Detecting chatter and estimating wear from the torque of end milling signals by using Index Based Reasoner (IBR)

International Journal of Advanced Manufacturing Technology

Volumn 58, Issue 1-4, 2012, Pages 109-118

  Tansel, I N ^a   Li, M ^a   Demetgul, M ^b   Bickraj, K ^a   Kaya, B ^c   Ozcelik, B ^c  

^a Florida International University   (United States)

^b MARMARA UNIVERSITY   (Turkey)

^c GEBZE TECHNICAL UNIVERSITY   (Turkey)

Author keywords

Chatter; Dynamometer design; Index Based Reasoner (IBR); Milling; The torque based machining monitor; Tool wear

Indexed keywords

CHATTER; DYNAMOMETER DESIGN; REASONER; TOOL WEAR; TORQUE-BASED;

COMMINUTION; DYNAMOMETERS; ESTIMATION; MILLING (MACHINING); PROGRAM DIAGNOSTICS; TABLE LOOKUP; WEAR OF MATERIALS;

SIGNAL DETECTION;

EID: 84855676302     PISSN: 02683768     EISSN: 14333015     Source Type: Journal    
DOI: 10.1007/s00170-010-2838-5     Document Type: Article

References (56)

1. Kamarthi SV (1994) On-line tool wear estimation in turning through sensor data fusion and neural networks. Dissertation, Pennsylvania State University
2. Burke LI, Rangwala S (1991) Tool condition monitoring in metal cutting: a neural network approach. J Intell Manuf 2:269-280
3. Dimla DE, Lister PM, Leighton NJ (1998) Automatic tool state identification in a metal turning operation using MLP neural networks and multivariate process parameters. Int J Mach Tools Manuf 38(4) : 343-352 (Pubitemid 128423996)
4. Leem CS, Dornfeld DA, Dreyfus SE (1995) A customized neural network for sensor fusion in on-line monitoring of cutting tool wear. J Eng Ind, Trans ASME 117:152-159
5. Ghasempoor A, Moore TN, Jeswiet J (1998) On-line wear estimation using neural networks. Proc Inst Mech Eng B 212(2) : 105-112 (Pubitemid 128738100)
6. Elanayar SVT, Shin YC (1994) Radial basis function neural network for approximation and estimation of nonlinear stochastic dynamic systems. IEEE Trans Neural Netw 5:594-603
7. Sick B (1998) On-line tool wear classification in turning with time-delay neural networks and process-specific pre-processing. In: International Joint Conference on Neural Networks (IJCNN'98), Anchorage, AK, 84-89
8. Elanayar S, Shin YC (1992) Robust tool wear estimation via radial basis function neural networks. In: Neural networks in manufacturing and robotics. New York: ASME, PED-57, pp 37-51 (Pubitemid 23610668)
9. Hong GS, Rahman M, Zhou Q (1996) Using neural network for tool condition monitoring based on wavelet decomposition. Int J Mach Tools Manuf 36(5) : 551-556
10. Fukuda T, Shibata T (1992) Hierarchical intelligent control for robotic motion by using fuzzy, artificial intelligence, and neural network. In: Proceedings of IJCNN'92, Baltimore, MD, pp 269-274.
11. Ko T, Cho D (1994) Tool wear monitoring in diamond turning by fuzzy pattern recognition. ASME J Eng Ind 116:225-232
12. Lee C (1990) Fuzzy logic in control systems: fuzzy logic controller-part II. IEEE Trans Syst Man Cybern 20(2) : 419-435 (Pubitemid 20702823)
13. Takagi T, Sugeno M (1983) Derivation of fuzzy control rules from human operator's control actions. In: Proceedings of the IFAC symposium on fuzzy information, knowledge representation and decision analysis, pp 55-60 (Pubitemid 14633040)
14. Devillez A, Dudzinski D (2007) Tool vibration detection with eddy current sensors in machining process and computation of stability lobes using fuzzy classifiers. Mech Syst Sig Process 21(1) : 441-456 (Pubitemid 44550080)
