Abstract
A control system to improve the efficiency of machining a workpiece with varying thickness in the wire electrical discharge machining (WEDM) process is proposed. The abnormal ratio R ab defined by the proportion of abnormal sparks in a sampling period is taken as the controlled variable. It is allowed to reduce temporarily as the cutting thickness is changing. A gain self-tuning fuzzy control algorithm is used so that the transient situation as the cutting thickness is suddenly increasing can be suppressed immediately, and a stable performance can be achieved. In addition, the grey predictor is adopted to compensate the time-delayed R ab caused by the low-pass filter data processing. Experiments reveal that there is a slight variance in the optimal reference of R ab when the cutting thickness is larger than 20 mm, and its value is set to 55% in these cases. Three cases were tested: the constant machining parameters, the constant R ab and the proposed adaptive R ab . The results show that the cutting speed can be obviously improved by the proposed control strategy.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Benedict GF (1987) Nontraditional manufacturing processes. Marcel Dekker, Inc.
Kinoshita N, Fukui M, Shichida H, Gamo G (1976) Study on E.D.M. with wire electrode; gap phenomena. Annals of the CIRP 25(1):141–145
Tanimura T, Heuvelman CJ (1977) The properties of the servo gap sensor with sparking-erosion machining. Annals of the CIRP 26(1):59–63
Huang YH, Zhao GG, Zhang ZR, Yu CY (1986) The identification and its means of servo feed adaptive control system in WEDM. Annals of the CIRP 35(1):121–123
Zhang W, Bai JC, Liu JC (1989) The application of adaptive control in WEDM. Proceedings of the International Symposium for Electro-Machining, (ISEM-9) 1989:378–381
Rajurkar KP, Wang WM (1994) WEDM identification and adaptive control for variable-height components. Ann CIRP 43(1):199–202
Yan MT, Liao YS (1998) Adaptive control of the WEDM process using the fuzzy control strategy. J Manuf Syst 17(4):263–273
Liao YS, Woo JC (2000) Design of a fuzzy controller for the adaptive control of WEDM process. Int J Mach Tools Manuf 40(15):2293–2307
Lee WM, Liao YS (2003) Self-tuning fuzzy control with grey prediction for wire rupture prevention in WEDM. Int J Adv Manuf Technol 22(7–8):481–490
Liao YS, Chiu YY, Yan MT (1997) Study of wire breaking process and monitoring of WEDM. Int J Mach Tools Manuf 37(4):555–567
Deng JL (1989) Introduction to grey system. J Grey Syst 1:1–24
Tsai TC (1999) Application of neural network and genetic algorithms in the machining-parameters optimization for WEDM. Master Thesis, Mechanical Engineering, National Taiwan University
Liao YS, Yu YP (2004) The energy aspect of material property in WEDM and its application. J Mater Process Technol 149:77–82
Wong CC, Liang WC, Feng HM, Chiang DA (1998) Grey prediction controller design. J Grey Syst 10(2):123–131
Lee CC (1990) Fuzzy logic in control systems: fuzzy logic controller ¯ Part I. IEEE Trans on Systems Man and Cybernetics 20:404–418
Driankov D, Hellendoorn H, Reinfrank M (1996) An introduction to fuzzy control. Springer, Berlin Heidelberg New York
Mudi RK, Pal RP (1999) A robust self-tuning scheme for PI- and PD-type fuzzy controllers. IEEE Trans on Fuzzy Syst 7(1):2–16
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Lee, W.M., Liao, Y.S. Adaptive control of the WEDM process using a self-tuning fuzzy logic algorithm with grey prediction. Int J Adv Manuf Technol 34, 527–537 (2007). https://doi.org/10.1007/s00170-006-0623-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-006-0623-2