机械制造与自动化2025，Vol.54Issue(5)：57-61,5.DOI:10.19344/j.cnki.issn1671-5276.2025.05.011
密度偏差抽样算法的设备样本点选择
Equipment Sample Point Selection for Density Biasd Sampling Algorithm
陈双 1伍铁军1
作者信息
- 1. 南京航空航天大学 机电学院,江苏 南京 210016
- 折叠
摘要
Abstract
A device typical sample point selection method based on variable grid and FCM density bias sampling is proposed to address the problems of enormous consumption of time and space resources in data-driven device fault diagnosis by direct calculation.The dataset is divided into several grids of different sizes by a variable grid partitioning method,the expected number of samples in each grid are calculated based on the sampling probability of data points within each grid unit,and FCM clustering is performed inside the grid to obtain the number of target sample points.The experimental results show that the proposed algorithm not only ensures the integrity of the original dataset,but also maintains relatively accurate clustering effect,which lays foundation for the subsequent recognition of equipment operating conditions.关键词
密度偏差抽样/模糊C均值/可变网格/设备典型样本点Key words
density biased sampling/fuzzy C-means/variable grid/typical sample points of equipment分类
信息技术与安全科学引用本文复制引用
陈双,伍铁军..密度偏差抽样算法的设备样本点选择[J].机械制造与自动化,2025,54(5):57-61,5.
