Automated UDD dragline digging algorithms

Samuel Leonard (2011). Automated UDD dragline digging algorithms MPhil Thesis, School of Mechanical and Mining Engineering, The University of Queensland.

       
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s33630423_mphil_thesis_final.pdf mPhil Thesis final submission: Automated UDD dragline algorithms Click to show the corresponding preview/stream application/pdf 2.78MB 27
Author Samuel Leonard
Thesis Title Automated UDD dragline digging algorithms
School, Centre or Institute School of Mechanical and Mining Engineering
Institution The University of Queensland
Publication date 2011-10
Thesis type MPhil Thesis
Total pages 114
Total colour pages 26
Total black and white pages 88
Subjects 09 Engineering
Abstract/Summary Improvements in dragline efficiency of one percent can reduce costs by one million dollars per annum. However, dragline research on full scale machines is difficult due to large costs associated with non productive time. A solution to this problem is to develop scale models. There are however many problems associated with the use of scale draglines: operator variability and material variability. The actions of a human operator may not be reproducible. Material properties such as particle size distribution, moisture content, rock shape, rock length, overburden composition variability can also significantly impact results. Careful consideration of the material properties is required to achieve similarity between scale models and real scale draglines. The aim of the thesis was to develop a semi autonomous 1:25 scale UDD (Universal Dump and Drag) dragline that is capable of producing results statistically similar to a human operator. The scale dragline was modelled with: a geometrically similar scale dragline, an accurately scaled muckpile and a computer controlled digging algorithm. The scale dragline was drafted from manufacturer dimensions. A field trial was conducted to obtain operator data and material properties. A heuristic computer program was developed to mimic human operators. Laboratory results indicate similarity with field results within five percent. The metrics used for comparison were: dig energy, dig time, dig length, payload, energy per unit payload, and payload per unit time. The laboratory dragline successfully achieved similarity with the full scale dragline.
Keyword Dragline
Dragline Buckets
Automated digging
Autonomous Digging
Autonomous excavation
Additional Notes 23-25,46-47,52-54,59,76,78-79,82-90,92,97-98,101-102

 
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Created: Mon, 10 Oct 2011, 17:32:36 EST by Mr Samuel Leonard on behalf of Library - Information Access Service