重庆理工大学学报（自然科学版）2017，Vol.31Issue(3)：52-57,6.DOI:10.3969/j.issn.1674-8425(z).2017.03.007
基于改进灰色GM模型的装备磨损趋势评估
Equipment Wear Trend Evaluation Based on Developed GM Model
摘要
Abstract
Wear is the key factor that affects the precision retentivity of high-end equipment.It is difficult to measure wear loss.To solve precision wear condition prediction problem,a new method of wear prediction based on GM model is studied.Meanwhile,a parameter optimization algorithm based on data driven model is constructed.The inner relationship of time series can be mined and reflected more effectively by this method.Then,wear monitoring test is carried out.Compared with the traditional GM model,the results show that the developed GM model has higher prediction precision and is very suitable for long-term forecasting compared with the predicted results of traditional GM model.关键词
磨损预测/趋势评估/GM模型/数据驱动Key words
wear prediction/trend evaluation/GM model/data driven分类
机械工程引用本文复制引用
王宁,曹蔚,王海文,杨科,彭润玲..基于改进灰色GM模型的装备磨损趋势评估[J].重庆理工大学学报（自然科学版）,2017,31(3):52-57,6.基金项目
国家自然科学基金资助项目(51505360) （51505360）
陕西省自然科学基础研究计划资助项目(2016JM5083) （2016JM5083）
陕西省教育厅科研计划项目(15JK1334) （15JK1334）
