Application status and prospect of AI video image analysis in intelligent coal preparation plant
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摘要: 人工智能（AI）视频图像分析是选煤厂智能化的重要组成部分，可实现对选煤厂设备、环境、人员、选煤全流程的重要参数的智能监测。给出了目前智能化选煤厂基本架构，指出现有研究大部分是利用AI视频图像分析技术构建对选煤厂人员、设备、环境、管理的安全监测系统，给出了智能视频图像监测系统的构建过程。针对选煤厂智能化建设中的安全环保生产和提高产品质量两大目标，从异物检测、智能分选、设备运行状态监测、煤炭粒度检测、人员行为监控和环境与安全检测等6个方面介绍了AI视频图像分析技术在选煤厂智能化选煤上的应用现状。对AI视频图像分析在选煤厂智能化应用进行了展望，指出不仅要从宏观架构上搭建基于5G通信、物联网、AI、智能控制理论和选煤行业技术的多层级视频监控系统，还要从微观上优化现有通用的智能视频监测方法或算法，开发出适用于选煤厂环境的智能视频图像分析技术：机器视觉、计算机视觉应与深度学习高度融合，面对不同工况，合理应用机器视觉与计算机视觉的不同优势；建立多层级一体化监控系统框架，在框架内部署并优化算法模型；建立多元化的视频图像数据库，充分利用不同图像类型的数据特征，开发针对性分析算法；深入研究分布式数据流与实时AI视频图像分析，构建实时AI分布式系统，合理调度视频图像分析模型，提高实时模型的计算效率与准确性。Abstract: Artificial intelligence (AI) video image analysis is an important part of intelligent coal preparation plant. It can realize the intelligent monitoring of important parameters of the equipment, environment, personnel and the whole process of coal preparation. The basic structure of the intelligent coal preparation plant is proposed. It is pointed out that the existing research mostly uses AI video image analysis technology to construct the safety monitoring system of coal preparation plant for personnel, machine, environment and management. The construction process of the intelligent video image monitoring system is proposed. In view of the two goals of safe and environment-friendly production and improving product quality in the intelligent construction of coal preparation plant, the application status of AI video image analysis technology in the intelligent coal preparation plant is introduced from six aspects. The aspects include foreign object detection, intelligent separation, equipment running state monitoring, coal particle size detection, personnel behavior monitoring and environmental safety detection. The intelligent application of AI video image analysis in coal preparation plant is proposed. It is pointed out that it is necessary to build a multi-level video monitoring system based on 5G communication, the Internet of Things, AI, intelligent control theory and coal preparation industry technology from the macro architecture. It is also necessary to optimize existing general intelligent video monitoring methods or algorithms from a micro perspective, and develop intelligent video image analysis technology suitable for the coal preparation plant environment. Machine vision and computer vision should be highly integrated with deep learning. The different advantages of machine vision and computer vision should be reasonably applied in different working conditions. It is suggested to establish a multi-level integrated monitoring system framework, and deploy and optimize the algorithm model within the framework. It is suggested to establish a diversified video image database, make full use of data characteristics of different image types, and develop targeted analysis algorithms. It is suggested to deeply study the distributed data stream and real-time AI video image analysis, build a real-time AI distributed system, reasonably schedule the video image analysis model, and improve the calculation efficiency and accuracy of the real-time model.
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表 1 烟煤、无烟煤和褐煤的粒度等级划分
Table 1. Classification of particle size of bituminous coal, anthracite and lignite
mm 粒度名称 无烟煤和烟煤粒度 褐煤粒度 特大块 ＞100~300 ＞100~300 大块 ＞50~100 ＞50~100 混大块 ＞50 ＞50 中块 ＞25~50, ＞25~80 ＞25~50, ＞25~80 小块 ＞13~25 ＞13~25 混中块 ＞13~50, ＞13~80 — 混块 ＞13, ＞25 — 混粒 ＞6~25 — 粒煤 ＞6~13 — 混煤 ＜50 — 末煤 ＜13, ＜25 ＜13, ＜25 粉煤 ＜6 — 
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