Analysis of the tap test for vacuum utilizing Digital Signal Processing (DSP) - Guantes, Arnel C.
The tap test for vacuum was analyzed utilizing Digital Signal Processing (DSP). The variables that were investigated for possibly affecting vacuum and frequency of tap-generated sounds are: sealing temperature, headspace, type and concentration of model food system, and can size. Statistical treatments (i.e., simple linear regression and analysis of variance) and visual examination of graphs were employed in data analysis. Results revealed that, within a particular sealing temperature range, the frequency of tap-generated sound increases with increasing vacuum, and that, at 99% level of confidence, vacuum may be predicted through the frequency. Moreover, DSP may be utilized for vacuum detection on a "go or no go" basis. It was also found that a difference of 1/4 inch headspace is not significant to affect vacuum and frequency readings. On the other hand, the concentration of model food system was found to be capable of significantly affecting vacuum, but not necessarily frequency. Lastly, big cans were found to produce higher vacuum and frequency than small cans. These results indicate that it is promising to explore the utilization of Artificial Intelligence (AI) for a local fabrication of a nondestructive digital vacuum detector.