计算机应用与软件2017，Vol.34Issue(9)：288-293,6.DOI:10.3969/j.issn.1000-386x.2017.09.056
大数据环境下离散制造车间异常事件发现方法
ABNORMAL EVENT DISCOVERY METHOD OF DISCRETE MANUFACTURE WORKSHOP IN BIG DATA
摘要
Abstract
To deal with the problems of effectively controlling abnormal events happened during the production process of the discrete manufacture enterprise in big data,this paper firstly studied the rationality and utility of building the early warning model of abnormal events in workshop in theory.Then the paper gave the data source and its calculation method of the abnornal triggering event from the technical realization aspect,combined the time series and the causal relationship,and established the early warning model of the workshop anomaly based on the multi-decision tree on the time series,which ensures the accuracy and reliability of the forecast.Finally,the validity of the model was verified by the production process data of a gas turbine rotor.关键词
异常事件发现/时间序列/决策树/预警Key words
Abnormal event discovery/Time series/Decision tree/Early warning分类
信息技术与安全科学引用本文复制引用
马超,徐迭石,张淑丽,刘胜辉..大数据环境下离散制造车间异常事件发现方法[J].计算机应用与软件,2017,34(9):288-293,6.基金项目
国家自然科学基金项目(51375128) （51375128）
黑龙江省教育厅科学技术研究项目(12541159). （12541159）
