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Clean Desulphurization of High-Sulfur Coal Based onSynergy Effect between Microwave Pretreatment and Magnetic Separation

机译:基于GIS的高硫煤清洁脱硫。微波预处理与磁分离的协同效应

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摘要

Coal is the world’s second largest energy resource and the primary energy resource in China. Coal-fired power generation is the dominant source for obtaining power both in China and the world. This situation is considered to remain unchanged for the coming few decades. The paper is to study the mechanism of microwave absorption capacity of the magnetic medium. A mechanism for the microwave energy absorption of fine coal is proposed by obtaining the parameters of dielectric properties of the magnetic medium. The prediction model of electromagnetic parameters during the process of microwave dielectric enhancement of fine coal is established by using the neural network method. The content of magnetic medium, by increasing the electromagnetic parameters to improve the energy utilization rate and reduce energy loss, can effectively improve the absorption and broaden bandwidth of the coal sample, improving the frequency adaptive design of coal by the microwave pretreatment process. A neural network model for the prediction of the electromagnetic parameters of fine coal is established by usingthe neural network method. The desulfurization rates were 23.99 and45.78% for Weinan and Lu’an coals, respectively.
机译:煤炭是世界第二大能源资源,也是中国的主要能源。燃煤发电是中国乃至世界上获取电力的主要来源。人们认为这种情况在未来几十年将保持不变。本文旨在研究磁性介质微波吸收能力的机理。通过获得磁性介质的介电特性参数,提出了一种吸收细粉煤微波能的机理。利用神经网络方法建立了粉煤微波介电增强过程中电磁参数的预测模型。磁性介质的含量可以通过增加电磁参数来提高能量利用率,减少能量损失,可以有效地提高煤样的吸收率和拓宽带宽,并通过微波预处理工艺改善煤的频率自适应设计。建立了预测细煤电磁参数的神经网络模型。神经网络方法。脱硫率为23.99和渭南煤和’安煤分别为45.78%。

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