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A wireless instrumented milling cutter system with embedded PVDF sensors

Luo, Ming; Luo, Huan; Axinte, Dragos; Liu, Dongsheng; Mei, Jiawei; Liao, Zhirong

A wireless instrumented milling cutter system with embedded PVDF sensors Thumbnail


Ming Luo

Huan Luo

Professor of Manufacturing Engineering

Dongsheng Liu

Jiawei Mei


Among all the monitoring data which could be captured in a machining process, the cutting forces could convey key knowledge on the conditions of the process. When the machining involves a single cutting edge the relationship between the output forces (measured with off-the-shelf dynamometers) and condition of the process, is somehow straight forward. However, when multiple cutting edges are in contact with the workpiece, the conventional dynamometers, that cannot separate the reaction forces on each cutting edge, lose significant information that could be used to in-detail monitor the machining process. To this end, this paper presents a novel concept of instrumented wireless milling cutter system with embedded thin film sensors in each cutting inserts, thus the cutting forces acting on each cutting edge could be monitored without reducing the stiffness and dynamic characteristics of the machining system. For this to happen, a dedicated milling force decoupling model for the developed instrumented milling cutter system is proposed and calibrated, and for the first time the accurate on-line estimation of the separate inserts’ working conditions is achieved. The validation demonstrates a satisfactory agreement between the forces measured from the dynamometer and the proposed monitoring system prototype with the error less than 10%. Furthermore, the experimental results also indicate that the monitoring system prototype could also identify the tool insert conditions such as worn and chipped, which could be of high relevance to the analysis of the insert failure mechanism and its progress. Not only the proposed method and easy implementable but above all, it allows the monitoring of the condition (e.g. worn, chipped) of each insert, ability that has not been previously reported.

Journal Article Type Article
Acceptance Date Mar 18, 2018
Online Publication Date Mar 30, 2018
Publication Date Sep 15, 2018
Deposit Date May 9, 2018
Publicly Available Date Mar 31, 2019
Journal Mechanical Systems and Signal Processing
Print ISSN 0888-3270
Electronic ISSN 0888-3270
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 110
Keywords Cutting forces ; Tool wear ; Sensor ; Smart tool
Public URL
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