The sound a machine makes can be used to generate a profile of the machine. By analyzing the properties of the audio signal, it is possible to determine the expected behavior of the equipment, allowin..
The sound a machine makes can be used to generate a profile of the machine. By analyzing the properties of the audio signal, it is possible to determine the expected behavior of the equipment, allowing for anomalies to be identified and diagnosed before they cause significant problems. By constantly monitoring the performance of assets, it is possible for maintenance to be proactive rather than reactive. As a preliminary investigation into the usage of spectral descriptors to predict mechanical failure, multiple pieces of equipment in the John Mica Engineering and Aerospace Innovation Complex were recorded. Trends were determined, and profiles of these machines were constructed. More than 24 hours of audio were recorded and analyzed, taken throughout the operation cycles of the machines. The da Vinci Super by XYZPrinting, a large format 3D printer, was monitored extensively; a failure to correctly print a part was successfully identified and predicted through audio signal processing before a visual inspection of the part confirmed the results of the algorithm.
