Detection of Discharge Activities During Pulsed-Electric-Field Food Processing

This paper presents a wavelet-based technique for monitoring food treatment process using pulsed electric field (PEF). The changes in the features of the applied pulses are extracted and used to monitor transient changes like internal arcing inside the processed food and/or the external arcing in the high-voltage pulse power supply. Compared to the classical fast Fourier transform, direct application of wavelet transform can be used effectively to predict the closeness of an arcing event and distinguish between internal and external arcing activities. This technique can be used as an integral part to monitor the quality control of the PEF process.