Research Of Submarine Pipeline Corrosion Status Modeling Based On Non-contact Detection

In recent years, large-scale of subsea pipelines are used, and all kinds of leakage accidents occur frequently, causing serious environmental pollution and huge economic losses. Statistics show that corrosion of the pipeline is one of the main causes of the accident, so the detection of submarine pipeline corrosion problem has become a major research project in the engineering field nowadays. Accurate and effective corrosion detection is great significance.Studies have shown that the electric field distribution around underwater pipeline are significantly correlated with and pipeline corrosion status. In this article, there are analysis and modeling of underwater non-contact detecting data, using the model to analyze the electric field data of non-contact detection that ROV acquires along the pipeline, to locate the corrosion position and eventually obtain the carrion status. In this way, the pipeline can be monitored timely and protected accurately and effectively. On the basis of this idea, in the article, the following two aspects of work has mainly completed:(1) The establishment of mathematical model of the corrosion electric field and the study on simulation algorithm. In the article, analyzing the relationship between submarine pipeline corrosion status and the damage state of pipeline corrosion protection layer, the conductivity of seawater and sacrificial anode protection current strength, and prove the significant correlation between submarine pipeline corrosion status and the electrode potential. And then put forward the method to determine subsea pipeline corrosion status based on the non-contact measurement of the electric field of seawater environment. First, make the mathematical model of corrosion electric potential distribution, followed use the numerical method to deduced the solution algorithm of the cathodic protection system model. Further calculate the electric field distribution of the marine environment and the surface potential of submarine pipelines.(2) The study on the submarine pipeline corrosion status’s judgement based on BP neural network. By measure the potential of the marine environment, the form the database, and take it as training sample to establish the BP neural network. As a result, obtain the nonlinear relationship between the potential distribution around underwater pipeline and subsea pipeline corrosion status, and obtain the corrosion status. The experimental results demonstrate the feasibility of neural network algorithm used in the subsea pipeline cathodic protection systems. The nonlinear mapping results meets the accuracy requirements, and the relative error is less than 0.10.