Magnetic-Acoustic Feature Extraction and Damage Fusion Evaluation of 45 Steel Specimens during Fatigue Process for Remanufacturing

To clarify the changes of the magnetic-acoustic features of 45 steel specimens during fatigue damage, an experimental platform was built to carry out magnetic memory and acoustic emission detection. The magnetic memory and acoustic emission signals of specimens in different damage states were collec...

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Main Authors: Tao Liu, Chaoyang Shen, Jingfa Lei, Zhiqiang Yin, Hong Sun, Jingxiong Wu
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Advances in Materials Science and Engineering
Online Access:http://dx.doi.org/10.1155/2022/1966794
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author Tao Liu
Chaoyang Shen
Jingfa Lei
Zhiqiang Yin
Hong Sun
Jingxiong Wu
author_facet Tao Liu
Chaoyang Shen
Jingfa Lei
Zhiqiang Yin
Hong Sun
Jingxiong Wu
author_sort Tao Liu
collection DOAJ
description To clarify the changes of the magnetic-acoustic features of 45 steel specimens during fatigue damage, an experimental platform was built to carry out magnetic memory and acoustic emission detection. The magnetic memory and acoustic emission signals of specimens in different damage states were collected, and the multi-scale entropy characteristics of magnetic memory signals, as well as the wavelet packet energy spectrum and singularity index characteristics of acoustic emission signals, were further extracted. A magnetic-acoustic feature fusion and damage assessment model was constructed by using Naive Bayes method. Results show that the average value of multi-scale entropy of normal magnetic field intensity Hp (y) increases gradually with the increase of fatigue cycles, and the average value of multi-scale entropy of magnetic field intensity gradient K gradually decreases. The cumulative ringing count and energy spectrum (proportion of frequency band 1) of acoustic emission signals decrease with the increase of fatigue cycles, while the amplitude singularity index gradually increases. The established model has high evaluation accuracy, and the conclusions of this paper can provide basic methods and data support for fatigue damage evaluation of remanufactured components.
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spelling doaj-art-d50604a3899a4b71befcab73a5f77cd22025-08-20T02:20:00ZengWileyAdvances in Materials Science and Engineering1687-84422022-01-01202210.1155/2022/1966794Magnetic-Acoustic Feature Extraction and Damage Fusion Evaluation of 45 Steel Specimens during Fatigue Process for RemanufacturingTao Liu0Chaoyang Shen1Jingfa Lei2Zhiqiang Yin3Hong Sun4Jingxiong Wu5School of Mechanical and Electrical EngineeringSchool of Mechanical and Electrical EngineeringSchool of Mechanical and Electrical EngineeringSchool of Mechanical and Electrical EngineeringSchool of Mechanical and Electrical EngineeringSchool of Mechanical and Electrical EngineeringTo clarify the changes of the magnetic-acoustic features of 45 steel specimens during fatigue damage, an experimental platform was built to carry out magnetic memory and acoustic emission detection. The magnetic memory and acoustic emission signals of specimens in different damage states were collected, and the multi-scale entropy characteristics of magnetic memory signals, as well as the wavelet packet energy spectrum and singularity index characteristics of acoustic emission signals, were further extracted. A magnetic-acoustic feature fusion and damage assessment model was constructed by using Naive Bayes method. Results show that the average value of multi-scale entropy of normal magnetic field intensity Hp (y) increases gradually with the increase of fatigue cycles, and the average value of multi-scale entropy of magnetic field intensity gradient K gradually decreases. The cumulative ringing count and energy spectrum (proportion of frequency band 1) of acoustic emission signals decrease with the increase of fatigue cycles, while the amplitude singularity index gradually increases. The established model has high evaluation accuracy, and the conclusions of this paper can provide basic methods and data support for fatigue damage evaluation of remanufactured components.http://dx.doi.org/10.1155/2022/1966794
spellingShingle Tao Liu
Chaoyang Shen
Jingfa Lei
Zhiqiang Yin
Hong Sun
Jingxiong Wu
Magnetic-Acoustic Feature Extraction and Damage Fusion Evaluation of 45 Steel Specimens during Fatigue Process for Remanufacturing
Advances in Materials Science and Engineering
title Magnetic-Acoustic Feature Extraction and Damage Fusion Evaluation of 45 Steel Specimens during Fatigue Process for Remanufacturing
title_full Magnetic-Acoustic Feature Extraction and Damage Fusion Evaluation of 45 Steel Specimens during Fatigue Process for Remanufacturing
title_fullStr Magnetic-Acoustic Feature Extraction and Damage Fusion Evaluation of 45 Steel Specimens during Fatigue Process for Remanufacturing
title_full_unstemmed Magnetic-Acoustic Feature Extraction and Damage Fusion Evaluation of 45 Steel Specimens during Fatigue Process for Remanufacturing
title_short Magnetic-Acoustic Feature Extraction and Damage Fusion Evaluation of 45 Steel Specimens during Fatigue Process for Remanufacturing
title_sort magnetic acoustic feature extraction and damage fusion evaluation of 45 steel specimens during fatigue process for remanufacturing
url http://dx.doi.org/10.1155/2022/1966794
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