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

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.