煤中杂物的危害与洗选过程中的有效清除方法

Hazards of impurities in coal and the effective removal methods in coal preparation

煤炭中混入的各种杂物不仅影响煤炭质量,还会对煤炭加工设备、运输工具造成损害,甚至引发安全事故,有效排除煤中杂物是煤炭生产亟待解决的关键问题。杂质脱除的难易程度随着科学技术的发展而发生着变化,也决定着除杂选用的方法与手段。传统的除杂很大程度上依靠杂质的物理性质,金属类杂物一般采用除铁器清除,跳汰分选与浅槽分选过程可清除部分轻质杂物,拦杂钩和拦杂网也可清除部分轻质杂物,往往多种方法联合使用,发挥各自的优势。随着人工智能技术的发展,通过实时捕获杂物的图像和三维数据,运用计算机视觉算法对杂物进行快速、准确的识别与定位,随后指导机械手进行精准抓取,可实现杂物的精准分离。该方法实施的关键是需要建立较完备的数据集、设计精准识别算法和抓取控制策略。煤炭洗选过程中杂物的智能清除有利于推动煤炭行业的智能化转型、提高生产效率和产品质量、降低劳动强度和成本。

The various impurities mixed in coal not only affect the quality of coal,but also cause damage to coal processing equipment and transportation machinery,and even lead to safety accidents.Effectively removing impurities from coal has become a key issue that needs to be addressed in the coal industry.The difficulty of impurity removal changes with the development of science and technology,and also determines the methods used for impurity removal.The traditional impurity removal largely relies on the physical properties of impurities,metal debris is generally removed by iron remover,jig sorting and shallow trough sorting process can remove part of the light debris,stray hook and stray net can also remove part of the light debris,often a variety of methods are used in combination,thus to play their respective advantages.With the development of artificial intelligence technology,accurate separation of impurities from coal can be achieved by capturing images and 3D data of impurities in real time,using computer vision algorithms to quickly and accurately identify and locate the impurities,and then guiding the robotic arm to perform precise grasping.The key to implementing this method is to establish a comprehensive datasets,design a precise recognition algorithm,and devise a capture control strategy.The intelligent removal of impurities in the coal preparation process is conducive to promoting the intelligent transformation of the coal industry,improving production efficiency and product quality,and reducing labor intensity and costs.