Detection and classification for faults in drilling process using vibration analysis

2014 International Conference on Prognostics and Health Management, PHM 2014

Volumn , Issue , 2015, Pages

  Kumar, Adarsh ^a   Ramkumar, J ^a   Verma, Nishchal K ^a   Dixit, Sonal ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY KANPUR   (India)

Author keywords

ANN; Bayes classifier; Drill; Fault diagnosis; SVM

Indexed keywords

CONDITION MONITORING; DRILLING; FAILURE ANALYSIS; FAULT DETECTION; FLEXIBLE MANUFACTURING SYSTEMS; INFILL DRILLING; MACHINING; NEURAL NETWORKS; SUPPORT VECTOR MACHINES;

AUTOMATIC DRILLING; BAYES CLASSIFIER; DRILLING PARAMETERS; DRILLING PROCESS; FAULT CLASSIFICATION; MACHINING PROCESS; VIBRATION SIGNAL; WORK MATERIAL;

VIBRATION ANALYSIS;

EID: 84929590770     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPHM.2014.7036393     Document Type: Conference Paper

References (23)

1. T. I. EL-Wardany, D Gao, M. A. Elbestawi; Tool condition monitoring in drilling using vibration signature analysis, Int. J. Maeh. Tools Manufaet. Vol. 36, No. 6, pp. 687-711, 1996
2. Wakefield, B. D., "Holes: That's Where Your Money Goes", Iron Age, vol. 208, no. 4, pp. 43-46, July 22, 1971.
3. Schivley Jr, George P. "Automatic control of drilling system." U. S. Patent No. 5, 449, 047. 12 Sep. 1995.
4. Kosmowski, Wojciech. "Method and apparatus for high speed, high precision drilling and machining." U. S. Patent No. 4, 088, 417. 9 May 1978.
5. Hill, Ricky C. "Hand-held drill with self-advancing bit." U. S. Patent No. 4, 752, 161. 21 Jun. 1988.
6. D. F. Galloway "Some Experiments on the influence of various factors in Drill Performance" Transactions of ASME, vol 79, no. 2, pp no. 191, 1957.
7. Moore, T., and Z. Rief. "SME Paper# M584-908." In Conference in Sensor Technology for Untended Manufacturing, Schaumburg, Chicago, Illinois, USA. 1984.
8. Jantunen, Erkki. "A summary of methods applied to tool condition monitoring in drilling." International Journal of Machine Tools and Manufacture vol 42, issue no. 9, pp no. 997-1010, July 2002
9. Byrne, G., D. Dornfeld, I. Inasaki, G. Ketteler, W. König, and R. Teti. "Tool condition monitoring (TCM)-the status of research and industrial application. " CIRP Annals-Manufacturing Technology 44. 2(1995):541-567.
10. K. Subramanian, N. H. Cook, "Sensing of drill wear and prediction of drill life (I) ", Journal of Engineering for Industry, Transactions of the ASME, Vol. 99, no. 2, pp. 295-301, 1977.
11. Snr, Dimla, and E. Dimla. "Sensor signals for tool-wear monitoring in metal cutting operations-a review of methods." International Journal of Machine Tools and Manufacture, vol. 40, no. 8, pp no. 1073-1098, 2000.
12. A. D. Dornfeld and M. F. DeVries, "Drill wear and fracture monitoring using acoustic emission", Presented at CIRP STC "C" meeting, Paris (1992).
13. A. Mahfouz, Issam. "Drilling wear detection and classification using vibration signals and artificial neural network", International Journal of Machine Tools & Manufacture, vol. 43, pp no. 707-720, 2003.
14. Kotsiantis, Sotiris B. "Supervised machine learning: a review of classification techniques." Informatica (03505596) 31. 3 (2007).
15. Armarego, E. J. A., and C. Y. Cheng. "Drilling with flat rake face and conventional twist drills-I. theoretical investigation. " International Journal of Machine Tool Design and Research, vol 12, no. 1, pp no. 17-35, 1972.
16. Huseyin M. Ertunc, Kenneth, A. Loparo, Hasan Ocak, "Tool wear condition monitoring in drilling operations using hidden Markov models (HMMs) " Published in International Journal of Machine Tools & Manufacture, vol. 41, pp no. 1363-1384, 2001
17. N. K. Verma., S. Sarkar, S. Dixit, R. K. Sevakula, and A. Salour. "Android app for intelligent CBM." International Symposium on Industrial Electronics (ISIE), pp. 1-6. IEEE, 2013.
18. F. Song, Z. Guo and D. Mei, "Feature Selection Using Principal Component Analysis", System Science, Engineering Design and Manufacturing Informatization (ICSEM), UiTM Shah Alam, Selangor Malaysia, vol. 1, pp. 27-30, Nov. 2010
19. R. O. Duda, P. E. Hart and D. G. Stork, "Pattern Classification", 2nd ed. John Wiley & Sons, 2006.
20. Devroye, Luc. "A probabilistic theory of pattern recognition", vol. 31. springer, 1996.
21. Cortes, Corinna, and Vladimir Vapnik. "Support vector machine." Machine learning, vol 20, no. 3, pp no. 273-297, 1995.
22. Chih-Chung Chang and Chih-Jen Lin. LIBSVM: a library for support vector machines. 2001. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm
23. Staelin, Carl. "Parameter selection for support vector machines." Hewlett-Packard Company, Tech. Rep. HPL-2002-354R1 (2003).