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51318-10975-Embedded Condition Monitoring System for Tank Coatings

Picture for Embedded Condition Monitoring System for Tank Coatings
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A technology to detect corrosion damage and estimate extent and location within an enclosed volume. This coating condition monitoring (CCM) system is a network of sensors that measure conditions and electrochemical parameters to evaluate the health of coating and substrate for steel plates and tanks.

Product Number: 51318-10975-SG
Author: Kevin Farinholt / Michael Desrosiers / Mark Kim / Ethan Thompson / Fritz Friedersdorf
Publication Date: 2018
Industry: Pipelines, Tanks, and Underground Systems
$0.00
$20.00
$20.00

A combination of material coating and cathodic protection systems are used to inhibit corrosion of steel tanks and enclosures on Navy ships. The state of these coating systems is often assessed through visual inspection of the confined space by human inspectors that enter tanks while vessels are in depot. Use of an automated or in-situ inspection method has the potential to reduce operating and maintenance costs by informing maintainers of specific tanks or enclosures that require further inspection or repair through condition based assessments. One such technology has been developed, using electrochemical sensors and stochastic models to detect the onset of damage and estimate the extent and location within an enclosed volume. This coating condition monitoring (CCM) system is composed of a network of sensor nodes that measure environmental conditions and electrochemical parameters to evaluate the health of coating and substrate for steel plates and tanks. Laboratory testing has shown that the technique works for 3 dimensional tanks treated with ultra-high solids protective coatings, and to length scales of at least 5.5 meters. A prototype of the sensors and embedded electronics has been built and tested in a physical scale model tank, and is currently being scheduled for relevant environment testing on a near full-scale test tank in open seawater. Performance of the prototype system under laboratory conditions will be presented, along with preliminary results from relevant environment testing on a representative ballast tank model.

Key words: Corrosion sensors, structural health monitoring, tank coating, electrochemistry, diagnostics.

A combination of material coating and cathodic protection systems are used to inhibit corrosion of steel tanks and enclosures on Navy ships. The state of these coating systems is often assessed through visual inspection of the confined space by human inspectors that enter tanks while vessels are in depot. Use of an automated or in-situ inspection method has the potential to reduce operating and maintenance costs by informing maintainers of specific tanks or enclosures that require further inspection or repair through condition based assessments. One such technology has been developed, using electrochemical sensors and stochastic models to detect the onset of damage and estimate the extent and location within an enclosed volume. This coating condition monitoring (CCM) system is composed of a network of sensor nodes that measure environmental conditions and electrochemical parameters to evaluate the health of coating and substrate for steel plates and tanks. Laboratory testing has shown that the technique works for 3 dimensional tanks treated with ultra-high solids protective coatings, and to length scales of at least 5.5 meters. A prototype of the sensors and embedded electronics has been built and tested in a physical scale model tank, and is currently being scheduled for relevant environment testing on a near full-scale test tank in open seawater. Performance of the prototype system under laboratory conditions will be presented, along with preliminary results from relevant environment testing on a representative ballast tank model.

Key words: Corrosion sensors, structural health monitoring, tank coating, electrochemistry, diagnostics.

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The cathodic protection (CP) system of an offshore complex was modeled using boundary element analysis. Results of the simulation were validated against existing inspection data and used to optimize the established CP inspection program.
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