模式识别技术在泥浆浓度反演中的应用
Application of Fuzzy Pattern Recognition in the Measurement of Slurry Concentration
泥浆在建筑工程中使用非常普遍,合理地控制泥浆的物理性能对于建筑工程施工及其质量控制非常 重要,通过声学方法可以有效地监测泥浆的体积浓度等物理参数。在通过声衰减和声速等介质的声学参数反演 泥浆浓度的过程中,数据拟合的好坏直接影响到反演的精确程度。通过模式识别技术,利用聚类算法,对数据 进行分类、归类处理,能有效的地提高反演的准确度。
Slurry is widely used in construction projects, and it is important to control the slurry's physical characteristic properly. The acoustic method is used, which can effectively monitor the physical parameters of slurry, such as concentration. Data processing affects directly the precision in the measurement of slurry concentration by the sound attenuation and velocity. Based on the fuzzy pattern recognition, data are sorted and further classified, with cooperative clustering algorithm.
fuzzy pattern recognition / nearest neighbor(NN) / cooperative clustering algorithm(CCA) / slurry concentration
李德军(1979-),男,山东莱阳市人,中国科学院上海声学实验室硕士,从事信号处理及声学理论的有关研究
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