Unveiling the Depths: A Comprehensive Exploration of Excavator Classifications
Keywords:
excavators, earthmoving endeavors, specific tasks and environments, excavator classificationsAbstract
Excavators, integral to modern construction and earthmoving endeavors, encompass a diverse array of machines tailored for specific tasks and environments. This article provides a concise overview of excavator classifications, emphasizing their varied designs and functionalities. Categorizations include crawler excavators, distinguished by tracked mobility for challenging terrains, and wheeled excavators, characterized by wheel-mounted agility on smoother surfaces. Mini excavators, compact and versatile, find applications in smaller-scale projects, while amphibious excavators navigate aquatic landscapes with specialized pontoons. Long reach excavators extend their arms for heightened reach in tasks such as dredging, while dragline excavators leverage cable systems for extensive mining operations. Backhoe loaders amalgamate backhoe and loader functions, catering to versatile construction needs. Suction excavators deploy vacuum systems for precision in sensitive environments, contrasting with the robust capabilities of hydraulic shovels, predominant in large-scale excavations. Skid steer excavators, compact and maneuverable, thrive in confined spaces, while trenchers specialize in efficient trench digging for utility installations. The emergence of robotic excavators introduces remote or autonomous operation, enhancing safety in hazardous environments or areas with limited human access. This article serves as an introductory exploration into the world of excavator classification, shedding light on the diverse machinery crucial to shaping the landscapes of modern infrastructure projects.
References
H. Fernando and J. Marshall, “What lies beneath: Material classification for autonomous excavators using proprioceptive force sensing and machine learning,” Autom Constr, 2020, [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0926580520309547
J. S. Lee, Y. Ham, H. Park, and J. Kim, “Challenges, tasks, and opportunities in teleoperation of excavator toward human-in-the-loop construction automation,” Autom Constr, 2022, [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0926580521005707
F. Ng, J. A. Harding, and J. Glass, “An eco-approach to optimise efficiency and productivity of a hydraulic excavator,” J Clean Prod, 2016, [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0959652615008434
H. Copur, L. Ozdemir, and J. Rostami, “Roadheader applications in mining and tunneling industries,” Preprints-society of mining …, 1998, [Online]. Available: https://www.researchgate.net/profile/Jamal-Rostami/publication/237780459_Roadheader_applications_in_mining_and_tunneling/links/0c96052dd3c0a95e04000000/Roadheader-applications-in-mining-and-tunneling.pdf?_sg%5B0%5D=started_experiment_milestone&origin=journalDetail&_rtd=e30%3D
L. Zhang et al., “An autonomous excavator system for material loading tasks,” Sci Robot, 2021, doi: 10.1126/scirobotics.abc3164.
J. Zhao et al., “Aes: Autonomous excavator system for real-world and hazardous environments,” arXiv preprint arXiv …, 2020, [Online]. Available: https://arxiv.org/abs/2011.04848
A. Stentz, J. Bares, S. Singh, and P. Rowe, “A robotic excavator for autonomous truck loading,” Auton Robots, 1999, doi: 10.1023/A:1008914201877.
K. J. Rustamov and L. O. Tojiev, “Types of Steering and Their Design Aspects,” Indonesian Journal of Innovation …, 2022, [Online]. Available: https://ijins.umsida.ac.id/index.php/ijins/article/view/746
K. J. Rustamov and B. M. Bazarbaev, “Theoretical study of the power balance of the equipment of a single bucket hydraulic excavator under the conditions of determining the productivity,” … on Agriculture Sciences, Environment, Urban and …, 2021.
N. Diaz, “Integrating Simulation and Emission Models for Equipment Cost Analysis in Earthmoving Operations,” Lecture Notes in Civil Engineering, vol. 251, pp. 609–622, 2023, doi: 10.1007/978-981-19-1029-6_46.
K. M. Rashid, “Automated Activity Identification for Construction Equipment Using Motion Data From Articulated Members,” Front Built Environ, vol. 5, 2020, doi: 10.3389/fbuil.2019.00144.
M. Alamaro, “Semiarid Terrain Alteration for Converting Dryland into Arable Land - Construction and Earthmoving Perspectives,” Proceedings of the International Symposium on Automation and Robotics in Construction, vol. 2022, pp. 646–652, 2022.
C. He, “Feature Selection-Based Multiview Concentration for Multivariate Time Series Classification and Its Application,” IEEE Sens J, vol. 24, no. 4, pp. 4798–4806, 2024, doi: 10.1109/JSEN.2023.3345631.
G. Liu, “Vision-based excavator pose estimation for automatic control,” Autom Constr, vol. 157, 2024, doi: 10.1016/j.autcon.2023.105162.
X. Bao, “Targeting proprotein convertase subtilisin/kexin type 9 (PCSK9): from bench to bedside,” Signal Transduct Target Ther, vol. 9, no. 1, 2024, doi: 10.1038/s41392-023-01690-3.
A. L. C. Ottoni, “A Statistical Approach to Hyperparameter Tuning of Deep Learning for Construction Machine Classification,” Arab J Sci Eng, vol. 49, no. 4, pp. 5117–5128, 2024, doi: 10.1007/s13369-023-08330-6.
S. Wang, “Keypoints-based Heterogeneous Graph Convolutional Networks for construction,” Expert Syst Appl, vol. 237, 2024, doi: 10.1016/j.eswa.2023.121525.
C. He, “Minimum Redundancy Maximum Relevancy-based Multiview Generation for Time Series Sensor Data Classification and Its Application,” IEEE Sens J, 2024, doi: 10.1109/JSEN.2024.3371400.
H. Song, “A novel data fusion based intelligent identification approach for working cycle stages of hydraulic excavators,” ISA Trans, 2024, doi: 10.1016/j.isatra.2024.03.006.
M. Theobald, “Activity Recognition for Attachments of Construction Machinery Using Decision Trees,” Lecture Notes in Civil Engineering, vol. 390, pp. 97–106, 2024, doi: 10.1007/978-3-031-44021-2_11.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Kamoliddin Juraboyevich Rustamov, G. G. Atabayev, L. O. Tojiyev, G. T. Jalilova
This work is licensed under a Creative Commons Attribution 4.0 International License.
