Development and testing of a wireless smart toolholder with multi-sensor fusion

Abstract

The smart toolholder is the core component in the development of intelligent and precise manufacturing. It enables in situ monitoring of cutting data and machining accuracy evolution and has become a focal point in academic research and industrial applications. However, current table and rotational dynamometers for milling force, vibration, and temperature testing suffer from cumbersome installation and provide only a single acquisition signal, which limits their use in laboratory settings. In this study, we propose a wireless smart toolholder with multi-sensor fusion for simultaneous sensing of milling force, vibration, and temperature signals. We select force, vibration, and temperature sensors suitable for smart toolholder fusion to adapt to the cutting environment. Thereafter, structural design, circular runout, dynamic balancing, static stiffness, and dynamic inherent frequency tests are conducted to assess its dynamic and static performance. Finally, the smart toolholder is tested for accuracy and repeatability in terms of force, vibration, and temperature. Experimental results demonstrate that the smart toolholder accurately captures machining data with a relative deviation of less than 1.5% compared with existing force gauges and provides high repeatability of milling temperature and vibration signals. Therefore, it is a smart solution for machining condition monitoring.

Graphical abstract

Keywords

wireless smart toolholder / multi-sensor fusion / circular runout / dynamic balancing / static stiffness / dynamic inherent frequency

References

[1] Liao Z R, la Monaca A, Murray J, Speidel A, Ushmaev D, Clare A, Axinte D, M’Saoubi R. Surface integrity in metal machining—Part I: fundamentals of surface characteristics and formation mechanisms. International Journal of Machine Tools and Manufacture, 2021, 162: 103687

[2] la Monaca A, Murray J W, Liao Z R, Speidel A, Robles-Linares J A, Axinte D A, Hardy M C, Clare A T. Surface integrity in metal machining—Part II: functional performance. International Journal of Machine Tools and Manufacture, 2021, 164: 103718

[3] Lauro C H, Brandão L C, Baldo D, Reis R A, Davim J P. Monitoring and processing signal applied in machining processes—a review. Measurement, 2014, 58: 73–86

[4] Abellan-Nebot J V, Romero Subirón F. A review of machining monitoring systems based on artificial intelligence process models. The International Journal of Advanced Manufacturing Technology, 2010, 47(1–4): 237–257

[5] Zhang P F, Gao D, Lu Y, Wang F L, Liao Z R. A novel smart toolholder with embedded force sensors for milling operations. Mechanical Systems and Signal Processing, 2022, 175: 109130

[6] Li X B, Liu X L, Yue C X, Liang S Y, Wang L H. Systematic review on tool breakage monitoring techniques in machining operations. International Journal of Machine Tools and Manufacture, 2022, 176: 103882

[7] Zhu D H, Zhang X M, Ding H. Tool wear characteristics in machining of nickel-based superalloys. International Journal of Machine Tools amd Manufacture, 2013, 64: 60–77

[8] Yao Q, Luo M, Zhang D H, Wu B H. Identification of cutting force coefficients in machining process considering cutter vibration. Mechanical Systems and Signal Processing, 2018, 103: 39–59

[9] Luo M, Luo H, Axinte D, Liu D S, Mei J W, Liao Z R. A wireless instrumented milling cutter system with embedded PVDF sensors. Mechanical Systems and Signal Processing, 2018, 110: 556–568

[10] Xie Z Y, Lu Y, Li J G. Development and testing of an integrated smart tool holder for four-component cutting force measurement. Mechanical Systems and Signal Processing, 2017, 93: 225–240

[11] Yaldız S, Ünsaçar F, Sağlam H, Işık H. Design, development and testing of a four-component milling dynamometer for the measurement of cutting force and torque. Mechanical Systems and Signal Processing, 2007, 21(3): 1499–1511

[12] Li Y X, Zhao Y L, Fei J Y, Zhao Y, Li X Y, Gao Y X. Development of a tri-axial cutting force sensor for the milling process. Sensors, 2016, 16(3): 405

[13] Totis G, Adams O, Sortino M, Veselovac D, Klocke F. Development of an innovative plate dynamometer for advanced milling and drilling applications. Measurement, 2014, 49: 164–181

[14] Zhou C A, Guo K, Sun J. An integrated wireless vibration sensing tool holder for milling tool condition monitoring with singularity analysis. Measurement, 2021, 174: 109038

[15] Totis G, Wirtz G, Sortino M, Veselovac D, Kuljanic E, Klocke F. Development of a dynamometer for measuring individual cutting edge forces in face milling. Mechanical Systems and Signal Processing, 2010, 24(6): 1844–1857

[16] RizalMGhani J ANuawiM ZChe HaronC H. Development and testing of an integrated rotating dynamometer on tool holder for milling process. Mechanical Systems and Signal Processing, 2015, 52–53: 559–576

[17] Liu M Y, Bing J J, Xiao L, Yun K, Wan L. Development and testing of an integrated rotating dynamometer based on fiber bragg grating for four-component cutting force measurement. Sensors, 2018, 18(4): 1254

[18] SuprockC AFussell B KHassanR ZJerardR B. A low cost wireless tool tip vibration sensor for milling. In: Proceedings of ASME 2008 International Manufacturing Science and Engineering Conference. Evanston: ASME, 2008, 465–474

[19] Chung T K, Yeh P C, Lee H, Lin C M, Tseng C Y, Lo W T, Wang C M, Wang W C, Tu C J, Tasi P Y, Chang J W. An attachable electromagnetic energy harvester driven wireless sensing system demonstrating milling-processes and cutter-wear/breakage-condition monitoring. Sensors, 2016, 16(3): 269

