Tool wear estimation from acoustic emissions: A model incorporating wear-rate

Proceedings - International Conference on Pattern Recognition

Volumn 16, Issue 1, 2002, Pages 492-495

  Varma, S ^a   Baras, J S ^a  

^a UNIVERSITY OF MARYLAND   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

HIDDEN MARKOV MODELS; MARKOV PROCESSES; PATTERN RECOGNITION; WEAR OF MATERIALS; ACOUSTIC EMISSIONS; ACOUSTIC WAVES; FEATURE EXTRACTION; VECTOR QUANTIZATION;

FEATURE VECTORS; TOOL WEAR; TOOL WEAR ESTIMATIONS; WEAR RATES;

ACOUSTIC EMISSION TESTING; PARAMETER ESTIMATION;

FEATURE VECTORS; HIDDEN MARKOV MODEL (HMM); WEAR-RATE INFORMATION;

EID: 33751571002     PISSN: 10514651     EISSN: None     Source Type: Journal    
DOI: 10.1109/ICPR.2002.1044773     Document Type: Article

References (12)

1. L. Atlas, M. Ostendorf, and G. Bernard. Hidden Markov models for monitoring machining tool-wear. Proc. of ICASSP, pages 3887-3890, 2000.
2. B. Berger, M. Rokni, and I. Minis. Complex dynamics in metal cutting. Quarterly of App. Math., 51:601-612, 1993.
3. M.-F. Chen, M. Natsuake, and Y. Ito. Preventive monitoring system for main spindle of machine tool - comparision of signal processing methods. In Proc. 27th Inter. MATADOR Conf., pages 179-186, April 1988.
4. R. Fischer. The case of multiple measurements in taxonomic problems. Annals of Eugenics, 7(11): 179-188, 1936.
5. S. Hong. Self-learning system for knowledge based diagnosis of drill condition in fully automatic manufacturing system. Proc. SPIE, 1707:195-206, 1992.
6. I. Inasaki and S. Yonetsu. In-process detection of cutting tool damage by acoustic emission measurement. In Proc. 22nd Int. Machine Tool Design and Res. Conf., pages 261-268, 1981.
7. P. Loughlin and G. Bernard. The applicability of time-frequency analysis to machine- and process-monitoring. In Proc. SAE Aerospace Manufacturing Technology and Exposition, pages 243-252, June 1997.
8. A. Noh and A. Kobayashi. Cutting tool failure detector. In Adv. in Hard Material Tool Tech.:Proc. Inter. Conf. on Hard Materials Tool Tech., pages 414-426, 1976.
9. L. Owsley, L. Atlas, and G. Bernard. Self-organizing feature maps and hidden Markov models for machine-tool monitoring. IEEE Trans. on Sig. Proc., 45(11):2787-2798, November 1997.
10. L. R. Rabiner. A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE, 77(2):257-286, February 1989.
11. S. Shumsheruddin and J. Lawrence. In-process prediction of milling tool wear. In Proc. 24th Int. Machine Tool Design and Res. Conf., pages 201-214, 1983.
12. S. Varma, J. Baras, and S. Shamma. Biologically inspired acoustic wear analysis. In Nonlinear Sig. and Image Proc. Conf., Baltimore, MD, June 2001.