A Research On Adaptive Imaging Method Of The Pipeline Magnetic Flux Leakage Signals

The in-pipe detector arrangement uses a plurality of sensors to collect data in parallel.The actual detection of the amount of data has dozens of TB or more.When professionals analysis detection data,they will face a huge workload which will leads difficulty and low efficiency.Therefore,the implementation of visualization will have dominant advantages.The defect can be displayed to the inspector in a variety of view modes such as curve view,grayscale view and color view.The defects can be analyzed and identified automatically,such as defects,welds,flanges,etc.,so that the inspectors can quickly find defects and manual analysis,greatly improve work efficiency.In this thesis,based on the characteristics of magnetic flux leakage detection data of the pipeline,It mainly studies the interpolation of magnetic flux leakage data,gray-scale transformation and pseudo-color image generation.It establishes an adaptive processing flow which makes the graph more recognizable.Gray-scale image and pseudo-color image can be displayed by the adaptive visualization system which is designed during the study.The specific research contents are as follows:First,multi-scale segmentation adaptive interpolation method is used to achieve the interpolation processing of magnetic flux leakage data.Based on the research and analysis of many kinds of interpolation methods,the advantages and disadvantages of several classical data interpolation methods are summarized.Combined with the characteristics of these methods,the multi-scale piecewise adaptive interpolation method is used to deal with magnetic flux leakage Data and generate curve graph.Second,the gray-scale image of the magnetic flux leakage data is generated and image enhancement is carried out.This chapter studys the mathematical model of the gray-level data of magnetic flux leakage data,and achieves the display of the gray-scale image.The image passivation and the image sharpening methods are used to carry on the digital image enhancement processing,The best gray-scale data of magnetic flux leakage is obtained.Thirdly,compared with a variety of pseudo-color image technologys,we establishehed a segmentation adaptive method which is based on density partition method to display the color map.A variety of classical pseudo-color techniques are used to further enhance the gray-scale image.Different pseudo-color techniques are compared and analyzed,and a segment adaptive pseudo-color enhancement technique based on density segmentation is designed.Meanwhile,the gray-scale and color-scale can be corresponded.Fourth,the establishment of magnetic flux leakage monitoring data adaptive imaging system.This chapter establishes a self-adaptive imaging system of pipeline magnetic flux leakage detection signal,including the establishment of each module of the system and displays the adaptive imaging of magnetic flux leakage data.By using the powerful image function of matlab,the system of magnetic flux leakage data visualization is designed,which achieves the curve graph,gray image and pseudo color image display of magnetic flux leakage data.It completes the analysis and judgment of the defect data.This thesis presents a variety of self-adaptive processing methods for magnetic flux leakage(MFL)detection data to realize the best display of magnetic flux leakage curve,gray scale image and pseudo color image which greatly improves the accuracy of the defect analysis and efficiency,reducing the professional staff in the analysis of subjective factors of error.