Application and Development of Oil Pipeline Magnetic Flux Leakage Detection Based on Machine Learning Algorithm

In order to evaluate the condition of oil pipeline, the main nondestructive testing method currently used is magnetic flux leakage testing technology. The magnetic flux leakage data of pipeline are collected by magnetic flux leakage detector, and the magnetic flux leakage signal curve is drawn according to the data, and then the variation characteristics of the curve are judged manually to judge the defects on pipeline components. This method has great error and low efficiency. With the rapid development of artificial intelligence technology, many magnetic flux leakage detection technologies based on machine learning algorithms have been proposed, which can realize more efficient and accurate intelligent detection. In this paper, the intelligent methods of pipeline magnetic flux leakage detection are summarized. At first, the basic principle of magnetic flux leakage detection is briefly introduced, and then the detection methods combining multiple physical fields and the methods using machine learning in pipeline magnetic flux leakage detection are emphasized in detail. Finally, the summary is made, and the problems that the intelligent methods still face are discussed.