摘要
分析了含沙水体对抽水泵叶轮磨蚀的原理及危害.以江南某水厂1～6号机组采用的日本荏原公司500VYM水泵大修数据为基础,针对样本极为有限、影响因素复杂多变的情况,提出采用模糊支持向量机对叶轮磨蚀特性进行预测.为各机组开机调度、大修时间、人员、经费安排、备件购置等提供决策支持.对相应算法进行了推导分析,并与人工神经网络、常用核函数等方法进行了实验对比,本算法具有更优的性能,可为这类问题的处理提供参考.
The principle of sandiness water ablating pump impeller and its serious affects are analyzed.Based on complete overhaul log files data of Jiangnan Water Factory 1～6 pump sets,500VYM pumps produced by Ebara co.ltd.,of Japan, fuzzy support vector machine is adopted to forecast ablation performance index under limited sample data sets and complex factors.It can support pump sets duty time and overhaul time setting,human and outlay arrangement,spare parts purchase, and so on.Corresponding algorithm is derived and analyzed,and its experiment result is compared with that of the ANN （artificial neural network） and common kernel functions.The proposed algorithm has better performance and it can provide reference for processing this kind of problem.
出处
《信息与控制》
CSCD
北大核心
2011年第1期90-94,104,共6页
Information and Control
基金
西南科技大学重点科研基金资助项目(07sx2107)
四川省教育厅科研基金资助项目(07ZA175)
关键词
模糊支持向量
核回归
含沙水体
离心泵叶轮
磨蚀特性
fuzzy support vector
kernel function regression
sandiness water
box-shrouded impeller
ablation performance index
