Kalman Residual Analysis based Sensor-less Tool-Workpiece Contact Detection on Ultra-precision Machine Tool

IF 2.8 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters Pub Date : 2026-10-01 Epub Date: 2026-10-05 DOI:10.1016/j.mfglet.2026.07.050

Zongze Li, Ryota Taniguchi, Kyungki Lee, Takehiro Hayasaka, Eiji Shamoto, Yuta Iwasaki, Ryosuke Imura

{"title":"Kalman Residual Analysis based Sensor-less Tool-Workpiece Contact Detection on Ultra-precision Machine Tool","authors":"Zongze Li, Ryota Taniguchi, Kyungki Lee, Takehiro Hayasaka, Eiji Shamoto, Yuta Iwasaki, Ryosuke Imura","doi":"10.1016/j.mfglet.2026.07.050","DOIUrl":null,"url":null,"abstract":"<div><div>A sensor-less tool-workpiece contact detection method for an ultra-precision machine tool based on Kalman Filter (KF) is proposed in this study. The servo thrust signal of feed axis is processed using KF, and its Kalman Residual (KR) is calculated in real time. Parameters of KF are analyzed to achieve the optimized contact detection performance. A cumulative Kalman Residual (CKR) is constructed, and its threshold is experimentally determined, to detect the external disturbance of feed axis under a constant feed rate. Experimental studies were conducted in which the workpiece moved towards the tool initially and retracted in the opposite direction as soon as the tool and workpiece got in contact. The experiments were implemented with three different feed rates. The experimental results validate that the proposed contact detection method can achieve the micro-level tool-workpiece detection.</div><div>© 2026 The Authors. Published by ELSEVIER Ltd. This is an open access article under the CC BY-NC-ND license (<span><span>https://creativecommons.org/licenses/by-nc-nd/4.0</span><svg><path></path></svg></span>)</div><div>Peer-review under responsibility of the scientific committee of the NAMRI|SME.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 399-409"},"PeriodicalIF":2.8000,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Manufacturing Letters","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S221384632600101X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/10/5 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}

引用次数: 0

Abstract

A sensor-less tool-workpiece contact detection method for an ultra-precision machine tool based on Kalman Filter (KF) is proposed in this study. The servo thrust signal of feed axis is processed using KF, and its Kalman Residual (KR) is calculated in real time. Parameters of KF are analyzed to achieve the optimized contact detection performance. A cumulative Kalman Residual (CKR) is constructed, and its threshold is experimentally determined, to detect the external disturbance of feed axis under a constant feed rate. Experimental studies were conducted in which the workpiece moved towards the tool initially and retracted in the opposite direction as soon as the tool and workpiece got in contact. The experiments were implemented with three different feed rates. The experimental results validate that the proposed contact detection method can achieve the micro-level tool-workpiece detection.

Peer-review under responsibility of the scientific committee of the NAMRI|SME.

查看原文本刊更多论文

基于卡尔曼残差分析的超精密机床无传感器刀工接触检测

提出了一种基于卡尔曼滤波（KF）的超精密机床无传感器刀工接触检测方法。利用KF对进给轴伺服推力信号进行处理，实时计算其卡尔曼残差（KR）。分析了KF的参数，实现了最优的接触检测性能。构造了累积卡尔曼残差（CKR），并通过实验确定了其阈值，用于检测恒定进给速率下进给轴的外部扰动。在实验研究中，工件最初向刀具方向移动，当刀具与工件接触时，工件向相反方向收缩。试验采用三种不同的进料速率进行。实验结果验证了所提出的接触检测方法能够实现刀具-工件的微观检测。©2026作者。爱思唯尔有限公司出版这是一篇在CC BY-NC-ND许可（https://creativecommons.org/licenses/by-nc-nd/4.0）Peer-review)下的开放获取文章，由NAMRI b| SME科学委员会负责。

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