The purpose of this study was to investigate and compare the impact of engine load on the emission characteristics of excavator engines, with the aim of improving the method for calculating the emission inventory of construction machinery. The engine load in excavators is directly correlated with the operational workload, and variations in the load factor (LF) can significantly influence the emission inventory. Thus, on-board diagnostic (OBD) data from an excavator at a construction site were systematically collected to measure engine output and emissions. The results revealed discernible differences in emissions based on engine load, even when the average excavator engine performance remained constant. This highlights the significant influence of the type and characteristics of the work being carried out on emission characteristics. Making realistic adjustments to the LF used in emission calculation formulas emerges as a crucial strategy for environmental improvement. Moreover, the analysis of the effects of engine load on emissions from excavators provides valuable insights for enhancing environmental protection measures.

In this paper, the selection of a reliable accelerated life test code for a 2-ton forklift was accomplished by choosing the driving resistance coefficient failure-free test time based on a 10,000-hour B₁₀ life. The overall life and average equivalent load of the vehicle were then calculated based on actual driving test conditions using the selected driving resistance coefficient. The gear train's accelerated life test code was selected by adjusting the equivalent load to a torque and rotation speed that did not exceed 125%(about 75HP) of the vehicle rated power. The safety of the test standards was validated by conducting an actual accelerated life test utilizing the proposed test method in this study and comparing the test result with the corresponding theoretical value. It is anticipated that the reliability of the accelerated life test in this paper will be enhanced, by incorporating actual driving performance data collected directly from the forklift and adjusting the conditions used in developing the accelerated life test code.

The aim of this study was to measure and evaluate the exhaust emission factors of agricultural tractors. Engine characteristics and three exhaust emissions (CO, NO_x, PM) were collected under actual agricultural operating conditions. Experiments were performed on idling, driving, plow tillage, and rotary tillage. The load factor (LF) was calculated using the collected engine data, and the emission factor was analyzed using the LF and exhaust emissions. The engine characteristics and exhaust emissions were significantly different for each working condition, and in particular, the LF was significantly different from the currently applied 0.48 LF. The data distribution of exhaust emissions was different depending on the engine speed. In some conditions, the emission factor was higher than the exhaust emission standards. However, since most emission limit standards are values calculated using an engine dynamometer, even if the emission factor measured under actual working conditions is higher, it cannot be regarded as wrong. It is expected that the results of this study can be used for the inventory construction of a calculation for domestic agricultural machinery emissions in the future.

In this study, we conducted a research on optimizing the spraying performance of agricultural drones and predicted the spraying performance in various flight conditions using the multi-layer perceptron (MLP). Data was collected using a test device for pesticide spraying performance according to the water sensitive paper (WSP) evaluation. MLP training involved supervised learning to achieve a coefficient of variation (CV), which indicates the degree of uniform spraying. The performance evaluation was conducted using R-squared (R²), the test samples showed an R² of 0.80. The results of this study showed that drone spraying performance can be predicted under various flight environments. In addition, the correlation analysis between flight conditions and predicted spraying performance will be useful for further research on optimizing the spraying performance of agricultural drones.

Radish and Chinese cabbage are the most produced and consumed vegetables in Korea. The mechanization of harvesting operations is necessary to minimize the need for manual labor. This study to develop and evaluate the performance of a multi-purpose driving platform that can apply modular Radish and Chinese cabbage harvesting devices. The multi-purpose driving platform consisted of driving, device control, engine, hydraulic, harvesting, conveying, and loading part. Radish and Chinese cabbage harvesting conducted using the multi-purpose driving platform each harvesting module. The performance of the multi-purpose driving platform was evaluated the field efficiency and loss rate. The total Radish harvesting operation time 34.3 min., including 28.8 min., of harvesting time, 1.9 min., of turning time, and 3.6 min., of replacement time of bulk bag. During Radish harvesting, the field efficiency and average loss rate of the multi-purpose driving platform were 2.0 hr/10a and 3.1 %. Chinese cabbage harvesting operation 49.3 min., including 26.6 min., of harvesting time, 4.6 min., of turning time, and 18.1 min., of replacement time of bulk bag. During Chinese cabbage harvesting, the field efficiency and average loss rate of the multi-purpose driving platform 2.1 hr/10a and 0.1 %. Performance evaluation of the multi-purpose driving platform that harvesting work was possible by installing Radish and Chinese cabbage harvest modules. Performance analysis through harvest performance evaluation in various Radish and Chinese cabbage cultivation environments is necessary.

In this study, the safety of fastening device for the agricultural by-product collector was evaluated according to the driving ground conditions by deriving the stress, static safety factor, and fatigue life using dynamic simulation. A 3D modeling of agricultural by-product collector was carried out, and simulation model was developed by applying the material properties. As a result of dynamic simulation, the magnitude of the maximum stress generated in the fastening device was the highest when driving on the flat off-road, followed by sloped pave-road and flat pave-road. Static safety factor and fatigue life were the highest when driving on the flat pave-road, followed by sloped pave-road and flat off-road. The safety of fastening device was confirmed that static safety factor was more than 1.0 and service life exceeded 9 years in all driving ground conditions.