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Research of uniformity evaluation model based on entropy clustering in the microwave heating processes

机译:基于熵聚类的微波加热过程均匀性评估模型研究

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This paper proposes a uniformity evaluation method based on Spectral Clustering and Maximum Information Entropy (ECUEM) for clustering the simulation results in the microwave heating system. The proposed method can effectively evaluate the dataset of the electric field E, the magnetic field H, the temperature field T, and analyze the non-uniformity phenomenon in the microwave heating processes. Compared with other clustering algorithms, the ECUEM can get better clustering results for the dataset in simulation of microwave heating. In particular, in the resonant cavity, the experimental results show that the minimum the evaluation results, the better the materials heating uniformity. In addition, when the ECUEM method is used to analyze the experiment of waveguide moving, the best position (0, 11/20*do, 3/14*ho) of waveguide can be obtained; at the same time, the uniformity or efficiency of materials microwave heating is the best. Moreover, other rules have been obtained in the microwave heating processes. Thus, the proposed method would provide a new method to guide the researchers who are working in the area of dataset clustering in the microwave heating. (C) 2015 Published by Elsevier B.V.
机译:提出了一种基于谱聚类和最大信息熵(ECUEM)的均匀性评估方法,用于对微波加热系统中的模拟结果进行聚类。所提出的方法可以有效地评估电场E,磁场H,温度场T的数据集,并分析微波加热过程中的不均匀现象。与其他聚类算法相比,ECUEM在微波加热模拟中可以获得更好的聚类结果。特别是在谐振腔中,实验结果表明,评估结果越小,材料加热均匀性越好。另外,当使用ECUEM方法分析波导运动的实验时,可以获得波导的最佳位置(0、11 / 20 * do,3/14 * ho);同时,材料微波加热的均匀性或效率是最好的。此外,在微波加热过程中还获得了其他规则。因此,所提出的方法将为指导在微波加热中数据集聚领域工作的研究人员提供一种新方法。 (C)2015由Elsevier B.V.发布

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