Identification of the Chip Form Using Neural Network

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A major problem in automation of turning operations is the difficulty in obtaining a sufficient and reliable chip control. The chip should be detected in order to provide a optimum chip control for unmanned turning operation. Using the difference of energy radiated from the chip, chip Patterns are estimated using pyrometer. From the initial output from the pyrometer, chips are identified according to the backpropagation algorithm developed in the research. The learning system developed in this work can be applied in real-time control of turning process with minor modification in drive system.