Tool Wear Prediction Based on Fuzzy Cluster Analysis

Hong Tao Chen; Deng Wan Li; Pan Fu

doi:10.4028/www.scientific.net/AMR.490-495.1589

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 490-495Tool Wear Prediction Based on Fuzzy Cluster...

Tool Wear Prediction Based on Fuzzy Cluster Analysis

Abstract:

There are several stages of tool wear in turning process. The theory and the algorithm of the fuzzy cluster analysis (FCA) are applied in the research of the CNC turning tool wear State.We collect of the force signals and vibration signals at each stage. Using wavelet filtering and power spectrum methods, typical parameters changes are detected. We extract the signal feature for fuzzy clustering. Experimental results show that the tool wear prediction is achieved in turning by using this pattern recognition method.

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Periodical:

Advanced Materials Research (Volumes 490-495)

Pages:

1589-1594

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.490-495.1589

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Online since:

March 2012

Authors:

Hong Tao Chen, Deng Wan Li, Pan Fu

Keywords:

Force, Fuzzy Cluster Analysis, Prediction, Tool Wear

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References

[1] Wang, H.L., Ma, C.X., Shao, H.: The tool wear and breakage monitoring in turning using neural network. J. Shanghai Jiaotong Univ. 40, 2057-2062 (2006).

Google Scholar

[2] Choi, D., Kwon, W.T., Chu, C.N.: Real-Time Monitoring of Tool Fracture in Turning Using Sensor Fusion. Int. J. Advanced Manufacturing Tech. 15, 305-310(1988).

DOI: 10.1007/s001700050071

Google Scholar

[3] Zadeh, L.A.: Fuzzy Sets. Inform. Contr. 8, 338-353 (1965).

Google Scholar

[4] Dimla, S., Dimla, E.: Sensor signals for tool-wear monitoring in metal cutting operations-A review of methods. Int. J. Mach. Tools Manuf. 40, 1073-1098 (2000).

DOI: 10.1016/s0890-6955(99)00122-4

Google Scholar