基于SVM与混沌模型的腐蚀深度预测

Pipeline of oil and gas have an increase risk because of pipeline punctures and rupture caused by corrosion. Therefore, it is very important to have a reliable way for pipeline corrosion prediction. The corrosion depth prediction models that based on the support vector machines and based on chaos were introduced in this paper. A real example was given in this paper, and the corrosion data were obtained by electricity probe. The predicted results shows that prediction has a more high precision. The prediction ways based the support vector machines and chaos are reasonable in the corrosion research, which can supply a scientific basis for pipeline safety management, service life prediction and repair.