Inicio  /  Applied Sciences  /  Vol: 12 Par: 24 (2022)  /  Artículo
ARTÍCULO
TITULO

Research on the Trajectory and Operational Performance of Wheel Loader Automatic Shoveling

Yanhui Chen    
Heng Jiang    
Gang Shi and Te Zheng    

Resumen

In the automatic shoveling operation of wheel loaders, the shovel trajectory has a significant influence on the operation?s performance. In order to obtain a suitable shovel trajectory and optimize the automatic shovel performance of the loader, we developed a test platform for the operational performance of loaders. Nine parallel shoveling trajectories of different depths were designed according to the coordination shoveling method. The formula for calculating the operational performance is established. The automatic shoveling test is performed according to the designed trajectory to obtain the real-time shoveling parameters, which are then combined with the calculation formula to calculate the operating parameters of the loader. Finally, the actual range of operational performance parameters is calculated by the normal distribution. The test results show that the trajectory with a shovel depth of 400 mm is the optimal trajectory. It was also verified by comparing manually controlled shoveling with it. With only a 1% difference in the full bucket rate, the operation time of automatic shoveling was 15.3% less than manually controlled shoveling, fuel consumption was 4.7% less, the energy consumption of practical work performed was 10.7% more, and maximum operation resistance was 20.5% lower. Therefore, the operational performance of the loader following this trajectory for shoveling meets the actual requirements.

 Artículos similares

       
 
Pengfei Ning, Dianjun Zhang, Xuefeng Zhang, Jianhui Zhang, Yulong Liu, Xiaoyi Jiang and Yansheng Zhang    
The Array for Real-time Geostrophic Oceanography (Argo) program provides valuable data for maritime research and rescue operations. This paper is based on Argo historical and satellite observations, and inverted sea surface and submarine drift trajectori... ver más

 
Jizhao Wang, Yunyi Liang, Jinjun Tang and Zhizhou Wu    
This research contributes to the development of a technological method to obtain highly accurate vehicle trajectory data. The reconstructed trajectory data play a key role in traffic state prediction, traffic management and the decision making of autonom... ver más
Revista: Applied Sciences

 
Liu Han and Peng Liu    
In an effort to enhance the efficiency and safety of open-pit mines, this study explores the optimization of end slope road parameters and slope structures, specifically focusing on unmanned driving lanes. A significant aspect of the study is the develop... ver más
Revista: Applied Sciences

 
Dimitrios Kaklis, Ioannis Kontopoulos, Iraklis Varlamis, Ioannis Z. Emiris and Takis Varelas    
Trajectory data holds pivotal importance in the shipping industry and transcend their significance in various domains, including transportation, health care, tourism, surveillance, and security. In the maritime domain, improved predictions for estimated ... ver más

 
Atefe Sedaghat, Homayoon Arbabkhah, Masood Jafari Kang and Maryam Hamidi    
This research introduces an online system for monitoring maritime traffic, aimed at tracking vessels in water routes and predicting their subsequent locations in real time. The proposed framework utilizes an Extract, Transform, and Load (ETL) pipeline to... ver más