现代电子技术2018，Vol.41Issue(5)：153-158,6.DOI:10.16652/j.issn.1004-373x.2018.05.035
基于改进的高斯混合回归的球磨机料位软测量
Soft measurement for ball mill fill level based on improved Gaussian mixture regression
摘要
Abstract
Since the fill level of the ball mill system in multimode complicated process is uncertain,and the vibration signal of ball mill has the characteristics of nonlinearity,noise and outside interference,a soft measurement method for ball mill fill level based on improved Gaussian mixture regression(GMR)is proposed to solve the problem that it is difficult to cluster the data embedding noise and abnormal value of the traditional Gaussian mixture model(GMM)initialization. The improved K-medoids clustering algorithm and EM algorithm are used respectively to initialize and optimize the optimal Gaussian component quantity and optimal model parameters. The GMR is used to predict the output level of the ball mill. The experimental results verify that the predicted fill level obtained by improved GMR model can track the real fill level accurately. The comparative analysis of experimental results verifies that the improved model is feasible and practical,and has high prediction accuracy.关键词
球磨机料位/多模态/振动信号/GMM/聚类/软测量/GMRKey words
ball mill fill level/multimode/vibration signal/Gaussian mixture model/clustering/soft measurement/Gaussian mixture regression分类
信息技术与安全科学引用本文复制引用
杨飞,乔铁柱,庞宇松,阎高伟..基于改进的高斯混合回归的球磨机料位软测量[J].现代电子技术,2018,41(5):153-158,6.基金项目
国家自然科学基金项目(61450011) （61450011）
山西省自然科学基金项目(2015011052) （2015011052）
山西省煤基重点科技攻关项目(MD 2014-07)Project Supported by NNSF of China(61450011),NNSF of Shanxi(2015011052),Shanxi Coal Base Key Technology Breakthrough Project(MD 2014-07) （MD 2014-07）
