Fuzzy Logic Controlled Paddle Wheel Aerator
Ertie C. Abana1, Ariel M. Lorenzo2, Krizel Angelie Argal3, Ian Kim Bacud4, Jeric Barcena5, Mervin Gabriel Anthony Berbano6, Khristian Russell Littaua7, Shawn Wayne Tiangco8
1Ertie C. Abana, Computer Engineering Program, University of Saint Louis, Tuguegarao City, Cagayan, Philippines. Email: ertie04@gmail.com
2Ariel M. Lorenzo, Electronics Engineering Program, University of Saint Louis, Tuguegarao City, Cagayan, Philippines.
3Krizel Angelie Argal, Electronics Engineering Program, University of Saint Louis, Tuguegarao City, Cagayan, Philippines.
4Ian Kim Bacud, Electronics Engineering Program, University of Saint Louis, Tuguegarao City, Cagayan, Philippines.
5Jeric Barcena, Electronics Engineering Program, University of Saint Louis, Tuguegarao City, Cagayan, Philippines.
6Mervin Gabriel Anthony Berbano, Electronics Engineering Program, University of Saint Louis, Tuguegarao City, Cagayan, Philippines.
7Khristian Russell Littaua, Electronics Engineering Program, University of Saint Louis, Tuguegarao City, Cagayan, Philippines.
8Shawn Wayne Tiangco, Information Technology Education Program, University of Saint Louis, Tuguegarao City, Cagayan, Philippines.
Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 1819-1824 | Volume-8 Issue-4, November 2019. | Retrieval Number: C6246098319/2019©BEIESP | DOI: 10.35940/ijrte.C6246.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Aeration, as an essential process in the aquaculture industry, has incorporated mechanical aerators especially paddle wheel which is dubbed as the most efficient type. However, an operation of such a device depends on traditional on/off mechanisms based on human intuitions when the need for aeration is necessary. In this paper, Mamdani Fuzzy Logic was integrated into automating the paddlewheel aerator to control and to ensure the correct level of dissolved oxygen in ponds. A microcontroller based on the received output from the dissolved oxygen sensor is capable of automatically controlling the impellers appropriate to the current environment condition. Series of testing was conducted to look at the accuracy of the sensing mechanism and a mean relative error of 1.32% was detected. The researchers compared theoretical and actual supply voltage for all possible dissolved oxygen readings and interpreted a 0.73% mean relative error. With the incorporation of Fuzzy Logic Controller, the system was able to maintain 6 parts per million in the test environment. The system can also reduce power consumption to 65.13% compared to traditional switching. The aerator developed in this study can be used in maintaining the dissolved oxygen in aquaculture farms without human intervention.
Keywords: Aquaculture, Dissolved Oxygen Sensor, Fuzzy Logic, Paddlewheel Aerator.
Scope of the Article: Fuzzy Logic.