A Fast Signal-Processing Method for Electromagnetic Ultrasonic Thickness Measurement of Pipelines Based on UKF and SMO

Huichao Zhu, Jun Tu, Chen Cai, Zhiyang Deng, Qiao Wu and Xiaochun Song ()
Additional contact information
Huichao Zhu: School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China
Jun Tu: School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China
Chen Cai: Wuhan Second Ship Design and Research Institute, Wuhan 430064, China
Zhiyang Deng: School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China
Qiao Wu: School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China
Xiaochun Song: School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China

Energies, 2022, vol. 15, issue 18, 1-14

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.

Keywords: electromagnetic acoustic transducer; pipeline; unscented Kalman filter; sliding mode observer (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/18/6554/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/18/6554/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:18:p:6554-:d:909539

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().