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Study On Submarine Pipeline Corrosion Detection And Corrosion Prediction

Posted on:2008-05-19Degree:DoctorType:Dissertation
Country:ChinaCandidate:G HuFull Text:PDF
GTID:1101360215990722Subject:Metallurgical engineering
Abstract/Summary:PDF Full Text Request
This research project comes from the State Hi-Tech Research and Development Plan (863) "Submarine Pipeline's Exterior Detection Devices and Detection Technology. "(2004AA602210)The marine environment is an extremely corrosive environment. The oil and gas transmission pipelines's corrosion in the marine environment are more serious than that on land. Physical, chemical and biological factors all could lead to corrosion of the submarine pipeline. Once the submarine pipeline corroded, it may be very difficult and expensive to maintain. Corrosion of the submarine pipeline is a long and slow process. With the increase of pipeline's service time, is the pipeline corroded? Can sacrificial anode work in a normal state? Does cathodic protection current density meet the design requirements? All these results will affect the integrity of pipeline during its design life. To study on the pipeline's corrosion features in the marine environment, real-time detect pipeline corrosion, and predict pipeline's corrosion rate, which is important to the design, operation and maintenance of pipeline cathodic protection system.In this paper, a non-contact detection method was the first time put forword for the pipeline with cathodic protection and a non-linear predictive model for pipeline corrosion was established. The study is divided into three main parts, including simulation calculation of cathode protection field. non-contact measurement of pipeline potential and corrosion rate prediction of pipeline. Firstly, boundary element method was used to calculate the potential distribution of corrosion electric field according to the anodes distribution on pipelines, and a database of environmental field and pipeline potential was established. Based on the virtual instrument technology, environment potential distribution measurement system was developed, which was carried by a ROV to measure the electric filed distribution along the pipeline, then the surface protection potential and current density were inversed by the above database, and then to fulfill pipelines damage points detection. Finally, based on the BP neural network model, a neural network prediction model in the marine environment was established. This model can be used to predict the rate of corrosion of pipelines.Numerical calculation study was based on the boundary element method (BEM). The corrosion electric field can be calculated. Matlab was used to calculate the potential distribution of corrosion electric field, and a database of environmental field to pipeline potential was established according to the calculated results. It through some examples showed that the simulation software was effective and feasible, laid an important foundation for non-contact measurement pipelines.Non-contact measurement was based on the significant correlation between the surrounding potential of seabed pipelines and pipeline corrosion. Through potential measure and data processing, pipeline corrosion can be known. The all-solid-state hardware AgCl electrodes used as the reference electrode. Ship-take workstation with integrated data acquisition card was used to acquire data and process signal. Labview software was used to develop real-time measurement software. Measurement results was inversed to get the pipeline surface potential, thus non-contact measurement cathodic protection potential was realised. Simulation tests in Qingdao coastal and field tests in Bohai Sea were done and the test results showed that the system within four meters to the pipeline could accurately measure electric field around the cathodic protected pipeline and detect its surface damage.Submarine Pipeline corrosion rate prediction is based on artificial neural network technology. Pipeline and the marine environment as a common factor affecting the rate of corrosion, BP artificial neural network algorithms was used to establish marine environment and the pipeline steel corrosion rate prediction model. Forecast software Calling MATLABScript nodes. MATLAB toolbox neurons completed the design of the core. The forecasting system can be used to predict the corrosion rate of steel pipe in the sea. Therefore, the application in the field of marine corrosion and protection is a general trend.Study on non-contact measurement system and submarine pipeline corrosion rate prediction system.Real-time monitoring of the effectiveness and long-term corruption corrosion rate prediction can be realized for the pipeline cathodic protection system, which has great value to know submarine pipeline operations and corrosion, and find some hidden danger to repair in time. It will provide basic data and basis for decision-making for the safe transportation and scientific management of marine oil and gas, and improvement of the pipeline's anti-corrosion system.
Keywords/Search Tags:Metal Corrosion, Cathodic Protection, Boundary Element Method, Artificial Neural Networks, Matlab, LabVIEW
PDF Full Text Request
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