Online assessment of complex industrial processes operating performance based on improved dynamic causality diagram
CHANG Yu-qing
HAN Ze-feng
ZOU Xiao-yu
Abstract：For complex industry production, good operating performance is a prerequisite for high profits, low costs and so on. In order to grasp the process operating performance in real time, an online assessment method for process operating performance is necessary. Faced with hybrid of qualitative and quantitative analysis, dynamic causality diagram (DCD) is improved in this paper. To reduce the losses of quantitative messages, the certain information which is detected from the production field online will be fused with the uncertain information. Besides, the complex nonlinear relations among variables are common in chemical production. To address this issue, a new concept of Joint Event which describes one fluctuated event that must be impacted by multiple non-independent events is proposed in this paper. The modeling data are utilized to develop the assessment model via improved DCD and get accurate results during online assessment. Finally, the proposed method is applied to a hydrometallurgical leaching process operating performance assessment to illustrate its validity and effectiveness.
Keywords：dynamic causality diagramuncertain informationhydrometallurgyoperating performance assessment
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：10( 345-354 )