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To examine the effects of water washing and acid-based deashing on the structure as well as combustion characteristics of Zhundong lignite, this study used high-speed planar laser-induced fluorescence measurements (OH-PLIF) with a specific burner and characterization techniques including XRD, BET, and ICP-AES as the method. The results indicated that both water washing and deashing can remove the ash and the main mineral alkali metals. Compared with RC, the total amount of OH release from WWC and UCC was increased attributing to the addition of combustibles and volatiles. The ignition of WWC and UCC was faster than that of RC, while the burning rate followed the opposite order. Experimental result confirms that the alkali metal and alkaline earth metals play a catalytic role in coal combustion. Meanwhile, the increase of the BET surface area and the reduction of ash are conducive to heat transfer, which is favorable for the ignition of pulverized coal. [ABSTRACT FROM AUTHOR]

By using the data collected by the cluster intelligent and complex optimization of the power system equipment, the cluster intelligent and complex optimization algorithms are introduced into the CAD-aided intelligent operation and maintenance of power system equipment (CAD-IOMPSE). Based on this, the CAD-aided intelligent operation and maintenance graph of power system equipment is used to apply the cluster intelligent complex data contained in the quality inspection of the different types of data obtained to restrict the relationship between different entities for the value of knowledge contained in the collected power data in the operation process and control stage of the power system. According to the types of equipment with problems in the operation of power system, the defects and problems are quickly diagnosed to quickly locate the problems and give solutions. Finally, the results of example analysis show that compared with the traditional naming entity recognition algorithm, BiLSTM-softmax and Seq2Seq-Attention model, the algorithm in this study is better than the traditional algorithm in the three evaluation index values of accuracy, recall, and F1 value. [ABSTRACT FROM AUTHOR]