基于SOM聚类算法的核级管道支吊架根部智能选型研究

Study on Nuclear Class Piping Hanger and Support Root Intelligent Selection Based on SOM Clustering Algorithm

基于数据挖掘技术,对核级管道支吊架根部智能选型数据预处理方法开展了研究,研究了根部选型预处理的分类方法,设计了数据预处理流程,确定了支吊架根部选型的优先级顺序;基于自组织映射网络(SOM)聚类算法,研究了支吊架根部智能选型数据的计算流程;设计了实验平台,基于实际工程数据,验证了算法的可行性和有效性,证明了数据的预处理及聚类效果明显。

Based on the data mining technology, the pre-processing method of intelligent root selection data for nuclear-level pipeline hanger and support is studied. The classification method of root selection pre-processing is studied. The data pre-processing flow is designed and the priority order of root selection of hanger and support is determined;Based on SOM clustering algorithm, the calculation process of intelligent selection data of the root of hanger and support is studied, the experimental platform is designed. Based on the actual engineering data, the feasibility and the effectiveness of the algorithm are verified, the data pre-processing is proved and the clustering effect is obvious.