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condition monitoring of grinding machine tools

condition monitoring of grinding machine tools

Good condition and dull condition of the grinding wheel is predicted using machine-learning techniques such as decision tree, artificial neural network, and support vector machine. Results indicate that there is a strong correlation exiting between the acoustic emission features and the surface roughness produced by the grinding process. Support vector machine trained with cubic kernel is appears to be predicting the grindingtoolcondition withgreater accuracy comparing with decision tree...

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