Intelligent Sensing Unit for Estimation Roughness of Electrical Discharge Machining

Q4 Computer Science

International Journal of Automation and Smart Technology Pub Date : 2017-09-01 DOI:10.5875/AUSMT.V7I3.1431

Haw-Ching Yang, Chun-hong Cheng, Ting-Wei Su, Kung Lu-Wen, Chia-Ming Jan, Wenchieh Wu, Min-Nan Wu

引用次数: 1

Abstract

Estimating the quality of an electrical discharge machining (EDM) workpiece is challenging when attempting to extract features from the stochastic and time-consuming processes. To solve this problem, an intelligent sensing unit for EDM (ISU-EDM) is proposed to extract key machining features for estimating workpiece roughness. During machining, the ISU-EDM simultaneously samples the signals of both the discharge current and voltage, while automatically segmenting the signals according to tool location and discharge effectiveness. Furthermore, the machining features could be extracted from the segmented data by a genetic-algorithm-based distribution fitting method. After applying the features to an automated virtual metrology system, experimental results show that the mean absolute percentage error of roughness estimation is less than 15%.

查看原文本刊更多论文

电火花加工粗糙度估计的智能传感单元

当试图从随机和耗时的过程中提取特征时，估计电火花加工（EDM）工件的质量是具有挑战性的。为了解决这一问题，提出了一种用于电火花加工的智能传感单元（ISU-EM），用于提取关键加工特征，用于估计工件粗糙度。在加工过程中，ISU-EDM同时对放电电流和电压的信号进行采样，同时根据刀具位置和放电效果自动分割信号。此外，可以通过基于遗传算法的分布拟合方法从分割的数据中提取加工特征。将这些特征应用于自动化虚拟计量系统后，实验结果表明，粗糙度估计的平均绝对百分比误差小于15%。

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

International Journal of Automation and Smart Technology Engineering-Electrical and Electronic Engineering

CiteScore

0.70

自引率

0.00%

发文量

审稿时长

16 weeks

期刊介绍： International Journal of Automation and Smart Technology (AUSMT) is a peer-reviewed, open-access journal devoted to publishing research papers in the fields of automation and smart technology. Currently, the journal is abstracted in Scopus, INSPEC and DOAJ (Directory of Open Access Journals). The research areas of the journal include but are not limited to the fields of mechatronics, automation, ambient Intelligence, sensor networks, human-computer interfaces, and robotics. These technologies should be developed with the major purpose to increase the quality of life as well as to work towards environmental, economic and social sustainability for future generations. AUSMT endeavors to provide a worldwide forum for the dynamic exchange of ideas and findings from research of different disciplines from around the world. Also, AUSMT actively seeks to encourage interaction and cooperation between academia and industry along the fields of automation and smart technology. For the aforementioned purposes, AUSMT maps out 5 areas of interests. Each of them represents a pillar for better future life: - Intelligent Automation Technology. - Ambient Intelligence, Context Awareness, and Sensor Networks. - Human-Computer Interface. - Optomechatronic Modules and Systems. - Robotics, Intelligent Devices and Systems.