15. Wang M, Fei R (2001) On-line chatter detection and control in boring based on an electrorheological fluid. Mechatronics 11(7) : 779-792 (Pubitemid 32768160)
16. Liang M, Xu D (2006) A fuzzy self-learning approach to chatter control in milling. In: Proceeding of eighth IASTED international conference control and applications 2006, Montreal, QC, Canada
17. Cho DW, Eman KF (1988) Pattern recognition for on-line chatter detection. Mech Syst Signal Process 2(3) : 279-290
18. Wu SM, Stephenson DA (1984) Academic excellence in manufacturing engineering. Rob Comput Integr Manuf 1 (3-4) : 417-421
19. Taejun C (2003) On-line chatter detection using wavelet-based parameter estimation. J Manuf Sci Eng 125(1) : 21-28
20. Hino J, Okubo S, Yoshimura T (2006) Chatter prediction in end milling by FNN model with pruning. JSME Int J Ser C 49(3) : 742-749 (Pubitemid 46563872)
21. Li Q, Wong Y, Nee A (1997) Tool wear and chatter detection using the coherence function of two crossed accelerations. Int J Mach Tools Manuf 37(4) : 425-435 (Pubitemid 127412200)
22. Kuo RJ, Cohen PH (1999) Multi-sensor integration for on-line tool wear estimation through radial basis function networks and fuzzy neural network. Neural Netw 12(3) : 355-370 (Pubitemid 29148453)
23. Lin C, Lee C (1991) Neural-network-based fuzzy logic control and decision system. IEEE Trans Comput 40(12) : 1320-1336
24. Dutta RK, Paul S, Chattopadhyay AB (2000) Fuzzy controlled back propagation neural network for tool condition monitoring in face milling. Int J Prod Res 38(13) : 2989-3010 (Pubitemid 35401974)
25. Shibata T, Fukuda T, Kosuge T, Arai F (1992) Skill-based control by using fuzzy neural network for hierarchical intelligent control. In: Proceedings of IJCNN'92, Baltimore, MD, pp 81-86
26. Takagi T, Hayashi I (1991) NN-driven fuzzy reasoning. Int J Approximate Reasoning 5:191-212
27. Wang L, Mendel J (1992) Back-propagation fuzzy system as nonlinear dynamic system identifiers. In: IEEE international conference on fuzzy systems 1992, San Diego, CA, pp 1409-1418 (Pubitemid 23590900)
28. Tansel IN, Li M, Yapici A (2007) Evaluation of performance of the index based reasoning (IBR) at a simulated UAV. In: The 6th international workshop structural health monitoring 2007, Stanford University, Stanford, pp 264-268
29. Tansel IN, Li M, Yapici A, Yenilmez A (2007) Integrated systems health monitoring for autonomous space access vehicles and satellites. In: 3rd international conference on recent advances in space technologies (RAST) 2007, Istanbul, Turkey, pp 187-192
30. Sata T, Inamura T (1975) Development of method to predict and prevent chattering in metal cutting. Ann CIRP 24:309-314
31. Tsai SY, Eman KF, Wu SM (1983) Chatter suppression in turning. In: Proceedings of NAMR Conference, pp 399-402
32. Clancy BE, Shin YC A (2002) Comprehensive chatter prediction model for face turning operation including the tool wear effect. Int J Mach Tools Manuf 42(9) : 1035-1044 (Pubitemid 34771994)
33. Chiou RY, Richard Y, Steven Y (2000) Analysis of acoustic emission in chatter vibration with tool wear effect in turning. Int J Mach Tools Manuf 40(7) : 927-941 (Pubitemid 30566210)
34. Rao BC, Shin YC (1999) A comprehensive dynamic cutting force model for chatter prediction in turning. Int J Mach Tools Manuf 39(10) : 1631-1654
