Tube Defect Leakage Magnetic Field Characteristics Analysis And Detection Method

Both the distributions and the geometric characteristics obtained from the corrosion and defect of metal pipeline are the important references for the operational state assessment of pipeline.In order to extract the defects' information from the leakage magnetic field signals, we take the defect leakage magnetic field as a research object and compute the distributions of the leakage magnetic field by using the finite element analysis. We assemble a device for detection the defect leakage magnetic field of specimen. We make the diagram of the plane distribution of the defects leakage magnetic field and discuss the experimental results. The works and results of thesis are as follow:The modeling method of the leakage magnetic field by finite element analysis is introduced. By using the Ansoft software, the magnetic field distributions for various cases, such as the depth changing of the crack-type defects, the width changing of the rectangular type defects and the curvature radius changing of the corrosion pits type defects, are calculated respectively. The relation between the leakage magnetic field and the changes of geometry parameters is also studied. Moreover, the differences of measurement results located the upper or lower surface of the sample are analyzed respectively.Based on the finite element analysis results, the scheme to detect the leakage magnetic field from the surface crack with Hall element is made and the device is assembled respectively, the basic images of leakage magnetic field are gotten. The results of leakage magnetic field detection influenced by the crack depth and the height of the probe lift-off are discussed. The results also provide a'value reference to choose best location of the sensors for multi-channel data acquisition.In order to detect the distribution profile of defects, pseudo-synchronous multi-channel data acquisition method is introduced base on LabVIEW. Through the parameters control of stepper motor, signals and coordinate of sensors location could be acquire synchronously. After data processing for the detection, the plane diagrams of the distribution of leakage magnetic field from multi-crack-type defects and multi-hole-type defects are made. The defects can be recognized clearly and intuitively by the colorful imaging as well as Magneto-Optical imaging methods.