PROCESS AUTOMATION OF CONTINUOUS QUALITY CONTROL OF MIXTURE PREPARATION AT THE DISTILLERY
Journal Title: Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska - Year 2014, Vol 4, Issue 4
Abstract
The process of mixture preparation at the distilleries is considered. Optimal structure of artificial neural networks for the dry residueof the mixture definition has been substantiated and accuracy of such networks has been analyzed. The system of continuous quality control of mixture preparation is proposed using modern information technologies.
Authors and Affiliations
Sergiy Vorobyuk, Volodymyr Drevetskiy
Keywords
Related Articles
- EP ID EP73262
- DOI 10.5604/20830157.1130194
- Views 116
- Downloads 0
A MODEL OF A MOBILE ANDROID APPLICATION FOR ENVIRONMENTAL PATIENT MONITORING
To use a smart phone as a part of a telemedical health monitoring system requires a dedicated application running under control of the device’s operating system. This article contains the project and functional requireme...
NON–INVASIVE METHODS OF INDUSTRIAL PROCESSES CONTROL
Monitoring and control systems constitute an important group of diagnostic tools used in the industry. When selected properly, they allow for the early detection of adverse conditions of the process, making it possible t...
NONLINEAR ANALYSIS OF HIGH Q RADIO FREQUENCY ENERGY HARVESTING NETWORKS
The paper focuses on nonlinear analysis of high and low Q RF energy harvesting circuits. The analysis is made mathematically and by large signal simulation via Keysight Advanced Design System. The mathematical analysis o...
METHODS OF SMALL CAPACITANCE MEASUREMENT IN ELECTRICAL CAPACITANCE TOMOGRAPHY
The paper presents the main methods of small capacitance measurement used in electrical capacitance tomography: the AC method with a sine wave excitation and the charge-discharge method with square wave excitation. Const...
DWA RÓWNOLEGŁE POMIARY WIETRZNOŚCI JAKO DOKŁADNA OCENA LOKALNYCH ZASOBÓW ENERGII WIATRU
Pomiary wietrzności przeprowadzono przy użyciu dwóch masztów pomiarowych oddalonych od siebie o 17,6 km. Wyznaczono dwa numeryczne modele terenu – numeryczny model wysokościowy terenu oraz numeryczny model szorstkości te...