zhu H: School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China; Hubei Key Laboratory of Modern Manufacturing Quality Engineering, Wuhan 430068, China
Tu J: School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China; Hubei Key Laboratory of Modern Manufacturing Quality Engineering, Wuhan 430068, China [ORCID]
Cai C: Wuhan Second Ship Design and Research Institute, Wuhan 430064, China
Deng Z: School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China; Hubei Key Laboratory of Modern Manufacturing Quality Engineering, Wuhan 430068, China [ORCID]
Wu Q: School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China; Hubei Key Laboratory of Modern Manufacturing Quality Engineering, Wuhan 430068, China
Song X: School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China; Hubei Key Laboratory of Modern Manufacturing Quality Engineering, Wuhan 430068, China [ORCID]
Tu J: School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China; Hubei Key Laboratory of Modern Manufacturing Quality Engineering, Wuhan 430068, China [ORCID]
Cai C: Wuhan Second Ship Design and Research Institute, Wuhan 430064, China
Deng Z: School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China; Hubei Key Laboratory of Modern Manufacturing Quality Engineering, Wuhan 430068, China [ORCID]
Wu Q: School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China; Hubei Key Laboratory of Modern Manufacturing Quality Engineering, Wuhan 430068, China
Song X: School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China; Hubei Key Laboratory of Modern Manufacturing Quality Engineering, Wuhan 430068, China [ORCID]
Journal Name
Energies
Volume
15
Issue
18
First Page
6554
Year
2022
Publication Date
2022-09-08
ISSN
1996-1073
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PII: en15186554, Publication Type: Journal Article
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Feb 27, 2023
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