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    基于AI技术的煤炭智能装车系统研究与应用

    Research and application of coal intelligent loading system based on AI technology

    • 摘要: 在我国工业转型升级的关键时期,煤炭工业正面临深层次的技术革新和系统性变革。作为国民经济的重要基础产业,选煤加工环节的智能化、数字化转型已成为推动行业高质量发展的战略性命题。神东洗选中心作为行业标杆,敏锐洞察到传统生产模式的局限性,近年来在装车系统现代化改造上持续投入大量资源和精力,展现出卓越的前瞻性和创新精神。通过对装车溜槽的自动化控制、设备故障的智能诊断、液压系统的精细化升级以及辅助系统的持续优化,企业在降低人工劳动强度、提升装车效率和设备可靠性等关键指标上取得了显著突破。这些改进不仅体现了技术创新的实践价值,更为传统选煤生产注入了新的发展动能。然而,在复杂的工业生产实践中,传统装车系统仍然存在诸多亟待解决的痛点和发展瓶颈。车厢车号和车型识别的精确性、煤炭堆料状态的实时动态监测、全流程无人值守以及突发情况的快速应对等一系列挑战,已经成为制约选煤生产智能化水平提升的关键瓶颈。面对这些深层次的技术难题,人工智能技术的引入为传统选煤生产带来了革命性突破的可能。机器视觉、深度学习、激光雷达等前沿技术正逐步成为推动煤炭加工智能化转型的重要技术支撑,为传统产业注入新的创新活力。基于此,选取神东洗选中心下辖的十余座选煤厂作为研究对象,聚焦煤炭装车这一关键生产环节,系统性地探索人工智能技术在选煤生产中的创新应用。通过引入机器视觉和激光雷达等前沿技术,旨在突破传统人工巡检与操作模式的固有局限,构建一套更加精准、高效、智能的装车状态监测与分析体系。这不仅将对提升选煤生产的智能化水平具有重要的现实意义,更将为传统工业企业的数字化转型提供可借鉴的技术路径和实践经验,为推动产业技术创新树立新的标杆。

       

      Abstract: In the critical period of industrial transformation and upgrading in our country, the coal industry is facing deep technical innovation and systemic change. As an important basic industry of the national economy, the intelligent and digital transformation of coal processing has become a strategic proposition to promote the high-quality development of the industry. Shendong washing center as the industry benchmark, keen insight into the limitations of traditional production mode, in recent years in the loading system modernization continues to invest a lot of resources and energy, showing excellent forward-looking and innovative spirit. Through the automatic control of loading chway, intelligent diagnosis of equipment fault, fine upgrading of hydraulic system and continuous optimization of auxiliary system, the enterprise has made significant breakthroughs in reducing manual labor intensity, improving loading efficiency and equipment reliability and other key indicators. These improvements not only reflect the practical value of technological innovation, but also inject new development momentum into traditional coal preparation production. However, in complex industrial production practice, there are still many pain points and development bottlenecks in the traditional loading system that need to be solved. A series of challenges, such as the accuracy of car number and vehicle type recognition, real-time dynamic monitoring of coal stacking status, unattended operation of the whole process, and rapid response to emergencies, have become key bottlenecks restricting the improvement of intelligent level of coal preparation production. In the face of these deep technical problems, the introduction of artificial intelligence technology has brought revolutionary change to the traditional coal preparation production. Cutting-edge technologies such as machine vision, deep learning, and laser radar are gradually becoming important technical support for promoting the intelligent transformation of coal processing, and injecting new innovation vitality into traditional industries. Based on this, selected more than ten coal preparation plants under the administration of Shendong Washing Center as research objects, focused on the key production link of coal loading, and systematically explored the innovative application of artificial intelligence technology in coal preparation production. By introducing advanced machine vision and laser radar and other cutting-edge technologies, aims to break through the inherent limitations of traditional manual inspection and operation mode, and build a more accurate, efficient and intelligent loading condition monitoring and analysis system. This will not only have important practical significance for improving the intelligent level of coal preparation production, but also provide a reference technology path and practical experience for the digital transformation of traditional industrial enterprises, and set a new benchmark for promoting industrial technology innovation.

       

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