Implementation of machine vision as an input to a fuzzy water level control system
Added Title
HNICEM 2017
International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (9th : 2017)
College
Gokongwei College of Engineering
Department/Unit
Manufacturing Engineering and Management
Document Type
Conference Proceeding
Source Title
HNICEM 2017 - 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management
Volume
2018
Issue
January
First Page
1
Last Page
6
Publication Date
7-2-2017
Abstract
In this paper, a Type I fuzzy logic controller (FLC) is applied to execute machine vision parameters such as object tracking and image processing on a specific color threshold. This system is used to compensate for large power consumption of current PID controllers that are currently being used in industrial tank systems. The aim of the implemented fuzzy controller is to utilize the conventional camera to replace existing level sensors and linear variable differential transformers (LVDT) in monitoring the water level inside a reservoir under a definite tolerance. The camera is integrated in a Roborealm machine vision software which analyses the input parameter. An embedded Arduino microcontroller handles the regulation pump which maintains the specified water level onto user defined conditions. It is found out that the fuzzy system produced a better solution than conventional control techniques. © 2017 IEEE.
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Digitial Object Identifier (DOI)
10.1109/HNICEM.2017.8269484
Recommended Citation
Alimuin, R. A., Calilung, E., & Dadios, E. P. (2017). Implementation of machine vision as an input to a fuzzy water level control system. HNICEM 2017 - 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, 2018 (January), 1-6. https://doi.org/10.1109/HNICEM.2017.8269484
Disciplines
Manufacturing
Keywords
Fuzzy logic; Computer vision; Electron tubes; Robots—Control systems
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