Deep Learning Augmented Intelligent Grinding Mill Simulation and Design

深度学习增强智能磨机仿真与设计

• 批准号: LP190100378
• 负责人: Prof Craig Wheeler
• 金额: $ 38.22万
• 依托单位: The University of Newcastle
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2021
• 资助国家: 澳大利亚
• 起止时间: 2021-05-17 至 2024-05-16
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP190100378
• 关键词: Deep; Learning; Augmented; Intelligent; Grinding

Comminution is a key operation in mineral processing that utilises grinding mills to reduce the size of ore for further mineral enrichment processing. The aim of this project is to provide a step change improvement in the operational efficiency and service life of grinding mills through the development of advanced numerical models to simulate the grinding mill process. The outcome will be a hierarchical deep learning program to select optimal model parameters from which computational algorithms will optimise grinding mill geometries. This research project will deliver substantial improvements to equipment used to process our most valuable exports and result in immediate industry impact.

粉碎是矿物加工中的关键操作，利用研磨机来减小矿石的尺寸，以进行进一步的矿物富集加工。该项目的目的是通过开发先进的数值模型来模拟磨机过程，从而显着提高磨机的运行效率和使用寿命。结果将是一个分层深度学习程序，用于选择最佳模型参数，计算算法将优化研磨机的几何形状。该研究项目将对用于加工我们最有价值的出口产品的设备进行重大改进，并产生直接的行业影响。