已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

In-Process Machining Process Monitoring Method Based on Impedance Model of Dielectric Coating Layer at Tool-Chip Interface

机械加工 材料科学 电阻抗 涂层 电介质 图层(电子) 阻抗匹配 电子工程 光电子学 复合材料 电气工程 工程类 冶金
作者
Heebum Chun,Jungsub Kim,Jungsoo Nam,Songhyun Ju,ChaBum Lee
标识
DOI:10.1115/msec2022-85794
摘要

Abstract In this study, we investigated a novel approach that enables the in-process machining process monitoring at the tool-chip interface (TCI) by utilizing the impedance characteristics of the dielectric coating layer of the cutting tool. This study first analyzes the Nyquist diagram that characterizes the impedance response of a few micrometer-thick dielectric layers coated on the surface of the cutting tool by using an impedance analyzer under various temperature conditions for establishing the relationship between the relative permittivity of the dielectric layer and temperature. Consequently, the impedance of the dielectric layer was subject to change according to given temperature conditions. Thus, under its temperature-dependent impedance characteristics, the machining processes could be in-situ tracked and analyzed by directly probing the localized TCI, the so-called cutting hot spot, during the machining. The current source was implemented with the machining system and the variations of impedance at TCI were monitored during the facing process. As a result, impedance responses were remarkably changed under various machining conditions. The impedance was further characterized under the varying depth of contact and the impedance was decreased as the depth of contact increased. Therefore, the preliminary study demonstrated that an electrical impedance model of the dielectric coating layer may be applied for an in-process machining process monitoring method to analyze and assess the phenomenon of the machining process at the local TCI region. This study is expected to potentially provide utilization in advanced manufacturing to improve final part quality and productivity.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
羽魄发布了新的文献求助10
1秒前
HLFC完成签到 ,获得积分10
2秒前
科研通AI6.3应助zhu采纳,获得10
2秒前
小马甲应助谢文轩采纳,获得10
2秒前
蝎子莱莱发布了新的文献求助10
4秒前
乔达摩完成签到 ,获得积分0
4秒前
7秒前
8秒前
9秒前
movoi完成签到 ,获得积分10
10秒前
WHL完成签到,获得积分10
12秒前
蝎子莱莱完成签到,获得积分10
13秒前
13秒前
蓝幻蓝发布了新的文献求助10
14秒前
14秒前
甜美的水杯完成签到 ,获得积分10
15秒前
乔达摩悉达多完成签到 ,获得积分0
16秒前
gyh关注了科研通微信公众号
16秒前
tyler23完成签到 ,获得积分10
16秒前
fansaiwang完成签到,获得积分10
17秒前
NexusExplorer应助失眠的老鼠采纳,获得30
21秒前
liuzhanyu发布了新的文献求助10
21秒前
万能图书馆应助我要进步采纳,获得10
22秒前
牧长一完成签到 ,获得积分0
23秒前
Dk完成签到,获得积分10
25秒前
26秒前
ZM完成签到,获得积分10
26秒前
Sober完成签到,获得积分10
27秒前
Orange应助zhy采纳,获得10
29秒前
29秒前
Dk发布了新的文献求助20
30秒前
夏Eason完成签到,获得积分10
32秒前
LJ发布了新的文献求助10
32秒前
zhangh65发布了新的文献求助30
32秒前
33秒前
33秒前
34秒前
Oscillator发布了新的文献求助10
34秒前
无花果应助神经蛙采纳,获得10
35秒前
充电宝应助长情诺言采纳,获得10
36秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场现状调查及投资机会研判报告 1000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场规模及竞争格局分析报告 1000
48V Low-voltage Power Distribution Network (PDN) Architecture Industry Report, 2024 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Introducing the Learning Sciences 600
Resiliency Scale for Adolescents--Chinese Version 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7322605
求助须知:如何正确求助?哪些是违规求助? 8938134
关于积分的说明 18950014
捐赠科研通 6980276
什么是DOI,文献DOI怎么找? 3215048
关于科研通互助平台的介绍 2382537
邀请新用户注册赠送积分活动 2194279