A Data Dependent Systems Strategy of On-Line Tool Wear Sensing

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Abstract
An indirect method of tool wear sensing and critical wear detection is suggested. It is based on the Data Dependent Systems (DDS) modeling of vibrations from an accelerometer mounted on the tool holder at a safe distance away from the cutting process. The DDS provides an estimate of the tool acceleration component, sensitive to wear alone, at the natural frequency of the tool confirmed by impulse response testing. This acceleration decreases at the beginning, approaches a minimum at the critical wear, and increases again, much the same way as a rate of wear curve. The trend remains unchanged under different cutting conditions, although the actual values change. Based on this finding, an on-line tool wear sensing strategy is proposed, verified by a confirmation experiment and supplemented by a block diagram of microprocessor implementation.

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