Cargando…

Comparison of Alternative Strategies Estimating the Kinetic Reaction Rate of the Gold Cyanidation Leaching Process

[Image: see text] It is very important to establish an accurate process model for implementing further control and optimization of the gold cyanidation leaching process. Unfortunately, the important kinetic reaction rates affecting process operation are unmeasurable, and moreover, their estimation i...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Jun, Tan, Yuanyuan, Li, Shujiang, Wang, Yanhong, Jia, Runda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2019
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6882123/
https://www.ncbi.nlm.nih.gov/pubmed/31788621
http://dx.doi.org/10.1021/acsomega.9b02803
Descripción
Sumario:[Image: see text] It is very important to establish an accurate process model for implementing further control and optimization of the gold cyanidation leaching process. Unfortunately, the important kinetic reaction rates affecting process operation are unmeasurable, and moreover, their estimation is an ill-posed inverse problem due to the fact that the noise in concentration measurements is easy to be amplified and propagated into the rate estimates by derivative operation. In this paper, the alternative strategies (finite difference, polynomial fitting, Savitzky–Golay filter, wavelet decomposition, and Tikhonov regularization) estimating the kinetic reaction rate of the gold cyanidation leaching process are investigated in detail. The simulation results show that the direct finite difference leads to poor estimating results for the noisy case and the other strategies are capable of avoiding the noise amplification and improving the estimating results to some extent. In all of the investigated strategies, the Tikhonov regularization leads to the satisfactory and acceptable estimating results in both the noiseless and noisy cases, which will lay an important foundation for the subsequent model identification, production index prediction, and operation optimization.