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AASCIT Communications | Volume 1, Issue 4 | Jan. 10, 2015 online | Page:120-124
A Novel Approach to Detect Sulphate-Reducing Bacteria - Main Contributor of Microbiologically Influenced Corrosion
Sulphate-reducing bacteria (SRB) is an anaerobic microorganism that has long been identified as one of the main contributor to the pipeline corrosion problem experienced in gas, petroleum, and water industry. The corrosion issue causes billions of dollars worth of damage each year and may lead to the deterioration of the quality of oil and water under the corroded pipeline. Currently, there are few kits and techniques available in the market targeted for early detection of SRB. Nevertheless, those detection methods have some crucial drawbacks, such as long detection period or have difficulty to conduct field test. Thus, this article proposes a rapid, accurate, and portable embedded-based electronic system to detect the presence of SRB. Preliminary experiment was conducted in lab to evaluate the function and the capability of the system. Based on the findings, the proposed technique was proven to be able to identify whether SRB presence in a presented sample within 1 hour. In addition, the system also includes data logging functionality to help users monitor the growth of SRB from time to time to reduce the damage caused by the corrosion.
Earn Tzeh Tan, School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Penang, Malaysia.
Zaini Abdul Halim, School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Penang, Malaysia.
Sulphate-Reducing Bacteria, Corrosion, Embedded System, Artificial Neural Network
World Corrosion Organization. (2014) Corrosion Costs and the Future. http://corrosion.org.
Ghazy, E. A., Mahmoud, M. G., Asker, M. S., Mahmoud, M. N., Abo Elsoud, M.M., and Abdel Sami, M. E. (2011) Cultivation and Detection of Sulfate Reducing Bacteria (SRB) in Sea Water. Journal of American Science. 7, pp. 604-608.
Postgate, J. R. (1984) The Sulphate reducing bacteria. Cambridge: Cambridge University Press.
Biosan Laboratories, INC. (2014) Sani-Check SRB: Test Kit for Counting Sulfate Reducing Bacteria. https://www.biosan.com/sulfate-bacteria-test-kit.
Rastogi, G., and Sani, R. K. (2011) Molecular Techniques to Assess Microbial Community Structure, Function and Dynamics in the Environment. Microbes and Microbial Technology: Agricultural and Environmental Applications. Springer.
Eitan, B. D., Brenner, A., and Kushmaro, A. (2007) Quantification of Sulfate-reducing Bacteria in Industrial Wastewater, by Real-time Polymerase Chain Reaction (PCR) Using dsrA and apsA Genes. Microbial Ecology. 54, pp. 439-451.
Tan, E. T., Abdul Halim, Z., Darah, I., Abdul Rahim, R., Mohamad Saleh, J., and Chandran, U. D. (2012) Artificial Neural Network-based Electronic Nose for the Detection of Sulfate-reducing Bacteria. Sensors and Transducers. 17, pp. 50-59.
Tan, E. T., and Abdul Halim, Z. (2012) Development of an Artificial Neural Network System for Sulphate-reducing Bacteria Detection by using Model-based Design Technique. 2012 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS 2012). Kaohsiung, Taiwan, pp. 352-355.
Arcticle History
Submitted: Dec. 19, 2014
Accepted: Jan. 7, 2015
Published: Jan. 10, 2015
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