基于灰色模糊方法的电火花加工工艺优化

D. Rodić, Marin Gostimirović, M. Sekulić, Branislav Batinić, Nikola M. Laković
{"title":"基于灰色模糊方法的电火花加工工艺优化","authors":"D. Rodić, Marin Gostimirović, M. Sekulić, Branislav Batinić, Nikola M. Laković","doi":"10.1109/ZINC50678.2020.9161443","DOIUrl":null,"url":null,"abstract":"The research investigated the optimization of various performance features on the basis of a gray-fuzzy analysis. The goal was to generate an intelligent system for the optimization of electrical discharge machining based on fuzzy logic and gray analysis. Taguchi's L9 experimental design was used as the research methodology. Two input parameters were selected, namely, discharge current and pulse duration. On the other hand, the material removal rate and surface roughness were taken as output machining performances. Depending on the response of the output performances, the input parameters are selected by applying the gray relation grade and signal-to-noise ratio strategy as performance index. The system is set up according to the following criteria: maximum material removal rate and minimum surface roughness. Based on these criteria, the optimal parameters were obtained, i.e. a discharge current of 5 A and a pulse duration of 5 μ. This combination results in a high gray fuzzy degree of 0.521, which is close to the reference value. Considering the results of the validation experiments, it is concluded that a gray-fuzzy approach can be successfully applied to obtain the optimal combination of influential control parameters.","PeriodicalId":6731,"journal":{"name":"2020 Zooming Innovation in Consumer Technologies Conference (ZINC)","volume":"42 1","pages":"307-312"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization of EDM process using grey-fuzzy approach\",\"authors\":\"D. Rodić, Marin Gostimirović, M. Sekulić, Branislav Batinić, Nikola M. Laković\",\"doi\":\"10.1109/ZINC50678.2020.9161443\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The research investigated the optimization of various performance features on the basis of a gray-fuzzy analysis. The goal was to generate an intelligent system for the optimization of electrical discharge machining based on fuzzy logic and gray analysis. Taguchi's L9 experimental design was used as the research methodology. Two input parameters were selected, namely, discharge current and pulse duration. On the other hand, the material removal rate and surface roughness were taken as output machining performances. Depending on the response of the output performances, the input parameters are selected by applying the gray relation grade and signal-to-noise ratio strategy as performance index. The system is set up according to the following criteria: maximum material removal rate and minimum surface roughness. Based on these criteria, the optimal parameters were obtained, i.e. a discharge current of 5 A and a pulse duration of 5 μ. This combination results in a high gray fuzzy degree of 0.521, which is close to the reference value. Considering the results of the validation experiments, it is concluded that a gray-fuzzy approach can be successfully applied to obtain the optimal combination of influential control parameters.\",\"PeriodicalId\":6731,\"journal\":{\"name\":\"2020 Zooming Innovation in Consumer Technologies Conference (ZINC)\",\"volume\":\"42 1\",\"pages\":\"307-312\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 Zooming Innovation in Consumer Technologies Conference (ZINC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ZINC50678.2020.9161443\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Zooming Innovation in Consumer Technologies Conference (ZINC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ZINC50678.2020.9161443","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在灰色模糊分析的基础上,研究了各种性能特征的优化问题。目的是建立一个基于模糊逻辑和灰色分析的智能电火花加工优化系统。采用田口L9实验设计作为研究方法。选择两个输入参数,即放电电流和脉冲持续时间。另一方面,以材料去除率和表面粗糙度作为输出加工性能。根据输出性能的响应,采用灰度关联度和信噪比策略作为性能指标来选择输入参数。该系统是根据以下标准设置的:最大材料去除率和最小表面粗糙度。在此基础上,得到了放电电流为5 a、脉冲持续时间为5 μ的最佳参数。这种组合得到的灰色模糊度较高,为0.521,接近参考值。结合验证实验的结果,得出灰色-模糊方法可以成功地获得影响控制参数的最优组合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Optimization of EDM process using grey-fuzzy approach
The research investigated the optimization of various performance features on the basis of a gray-fuzzy analysis. The goal was to generate an intelligent system for the optimization of electrical discharge machining based on fuzzy logic and gray analysis. Taguchi's L9 experimental design was used as the research methodology. Two input parameters were selected, namely, discharge current and pulse duration. On the other hand, the material removal rate and surface roughness were taken as output machining performances. Depending on the response of the output performances, the input parameters are selected by applying the gray relation grade and signal-to-noise ratio strategy as performance index. The system is set up according to the following criteria: maximum material removal rate and minimum surface roughness. Based on these criteria, the optimal parameters were obtained, i.e. a discharge current of 5 A and a pulse duration of 5 μ. This combination results in a high gray fuzzy degree of 0.521, which is close to the reference value. Considering the results of the validation experiments, it is concluded that a gray-fuzzy approach can be successfully applied to obtain the optimal combination of influential control parameters.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Predicting Plant Water and Soil Nutrient Requirements RFM and Classification Predictive Modelling to Improve Response Prediction Rate Utility analysis and rating of energy storages in trolleybus power supply system Face recognition based on selection approach via Canonical Correlation Analysis feature fusion The Concept of Consumer IP Address Preservation Behind the Load Balancer
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1