Open Access
Subscription Access
Open Access
Subscription Access
Machine Tool Multibody Dynamic Model Updating Using Vision-Based Modal Analysis
Subscribe/Renew Journal
Machine tool dynamic behaviour is influenced by the structural properties of its subsystems assembled at interfaces as well as by the interface characteristics. Interfaces are commonly modelled as spring-damper connections, parameters of which are usually updated by minimizing the difference between model-predicted and measured dynamics characterized by frequency response functions. This model updating approach requires global mode shapes to be measured by roving the hammer and/or the sensor such as to localize the joint parameters to be updated. Such measurements are time consuming and fraught with errors. As a new, alternative, and simpler way to update joint parameters of a machine tool multibody dynamic model, this paper reports on the use of full-field vision-based modal analysis methods. Mode shapes thus identified agree with those estimated with the traditional experimental modal analysis procedures. The updated machine tool multibody dynamic model is a step towards realizing an accurate digital twin.
Keywords
- Bianchi, G., Paolucci, F., Braembussche, P. D., Brussel, H., & Jovane, F. (1996). Towards virtual engineering in machine tool design. CIRP Annals, 45, 1. https://doi. org/10.1016/S0007-8506(07)63085-6
- Chen, J. G., Wadhwa, N., Cha, Y-J., Durand, F., Freeman, W. T., & Buyukozturk, O. (2015). Modal identification of simple structures with high-speed video using motion magnification. Journal of Sound and Vibration, 345, 58-71. https:// doi.org/10.1016/j.jsv.2015.01.024
- Gupta, P., Rajput, H. S., & Law, M. (2022). Vision-based modal analysis of cutting tools. CIRP Journal of Manufacturing Science and Technology, 32, 91-107. https://doi.org/10.1016/j.cirpj.2020.11.012
- Gupta, P., & Law M. (2021). Evaluating tool point dynamics using smartphone-based visual vibrometry. Procedia CIRP, 101, 250-253. https://doi. org/10.1016/j.procir.2020.09.196
- Huynh, H. N., & Altintas, Y. (2020). Modeling the dynamics of five-axis machine tool using the multibody approach. ASME J. Manuf. Sci. Eng., 143(2). https://doi.org/10.1115/1.4048854
- Lambora, R., Nuhman, A. P., Law, M., & Mukhopadyay, S. (2022). Recovering cutting tool modal parameters from fractionally uncorrelated and potentially aliased signals. CIRP Journal of Manufacturing Science and Technology, 38, 414-426.
- Law, M., & Ihlenfeldt, S. (2014). A frequency-based substructuring approach to efficiently model position-dependent dynamics in machine tools. Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-body Dynamics, 229(3), 304-317. https://doi.org/10.1177%2F146441 9314562264
- Law, M., Ihlenfeldt, S., Wabner, M., Altintas, Y., & Neugebauer, R. (2013a). Position-dependent dynamics and stability of serial-parallel kinematic machines. CIRP Annals, 62, 375-378. https://doi. org/10.1016/j.cirp.2013.03.134
- Law, M., Phani, A. S., & Altintas, Y. (2013b). Position- dependent multibody dynamic modeling of machine tools based on improved reduced order models, ASME J. Manuf. Sci. Eng., 135 (2).
- Law, M., Altintas, Y., & Phani, A. S. (2013c). Rapid evaluation and optimization of machine tools with position-dependent stability. International Journal of Machine Tools and Manufacture, 68, 81-90. https://doi.org/10.1016/j.ijmachtools.2013.02.003
- Law, M., Gupta, P., & Mukhopadhyay, S. (2020). Modal analysis of machine tools using visual vibrometry and output-only methods. CIRP Annals, 69(1), 357-360. https://doi.org/10.1016/j.cirp.2020.04.043
- Law, M., Lambora, R., Nuhman, A. P., & Mukhopadhyay, S. (2022). Modal parameter recovery from temporally aliased video recordings of cutting tools. CIRP Annals, 71(1), 329-332.
- Nuhman A. P., Singh, A., Lambora, R., & Law, M. (2022). Methods to estimate subpixel level small motion from video of vibrating cutting tools. CIRP Journal of Manufacturing Science and Technology, 39, 175-184.
Abstract Views: 253
PDF Views: 0