Ping Fu , Shurui Zhang , Yujue Wang , Xiucheng Liu , Hexuan Li , Peng Li , Cunfu He
{"title":"磁巴克豪森噪声时频谱的理论模型","authors":"Ping Fu , Shurui Zhang , Yujue Wang , Xiucheng Liu , Hexuan Li , Peng Li , Cunfu He","doi":"10.1016/j.ndteint.2025.103553","DOIUrl":null,"url":null,"abstract":"<div><div>The magnetic Barkhausen noise (MBN) signal originates from the discontinuous motion of magnetic domains and domain walls. MBN is highly sensitive to microstructural characteristics in ferromagnetic materials and its time-frequency domain contains a wealth of information about material properties. However, there are few models that explore the time-frequency spectrum model of MBN. This study develops a time-frequency spectrum model of MBN grounded in its generation mechanism. By employing basis functions to characterize the jump characteristics of MBN, we construct a quantitative model utilizing the Pearson distribution function and bimodal Gaussian distribution function. Then, similarity index is used to evaluate the accuracy of the model. MBN signals from various ferromagnetic materials are collected and compared against the model's predictions. The results demonstrate that the similarity index between the model outcomes and experimental data exceed 85 %. This suggests that the proposed MBN time-frequency spectrum model is applicable to a range of ferromagnetic materials.</div></div>","PeriodicalId":18868,"journal":{"name":"Ndt & E International","volume":"158 ","pages":"Article 103553"},"PeriodicalIF":4.5000,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Theoretical model for the time-frequency spectrum of magnetic Barkhausen noise\",\"authors\":\"Ping Fu , Shurui Zhang , Yujue Wang , Xiucheng Liu , Hexuan Li , Peng Li , Cunfu He\",\"doi\":\"10.1016/j.ndteint.2025.103553\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The magnetic Barkhausen noise (MBN) signal originates from the discontinuous motion of magnetic domains and domain walls. MBN is highly sensitive to microstructural characteristics in ferromagnetic materials and its time-frequency domain contains a wealth of information about material properties. However, there are few models that explore the time-frequency spectrum model of MBN. This study develops a time-frequency spectrum model of MBN grounded in its generation mechanism. By employing basis functions to characterize the jump characteristics of MBN, we construct a quantitative model utilizing the Pearson distribution function and bimodal Gaussian distribution function. Then, similarity index is used to evaluate the accuracy of the model. MBN signals from various ferromagnetic materials are collected and compared against the model's predictions. The results demonstrate that the similarity index between the model outcomes and experimental data exceed 85 %. This suggests that the proposed MBN time-frequency spectrum model is applicable to a range of ferromagnetic materials.</div></div>\",\"PeriodicalId\":18868,\"journal\":{\"name\":\"Ndt & E International\",\"volume\":\"158 \",\"pages\":\"Article 103553\"},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2025-09-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ndt & E International\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0963869525002348\",\"RegionNum\":2,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATERIALS SCIENCE, CHARACTERIZATION & TESTING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ndt & E International","FirstCategoryId":"88","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0963869525002348","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, CHARACTERIZATION & TESTING","Score":null,"Total":0}
Theoretical model for the time-frequency spectrum of magnetic Barkhausen noise
The magnetic Barkhausen noise (MBN) signal originates from the discontinuous motion of magnetic domains and domain walls. MBN is highly sensitive to microstructural characteristics in ferromagnetic materials and its time-frequency domain contains a wealth of information about material properties. However, there are few models that explore the time-frequency spectrum model of MBN. This study develops a time-frequency spectrum model of MBN grounded in its generation mechanism. By employing basis functions to characterize the jump characteristics of MBN, we construct a quantitative model utilizing the Pearson distribution function and bimodal Gaussian distribution function. Then, similarity index is used to evaluate the accuracy of the model. MBN signals from various ferromagnetic materials are collected and compared against the model's predictions. The results demonstrate that the similarity index between the model outcomes and experimental data exceed 85 %. This suggests that the proposed MBN time-frequency spectrum model is applicable to a range of ferromagnetic materials.
期刊介绍:
NDT&E international publishes peer-reviewed results of original research and development in all categories of the fields of nondestructive testing and evaluation including ultrasonics, electromagnetics, radiography, optical and thermal methods. In addition to traditional NDE topics, the emerging technology area of inspection of civil structures and materials is also emphasized. The journal publishes original papers on research and development of new inspection techniques and methods, as well as on novel and innovative applications of established methods. Papers on NDE sensors and their applications both for inspection and process control, as well as papers describing novel NDE systems for structural health monitoring and their performance in industrial settings are also considered. Other regular features include international news, new equipment and a calendar of forthcoming worldwide meetings. This journal is listed in Current Contents.