• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.642-648
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• 2019

This paper presents a fast back-type transfer device for snack food processing that uses the inertia of transferred material. A conventional conveying system is a drive system that uses a belt conveyor and mechanical crank, which generate noise and vibration and cause environmental pollution. Vibration and noise are reduced in the proposed fast back feeding device by using a counterweight. The crank drive unit was replaced with a linear servomotor, and an equilibrium device was designed to balance the force due to acceleration. This makes it is possible to adjust the forward and backward speed and acceleration through PLC control. A vibration damper device offsets the vibration force of the periodic shock form. The main cause of the vibration was identified through vibration analysis, and reduction measures were established. We verified the effectiveness of the vibration by making a prototype and performing about 10 vibration tests. Because no mechanical transducer is needed, energy loss, noise, and vibration do not occur, and the operating speed is not limited.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.164-178
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• 2022

Uncertainties in weather forecasts would affect the reliability of yield prediction using crop models. The objective of this study was to compare uncertainty in crop yield prediction caused by the use of the weather forecast data. Daily weather data were produced at 10 km spatial resolution using W eather Research and Forecasting (W RF) model. The nearest neighbor method was used to downscale these data at the resolution of 5 km (W RF5K). Parameter-elevation Regressions on Independent Slopes Model (PRISM) was also applied to the WRF data to produce the weather data at the same resolution. W RF5K and PRISM data were used as inputs to the CROPGRO-SOYBEAN model to predict crop yield. The uncertainties of the gridded data were analyzed using cumulative growing degree days (CGDD) and cumulative solar radiation (CSRAD) during the soybean growing seasons for the crop of interest. The degree of agreement (DOA) statistics including structural similarity index were determined for the crop model outputs. Our results indicated that the DOA statistics for CGDD were correlated with that for the maturity dates predicted using WRF5K and PRISM data. Yield forecasts had small values of the DOA statistics when large spatial disagreement occured between maturity dates predicted using WRF5K and PRISM. These results suggest that the spatial uncertainties in temperature data would affect the reliability of the phenology and, as a result, yield predictions at a greater degree than those in solar radiation data. This merits further studies to assess the uncertainties of crop yield forecasts using a wide range of crop calendars.