[20] Sugita N, Ishii K, Furusho T, Harada K, Mitsuishi M. Cutting temperature measurement by a micro-sensor array integrated on the rake face of a cutting tool. CIRP Annals, 2015, 64(1): 77–80

[21] Kerrigan K, O’Donnell G E. Temperature measurement in CFRP milling using a wireless tool-integrated process monitoring sensor. International Journal of Automotive Technology, 2013, 7(6): 742–750

[22] Wright P K, Dornfeld D A, Hillaire R G, Ota N K. A wireless sensor for tool temperature measurement and its integration within a manufacturing system. Transactions of the North American Manufacturing Research Institution of SME, 2006, 34: 63–70

[23] Choi Y J, Park M S, Chu C N. Prediction of drill failure using features extraction in time and frequency domains of feed motor current. International Journal of Machine Tools and Manufacture, 2008, 48(1): 29–39

[24] Eynian M, Das K, Wretland A. Effect of tool wear on quality in drilling of titanium alloy Ti6Al4V, Part I: cutting forces, burr formation, surface quality and defects. High-Speed Machining, 2017, 3(1): 1–10

[25] Dimla D E, Lister P M. On-line metal cutting tool condition monitoring.: I: force and vibration analyses. International Journal of Machine Tools and Manufacture, 2000, 40(5): 739–768

[26] Liu Q, Zhang H J, Liu X L, Gao D Y, Zhang M J. A review of research on intelligent cutting tools. Journal of Mechanical Engineering, 2021, 57(21): 248–268

[27] ShawM CCookson J O. Metal Cutting Principles. New York: Oxford University Press, 2005

[28] Zhang P F, Gao D, Lu Y, Ma Z F, Wang X R, Song X. Cutting tool wear monitoring based on a smart toolholder with embedded force and vibration sensors and an improved residual network. Measurement, 2022, 199: 111520

[29] Liu C F, Liu B, Zhou Y, He Y, Chi D X, Gao X J, Liu Q K. A real-time cutting temperature monitoring of tool in peripheral milling based on wireless transmission. International Journal of Thermal Sciences, 2023, 186: 108084

[30] Chen G, Gao Q, Yang X P, Liu J, Su Y X, Ren C Z. Investigation of heat partition and instantaneous temperature in milling of Ti−6Al−4V alloy. Journal of Manufacturing Processes, 2022, 80: 302–319

[31] Jiang F L, Liu Z Q, Wan Y, Shi Z Y. Analytical modeling and experimental investigation of tool and workpiece temperatures for interrupted cutting 1045 steel by inverse heat conduction method. Journal of Materials Processing Technology, 2013, 213(6): 887–894

[32] Rizal M, Ghani J A, Nuawi M Z, Haron C H C. An embedded multi-sensor system on the rotating dynamometer for real-time condition monitoring in milling. The International Journal of Advanced Manufacturing Technology, 2018, 95(1–4): 811–823

Nomenclature

Ax, Ay, Az	Average values of milling vibration in the x-, y-, and z-direction, respectively
E_{F_x}, E_{F_y}, E_{F_{\mathit{\text{z}}}}	Force measurement errors in the x-, y-, and z-direction, respectively
E_{T_x}, E_{T_y}, E_{T_{\mathit{\text{z}}}}	Torque measurement errors in the x-, y-, and z-direction, respectively
fs	Design frequency of the smart toolholder
Fhf	Free mode force
Fhwx, Fhwy	Working mode forces in the x- and y-direction, respectively
Fp	Perpendicular force
Fr	Radial force
Fv	Velocity force
Fx, Fy, Fz	Forces in the x-, y-, and z-direction, respectively
\overline{F_{imax}}, \overline{F_{imin}}	Maximum and minimum milling force average values among the three measured datasets, respectively
\overline{F_{\text{k}x}}, \overline{F_{\text{k}y}}, \overline{F_{\text{k}\mathit{\text{z}}}}	Kistler’s average values of 100000 consecutive force data points in the x-, y-, and z-direction, respectively
\overline{F_{\mathit{\text{z}}}}	Smart toolholder’s average value of 100000 consecutive force data points in the z-direction
Ktx, Kty, Ktz	Torque stiffness indexes in the x-, y-, and z-direction, respectively
Kx, Ky, Kz	Stiffness indexes in the x-, y-, and z-direction, respectively
L	Distance from the tip of the tool to the reference center of the force sensor
\overline{M_x}, \overline{M_y}	Smart toolholder’s average values of 100000 consecutive bending moment data points in the x- and y-direction, respectively
n	Spindle speed
p	Number of sampling points of per cutting tooth
R	Tool radius
Tmax, Tmin	Milling temperatures during machining
Tx, Ty, Tz	Torques in the x-, y-, and z-direction, respectively
vf	Feed speed
z	Number of cutting teeth
αe	Radial cut width
αp	Axial cutting depth
{\epsilon }_i	Measurement bending moment and force error
\delta	Measurement vibration error
\eta	Temperature difference
{\mu }_x, {\mu }_y, {\mu }_{\mathit{\text{z}}}	Percentage errors in the x-, y- and z-direction, respectively
θ	Angle between Fr and the x-axis

Acknowledgements

This work was supported by the National Key R&D Program of China (Grant No. 2022YFB3206700), the Fundamental Research Funds for the Central Universities, China (Grant No. 2022CDJKYJH060), and the Graduate Research and Innovation Foundation of Chongqing, China (Grant No. CYB23017).

Conflict of Interest

The authors declare that they have no conflict of interest.

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