35. Gradisek J, Govekar E, Brabec I (1998) Time series analysis in metal cutting: chatter versus chatter-free cutting. Mech Syst Signal Process 12(6) : 839-854 (Pubitemid 128398631)
36. Chen SG, Ulsoy AG, Koren Y (1996) Computational stability analysis of chatter in turning. J Manuf Sci Eng 119:457-460
37. Tansel IN, Clarke B (1988) Use of a fast sequential algorithm for identification of end milling operations. In: Proc. of 3rd international conference on computer-aided production, 518-525
38. Dornfeld DA (1990) Neural network sensor fusion for tool condition monitoring. Ann CIRP 39(1) : 101-1051
39. Ko T, Cho D (1995) On-line monitoring of tool breakage in face milling using a self-organized neural network. J Manuf Syst 14(2) : 80-90
40. Fu L, Ling S, Tseng C (2007) On-line breakage monitoring of small drills with input impedance of driving motor. Mech Syst Sig Process 21(1) : 457-465 (Pubitemid 44528216)
41. Karali P, Surjya K, Bhattacharyya K (2007) Artificial neural network based prediction of drill flank wear from motor current signals. Appl Soft Comput 7(3) : 929-935 (Pubitemid 46551928)
42. Kuo RJ (2000) Multi-sensor integration for on-line tool wear estimation through artificial neural networks and fuzzy neural network. Eng Appl Artif Intell 13(3) : 249-261
43. Choi Y, Narayanaswami R, Chandra A (2004) Tool wear monitoring in ramp cuts in end milling using the wavelet transform. Int J Adv Manuf Technol 23(4) : 419-4228
44. Xiaoli L, Yingxue Y, Zhejun Y (1997) On-line tool condition monitoring system with wavelet fuzzy neural network. J Intell Manuf 8(4) : 271-276
45. Xiaoli L, Yingxue Y, Zhejun Y (1999) Tool wear detection with fuzzy classification and wavelet fuzzy neural network. Int J Mach Tools Manuf 39:1525-1538
46. Kasashima N (1995) On-line failure detection in face milling using discrete wavelet transform. Ann CIRP 44(1) : 483-487
47. Xiaoli L, Shiu T, Wang J (2000) Real-time tool condition monitoring using wavelet transforms and fuzzy techniques. IEEE Trans Syst Man Cybern, Part C Appl Rev 30(3) : 352-347
48. Souquet P, Gsib N, Deschamps M, Roget J, Tanguy JC (1987) Tool monitoring with acoustic emission-industrial results and future prospects. Ann CIRP 36(1) : 57-60 (Pubitemid 17591973)
49. Castejóna M, Alegrea E, Barreiroa J, Hernández LK (2007) Online tool wear monitoring using geometric descriptors from digital images. Int J Mach Tools Manuf 47 (12-13) : 1847-1853 (Pubitemid 47225020)
50. Castañeda EC (2003) On-line wear detection of milling tools using a displacement fiber optic sensor. J Appl Res Technol 1(2) : 164-174
51. Matsumura T, Murayama T, Usui E (2001) Tool wear monitoring in milling process with laser scan micrometer. In: 10th international conference on precision engineering (ICPE), Yokohama, Japan
52. Tsai SY, Eman KF, Wu SM (1983) Chatter suppression in turning. In: Proceedings of NAMR Conference, pp 399-402
53. Tlusty J, Ismail F (1983) Special aspects of chatter in milling. ASME J Vib Acoustics, Stress and Reliability 105:24-32
54. Ismail F, Bastami A (1986) Improving stability of slender end mills against chatter. Trans ASME J Eng Ind 108:264-268 (Pubitemid 17482383)
55. Cook NH, Subramanian K, Basile SA (1975) Survey of the state of the art tool wear sensing techniques material processing lab. Dept of M. E., MIT, Cambridge MA
56. Stockwell RG, Mansinha L, Lowe RP (1996) Localization of the complex spectrum: the S transform. IEEE Trans Signal Process 44(4) : 998-1001