Grinding acoustic emission features in relation to abrasive scratch characteristics

. On-line monitoring of grinding process has substantial advantages over traditional post-process quality control techniques for detecting malfunctions and reducing costs and inspection times. The selection of appropriate sensors and adequate signal processing methods are essential to establish optimum grinding control strategies with good prediction quality within acceptable response times. This paper assessed three signal-processing methods for grinding surface creation monitoring based on acoustic emission ( AE ) signals in abrasive scratch experiments. The AE signals are analysed in time domain (time direct analysis, TDA), frequency domain (fast Fourier transform, FFT) and in the combined time-frequency domain (singular spectrum analysis, SSA). The result showed that the FFT and SSA signal feature extraction methods gives better indication in correlation to the surface creation with different abrasive geometrical characteristics. For both sapphire and zirconia materials, the results of FFT method showed the best correlation between AE features and surface creation characteristics in scratching tests and the most significative information was in the frequency range between 0 and 200 kHz. This finding allows a great reduction in the sampling frequency of the signal, making this method the most suitable for real time applications. This work reveals that the AE signals processed with the adequate feature extraction method can present good correlation with the characteristics of interaction between abrasive and workpiece in scratching tests and can provide meaningful information for the on-line monitoring of surface creation in grinding processes.