Structural Optimization of Backhoe Hydraulic Excavator Working Attachment Based on Tested Dangerous Conditions

DOI

10.2991/tmcm-15.2015.4How to use a DOI?

Keywords

excavator; working attachment; dangerous condition; structural optimization; FEA

Abstract

The structural parameter of excavator attachment plays an important role in the structural design, so it is very important to select the most dangerous working condition to improve the structural strength by optimizing the parameters. However, the previous traditional dangerous condition comes from specialized mechanism parameters, which may not be appropriate in the real digging process. Moreover, excavators of same tonnage are quite different in the number and position of inside reinforce plate. In this paper, the actual dangerous condition is concluded from performance testing of a certain backhoe hydraulic excavator. Based on the tested dangerous condition, the best position of the inside reinforce plate is discussed first and then the parameters of the arm are optimized by Genetic Algorithm as an example. The result shows that there is a big difference between the tested dangerous working condition and the traditional condition, and also, the mass of the excavator decreases by 2.38%, the maximum resultant displacement decreases by 1.90% and the average resultant displacement decreases by 2.09% after optimization.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yuan Wang
AU  - Xiaoping Pang
AU  - Jin Chen
AU  - Xingtong Gu
PY  - 2015/11
DA  - 2015/11
TI  - Structural Optimization of Backhoe Hydraulic Excavator Working Attachment Based on Tested Dangerous Conditions
BT  - Proceedings of the 2015 International Conference on Test, Measurement and Computational Methods
PB  - Atlantis Press
SP  - 12
EP  - 15
SN  - 2352-538X
UR  - https://doi.org/10.2991/tmcm-15.2015.4
DO  - 10.2991/tmcm-15.2015.4
ID  - Wang2015/11
ER  -