Key Technologies and Engineering Demonstration of Intelligent Machine Group for Bulk Loose Material Sampling, Preparation, and Analysis
Abstract：To address industry pain points such as low efficiency, large errors, and data distortion in quality inspection of bulk loose materials such as coal, ore, and grain, an intelligent machine group system covering the entire process of sampling, preparation, analysis, storage, transmission, and control has been proposed and developed. Based on industrial Internet of Things + 5G + edge computing + blockchain, a technical path from single-point intelligence to cluster intelligence and then to unmanned workshops has been innovatively established. Key technologies such as multi-material adaptive sampling and preparation, large-scale robot cluster collaboration, blockchain data integrity, full life cycle fault prediction, and complete technical systems compliant with national standards have been successfully overcome. The operation results of the demonstration project show that a single system can achieve an annual inspection capacity of 15 million tons, with a detection error rate ≤0.5%, 100% traceability of data, a 48% reduction in coal quality inspection cost per ton, and an annual CO₂ reduction of 36,000 tons, meeting the 'Level One' standard of the National Energy Administration for intelligent coal washing plants. The relevant technological achievements have been promoted to more than 20 units including China Energy Group, Shaanxi Coal Group, Jiaomei Group, and HuaiBei Mining Group, with significant social and economic benefits. It can provide a complete technical model for the clean and efficient utilization and intelligent transformation of China's coal.
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Publication Date：2025-10-30
Online Publishing Date：2025-11-21(First online date of this platform, not the publication date of the document)
Pages：8( 79-86 )