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RSBO based LSTM network for pulsed eddy current steel wall-thinning inspection

  • Zhenyue Lin
  • , Huade Zeng
  • , Ruochen Huang*
  • , Wancheng Dang
  • , Zihan Xia
  • , Wuliang Yin
  • *Corresponding author for this work
  • Fuzhou University
  • State Grid Fujian Ningde Electric Power Supply Company
  • University of Manchester

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Corrosion-induced wall thinning in steel pressure vessels presents a critical threat to the safety and reliability of industrial operations, requiring effective inspection methods. In this paper, the random searching Bayesian optimization (RSBO) based long-and short-term memory (LSTM) network is proposed to estimate the wall thinning. To improve computational efficiency and reduce data redundancy, data augmentation is firstly conducted by selecting the sample interval with more features. Then the RSBO based LSTM model is designed to estimate the thickness. With the designed estimator, it can automatically tune the hyperparameters for the LSTM network which is friendly for the users. Experiments have been carried out and, from the experimental results, the proposed model has a better performance and can achieve the thickness estimation with the average MAPE of 5.54% and MAE of 1.98 mm.

Original languageEnglish
Title of host publicationProceedings - 2024 IEEE Smart World Congress, SWC 2024 - 2024 IEEE Ubiquitous Intelligence and Computing, Autonomous and Trusted Computing, Digital Twin, Metaverse, Privacy Computing and Data Security, Scalable Computing and Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1967-1972
Number of pages6
ISBN (Electronic)9798331520861
DOIs
StatePublished - 2024
Externally publishedYes
Event10th IEEE Smart World Congress, SWC 2024 - Nadi, Fiji
Duration: 2 Dec 20247 Dec 2024

Publication series

NameProceedings - 2024 IEEE Smart World Congress, SWC 2024 - 2024 IEEE Ubiquitous Intelligence and Computing, Autonomous and Trusted Computing, Digital Twin, Metaverse, Privacy Computing and Data Security, Scalable Computing and Communications

Conference

Conference10th IEEE Smart World Congress, SWC 2024
Country/TerritoryFiji
CityNadi
Period2/12/247/12/24

Keywords

  • Corrosion
  • LSTM
  • PEC
  • RSBO
  • thickness estimation
  • wall-thinning

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