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Quantitative characterization of pulverized coal and biomass-coal blends in pneumatic conveying pipelines using electrostatic sensor arrays and data fusion techniques

机译:使用静电传感器阵列和数据融合技术定量表征气力输送管道中的煤粉和生物质煤混合物

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摘要

Quantitative data about the dynamic behaviour of pulverized coal and biomass-coal blends in fuel injection pipelines allow power plant operators to detect variations in fuel supply and oscillations in the flow at an early stage, enable them to balance fuel distribution between fuel feeding pipes and ultimately to achieve higher combustion efficiency and lower greenhouse gas emissions. Electrostatic sensor arrays and data fusion algorithms are combined to provide a non-intrusive solution to the measurement of fuel particle velocity, relative solid concentration and flow stability under pneumatic conveying conditions. Electrostatic sensor arrays with circular and arc-shaped electrodes are integrated in the same sensing head to measure 'averaged' and 'localized' characteristics of pulverized fuel flow. Data fusion techniques are applied to optimize and integrate the results from the sensor arrays. Experimental tests were conducted on the horizontal section of a 150 mm bore pneumatic conveyor circulating pulverized coal and sawdust under various flow conditions. Test results suggest that pure coal particles travel faster and carry more electrostatic charge than biomass-coal blends. As more biomass particles are added to the flow, the overall velocity of the flow reduces, the electrostatic charge level on particles decreases and the flow becomes less stable compared to the pure coal flow.
机译:有关喷油管道中煤粉和生物质-煤混合物的动态行为的定量数据,使发电厂的运营商可以及早发现燃料供应的变化和流动的波动,从而使他们能够平衡进料管之间的燃料分配并最终平衡实现更高的燃烧效率和更低的温室气体排放。静电传感器阵列和数据融合算法相结合,为在气动输送条件下测量燃料颗粒速度,相对固体浓度和流动稳定性提供了一种非侵入式解决方案。具有圆形和弧形电极的静电传感器阵列集成在同一个传感头中,以测量粉状燃料流的“平均”和“局部”特性。应用数据融合技术来优化和整合传感器阵列的结果。在150毫米口径的气动输送机的水平截面上进行了试验测试,该输送机在各种流量条件下循环粉煤和锯末。测试结果表明,与生物质-煤混合物相比,纯煤颗粒运动更快并且带有更多的静电荷。与更多的生物质颗粒相比,与纯煤流相比,流的总速度降低,颗粒上的静电荷水平降低,并且流变得不稳定。

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