Cutting Process Monitoring by Means of Acoustic Emission Method; Part I - New Approach of Acoustic Emission Sensor; Part II - Transformation of Acoustic Emission into Audible Sound

Abstract

Development of modern society is converging to a status where many human actions can be performed by machines. To achieve production without human intervention, machines require artificial receptors. Data gathering for processing and analysis of signals, together with determination of feedback reactions can be achieved by a suitable decision maker unit. A sensed value suited to this so-called intelligent sensing process would be the acoustic emission signal. In the case of intelligent cutting tools this would require miniature highly sensitive sensors integrated into the cutting tool body. Part I of this paper deals with the possibility of practical usage of the piezoelectric properties of copolymer foils for the acoustic emission sensor as a transducer of a mechanical surface wave into electrical signal. Part II of the paper deals with the most fundamental requirement for monitoring of cutting conditions during machining, i.e. excellent processing of measured data. Data obtained from machining process obtained by means of acoustic emission sensors, as discussed in the first part of this article, have high-frequency and continuous character of a white noise. These data are very difficult to process. New apparatus for transformation of acoustic emission into audible sound in the workplace is presented. The first stage of processing is by listening to transformed data it is subjectively possible to recognize differences in audible spectrum, corresponding to different states of the cutting tool. The second step is visualization of the differences via the fast Fourier transform (FFT) in the spectrum graphic chart.

Analysis of acoustic emission signals and surface integrity in the high-speed turning of Inconel 718

“…It represents the average behaviour of the dislocation velocity spectrum and is a frequency that divides the total power in the spectrum into two equal parts [25] as given by suitable for the detection of deformation activities in machining [30]. Therefore, a commercial piezoelectric AE sensor R15 with a response frequency range 50-200 kHz with a high sensitivity to noise characteristics supplied by Mistras, Physical Acoustic Corporation, was used in this work [4].…”