Tool-wear monitoring based on continuous hidden markov models

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3773 LNCS, Issue , 2005, Pages 880-890

  Vallejo Jr , Antonio G ^a   Nolazco Flores, Juan A ^a   Morales Menéndez, Rubén ^a   Enrique Sucar, L ^a   Rodríguez, Ciro A ^a  

^a SCHOOL OF ENGINEERING AND SCIENCES   (Mexico)

Author keywords

Hidden Markov Models; Remote Sensing Applications of Pattern Recognition; Signal Processing and Analysis; Tool wear monitoring

Indexed keywords

COMMINUTION; CONDITION MONITORING; MACHINING; MARKOV PROCESSES; SIGNAL PROCESSING; VIBRATION MEASUREMENT;

HIDDEN MARKOV MODELS; REMOTE SENSING APPLICATIONS OF PATTERN RECOGNITION; SIGNAL PROCESSING AND ANALYSIS; TOOL-WEAR MONITORING;

CUTTING TOOLS;

EID: 33745355754     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11578079_91     Document Type: Conference Paper

References (15)

1. O B Abouelatta and J Madl. Surface roughness prediction based on cutting parameters and tool vibrations in turning operations. Materials Processing Technology, (118):269-277, 2001.
2. L Atlas, M Ostendorf, and G D Bernard. Hidden markov models for monitoring machining tool-wear. IEEE, pages 3887-3890, 2000.
3. Jeff Bilmes. What hmms can do. Technical report.
4. Steven B. Davis and Paul Mermelstein. Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences. IEEE Transactions on Acoustic, Speech, and Signal Processing, 4(28):357-366, 1980.
5. R E Haber and A Alique. Intelligent process supervision for predicting tool wear in machining processes. Mechatronics, (13):825-849, 2003.
6. R E Haber, J E Jiménez, C R Peres, and J R Alique. An investigation of tool-wear monitoring in a high-spped machining process. Sensors and Actuators A, (116):539-545, 2004.
7. Y Koren, U Heisel, F Jovane, T Moriwaki, G Pritschow, G Ulsoy, and H Van Brussel. Reconfigurable manufacturing systems. Annals of the CIRP, 48(2):527-540, 1999.
8. K Y Lee, M C Kang, Y H Jeong, D W Lee, and J S Kim. Simulation of surface roughness and profile in high-speed and milling. Materials Processing Technology, (113):410-415, 2001.
9. S Y Liang, R L Hecker, and R G Landers. Machining process monitoring and control: The state-of-the-art. ASME International Mechanical Engenieering Congress and Exposition, pages 1-12, 2002.
10. L M D Owsley, L E Atlas, and G D Bernard'. Self-organizing feature maps and hidden markov models for machine-tool monitoring. IEEE Transactions on Signal Processing, 45(11):2787-2798, 1997.
11. L R Rabiner. A tutorial on hidden markov models and selected applications in speech recognition. Proceedings of the IEEE, 77(2):257-286, 1989.
12. L R Rabiner and B H Juang. Fundamentals of speech recognition. Prentice-Hall, New-Jersey, 1993.
13. H Saglam and A Unuvar. Tool condition monitoring in milling based on cutting forces by a neural network. International Journal of Production Research, 41(7):1519-1532, 2003.
14. Y H Tsai, J C Chen, and S J Lou. An in-process surface recognition system based on neural networks in end milling cutting operations. Machine Tools and Manufacture, (39):583-605, 1999.
15. G M Zhang and C Lin. A hidden markov model approach to the study of random tool motion during machining. Technical report.