DocumentCode :
2401977
Title :
Real time recognition and monitoring automation of multiple sensitive parameters for multi processes through a single neural system using TDM in dynamic environment with very high precision
Author :
Pavale, Priti S. ; Rao, D.H. ; Naidu, K. Rama
Author_Institution :
Dayananda Sager Coll. of Eng., Bangalore, India
fYear :
2010
fDate :
28-29 Dec. 2010
Firstpage :
1
Lastpage :
4
Abstract :
Precision control is one of the most important parameter of real time application. Area of application are numerous, a couple of them may be medical application or space application. Objectives are highly dependent upon the controlling mechanism. To visualize this scenario any production plant is the best example. Conventional means of controlling are facing difficulties in providing the response as expected. A new methodology with respect to Artificial Neural Network (ANN) is looked as an option for improving the result. Control chart pattern plays very important role in the controlling mechanism. This provides the information of flow about parameters of interest. To design the Neural system to recognize the variation in the control chart pattern. The six patterns are Normal, Cyclic, Incremental, Decremental, Upward shift, and downward shift that are the maximum possible patterns obtained from any industrial process. And To design a mechanism to provide the solution for different process through a single neural system i.e. multi process neuro monitoring system using time division multiplexing.
Keywords :
backpropagation; computerised monitoring; control charts; control engineering computing; multiprocessing systems; neural nets; precision engineering; production control; real-time systems; time division multiplexing; TDM; artificial neural network; control chart pattern; industrial process; multiprocess neuro monitoring; precision control; real time recognition; single neural system; time division multiplexing; Artificial neural networks; Computer science; Educational institutions; Monitoring; Real time systems; Time division multiplexing; Training; Error Back Propagation Algorithm (EBPA); Generalized delta rule (GDR); Multi Process Neuro Monitoring System (MNMS); Time Division Multiplexing (TDM);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Computing Research (ICCIC), 2010 IEEE International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4244-5965-0
Electronic_ISBN :
978-1-4244-5967-4
Type :
conf
DOI :
10.1109/ICCIC.2010.5705814
Filename :
5705814
Link To Document :
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