TPA and RCSA based frequency response function modelling for cutting forces compensation

Significance 

Machining processes is a crucial aspect of numerous industrial operations. As such, it is important to directly and accurately measure the cutting forces to enhance monitoring and adaptive control of the machining operations process. Unfortunately, the dynamic characteristic of the measurement systems hinders accurate measurement of the cutting forces and, therefore, an alternative and effective approach is required. In a recently published literature, researchers proposed the compensation of the cutting forces based on the frequency response function. However, it is difficult to measure the function in actual production.

To this note, Xi’an Jiaotong University scientists: Chenxi Wang (PhD candidate), Dr. Baijie Qiao, Dr. Xingwu Zhang, Professor Hongrui Cao, and Professor Xuefeng Chen developed an new effective method for calculating and modeling of the frequency response function based on the transfer path analysis and receptance coupling substructure analysis. Their main objective was to enhance the prediction of the frequency response function of the cutting forces and utilizing the proposed method for compensation of the cutting forces. The research work is currently published in Journal of Sound and Vibration.

Briefly, the research team first performed a frequency response function derivation based on the transfer path analysis and receptance coupling substructure analysis. Transfer path analysis being an effective method for vibration and noise analysis based on impact tests, it was of great benefit in finding the specific vibration components from the vibration source of the corresponding transmission path. On the other hand, receptance coupling substructure analysis could be used in solving the frequency response function prediction problem for complex systems. The measurement system was divided into three substructures namely the workpiece, table dynamometer with screws and the joint surface between the two previous substructures.

Whereas the joint surface was simplified to represent a spring-damping model with damping and contact stiffness components, a finite element method was used to obtain the frequency response function of the workpiece. This was adjustable for different workpieces and tool positions to enhance measurement accuracy. On the other hand, a single impact test was required to measure the frequency response function of the dynamometer. Additionally, a few impact tests could be used in the identification of the contact parameters which could, in turn, be applied in other cutting conditions.

To prove the concept, impact and milling tests were implemented for identification of parameters, algorithm verification and cutting forces compensation. Based on the experimental results, the authors concluded that the proposed method exhibited sufficient accuracy for the assembly frequency response function prediction. For instance, for a frequency response function more than 1, the compensated amplitude was observed to be less than the measured amplitude in the frequency domain. The compensated frequencies exhibited a similar variation tendency to the experimental results in the literature thus upholding the correctness of the method.

In summary, the study by Xi’an Jiaotong University scientists demonstrated successfully an effective frequency response function modeling for cutting forces compensation based on transfer path analysis and receptance coupling substructure analysis. Apart from milling, the method can be extended to other machining operations such as turning and drilling. Altogether, as stated by Dr. Qiao the corresponding author, the study paves the way for further future works like building a model to describe the axial frequency response function.

TPA and RCSA based frequency response function modelling for cutting forces compensation - Advances in Engineering

About the author

Chenxi Wang is a Ph.D candidate in School of Mechanical Engineering, Xi’an Jiaotong University. He received the Bachelor degree from Xi’an Jiaotong University, Xi’an, China, 2015. Now, He is working hard for the Ph.D degree.

His research interests are milling dynamic and chatter, vibraton active control, wavelet finite element method, inverse problem modelling. He holds 6 patents and has published 13 peer-reviewed journal papers and most of them were published in the respected journals with H index of 6. He has undertaken one project funded by Xi’an Jiaotong University for excellent doctoral students.

About the author

Xingwu Zhang is an associate professor in School of Mechanical Engineering, Xi’an Jiaotong University. He received the Ph.D. degree from Xi’an Jiaotong University, Xi’an, China, 2012. His research interests are dynamic system modeling and analysis, structural health monitoring and active vibration control. He is the PI of over 4 projects, including National Natural Science Foundation of China etc.

He holds more than 30 patents and published over 50 academic papers with H index of 16. Dr. Zhang is the member of IEEE Instrument and Measurement, the technical committee member of IEEE Instruments and Measurement Society TC-7 Signals and Systems in Measurement.

About the author

Baijie Qiao, received his B.S., M.S. and Ph.D. in mechanical Engineering from Xi’an Jiaotong Universtiy, China in 2010, 2012 and 2017, respectively. He was a visiting scholar in the Structural Dynamics and Acoustic Systems Laboratory at the University of Massachusetts Lowell in 2015-2016. Currently, he is an Associate Professor in School of Mechanical Engineering, Xi’an Jiaotong University. He spends a short period as an academic visitor in the Institute of Sound and Vibration Research at University of Southampton.

His research interests include inverse problems in engineering, dynamic force identification, sparse regularization, structural health monitoring, dynamic strain/stress full-field reconstruction. He has published more than 30 international journal papers and owned 30 Chinese Patents. He is also the reviewer of more than 10 international journals.

About the author

Hongrui Cao is currently a professor in mechanical engineering at Xi’an Jiaotong University, China. He received his Bachelor degree at Harbin institute of Technology (2004), and PhD at Xi’an Jiaotong University, China (2010). He studied at University of British Columbia (Canada) as a visiting student in 2008-2010, and worked at Bremen University (Germany) as a Research Fellow of Alexander von Humboldt Foundation in 2015-2016. Dr. Cao has undertaken 2 projects funded by National Natural Science Foundation of China and several provincial/ministerial projects. He has published about 50 peer-reviewed journal papers and most of them were published in the respected journals. He serves as a peer reviewer for more than 5 international journals. He is a Research Affiliate in CIRP and an active member of IEEE.

His research interest includes intelligent spindles, machine tool dynamics, cutting process monitoring and control, fault diagnosis of rotating machinery.

About the author

Xuefeng Chen is a professor and the dean of School of Mechanical Engineering, Xi’an Jiaotong University. He received the Ph.D degree from Xi’an Jiaotong University, Xi’an, China, in 2004. His research interests include finite element method, fault diagnosis and prognosis, active vibration control and optimization.

Dr. Chen has published over 200 papers in refereed journals, with google scholar citation > 8000 and H index of 49. He is the Chapter Chairman of the Xi’an and Chengdu Joint Section of the IEEE Instrumentation and Measurement Society. He was a recipient of the National Excellent Doctoral Dissertation of China in 2007, the Second Awards of Technology Invention of China in 2009, The China National Funds for Distinguished Young Scientists in 2012, and a Chief Scientist of the National Key Basic Research Program of China (973 Program) in 2015.

Reference

Wang, C., Qiao, B., Zhang, X., Cao, H., & Chen, X. (2019). TPA and RCSA based frequency response function modelling for cutting forces compensation. Journal of Sound and Vibration, 456, 272-288.

Go To Journal of Sound and Vibration

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