@inproceedings{scholars1250,
           pages = {553--557},
         journal = {2010 The 2nd International Conference on Computer and Automation Engineering, ICCAE 2010},
            year = {2010},
           title = {Early detection method of corrosion on buried steel gas pipeline using wireless sensor network},
         address = {Singapore},
             doi = {10.1109/ICCAE.2010.5451824},
            note = {cited By 5; Conference of 2nd International Conference on Computer and Automation Engineering, ICCAE 2010 ; Conference Date: 26 February 2010 Through 28 February 2010; Conference Code:80373},
          volume = {3},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77952667706&doi=10.1109\%2fICCAE.2010.5451824&partnerID=40&md5=8bfc227e65e1f6cd780303487c1691b2},
        keywords = {Buried pipelines; Changing temperature; CO2 corrosion; Early detection; Gas flows; Maintenance work; Operational costs; Pipe burst; Pipeline monitoring; Proactive maintenance; Rate models; Reference models; Steel gas pipelines; Wireless sensor, Computer simulation; Corrosion rate; Maintainability; Sensors, Pipelines},
        abstract = {Early detection on any abnormality on the pipeline such as leakage is essential for efficient management. As to date, wireless sensors have been widely used to gather information in monitoring reliability of the pipeline. The commonly used sensors are temperature and pressure sensors. One of the issues that relate to pipeline monitoring is the reactive rather than proactive maintenance approach to leakage and abnormality. The objective of this research is to develop a method for early detection of corrosion, which the buried pipeline is exposed to changing temperatures and gas flow pressures. This will ensure that maintenance works can be done quickly to prevent pipe burst, as well as to minimize operational cost. The NORSOK CO2 corrosion rate model is used as a basic reference model. Simulation will be developed to see the performance of the model. {\^A}{\copyright}2010 IEEE.},
          author = {Rahman, M. S. A. and Hasbullah, H.},
            isbn = {9781424455850}
}