Machining Process Monitoring System Using Audible Energy Sound Sensors

This work reports on the approach for the development of a machining process monitoring system based on audible sound sensors. Audible sound energy appears as one of the most practical techniques since it can serve to replace the traditional ability of the operator, based on his experience and senses (mainly vision and hearing), to determine the process state and react adequately to any machine performance decay. This technique has been attempted for decision making on machining process conditions but it has not been extensively studied yet for applications in industrial process monitoring. The main critical issues related to the employment of this technology in industry are the need to protect the sensor from the hazardous machining environment (cutting fluids and metal chips) and the environment noise (from adjacent machines, motors, conveyors or other processes) that may contaminate the relevant signals during machining. The principal benefits of audible sound sensors for machining process monitoring are associated with the nature of the sensors employed in the acquisition of the signals. These are, in general, easy to mount on the machine tool, in particular near the machining point, with little or no interference with the machine, the tool, the workpiece or the chip formation. Besides, these sensors, basically microphones, are easy to use in combination with standard phonometers or spectrum analysers. These characteristics of audible sound sensors make the realization of the monitoring procedure quite straightforward. In addition, their maintenance is simple since they only require a careful handling to avoid being hit or damaged. Accordingly, they usually provide for a favourable cost/benefit ratio. The key novelties of the approach proposed in this work are, on the one hand, the application of a systematic methodology to set up the cutting trials allowing for a better comparison with other similar experimental works and, as a result, the advance in the standardization for the development of such systems. On the other hand, the independent signal analysis of the noise generated by the machine used for the cutting trials and by the working environment allows to filter this noise out of the signals obtained during the actual material processing. Lastly, the possibility has been verified to apply the results of this approach for the development of process monitoring procedures based on sensors of a different type, in particular acoustic emission sensors, where the stress waves produced within the work material do not travel through air but only in the work material itself. The combined application of audible sound energy sensors and acoustic emission sensors could allow for the acquisition of more exhaustive information from both low frequency (audible sound) and high frequency (acoustic emission) acoustic signal analysis. This would decidedly contribute to the realization of the concept of sensor fusion technology for process monitoring