In this paper, a Cu-Zn galvanic sensor is developed for the internal-pipeline corrosion on-line monitoring system, in which the internal-pipeline corrosion state is grasped based on monitoring the corrosion capability of the internal electrolyte environment. The galvanic corrosion behaviors of the sensor in a simulated seawater environment are investigated using a 50-m-long pipeline in the laboratory. After long-term test and analysis, the effective working period of the sensor is confirmed, and the influence caused by the oxidative film on the electrode working face is eliminated by an amendatory correlation coefficient relating to the electrolyte flow rate and the temperature. A complex and non-linear relationship, among the electric current of the galvanic sensor, flow rate and temperature of the electrolyte, the concentration of dissolved oxygen (DO) in pipeline, is acquired. Finally, back-propagation artificial neural network (BP-ANN) is employed to estimate the concentration of DO of the electrolyte according to the measured factors such as the electric current of the galvanic sensor, flow rate and temperature of the internal electrolyte. Based on the comparison between corrosion coupons test and monitoring system, it is affirmed that a more reasonable evaluation of internal-pipeline corrosion can be proposed in the monitoring system.
Experimental study on seawater-pipeline internal corrosion monitoring system
Experimentelle Untersuchung eines Korrosionsüberwachungssystems für Seewasser-Pipelines
Sensors and Actuators, B, Chemical ; 135 , 1 ; 375-380
2008
6 Seiten, 9 Bilder, 2 Tabellen, 20 Quellen
Aufsatz (Zeitschrift)
Englisch
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