Graduation Project

We worked on a design and implementation of an intelligent monitoring system for Industrial grinding processes. The monitoring system analyzes the data from machine implemented Acoustic Emission sensors. Gathered AE signas are analyzed in the frequency domain and compared with an ideal (correct) process which is already stored in our Database. Using a coherence estimation between the ideal data and the new grinding process we estimated whether the current grinding operation is normal or abnormal (failed).