Journal article
A new approach for the automatic measurement of the angle of repose of granular materials with maximal least square using digital image processing
Computers and Electronics in Agriculture, Vol.172, 105356
01/05/2020
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Abstract
Angle of repose (AOR) is one of the essential parameters to study the flowability of granular materials. It is also commonly used to calibrate the parameters of discrete element method (DEM). In practice, AOR is measured manually or using digital image processing (DIP). However, reliable and consistent measurement of AOR is still a challenging task due to the irregular or nonlinear shape of the material pile, particularly for the AOR of cohesive materials like soils. This study suggests an accurate and consistent way to measure AOR using DIP. The developed algorithm automatically finds the AOR of the material pile by a search algorithm for the unique maximal least square using linear regression analysis. The proposed algorithm is validated using customised templates with known angles, followed by an evaluation study against (a) an existing DIP method using a linear regression within “manually” selected region of interest and (b) the results of manual measurements using a protractor. The results showed that the developed algorithm can accurately measure and quantify AOR of soil piles. It was concluded from the results that the developed algorithm can be used to accurately measure AOR without error-prone subjective judgement.
Details
- Title
- A new approach for the automatic measurement of the angle of repose of granular materials with maximal least square using digital image processing
- Creators
- Peilin Li - School of Engineering, University of South Australia, Mawson Lakes, SA 5095, AustraliaMustafa Ucgul - University of South AustraliaSang-Heon Lee - School of Engineering, University of South Australia, Mawson Lakes, SA 5095, AustraliaChris Saunders - Agricultural Machinery Research and Design Centre, School of Engineering, University of South Australia, Mawson Lakes, SA 5095, Australia
- Publication Details
- Computers and Electronics in Agriculture, Vol.172, 105356
- Publisher
- Elsevier B.V
- Identifiers
- 991013001598402368
- Academic Unit
- Faculty of Science and Engineering
- Language
- English
- Resource Type
- Journal article