{"title":"基于磁记忆法的钢丝微缺陷应力相关磁荷模型","authors":"S. Su, Xiaoping Ma, Wei Wang, Yiyi Yang","doi":"10.1080/09349847.2019.1617914","DOIUrl":null,"url":null,"abstract":"ABSTRACT Magnetic memory method (MMM) is widely used for diagnosing ferromagnetic material on early stage as a nondestructive technology, but no clear description exists for the influence of stress on MMM signals at the micro-defect position on the surface of steel wire yet. Hence, based on traditional magnetic charge model, a stress-dependent magnetic charge model that combined the Jiles magneto-mechanical constitutive relation was intended to calculate the MMM signals around micro-defect on surface of steel wire. Meanwhile, the Hp(y) signals on surface of steel wire with different defects were measured during the whole tension test. By comparing the results of theoretical model and experiment, some conclusions can be drawn. First, the position of vale-peak on Hp(y) signals curves can be used to determine the micro-defect on steel wire. Secondly, the vale-peak amplitude (Sv-p) and vale-peak width (Lv-p) of Hp(y) signals curves, as two characteristic parameters of magnetic signals, not only can reflect the variations of defect depth and defect width, but also judge the load subjected by specimen. Sv-p has an approximate growth with the increase of defect depth as a whole, but decreases with the increase of loads. And the effect of load on Sv-p increases with defect depth. Lv-p has an approximate growth with the increase of defect width as a whole, but does not change with the increase of loads. Finally, the stress-dependent magnetic charge model can be better to reflect the changing laws of Hp(y) signals around defect and can be used for the numerical analysis of MMM signals on surface of steel wire.","PeriodicalId":54493,"journal":{"name":"Research in Nondestructive Evaluation","volume":"78 1","pages":"24 - 47"},"PeriodicalIF":1.0000,"publicationDate":"2020-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Stress-Dependent Magnetic Charge Model for Micro-Defects of Steel Wire Based on the Magnetic Memory Method\",\"authors\":\"S. Su, Xiaoping Ma, Wei Wang, Yiyi Yang\",\"doi\":\"10.1080/09349847.2019.1617914\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Magnetic memory method (MMM) is widely used for diagnosing ferromagnetic material on early stage as a nondestructive technology, but no clear description exists for the influence of stress on MMM signals at the micro-defect position on the surface of steel wire yet. Hence, based on traditional magnetic charge model, a stress-dependent magnetic charge model that combined the Jiles magneto-mechanical constitutive relation was intended to calculate the MMM signals around micro-defect on surface of steel wire. Meanwhile, the Hp(y) signals on surface of steel wire with different defects were measured during the whole tension test. By comparing the results of theoretical model and experiment, some conclusions can be drawn. First, the position of vale-peak on Hp(y) signals curves can be used to determine the micro-defect on steel wire. Secondly, the vale-peak amplitude (Sv-p) and vale-peak width (Lv-p) of Hp(y) signals curves, as two characteristic parameters of magnetic signals, not only can reflect the variations of defect depth and defect width, but also judge the load subjected by specimen. Sv-p has an approximate growth with the increase of defect depth as a whole, but decreases with the increase of loads. And the effect of load on Sv-p increases with defect depth. Lv-p has an approximate growth with the increase of defect width as a whole, but does not change with the increase of loads. Finally, the stress-dependent magnetic charge model can be better to reflect the changing laws of Hp(y) signals around defect and can be used for the numerical analysis of MMM signals on surface of steel wire.\",\"PeriodicalId\":54493,\"journal\":{\"name\":\"Research in Nondestructive Evaluation\",\"volume\":\"78 1\",\"pages\":\"24 - 47\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2020-01-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Research in Nondestructive Evaluation\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1080/09349847.2019.1617914\",\"RegionNum\":4,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MATERIALS SCIENCE, CHARACTERIZATION & TESTING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Research in Nondestructive Evaluation","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1080/09349847.2019.1617914","RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATERIALS SCIENCE, CHARACTERIZATION & TESTING","Score":null,"Total":0}
Stress-Dependent Magnetic Charge Model for Micro-Defects of Steel Wire Based on the Magnetic Memory Method
ABSTRACT Magnetic memory method (MMM) is widely used for diagnosing ferromagnetic material on early stage as a nondestructive technology, but no clear description exists for the influence of stress on MMM signals at the micro-defect position on the surface of steel wire yet. Hence, based on traditional magnetic charge model, a stress-dependent magnetic charge model that combined the Jiles magneto-mechanical constitutive relation was intended to calculate the MMM signals around micro-defect on surface of steel wire. Meanwhile, the Hp(y) signals on surface of steel wire with different defects were measured during the whole tension test. By comparing the results of theoretical model and experiment, some conclusions can be drawn. First, the position of vale-peak on Hp(y) signals curves can be used to determine the micro-defect on steel wire. Secondly, the vale-peak amplitude (Sv-p) and vale-peak width (Lv-p) of Hp(y) signals curves, as two characteristic parameters of magnetic signals, not only can reflect the variations of defect depth and defect width, but also judge the load subjected by specimen. Sv-p has an approximate growth with the increase of defect depth as a whole, but decreases with the increase of loads. And the effect of load on Sv-p increases with defect depth. Lv-p has an approximate growth with the increase of defect width as a whole, but does not change with the increase of loads. Finally, the stress-dependent magnetic charge model can be better to reflect the changing laws of Hp(y) signals around defect and can be used for the numerical analysis of MMM signals on surface of steel wire.
期刊介绍:
Research in Nondestructive Evaluation® is the archival research journal of the American Society for Nondestructive Testing, Inc. RNDE® contains the results of original research in all areas of nondestructive evaluation (NDE). The journal covers experimental and theoretical investigations dealing with the scientific and engineering bases of NDE, its measurement and methodology, and a wide range of applications to materials and structures that relate to the entire life cycle, from manufacture to use and retirement.
Illustrative topics include advances in the underlying science of acoustic, thermal, electrical, magnetic, optical and ionizing radiation techniques and their applications to NDE problems. These problems include the nondestructive characterization of a wide variety of material properties and their degradation in service, nonintrusive sensors for monitoring manufacturing and materials processes, new techniques and combinations of techniques for detecting and characterizing hidden discontinuities and distributed damage in materials, standardization concepts and quantitative approaches for advanced NDE techniques, and long-term continuous monitoring of structures and assemblies. Of particular interest is research which elucidates how to evaluate the effects of imperfect material condition, as quantified by nondestructive measurement, on the functional performance.