漏磁内检测数据中的管壁缺陷特征提取方法
Method of Feature Extraction for Flaws in Pipeline Magnetic Flux Leakage Data
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摘要: 提出一种管壁漏磁数据的管道缺陷特征提取方法, 该方法利用管道内检测装置的轴向数据作为特征提取数据, 通过磁场强度和像素的映射关系将单轴漏磁数据转换成灰度图像, 并对图像进行滤波处理, 通过简单判断找出缺陷的可能位置, 再用一个检测阈值对图像进行二值化处理, 然后通过连通和链码确定缺陷的边界, 实现缺陷特征的提取.最后以一个实际含有缺陷的灰度图像为例验证了提出方法的有效性.Abstract: A method for the feature extraction of flaws in magnetic flux leakage data of pipeline is proposed in this paper. The method takes the data from the inspection device of the pipeline as the data for feature extraction. The data is converted into gray image by the relation of magnetic density and pixel, and then the image is filtered. Then, the possible positions of pipeline flaws are found by simple judgment. Binary process of the image by using the suitable threshold is applied to grayscale images. The pipeline flaws' boundary is determined by the information of connectivity and chain code, and the type of flaws is also determined according to the sensors of inspection device.