Progress in Research on Magnetic Flux Leakage Data Processing and Defect Identification Quantification Methods

Magnetic flux leakage (MFL) method is one of the most stable nondestructive on-line testing techniques used to assess the health of oil and gas pipelines. The methods and steps of MFL data pre-processing are described from four aspects: channel baseline correction, outlier discrimination, data gap recovery and filtering. According to the dominant characteristics such as the peak-valley value of the defect in MFL data, the essential characteristics of the defect signal under different feature extraction methods are summarized. The defect inversion models based on support vector machine, neural network, image processing and morphology are introduced. Finally, the future research directions of MFL signal processing was prospected from two aspects: data pre-processing and defect identification quantification.