Abstract
Efficient production machining needs heavier chip loads to be used, because of which, probability of damage (to tool, workpiece or machine) has increased. It is iirportant, particularly for untended manufacturing, to detect inciepient damage, before it can accumulate and lead to catastrophic consequences. Adaptive control and condition monitoring systems have been proposed for detecting chip congestion, tool wear and breakage.
Many signals like tool forces, tool tip temperature, torque, vibrations, acoustic emission (AE), etc., have been used in condition monitoring of machining.Of these, vibrations and AE signals look prospective because of the ease of measurement and ruggedness and sensitivity of sensor.
Cofrparitive analysis of the results obtained by researchers, in monitoring the machining process, using these two signals, indicates AE to be more sensitive to the actual cutting process. Moreover, AE signals seem to be affected by process variables only and are not dependent on the structural rigidity of machine tool, as do vibration signals. Hence, real-time determination of structural modes is needed for an effective vibration based monitoring. Studies with vibration and AE signals, are on, at present, to investigate the effect of process variables and develop efficient signal processing methodologies.
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Raghunandan, M., Krishnamurthy, R. (1990). Condition monitoring systems for machining applications. In: Rao, R.B.K.N., Au, J., Griffiths, B. (eds) Condition Monitoring and Diagnostic Engineering Management. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-0431-6_9
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DOI: https://doi.org/10.1007/978-94-009-0431-6_9
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