Modeling of Wet Grinding Operation Using Artificial Intelligence Based Techniques
نویسندگان
چکیده
The Artificial Intelligence (AI) based modeling techniques applied to the industrial grinding operation of a lead-zinc ore-beneficiation plant to predict the key performance indicators (KPIs) for the circuit. As system identification of the non-linear process is a must in advanced control, AI based techniques are applied to predict the KPIs within some acceptable limits. The nonparametric model for these KPIs is constructed using Feed-Forward Neural Networks (FNN), and wavelet-frames. A well-validated hybrid-model, using physico-empirical methodologies, is used to approximate the actual behaviour of the plant. Merits and demerits of each of these techniques are presented. Copyright © 2005 IFAC
منابع مشابه
Petri Net Modeling for Parallel Bank ATM Systems
In this paper the real time operation of an automatic teller machine (ATM) is analyzed using aTimed Petri Net (TPN) model. In the modeling, the probability of arrivals, the speed andattentiveness of customers (clients) are taken to account. Different parameters are based onthe statistical data. The model is simulated for 24 hours. The diagrams of number ofsucceeded customers, failed references ...
متن کاملThe Intelligent Modeling of Human Hand Motion Using Magnetic Based Techniques
With increasing use of robots instead of human in industrial, medicine and military applications etc.the importance of research on designing and building of robots is increasing. In this paper variousmethods of the human hand motion simulation has been investigated and we used one of most commonmethod named Data-gloves which extract data from hand and then we simulated hand motion duringseveral...
متن کاملApplication of Statistical and Soft Computing techniques for the Prediction of Grinding Performance
Thermal load in manufacturing processes is of special interest as it is closely connected with the surface integrity and life-cycle of the finished product. Especially in grinding, heat affected zones are created due to excessive heat dissipated within the workpiece during the process. In these zones, defects are created that undermine the quality of the workpiece and as grinding is a precision...
متن کاملUse of artificial intelligence techniques to predict distribution of heavy metals in groundwater of Lakan lead-zinc mine in Iran
Determining the distribution of heavy metals in groundwater is important in developing appropriate management strategies at mine sites. In this paper, the application of artificial intelligence (AI) methods to data analysis,namely artificial neural network (ANN), hybrid ANN with biogeography-based optimization (ANN-BBO), and multi-output adaptive neural fuzzy inference system (MANFIS) to estima...
متن کاملYarn tenacity modeling using artificial neural networks and development of a decision support system based on genetic algorithms
Yarn tenacity is one of the most important properties in yarn production. This paper addresses modeling of yarn tenacity as well as optimally determining the amounts of the effective inputs to produce yarn with desired tenacity. The artificial neural network is used as a suitable structure for tenacity modeling of cotton yarn with 30 Ne. As the first step for modeling, the empirical data is col...
متن کامل