Electrical Engineering and Intelligent Systems pp 347-359 | Cite as
High-Precision Machining by Measuring and Compensating the Error Motion of Spindle’s Axis of Rotation in Radial Direction
Abstract
This paper deals with cutting force monitoring for high-precision machining. The authors have employed displacement sensors to monitor the cutting forces, as they are cheap and small enough to be built in the spindle structure. A monitoring method, which utilizes sensitive displacement sensors, is discussed. The sensors are installed in X–Y directions near the front bearings of the spindle to detect the small displacements of a spindle caused by cutting forces. Monitoring tests are carried out under end-milling operations and the cutting forces are estimated from the displacement signals by the simple signal processing technique. However, as the displacement sensor measures the variation of the gap size between the sensor head and the target surface, it also records displacements due to error motion of a spindle's axis of rotation in radial direction and roundness errors of the target surface. By comparing the cutting force estimated from displacement sensors with the cutting force measured by using a dynamometer, the machine tool spindle error motions are investigated, and its compensation scheme is proposed. The test results show that the monitoring system is reliable for the adaptive control of machining accuracy for end-milling process.
References
- 1.Martin KF (1994) A review by discussion of condition monitoring and fault diagnosis in machine tools. Int J Mach Tools Manuf 34(4):527–551CrossRefGoogle Scholar
- 2.Andrews GC, Tlusty J (1983) A critical review of sensors for unmanned machining. Ann CIRP 32–2:563–572Google Scholar
- 3.Byrne G, Dornfeld D, Inasaki I, Ketteler G, Konig W, Teti R (1995) Tool condition monitoring (tcm)—status of research and industrial application. Ann CIRP 44(2):541–567CrossRefGoogle Scholar
- 4.Strafford KN, Audy J (1997) Indirect monitoring of machinability in carbon steels by measurement of cutting forces. J Mater Process Technol 67(1–3):150–156CrossRefGoogle Scholar
- 5.DimlaSr DE, Lister PM (2000) On-line metal cutting tool condition monitoring: I: force and vibration analyses. Int J Mach Tools Manuf 40(5):739–768CrossRefGoogle Scholar
- 6.Song D-Y, Otani N, Aoki T, Kamakoshi Y, Ohara Y, Tamaki H (2005) A new approach to cutting state monitoring in end-mill machining. Int J Mach Tools Manuf 45(7–8):909–921CrossRefGoogle Scholar
- 7.Sarhan A, Sayed R, Nasr AA, El-Zahry RM (2001) Interrelation between cutting force variation and tool wear in end-milling. J Mater Process Technol 109(3):229–235CrossRefGoogle Scholar
- 8.Lee P, Altintas Y (1996) Prediction of ball end milling forces from orthogonal cutting data. Int J Mach Tools Manuf 36:1059–1072CrossRefGoogle Scholar
- 9.Feng HS, Menq CH (1994) The prediction of cutting forces in the ball end milling process—II. Cut geometry analysis and model verification. Int J Mach Tools Manuf 34:711–719CrossRefGoogle Scholar
- 10.Sokolowski S, Kosmol J (1996) Intelligent monitoring system designer. In: Japan/USA symposium on flexible automation, vol 2. ASME, New YorkGoogle Scholar
- 11.Feng HS, Menq CH (1994) The prediction of cutting forces in the ball end milling process model-I. Formulation and model building procedure. Int J Mach Tools Manuf 34:697–710CrossRefGoogle Scholar
- 12.Teti R, Jawahir IS, Jemielniak K, Segreto T, Chen S, Kossakowska J (2006) Chip form monitoring through advanced processing of cutting force sensor signals. CIRP Ann Manuf Technol 55(1):75–80CrossRefGoogle Scholar
- 13.DimlaSnr DE (2000) Sensor signals for tool-wear monitoring in metal cutting operations—a review of methods. Int J Mach Tools Manuf 40(8):1073–1098CrossRefGoogle Scholar
- 14.Huang SN, Tan KK, Wong YS, de Silva CW, Goh HL, Tan WW (2007) Tool wear detection and fault diagnosis based on cutting force monitoring. Int J Mach Tools Manuf 47(3–4):444–451CrossRefGoogle Scholar
- 15.Matsubara A, Kakino Y, Ogawa T, Nakagawa H, Sato T (2000) Monitoring of cutting forces in end-milling for intelligent machine tools. In: Proceedings of the 5th international conference on progress of machining technology, Beijing, p 615Google Scholar
- 16.Chung YL, Spiewak SA (1994) A model of high performance dynamometer. J Eng Ind (ASME) 16:279–288CrossRefGoogle Scholar
- 17.Santochi M, Dini G, Tantussi G, Beghini M (1997) A sensor-integrated tool for cutting force monitoring. CIRP Ann Manuf Technol 46(1):49–52CrossRefGoogle Scholar
- 18.Altintas Y (1992) Prediction of cutting forces and tool breakage in milling from feed drive current measurement. J Eng Ind (ASME) 114(4):386–391CrossRefGoogle Scholar
- 19.Sarhan AAD, Sugihara M, Saraie H, Ibaraki S, Kakino Y (2006) Monitoring method of cutting force by using additional spindle sensors. JSME Int J Ser C 49(2):307–315CrossRefGoogle Scholar
- 20.Donaldson RR (1972) A simple method for separating spindle error from test ball roundness. Ann CIRP 21:125–26Google Scholar
- 21.Tu JF, Bossmanns B, Hung Spring C C (1997) Modeling and error analysis for assessing spindle radial error motions. Precis Eng 21(2–3):90–101CrossRefGoogle Scholar
- 22.Shinno H, Mitsui K, Tatsue Y, Tanaka N, Omino T, Tabata T, Nakayama K (1987) A new method for evaluating error motion of ultra precision spindle. CIRP Ann Manuf Technol 36(1):381–384CrossRefGoogle Scholar
- 23.Fujimaki K, Mitsui K (2007) Radial error measuring device based on auto-collimation for miniature ultra-high-speed spindles. Int J Mach Tools Manuf 47(11):1677–1685CrossRefGoogle Scholar
- 24.Castro HFF (2008) A method for evaluating spindle rotation errors of machine tools using a laser interferometer. Measurement 41(5):526–537CrossRefGoogle Scholar
- 25.Noguchi S, Tsukada T, Sakamoto A (1995) Evaluation method to determine radial accuracy of high-precision rotating spindle units. Precis Eng 17(4):266–273CrossRefGoogle Scholar
- 26.Sarhan AAD, Hassan MA, Matsubara A, Hamdi M (2011) Compensation of machine tool spindle error motions in the radial direction for accurate monitoring of cutting forces utilizing sensitive displacement sensors. In: Proceedings of the world congress on engineering 2011 (WCE 2011), vol I, London, 6–8 July 2011, pp 535–539Google Scholar