Abstract
A system based on Artificial Neural Networks (ANN) is proposed to detect and diagnose multiple leaks in a pipeline leaks by recognizing the pattern of the flow using only two measurements. A nonlinear mathematical model of the pipeline is exploited for training, testing and validating the ANN-based system. This system was trained with tapped delays in order to include the system dynamics. Early results demonstrate the effectiveness of the approach in the detection and diagnosis of simultaneous multiple faults.
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References
Ashton, S.A., Shields, D.N., Daley, S.: Fault Detection in Pipelines using Nonlinear Observers. In: UKACC Int. Conf. on Control IEE Conf., vol. 455, pp. 135–140 (1998)
Belsito, S., Lombardi, P., Andreussi, P., Banerjee, S.: Leak Detection in Liquefied Gas Pipelines by Artificial Neural Networks. AIChE J. 44(12), 2675–2688 (1998)
Billman, L., Issermann, R.: Leak Detection Methods for Pipelines. Automática 23(3), 381–385 (1987)
Blanke, M., Frei, Ch., Kraus, F., Patton, R.J., Staroswiecki, M.: What is Fault Tolerant Control? Safeprocess 35, 123–126 (2000)
Crowther, W.J., Edge, K.A., Burrows, C.R., Atkinson, R.M., Wollons, D.J.: Fault Diagnosis of a Hydraulic Actuator Circuit using Neural Networks an Output Vector Space Classification approach. Proc. Inst. Mech. Eng. Part I: J. Syst. Control Eng. 212(11), 57–68 (1998)
Izquierdo, J., López, P.A., Martínez, F.J., Pérez, R.: Fault Detection in Water Supply Systems using Hybrid Modelling. Mathematical and Computer Modelling 46, 341–350 (2007)
Verde, C.: Multi-leak Detection and Isolation in Fluid Pipelines. Control Eng. Practice 9, 673–682 (2001)
Verde, C.: Accommodation of Multi-leaks Positions in a Pipeline. Control Eng. Practice 13, 1071–1078 (2005)
Verde, C., Visairo, N., Gentil, S.: Two Leaks Isolation in a Pipeline by Transient Response. Advances in Water Resources 30, 1711–1721 (2007)
Verde, C., Morales-Menendez, R., Garza, L.E., De La Fuente, O., Vargas-Martínez, A., Velasquez, P., Aparicio, C., Rea, C.: Multi-Leak Diagnosis in Pipelines - A Comparison of Approaches. In: Special Session of the Mexican Int. Conf. on Artificial Intelligence, pp. 352–357 (2008)
Visairo: Detección y Localización de Fugas en un Ducto, PhD Thesis, SEP-CENIDET, México (2004)
Zhidkova, M.A.: Gas Transportation in Pipelines. In: Internal report written in Russian. Naukov, Dumka, USSR (1973)
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Barradas, I., Garza, L.E., Morales-Menendez, R., Vargas-Martínez, A. (2009). Leaks Detection in a Pipeline Using Artificial Neural Networks. In: Bayro-Corrochano, E., Eklundh, JO. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2009. Lecture Notes in Computer Science, vol 5856. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10268-4_75
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DOI: https://doi.org/10.1007/978-3-642-10268-4_75
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