Abstract
For long distance pipelines of oil and gas pipeline, the magnetic flux leakage detection in data storage and discriminant quantity is larger and the problem of recognition is slow. By using the convolution neural network, the detection data of the leakage magnetic field is processed to realize the detection of magnetic leakage and the intelligent processing of the data discriminant. The method of the pipeline magnetic flux leakage detection image formation based on the artificial intelligence achieving leakage magnetic detection imaging, and it is the earlier processing of the intelligence identification. The original image is analyzed and pretreated by the imaging processing method of image corrosion and grayscale. The method is highlights the image features, and it makes the pipeline features display clearly, which provides a clearly image feature for the intelligent identification of pipeline features and improves the efficiency of intelligent identification of the magnetic flux leakage data.
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