Payload Estimation in Excavators Using a Machine Learning Based Parameter Identification Method

You are here: Homepage > Search

Payload Estimation in Excavators Using a Machine Learning Based Parameter Identification Method

Walawalkar, Ashwin / Heep, Steffen / Frank, Martin / Schindler, Christian

This paper documents a part aspect of a broader work, where the goal is to develop a self-sufficient method for continuous and dynamic payload estimation for hydraulic excavators. Self-sufficiency here implies that the required unknowns are either measurable or can be identified using simple sensors. Results from field tests have showed that the approach for identification in its basic form is easy to implement which comes at the cost of diminished estimation accuracy, especially concerning the moment of inertia and friction behavior. Specifically, this paper covers the work done regarding application of machine learning methods to improve the accuracy and reliability of the identification approach, thereby consequently improving the accuracy of the payload estimation.

Access

Check access

Check availability in my library

Order at Subito €

Export, share and cite

Document information

Title :

Payload Estimation in Excavators Using a Machine Learning Based Parameter Identification Method

Additional title:

Lect.Notes Mechanical Engineering

Contributors:

Klomp, Matthijs (editor) / Bruzelius, Fredrik (editor) / Nielsen, Jens (editor) / Hillemyr, Angela (editor) / Walawalkar, Ashwin (author) / Heep, Steffen (author) / Frank, Martin (author) / Schindler, Christian (author)

Conference:

The IAVSD International Symposium on Dynamics of Vehicles on Roads and Tracks ; 2019 ; Gothenburg, Sweden August 12, 2019 - August 16, 2019

Published in:

Advances in Dynamics of Vehicles on Roads and Tracks ; Chapter : 190 ; 1670-1680

Lecture Notes in Mechanical Engineering

Publication date :

2020-02-13

Size :

11 pages

ISBN :

978-3-030-38077-9 , 978-3-030-38076-2

ISSN :