翻转(web设计)
移植
汽车工程
理论(学习稳定性)
工程类
结构工程
环境科学
模拟
数学
计算机科学
农学
播种
机器学习
万维网
生物
作者
Milon Chowdhury,Mohammod Ali,Eliezel Habineza,Md Nasim Reza,Md Shaha Nur Kabir,Seung-Jin Lim,Il-Su Choi,Sun–Ok Chung
出处
期刊:Agriculture
[Multidisciplinary Digital Publishing Institute]
日期:2023-03-10
卷期号:13 (3): 652-652
被引量:3
标识
DOI:10.3390/agriculture13030652
摘要
The rollover tendency of upland farm machinery needs to be carefully considered because upland crop fields are typically irregular, and accidents frequently result in injuries and even death to the operators. In this study, the rollover characteristics of an underdeveloped 12 kW automatic onion transplanter were determined theoretically and evaluated through simulation and validation tests considering the mounting position of the transplanting unit and load conditions. The center of gravity (CG) coordinates for different mass distributions, and static and dynamic rollover angles were calculated theoretically. Simulation and validation tests were conducted to assess the static rollover angle under different mounting positions of the transplanting unit and load conditions of the onion transplanter. The dynamic rollover tendency was evaluated by operating the onion transplanter on different surfaces and at different speeds. According to the physical properties and mass of the onion transplanter, the theoretical rollover angle was 34.5°, and the coordinates of the CG gradually moved back to the rear wheel axle after attaching the transplanting part and under upward riding conditions. The average simulated rollover angle was 43.9°. A turning difference of 4.5° was observed between the right and left sides, where a 3° angle difference occurred due to the load variation. During the dynamic stability test, angle variations of 2~4° and 3~6° were recorded for both high and low driving speeds in the vehicle platform and transplanting unit, respectively. The overturning angles also satisfied the ISO standard. This study provides helpful information for ensuring the safety of upland crop machinery operating under rough and sloped field conditions.
科研通智能强力驱动
Strongly Powered by AbleSci AI