WANG Jun-ping, JING Zhong-liang, WANG An. TOOL WEAR ESTIMATION BY SOFT-SENSING TECHNOLOGY BASED ON STOCHASTIC FUZZY NEURAL NETWORK[J]. INFORMATION AND CONTROL, 2002, 31(6): 534-537.
Citation: WANG Jun-ping, JING Zhong-liang, WANG An. TOOL WEAR ESTIMATION BY SOFT-SENSING TECHNOLOGY BASED ON STOCHASTIC FUZZY NEURAL NETWORK[J]. INFORMATION AND CONTROL, 2002, 31(6): 534-537.

TOOL WEAR ESTIMATION BY SOFT-SENSING TECHNOLOGY BASED ON STOCHASTIC FUZZY NEURAL NETWORK

  • Tool wear measurement would be a great significance for improving the automation, accuracy and intellegence of the manufacturing process. Through measuring the electric current signal, the soft-sensing model used for tool wear estimation based on stochastic fuzzy neural network(SFNN) is presented in this paper. In the model, the cutting parameters are used to adjust several parameters of SFNN on line, so the influence on the tool wear estimation by the relation of the electric current signal and the cutting parameters is eliminated and the model is dynamic. The experimental results have shown the effectiveness of this method.
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