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Development of an Electrostatic Air Filtration System Using Fuzzy Logic Control

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@article{IJASEIT6512,
   author = {Dewi Nurhaji Meivita and Muhammad Rivai and Astria Nur Irfansyah},
   title = {Development of an Electrostatic Air Filtration System Using Fuzzy Logic Control},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {8},
   number = {4},
   year = {2018},
   pages = {1284--1289},
   keywords = {Air Pollution, Electrostatic Filter, Fuzzy Logic, Ozone Generator},
   abstract = {Particulate matter is one of the factors that can affect air quality. The air quality can be determined by the Air Pollution Index, which has several parameters including PM10 and ozone (O3). Air pollution can be overcome by using a filtration system based on electrostatic precipitation when particles are attached to the static charges. In this study, we have developed a prototype of electrostatic filter based on fuzzy logic control to reduce air pollution of particulate matters. The electrostatic filter is an ozone generator consisting of plate-type corona discharge and a high voltage dc generator. The experimental results showed that the more ozone generators used as electrostatic filters, the faster the particulate concentration decreases. However, the use of ozone generators may increase the concentration of ozone in the air that can be harmful to human health. Therefore, we have developed an electrostatic precipitation-based air pollution control using fuzzy logic. Semiconductor gas sensor and laser dust sensor are used as feedback signals for the system in regulating the amount of charges released by ozone generators. Implementation of this control system can reduce the particulates of PM10 by 80% within 10 minutes while maintaining a low level of ozone during air purification process.},
   issn = {2088-5334},
   publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},
   url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=6512},
   doi = {10.18517/ijaseit.8.4.6512}
}

EndNote

%A Meivita, Dewi Nurhaji
%A Rivai, Muhammad
%A Irfansyah, Astria Nur
%D 2018
%T Development of an Electrostatic Air Filtration System Using Fuzzy Logic Control
%B 2018
%9 Air Pollution, Electrostatic Filter, Fuzzy Logic, Ozone Generator
%! Development of an Electrostatic Air Filtration System Using Fuzzy Logic Control
%K Air Pollution, Electrostatic Filter, Fuzzy Logic, Ozone Generator
%X Particulate matter is one of the factors that can affect air quality. The air quality can be determined by the Air Pollution Index, which has several parameters including PM10 and ozone (O3). Air pollution can be overcome by using a filtration system based on electrostatic precipitation when particles are attached to the static charges. In this study, we have developed a prototype of electrostatic filter based on fuzzy logic control to reduce air pollution of particulate matters. The electrostatic filter is an ozone generator consisting of plate-type corona discharge and a high voltage dc generator. The experimental results showed that the more ozone generators used as electrostatic filters, the faster the particulate concentration decreases. However, the use of ozone generators may increase the concentration of ozone in the air that can be harmful to human health. Therefore, we have developed an electrostatic precipitation-based air pollution control using fuzzy logic. Semiconductor gas sensor and laser dust sensor are used as feedback signals for the system in regulating the amount of charges released by ozone generators. Implementation of this control system can reduce the particulates of PM10 by 80% within 10 minutes while maintaining a low level of ozone during air purification process.
%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=6512
%R doi:10.18517/ijaseit.8.4.6512
%J International Journal on Advanced Science, Engineering and Information Technology
%V 8
%N 4
%@ 2088-5334

IEEE

Dewi Nurhaji Meivita,Muhammad Rivai and Astria Nur Irfansyah,"Development of an Electrostatic Air Filtration System Using Fuzzy Logic Control," International Journal on Advanced Science, Engineering and Information Technology, vol. 8, no. 4, pp. 1284-1289, 2018. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.8.4.6512.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Meivita, Dewi Nurhaji
AU  - Rivai, Muhammad
AU  - Irfansyah, Astria Nur
PY  - 2018
TI  - Development of an Electrostatic Air Filtration System Using Fuzzy Logic Control
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 8 (2018) No. 4
Y2  - 2018
SP  - 1284
EP  - 1289
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - Air Pollution, Electrostatic Filter, Fuzzy Logic, Ozone Generator
N2  - Particulate matter is one of the factors that can affect air quality. The air quality can be determined by the Air Pollution Index, which has several parameters including PM10 and ozone (O3). Air pollution can be overcome by using a filtration system based on electrostatic precipitation when particles are attached to the static charges. In this study, we have developed a prototype of electrostatic filter based on fuzzy logic control to reduce air pollution of particulate matters. The electrostatic filter is an ozone generator consisting of plate-type corona discharge and a high voltage dc generator. The experimental results showed that the more ozone generators used as electrostatic filters, the faster the particulate concentration decreases. However, the use of ozone generators may increase the concentration of ozone in the air that can be harmful to human health. Therefore, we have developed an electrostatic precipitation-based air pollution control using fuzzy logic. Semiconductor gas sensor and laser dust sensor are used as feedback signals for the system in regulating the amount of charges released by ozone generators. Implementation of this control system can reduce the particulates of PM10 by 80% within 10 minutes while maintaining a low level of ozone during air purification process.
UR  - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=6512
DO  - 10.18517/ijaseit.8.4.6512

RefWorks

RT Journal Article
ID 6512
A1 Meivita, Dewi Nurhaji
A1 Rivai, Muhammad
A1 Irfansyah, Astria Nur
T1 Development of an Electrostatic Air Filtration System Using Fuzzy Logic Control
JF International Journal on Advanced Science, Engineering and Information Technology
VO 8
IS 4
YR 2018
SP 1284
OP 1289
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 Air Pollution, Electrostatic Filter, Fuzzy Logic, Ozone Generator
AB Particulate matter is one of the factors that can affect air quality. The air quality can be determined by the Air Pollution Index, which has several parameters including PM10 and ozone (O3). Air pollution can be overcome by using a filtration system based on electrostatic precipitation when particles are attached to the static charges. In this study, we have developed a prototype of electrostatic filter based on fuzzy logic control to reduce air pollution of particulate matters. The electrostatic filter is an ozone generator consisting of plate-type corona discharge and a high voltage dc generator. The experimental results showed that the more ozone generators used as electrostatic filters, the faster the particulate concentration decreases. However, the use of ozone generators may increase the concentration of ozone in the air that can be harmful to human health. Therefore, we have developed an electrostatic precipitation-based air pollution control using fuzzy logic. Semiconductor gas sensor and laser dust sensor are used as feedback signals for the system in regulating the amount of charges released by ozone generators. Implementation of this control system can reduce the particulates of PM10 by 80% within 10 minutes while maintaining a low level of ozone during air purification process.
LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=6512
DO  - 10.18517/ijaseit.8.4.6512