M. Eftekhari, M. Moallem, M. A. Ghadamyari, Hosein Monajati, Davood Asefi, Abbas Kamranian Marnani
{"title":"Predicting mechanical properties of cold- rolled low carbon steel based on magnetic parameter measurement using ANFIS model","authors":"M. Eftekhari, M. Moallem, M. A. Ghadamyari, Hosein Monajati, Davood Asefi, Abbas Kamranian Marnani","doi":"10.1109/IAS.2011.6074385","DOIUrl":null,"url":null,"abstract":"In this paper, a novel method for predicting mechanical properties of cold- rolled low carbon steel based on magnetic parameter measurement using Adaptive Neuro Fuzzy Inference System (ANFIS) is presented. The Yield Stress (YS) and Ultimate Tensile Strength (UTS) are predicted using two ANFIS models on the basis of B-H curve parameter measurement. B-H curve parameter measurement is carried out using a measurement system specially developed for this project. Using this system, remanence (Br), coercive force (Hc), harmonic components of the field intensity, and flux density are extracted and used as input parameters of the ANFIS models. The individual influence of different input parameters is evaluated and compared with metallurgical test results. The ANFIS models show good performance and the results are in agreement with the experimental data. The developed models can be used as an on-line, non-destructive evaluation technique in steel mill factories.","PeriodicalId":268988,"journal":{"name":"2011 IEEE Industry Applications Society Annual Meeting","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE Industry Applications Society Annual Meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAS.2011.6074385","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this paper, a novel method for predicting mechanical properties of cold- rolled low carbon steel based on magnetic parameter measurement using Adaptive Neuro Fuzzy Inference System (ANFIS) is presented. The Yield Stress (YS) and Ultimate Tensile Strength (UTS) are predicted using two ANFIS models on the basis of B-H curve parameter measurement. B-H curve parameter measurement is carried out using a measurement system specially developed for this project. Using this system, remanence (Br), coercive force (Hc), harmonic components of the field intensity, and flux density are extracted and used as input parameters of the ANFIS models. The individual influence of different input parameters is evaluated and compared with metallurgical test results. The ANFIS models show good performance and the results are in agreement with the experimental data. The developed models can be used as an on-line, non-destructive evaluation technique in steel mill factories.