In order to effectively analyse the multivariate time series data of complex process,a generic reconstruction technology based on reduction theory of rough sets was proposed,Firstly,the phase space of multivariate time series was originally reconstructed by a classical reconstruction technology.Then,the original decision-table of rough set theory was set up according to the embedding dimensions and time-delays of the original reconstruction phase space,and the rough set reduction was used to delete the redundant dimensions and irrelevant variables and to reconstruct the generic phase space,Finally,the input vectors for the prediction of multivariate time series were extracted according to generic reconstruction results to identify the parameters of prediction model.Verification results show that the developed reconstruction method leads to better generalization ability for the prediction model and it is feasible and worthwhile for application.
在工业现场,由于浮选过程的复杂性,精矿品位很难在线检测。针对这一问题,提出一种基于滑窗B样条偏最小二乘(B-Spline Partial Least Squares,BS-PLS)方法对其进行软测量。该方法首先应用数字图像处理技术,从实时获取的泡沫图像中提取泡沫特征;然后对获得的特征数据进行小波滤波预处理,再利用BS-PLS建立泡沫特征关于精矿品位的回归模型;最后采用滑窗滚动更新参数和偏差补偿输出两种策略配合对模型进行在线校正,实现精矿品位实时软测量。工业数据的仿真结果表明,该方法能有效软测量浮选过程的精矿品位。
