Work

Material Flow Detection Method for Grinding Conveyor Belt Based on Improved GOOSE Algorithm

Year: 2025

Type: article

Abstract: The detection of material flow rate on grinding conveyor belts is of great significance in grinding operations. In order to overcome the shortcomings of existing material flow rate detection methods and improve the accuracy and adaptability of material flow rate detection, this paper applies digital image processing technology and intelligent optimization algorithms to it. A material flow rate detection method for grinding conveyor belts based on the improved GOOSE algorithm is proposed, which detects the cross-sectional area of mineral materials using the improved GOOSE algorithm, and finally calculates the material flow rate of grinding conveyor belts based on mathematical models. Comparative experiments show that the method proposed in this paper has the advantages of high detection accuracy and strong adaptability.

Source: Minerals

DOI: 10.3390/min15030300

Authors: Hao Peng, Lifang He, Danyang Li, Haopo Tang

Institutions: Yunnan Normal University, Kunming University of Science and Technology

Language: English

Topic: Mineral Processing and Grinding

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,896