Input current of driving motor has been employed with success as monitoring signature for tool breakage and wear detection in manufacturing processes for more than a decade. In micro-drilling, however, the accuracy of current signature downgrades significantly owing to the disturbances often seen in electrical power supply. This paper reports the investigation results on the effectiveness of using the input impedance of the spindle motor as monitoring signature for detecting drill breakage in micro-drilling. As input impedance is an inherent property of a dynamic system and independent upon the system input such as voltage or current fluctuations and thus avoids the difficulties faced by the methods using current signature. Experimental results show that impedance signature reflects torque variations well and indicates health conditions of drills properly during micro-drilling processes. When associated with an artificial neural network to recognise its waveform, impedance signature is capable of identifying drill breakages promptly and accurately.
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