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Plenary
Lecture
Abstract: Virtual sensors constitute a novel area of virtual instrumentation, whose principal mission is to perform indirect measurements of process important variables using historical data of the desired variable and some other variable that affects its performance. Virtual sensors are widely used because they are computer programs that can be change or updated when it is necessary. These programs can consist of a mathematical model, heuristic models or intelligent model. Virtual sensors are some times designed for working in parallel with a physical sensor in order to evaluate its performance, but they can also be used for having on-line estimation of the desired measurement. Neural networks have been one of the most used intelligent tool for designing and developing Virtual Sensors due to its accurate, its capability for identifying complex nonlinear dynamical systems, giving appropriate results in different situations, modeling and Identification capabilities and easy for implantation. This plenary will present some methodological frameworks for designing Virtual Sensors using Artificial Neural Networks. This Methodology is based upon Software Engineering, Knowledge-Based Systems and Neural Networks schemes. It includes both technical and economical feasibility for building the virtual sensors and considers important aspects concerning computational platform, data processing, virtual sensor requirements, among others. It also considers the computational nature of virtual sensors. It will be also presented some industrial examples.
Brief Biography of the Speaker:
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