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Title: | ERAS for Distillation Column : ANN BASED ESTIMATOR and Experimental Verification |
Authors: | Gulati, Puneet |
Keywords: | ELECTRICAL ENGINEERING;ERAS;DISTILLATION COLUMN;ANN BASED ESTIMATOR |
Issue Date: | 2004 |
Abstract: | The invariable necessity of data acquisition for monitoring and control of various industrial applications has fueled the need for the design and development of modular, reliable and accurate tailor made Data Acquisition systems. The system "EDAS for Distillation column : ANN BASED ESTIMATOR and Experimental Verification" developed as part of the dissertation work is aimed at providing a standard data acquisition system. The basic objective is to develop a system for Distillation Column, which can acquire the parameters and then estimate the distillate composition. As the composition cannot be measured directly using sensors so secondary measurement technique is applied. Once the distillate composition is known, any of the control strategies can be applied to control the composition. In the developed system all the parameters from the Distillation Column like tray temperatures, reflux temperature, top pressure, bottom pressure and reboiler level etc. are acquired by using the appropriate transducers. The output of these transducers are connected to Field Point server provided by National Instruments to access the readings from any client PC via the Ethernet. Ethernet based Data Acquisition technique which is a fast growing trend is effectively utilized by making use of OPC technology to acquire data on the client PC. Thus the acquired data from the Distillation Column can be viewed on any client PC. Rigorous experimentation has been carried out by varying the heat input to the reboiler by operating the PID controller in the manual mode, to obtain the training pattern which are used by the Artificial Neural Network. The Artificial Neural Network are implemented with one and two hidden layers. Also two types of patterns are used for the training i.e with and without PID controller. The Artificial Neural Networks thus trained are tested thoroughly and then finally applied to Distillation Column to estimate the distillate composition online. Also control option has been demonstrated which can be used for controlling the tray temperature with the help of PID controller to control the composition, which is the ultimate objective in Distillation Column. iii The software for the above stated application is made in Visual Basic 6.0 and Turbo C programming environment and Ms Access 2000 is used as the back-end for storing the acquired readings. iv |
URI: | http://hdl.handle.net/123456789/7953 |
Other Identifiers: | M.Tech |
Research Supervisor/ Guide: | Gupta, Indra |
metadata.dc.type: | M.Tech Dessertation |
Appears in Collections: | MASTERS' THESES (Electrical Engg) |
Files in This Item:
File | Description | Size | Format | |
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EED G11872.pdf | 7.4 MB | Adobe PDF | View/Open |
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