A method for tool condition monitoring based on sensor fusion-Reference-Cited by-同舟云学术

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A method for tool condition monitoring based on sensor fusion

Published:2015-06-19 Issue:5 Volume:26 Page:1011-1026
ISSN:0956-5515
Container-title:Journal of Intelligent Manufacturing
language:en
Short-container-title:J Intell Manuf

Author:

Zhang Kai-feng,Yuan Hui-qun,Nie Peng

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Industrial and Manufacturing Engineering,Software

Link

http://link.springer.com/content/pdf/10.1007/s10845-015-1112-y.pdf

Reference24 articles.

1. Agustin, G., Rodolfo, H., Rauldel, T., Pastora, V., & Andres, B. (2012). Tool wear monitoring using neuro-fuzzy techniques: A comparative study in a turning process. Journal of Intelligent Manufacturing, 23, 869–882.

2. Ai, C. S., Sun, Y. J., & He, G. W. (2012). The milling tool wear monitoring using the acoustic spectrum. International Journal of Advanced Manufacturing Technology, 61, 457–463.

3. Bahador, K., Alaa, K., Fakhreddine, O. K., & Saiedeh, N. R. (2013). Multisensor data fusion: A review of the state-of-the-art. Information Fusion, 14, 28–44.

4. Bhaskaran, J., Murugan, M., Balashanmugam, N., & Chellamalai, M. (2012). Monitoring of hard turning using acoustic emission signal. Journal of Mechanical Science and Technology, 26(2), 609–615.

5. Chen, J. C. (2000). An effective fuzzy-nets training scheme for monitoring tool breakage. Journal of Intelligent Manufacturing, 11, 85–101.

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