摘要
在分析传统松动件质量估计方法的基础上,提出一种基于支持向量机(SVM)的核电站松动件质量估计方法.分析松动件跌落碰撞信号的频率分布特征与松动件质量之间的关系,提取表征信号频谱的特征向量.以该特征向量为SVM的输入,松动件质量为输出,实现对核电站松动件质量大小的估计.最后进行平板实验验证,实验结果表明,该方法比传统方法具有更高的计算精度和实现方便性,为核电站松动件质量估计提供了一种新的方法.
By the analysis of traditional mass estimation methods,a new method for mass estimation of loose parts in Nuclear Power Plant（NPP）based on the support vector machine（SVM）was proposed.A vector was obtained which represent the burst signal＇s spectrum by analyzing the relationship between the burst signals＇frequency spectrum and the mass of loose parts.Set the vector as input data and the mass of loose part as the output data to train the SVM,and then the mass of loose part can be estimated by the trained SVM model.Experimental results show that the method has higher accuracy and easier to achieve than the traditional methods.It provides a new way for mass estimation of loose parts in Nuclear power plants.
出处
《浙江大学学报（工学版）》
EI
CAS
CSCD
北大核心
2010年第8期1525-1529,共5页
Journal of Zhejiang University：Engineering Science
基金
国家"863"高技术研究发展计划资助项目(2007AA04Z426)
关键词
核电站
松动件
质量估计
支持向量机
nuclear power plant
loose part
mass estimation
support vector machine（SVM）
