Research on the Machining Status Monitoring of CNC Machine Tools Based on Artificial Neural Network

Jin Hua Li; Yong Xian Liu; Deng Li Yi; De Qiang Zhang

doi:10.4028/www.scientific.net/AMR.338.685

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 338Research on the Machining Status Monitoring of CNC...

Research on the Machining Status Monitoring of CNC Machine Tools Based on Artificial Neural Network

Abstract:

Vibration acceleration and AE signal were analyzed in the time domain, and they sampled the mean value and mean value of energy. The two values were used as the basis of the state recognition and tool wear prediction. In Labview, the neural network model was established, and it had three-layer structure. the nonlinear mapping was realized between machining state and characteristic quantity. The outcome could show that the machining state was monitored by the neural network training.

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Periodical:

Advanced Materials Research (Volume 338)

Pages:

685-688

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.338.685

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Online since:

September 2011

Authors:

Jin Hua Li, Yong Xian Liu, Deng Li Yi, De Qiang Zhang

Keywords:

Artificial Neural Network (ANN), In-Line Prediction, State Recognition, Tool

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References

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DOI: 10.1006/mssp.2001.1460

Google Scholar