Abstract
The vast majority of tool condition monitoring systems use the motor current instead of the cutting force as the predictor signal. The measured motor current signal is time-dependant and instable. It is difficult to detect the cutting force token signal from such motor current signal. This paper presents a method that uses the wavelet transforms to reconstruct the cutting force token signal from the current signal based on the time frequency analysis of the cutting force signal. The result of the cutting force measurement experiment shows that the proposed reconstruct method could be used to analyze the spindle current and monitor the time-varying cutting force.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Satish B, Soundar R K, Akhlesh L, et al. Fractal estimation of flank wear in turning. ASME J Dyn Syst Meas Cont, 2000, 122: 89–94
Dimla E, Dimlasnr, Sensor signals for tool wear monitoring in metal cutting operations: review of methods. Int J Mach Tool Manuf, 2000, 40: 1073–1098
Karuda S, Bradley C. A review of machine vision sensors for tool condition monitoring. Compu Indust, 1997, 34: 55–72
Sun J, Hong G S, Rahman M, et al. Identification of feature set for effective tool condition monitoring by acoustic emission sensing. Int J Prod Res, 2004, 42(5): 901–918
Wang L, Mehrabi M G, Kannatey E J R, et al. Hidden Markov model-based tool wear monitoring in turning. J Manuf Sci Eng, 2002, 124(3): 651–658
Balazinski M, Czogala E, Jemielniak, K, et al. Tool condition monitoring using artificial intelligence. Eng Appl Artif Intel, 2002, 15: 73–80
Bernhard S. On-line and indirect tool wear monitoring in turning with artificial neural networks: a review of more than a decade of research. Mech Syst Sig Proc, 2002, 16(4): 487–546
Lee B Y, Tarng Y S. Application of the discrete wavelet transform to the monitoring of tool failure in end milling using the spindle motor current. Int J Adv Manuf Technol, 1999, 15: 238–243
Xu M, Jerard R B, Fussell B K. Energy based cutting force model calibration for milling. Comput Aided Des Appl, 2007, 4(1–4): 341–351
Jeong Y-H, Cho D-W. Estimating cutting force from rotating and stationary feed motor currents on a milling machine. Int J Mach Tool Manuf, 2002, 42(14): 1559–1566
Li B, Zhang C, Liu H Q, et al. Indirect measurement of the milling forces based on spindle motor current (in Chinese). J Huazhong Univ Sci Technol (Natl Sci.), 2008, 36(3): 5–7
Bhattacharyya P, Sengupta D, Mukhopadhyay S, et al. On-line tool condition monitoring in face milling using current and power signals. Int J Prod Res, 2008, 46(4): 1187–1201
Author information
Authors and Affiliations
Corresponding author
Additional information
Supported by the State Key Laboratory of Digital Manufacturing Equipment and Technology of China, the National Basic Research Program of China (“973” Project) (Grant No. 2005CB724100) and the National Natural Science Foundation of China (Grant No. 50875098)
Rights and permissions
About this article
Cite this article
Mao, X., Liu, H. & Li, B. Time-frequency analysis and detecting method research on milling force token signal in spindle current signal. Sci. China Ser. E-Technol. Sci. 52, 2810–2813 (2009). https://doi.org/10.1007/s11431-009-0303-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11431-009-0303-1