基于表面形貌模拟的数控铣削表面粗糙度预测和粗糙度可靠性评估

Ziling Zhang, Xiaodong Lv, Baobao Qi, Yin Qi, Milu Zhang, Zhiqiang Tao
{"title":"基于表面形貌模拟的数控铣削表面粗糙度预测和粗糙度可靠性评估","authors":"Ziling Zhang, Xiaodong Lv, Baobao Qi, Yin Qi, Milu Zhang, Zhiqiang Tao","doi":"10.17531/ein/183558","DOIUrl":null,"url":null,"abstract":"Surface roughness is influenced by various factors with uncertainty characteristics, and roughness reliability can be used for the assessment of the surface quality of CNC milling. The paper develops a method for the assessment of surface quality by considering the coupling effect and uncertainty characteristic of various factors. According to the milling kinematics theory, the milling surface topography simulation was conducted by discretizing the cutting edge, machining time, and workpiece. Considering the coupling effect of various factors, a roughness prediction model is established by the SSA-LSSVM, and its prediction accuracy reaches more than 95%. Then, the roughness reliability model was developed by applying the response surface methodology to achieve the assessment of surface quality. The proposed method is verified by the milling experiments. The maximum values of the relative errors between the simulation and experimental results of the surface roughness and roughness reliability are 9% and 1.5% respectively, indicating the correctness of the method proposed in the paper.","PeriodicalId":335030,"journal":{"name":"Eksploatacja i Niezawodność – Maintenance and Reliability","volume":"43 5","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Surface roughness prediction and roughness reliability evaluation of CNC milling based on surface topography simulation\",\"authors\":\"Ziling Zhang, Xiaodong Lv, Baobao Qi, Yin Qi, Milu Zhang, Zhiqiang Tao\",\"doi\":\"10.17531/ein/183558\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Surface roughness is influenced by various factors with uncertainty characteristics, and roughness reliability can be used for the assessment of the surface quality of CNC milling. The paper develops a method for the assessment of surface quality by considering the coupling effect and uncertainty characteristic of various factors. According to the milling kinematics theory, the milling surface topography simulation was conducted by discretizing the cutting edge, machining time, and workpiece. Considering the coupling effect of various factors, a roughness prediction model is established by the SSA-LSSVM, and its prediction accuracy reaches more than 95%. Then, the roughness reliability model was developed by applying the response surface methodology to achieve the assessment of surface quality. The proposed method is verified by the milling experiments. The maximum values of the relative errors between the simulation and experimental results of the surface roughness and roughness reliability are 9% and 1.5% respectively, indicating the correctness of the method proposed in the paper.\",\"PeriodicalId\":335030,\"journal\":{\"name\":\"Eksploatacja i Niezawodność – Maintenance and Reliability\",\"volume\":\"43 5\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Eksploatacja i Niezawodność – Maintenance and Reliability\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17531/ein/183558\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Eksploatacja i Niezawodność – Maintenance and Reliability","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17531/ein/183558","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

表面粗糙度受多种因素影响,具有不确定性特征,粗糙度可靠性可用于评估数控铣削的表面质量。本文通过考虑各种因素的耦合效应和不确定性特征,建立了一种表面质量评估方法。根据铣削运动学理论,将切削刃、加工时间和工件离散化,进行铣削表面形貌仿真。考虑到各种因素的耦合效应,利用 SSA-LSSVM 建立了粗糙度预测模型,其预测精度达到 95% 以上。然后,应用响应面方法建立了粗糙度可靠性模型,实现了对表面质量的评估。铣削实验验证了所提出的方法。表面粗糙度和粗糙度可靠度的模拟结果与实验结果的最大相对误差分别为 9% 和 1.5%,表明本文提出的方法是正确的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Surface roughness prediction and roughness reliability evaluation of CNC milling based on surface topography simulation
Surface roughness is influenced by various factors with uncertainty characteristics, and roughness reliability can be used for the assessment of the surface quality of CNC milling. The paper develops a method for the assessment of surface quality by considering the coupling effect and uncertainty characteristic of various factors. According to the milling kinematics theory, the milling surface topography simulation was conducted by discretizing the cutting edge, machining time, and workpiece. Considering the coupling effect of various factors, a roughness prediction model is established by the SSA-LSSVM, and its prediction accuracy reaches more than 95%. Then, the roughness reliability model was developed by applying the response surface methodology to achieve the assessment of surface quality. The proposed method is verified by the milling experiments. The maximum values of the relative errors between the simulation and experimental results of the surface roughness and roughness reliability are 9% and 1.5% respectively, indicating the correctness of the method proposed in the paper.
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
×
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:604180095
Book学术官方微信