A Study On Detecting The Presence Of Sulfate Reducing Bacteria Using Artificial Neural Network Based On Electronic Sensor Data
Sulfate Reducing Bacteria (SRB) are nonpathogenic and anaerobic bacteria (cannot grow with the presence of oxygen). SRB can produce enzyme to accelerate the reduction of sulfate compounds to hydrogen sulfide (H2S) that corrodes metal. There are a few methods of detecting SRB such as laboratory an...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2012
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| Subjects: | |
| Online Access: | http://eprints.usm.my/61081/1/24%20Pages%20from%2000001780134.pdf |
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| Summary: | Sulfate Reducing Bacteria (SRB) are nonpathogenic and anaerobic bacteria (cannot
grow with the presence of oxygen). SRB can produce enzyme to accelerate the
reduction of sulfate compounds to hydrogen sulfide (H2S) that corrodes metal. There
are a few methods of detecting SRB such as laboratory analysis and field test kit but
the procedures are costly and take longer time, whereby the detection period can
reach more than 12 hours. This research is a study on the possibility of using
electronic sensor to detect SRB. A few experiments are carried out using medium
with nutrient agar inside 28 ml universal bottle to determine the presence of SRB.
The sensors that are used in this research are H2S gas sensor, temperature sensor and
humidity sensor. Data in the form of voltage, temperature and humidity from these
sensors are collected and stored in a personal computer (PC). These data are
analyzed using Analysis of Variance (ANOVA) to determine the coefficient of
determination for SRBs' growth. Results show that voltage from H2S sensor and
temperature from temperature sensor contribute to the presence of SRB. |
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