中北大学学报（自然科学版）2017，Vol.38Issue(5)：574-579,598,7.DOI:10.3969/j.issn.1673-3193.2017.05.012
基于OBE-ELM的球磨机料位软测量
Soft Sensor for Ball Mill Fill Level Based on OBE-ELM Model
摘要
Abstract
In the process of soft sensor modeling of ball mill fill level using traditional extreme learning machine,existing the issue of poor robustness and low accuracy.To solve the problem,an improved ex-treme learning machine (ELM)soft sensor method based on optimal bounding ellipsoid (OBE)was pro-posed.The ball mill vibration signal was viewed as observed variables,and the features were extracted by partial least squares (PLS).Then,extracted features were put into ELM for model training.OBE was used to optimize the weights of the network under the condition that the model error was unknown but bounded.The experiment tested on a dataset of the lab-scale ball mill illustrate that the evaluation index is improved in the prediction of the ball mill fill level,and the box-plot shows that the proposed method has better robustness.关键词
球磨机料位/软测量/最优定界椭球/极限学习机Key words
fill level of ball mill/soft sensor/optimal bounding ellipsoid/extreme learning machine分类
信息技术与安全科学引用本文复制引用
程瑞辉,阎高伟..基于OBE-ELM的球磨机料位软测量[J].中北大学学报（自然科学版）,2017,38(5):574-579,598,7.基金项目
国家自然科学基金资助项目(61450011) （61450011）
山西省煤基重点科技攻关项目(MD2014-07) （MD2014-07）
山西省自然科学基金资助项目(20150110052) （20150110052）
