In this paper, the identification problem of local weighted linear models is considered for the adhesion behav...
ZHONG Lusheng, YANG Hui, Gong Jinhong, Zhang Yongxian College of Electrical and Electronic Engineering, East China Jiaotong University,Nanchang Jiangxi 330013
Considering that the on-line measurement and automatic control of element component content(ECC) are difficult to perform in rare earth cascade extraction process, the ECC distribution profile is dynamically regulated at all stages to assess the effect of product purity control. Focusing on the theory of countercurrent extraction, the technology parameters and pre-setting flow-rates during the extract process are designed. Under varying process parameters, a novel step by step model is also proposed for each stage to analyze the impact on the distribution profile change. Combining the mass balance model and ECC changing trend at the monitoring stage, the ECC distribution profile can be automatically regulated by dynamically compensating the related extract or scrubbing liquid flow-rate. To this end, the required product purity at the two outlets is achieved. Based on Wincc and Matlab dynamic simulators, a specific Pr/Nd cascade extraction process is used to illustrate and demonstrate the application of the present approach.
For measurement of component content in the extraction and separation process of praseodymium/neodymium(Pr/Nd), a soft measurement method was proposed based on modeling of ion color features, which is suitable for fast estimation of component content in production field. Feature analysis on images of the solution is conducted,which are captured from Pr/Nd extraction/separation field. H/S components in the HSI color space are selected as model inputs, so as to establish the least squares support vector machine(LSSVM) model for Nd(Pr) content,while the model parameters are determined with the GA algorithm. To improve the adaptability of the model,the adaptive iteration algorithm is used to correct parameters of the LSSVM model, on the basis of model correction strategy and new sample data. Using the field data collected from rare earth extraction production, predictive methods for component content and comparisons are given. The results indicate that the proposed method presents good adaptability and high prediction precision, so it is applicable to the fast detection of element content in the rare earth extraction.
