Comprehensive analysis of ultrasound-assisted electrohydrodynamic technology on drying characteristics, quality attributes, and volatile profiles of yam (Dioscorea opposita).

In this study, the systematic investigation focused on how varying power levels of ultrasonic (US) pretreatment, when integrated with electrohydrodynamic (EHD) drying, influence the physicochemical properties of yam. Yam samples were subjected to ultrasonic pretreatment at 30 °C for 30 min using power levels of 0 W (Control), 150 W, 180 W, 210 W, 240 W, and 270 W, respectively, followed by drying in an EHD system. During the drying process, a range of metrics were measured, including moisture content, average drying rate, color change, as well as rehydration capacity.

Partial Discharge Signal Pattern Recognition of Composite Insulation Defects in Cross-Linked Polyethylene Cables.

To investigate the pattern recognition of complex defect types in XLPE (cross-linked polyethylene) cable partial discharges and analyze the effectiveness of identifying partial discharge signal patterns, this study employs the variational mode decomposition (VMD) algorithm alongside entropy theories such as power spectrum entropy, fuzzy entropy, and permutation entropy for feature extraction from partial discharge signals of composite insulation defects. The mean power spectrum entropy (PS), mean fuzzy entropy (FU), mean permutation entropy (PE), as well as the permutation entropy values of IMF2 and IMF13 (Pe) are selected as the characteristic quantities for four categories of partial discharge signals associated with composite defects. Six hundred samples are selected from the partial discharge signals of each type of compound defect, amounting to a total of 2400 samples for the four types of compound defects combined.