Design-LIME: An Interpretable Visualization Method for Electric Motor Design Based on Deep Learning

IF 3.4 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Kazuhisa Iwata;Hidenori Sasaki
{"title":"Design-LIME: An Interpretable Visualization Method for Electric Motor Design Based on Deep Learning","authors":"Kazuhisa Iwata;Hidenori Sasaki","doi":"10.1109/ACCESS.2025.3563351","DOIUrl":null,"url":null,"abstract":"A novel visualization method for interpreting the resultant design from topology optimization (TO) is proposed. We employ a pre-trained deep learning (DL) model to predict the degree of influence of transitions from air to magnetic materials, and build an interpretable linear model to display the visualization result. The proposed method, Design-LIME, is applied for visualizing the impact of effective regions on the torque characteristics of interior permanent magnet synchronous motors (IPMSMs). Compared to conventional visualization methods based on explainable artificial intelligence (XAI), Design-LIME presents accurate and simple visualization results. Furthermore, a novel multistep TO method is proposed. The proposed TO utilizes Design-LIME to efficiently address the electromagnetic and mechanical characteristics of IPMSMs by extracting the effective region of the IPMSM characteristics. The proposed TO method improves search performance by 18.7% when compared with the conventional single-step optimization method. The proposed method enables more efficient motor designs with improved electromagnetic and mechanical performance. The proposed method contributes to the streamlining of the design process not only for motors but also for various electrical devices.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"73697-73708"},"PeriodicalIF":3.4000,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10973077","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Access","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10973077/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

A novel visualization method for interpreting the resultant design from topology optimization (TO) is proposed. We employ a pre-trained deep learning (DL) model to predict the degree of influence of transitions from air to magnetic materials, and build an interpretable linear model to display the visualization result. The proposed method, Design-LIME, is applied for visualizing the impact of effective regions on the torque characteristics of interior permanent magnet synchronous motors (IPMSMs). Compared to conventional visualization methods based on explainable artificial intelligence (XAI), Design-LIME presents accurate and simple visualization results. Furthermore, a novel multistep TO method is proposed. The proposed TO utilizes Design-LIME to efficiently address the electromagnetic and mechanical characteristics of IPMSMs by extracting the effective region of the IPMSM characteristics. The proposed TO method improves search performance by 18.7% when compared with the conventional single-step optimization method. The proposed method enables more efficient motor designs with improved electromagnetic and mechanical performance. The proposed method contributes to the streamlining of the design process not only for motors but also for various electrical devices.
Design- lime:一种基于深度学习的电机设计可解释可视化方法
提出了一种新的可视化方法来解释拓扑优化的结果设计。我们使用预训练的深度学习(DL)模型来预测从空气到磁性材料的转变的影响程度,并建立一个可解释的线性模型来显示可视化结果。提出的Design-LIME方法用于可视化有效区域对内置永磁同步电机转矩特性的影响。与传统的基于可解释人工智能(XAI)的可视化方法相比,Design-LIME的可视化结果准确、简单。在此基础上,提出了一种新的多步TO方法。该算法利用Design-LIME方法,通过提取IPMSM特性的有效区域,有效地解决了IPMSM的电磁和机械特性问题。与传统的单步优化方法相比,该方法的搜索性能提高了18.7%。所提出的方法使更有效的电机设计与改进的电磁和机械性能。该方法不仅简化了电机的设计过程,而且简化了各种电气设备的设计过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
IEEE Access
IEEE Access COMPUTER SCIENCE, INFORMATION SYSTEMSENGIN-ENGINEERING, ELECTRICAL & ELECTRONIC
CiteScore
9.80
自引率
7.70%
发文量
6673
审稿时长
6 weeks
期刊介绍: IEEE Access® is a multidisciplinary, open access (OA), applications-oriented, all-electronic archival journal that continuously presents the results of original research or development across all of IEEE''s fields of interest. IEEE Access will publish articles that are of high interest to readers, original, technically correct, and clearly presented. Supported by author publication charges (APC), its hallmarks are a rapid peer review and publication process with open access to all readers. Unlike IEEE''s traditional Transactions or Journals, reviews are "binary", in that reviewers will either Accept or Reject an article in the form it is submitted in order to achieve rapid turnaround. Especially encouraged are submissions on: Multidisciplinary topics, or applications-oriented articles and negative results that do not fit within the scope of IEEE''s traditional journals. Practical articles discussing new experiments or measurement techniques, interesting solutions to engineering. Development of new or improved fabrication or manufacturing techniques. Reviews or survey articles of new or evolving fields oriented to assist others in understanding the new area.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信