Journal of Intelligent Manufacturing and Special Equipment最新文献

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Comparative study on equivalent models calculating magnetic force between permanent magnets 永磁体间磁力等效模型的比较研究

Journal of Intelligent Manufacturing and Special Equipment Pub Date : 2020-11-18 DOI: 10.1108/jimse-09-2020-0009

Yuyang Zhang, Y. Leng, Hao Zhang, Xukun Su, Shuailing Sun, Xiaoyu Chen, Junjie Xu

{"title":"Comparative study on equivalent models calculating magnetic force between permanent magnets","authors":"Yuyang Zhang, Y. Leng, Hao Zhang, Xukun Su, Shuailing Sun, Xiaoyu Chen, Junjie Xu","doi":"10.1108/jimse-09-2020-0009","DOIUrl":"https://doi.org/10.1108/jimse-09-2020-0009","url":null,"abstract":"PurposeAn appropriate equivalent model is the key to the effective analysis of the system and structure in which permanent magnet takes part. At present, there are several equivalent models for calculating the interacting magnetic force between permanent magnets including magnetizing current, magnetic charge and magnetic dipole–dipole model. How to choose the most appropriate and efficient model still needs further discussion.Design/methodology/approachThis paper chooses cuboid, cylindrical and spherical permanent magnets as calculating objects to investigate the detailed calculation procedures based on three equivalent models, magnetizing current, magnetic charge and magnetic dipole–dipole model. By comparing the accuracies of those models with experiment measurement, the applicability of three equivalent models for describing permanent magnets with different shapes is analyzed.FindingsSimilar calculation accuracies of the equivalent magnetizing current model and magnetic charge model are verified by comparison between simulation and experiment results. However, the magnetic dipole–dipole model can only accurately calculate for spherical magnet instead of other nonellipsoid magnets, because dipole model cannot describe the specific characteristics of magnet's shape, only sphere can be treated as the topological form of a dipole, namely a filled dot.Originality/valueThis work provides reference basis for choosing a proper model to calculate magnetic force in the design of electromechanical structures with permanent magnets. The applicability of different equivalent models describing permanent magnets with different shapes is discussed and the equivalence between the models is also analyzed.","PeriodicalId":34604,"journal":{"name":"Journal of Intelligent Manufacturing and Special Equipment","volume":"50 s249","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/jimse-09-2020-0009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72386629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

The multi-objective optimization of tunneling boring machine control based on geological conditions identification 基于地质条件识别的隧道掘进机控制多目标优化

Journal of Intelligent Manufacturing and Special Equipment Pub Date : 2020-11-05 DOI: 10.1108/jimse-07-2020-0005

Hongyuan Wang, Jingcheng Wang

{"title":"The multi-objective optimization of tunneling boring machine control based on geological conditions identification","authors":"Hongyuan Wang, Jingcheng Wang","doi":"10.1108/jimse-07-2020-0005","DOIUrl":"https://doi.org/10.1108/jimse-07-2020-0005","url":null,"abstract":"PurposeThe purpose of this paper aims to design an optimization control for tunnel boring machine (TBM) based on geological identification. For unknown geological condition, the authors need to identify them before further optimization. For fully considering multiple crucial performance of TBM, the authors establish an optimization problem for TBM so that it can be adapted to varying geology. That is, TBM can operate optimally under corresponding geology, which is called geology-adaptability.Design/methodology/approachThis paper adopted k-nearest neighbor (KNN) algorithm with modification to identify geological conditions. The modification includes adjustment of weights in voting procedure and similarity distance measurement, which at suitable for engineering and enhance accuracy of prediction. The authors also design several key performances of TBM during operation, and built a multi-objective function. Further, the multi-objective function has been transformed into a single objective function by weighted-combination. The reformulated optimization was solved by genetic algorithm in the end.FindingsThis paper provides a support for decision-making in TBM control. Through proposed optimization control, the advance speed of TBM has been enhanced dramatically in each geological condition, compared with the results before optimizing. Meanwhile, other performances are acceptable and the method is verified by in situ data.Originality/valueThis paper fulfills an optimization control of TBM considering several key performances during excavating. The optimization is conducted under different geological conditions so that TBM has geological-adaptability.","PeriodicalId":34604,"journal":{"name":"Journal of Intelligent Manufacturing and Special Equipment","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90321475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

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