A multi-sensor integrated smart tool holder for cutting process monitoring
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ORIGINAL ARTICLE
A multi-sensor integrated smart tool holder for cutting process monitoring Zhengyou Xie 1
&
Yong Lu 2 & Xinlong Chen 1
Received: 15 April 2020 / Accepted: 9 August 2020 / Published online: 17 August 2020 # Springer-Verlag London Ltd., part of Springer Nature 2020
Abstract As two of the most significant parameters reflecting the cutting process, cutting force, and vibration are often adopted for tool condition monitoring (TCM) which is especially important in modern machining. Hence, various methods and sensors for detecting these two signals have been proposed and developed. In this study, an innovative multi-sensor integrated smart tool holder is designed, constructed, and tested, which is capable of measuring triaxial cutting force, torque, and cutting vibration simultaneously and wirelessly in milling operations. A standard commercial tool holder is firstly modified to integrate six capacitive sensors and an acceleration sensor. All the sensors and other electronics, like data acquisition and transmitting unit, are incorporated into the tool holder as a whole system. The characteristics of the device are then determined by a series of tests. Besides, an effective TCM model is built by fusing the features of cutting force and vibration. Experimental results showed good performance of the proposed system which could support wide and flexible application scenarios. Keywords Smart tool holder . Sensor integration . Cutting force measurement . Vibration measurement . Milling process . Tool condition monitoring
1 Introduction Tool condition monitoring (TCM) is of great importance in the modern machining process. The cutting process signal acquisition, as the first link of TCM, is especially crucial. Therefore, how to collect signal during the cutting process timely and accurately has been widely concerned. Early researchers mostly used a single-parameter sensor signal for TCM, which has drawbacks of low robustness and poor reliability due to the complexity of machining. Multi-sensor can provide redundant or complementary information reflecting multiple aspects of the cutting process, which is able to ensure high monitoring accuracy [1, 2]. Thus, there is a trend to identify tool condition by using multi-sensor information fusion technology.
* Zhengyou Xie [email protected] 1
Qian Xuesen Laboratory of Space Technology, China Academy of Space Technology, Beijing 100094, China
2
School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China
In the practical application of TCM technology based on multi-sensor fusion, it is equally important to develop a costefficient and widely applicable multi-sensor signal detection system and research reliable and effective multi-sensor fusion algorithms [3]. However, there are more studies on the latter but relatively fewer on the former. Currently, most researchers simply use a variety of commercial single-parameter sensors such as dynamometer, accelerometer, and acoustic emission sensor to detect cutting process information ind
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