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    燃煤智能化采制样系统布局模式研究

    Research on layout mode of intelligent coal sampling and sample preparation system in power plants

    • 摘要: 针对当前电厂燃料智能化采制样系统缺乏系统性设计,不能根据自身条件选择最优布局的问题,开展了智能化采制样系统布局模式研究。通过深入分析当前主流的“采样–转运–制样”3段式布局模式优缺点,及其存在的转运复杂、水分易损失、效率瓶颈等问题,提出了3种渐进式的新业务布局模式:采样端缩分至15 kg模式、采样端制备6 mm样模式、采样端制备6 mm样3 mm样模式,分析了各模式的业务流程、设备配置核心及其优缺点,深入探讨了新业务布局模式下采样组织形式、破碎粒度优化、样品气力输送、全水分保全计量及弃料集中处理等关键问题的解决办法,并创新提出采样点数量及其布局是决定布局模式选择的核心因素。研究表明:3种系统性设计的新业务布局模式可以为不同基础设施条件的电厂提供从“简化采样端、强化制样端”到“强化采样端、简化后端”的差异化选型策略。通过业务流程再造与技术深度融合,构建更简洁、可靠、公平的新一代智能化采制样系统,对提升电厂燃料管理的整体水平具有重要的实践指导意义和工程应用价值。

       

      Abstract: In response to the lack of systematic design in the current power plant intelligent sampling system, which cannot select the optimal layout based on its own conditions a study on the layout mode of the intelligent sampling system was carried out: By deeply analyzing the advantages and disadvantages of the current mainstream “sampling-transportation-preparation” threestage layout mode and its existing complex transportation, easy loss of moisture, efficiency bottlenecks and other issues, three progressive new business layout modes were proposed: Sampling end reduction to 15 kilograms mode, sampling end preparation of 6 mm samples mode, sampling end preparation of 6 mm samples 3 mm samples mode, the business process, equipment configuration and its advantages and disadvantages of each mode were analyzed, and the solutions to key issues such as sampling organization form, crushing particle size optimization, sample pneumatic transportation, total moisture preservation metering, and waste centralized treatment under the new business layout mode were discussed in depth, and it was innovatively proposed that the number of sampling points and its layout was the core to determine the choice of layout mode. The research conclusion was: The three systematic design of new business layout modes could provide differentiated selection strategies for power plants with different infrastructure conditions “simplifying the sampling end and strengthening the preparation end” to “strengthening the sampling end and simplifying the back-end”. Through business process reengineering and deep integration of technology, a new generation of intelligent sampling system was constructed, which was more concise, reliable and fair. It was of great practical guiding significance and engineering application value to improve the overall level of fuel management in power plants.

       

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