基于模糊C均值聚类算法模型的核电厂蓄电池运维更换策略研究

Research on the Replacement Strategy of Nuclear Power Plant Battery Operation and Maintenance Based on Fuzzy C-means Clustering Algorithm Model

针对核电厂运维中的蓄电池整组更换最优策略问题,以某厂在役的GroE型蓄电池1BTG14等6组636只电池样本为实验研究对象,在研究容量试验放电电压曲线的基础上,选取最近三次大修该曲线的特征点,利用数据聚类分析技术建立模糊C均值聚类算法模型,并通过有效性函数选取最优实验结果,对基于电压特征数据呈现的分类结果进行研究,从而得出相同运行条件下蓄电池组的最优更换策略。该方法在保证性能可靠的基础上实现蓄电池在寿期内的充分利用,从而节约核电厂运维经济成本,实现经济效益最大化。

Aiming at the problem of the optimal strategy of battery replacement in the operation and maintenance of nuclear power plants,six groups of 636 battery samples such as GroE battery 1BTG14 in service in a plant were taken as experimental research objects.On the basis of studying the discharge voltage curve of capacity test,the characteristic points of the curve of the last three overhauls were selected,and the fuzzy C-means clustering algorithm model was established using cluster analysis analysis technology,and the optimal experimental results were selected through the effectiveness function,Study the classification results presented based on voltage characteristic data to obtain the optimal replacement strategy for battery packs under the same operating conditions.This method achieves full utilization of batteries within their lifespan while ensuring reliable performance,thereby saving economic costs for nuclear power plant operation and maintenance and maximizing economic benefits.