摘要
应用漏磁检测仪进行埋地油气管道腐蚀检测和识别,叙述了检测仪的硬件采集和信号处理过程。在直径273 mm的管道表面上加工人工缺陷,采集缺陷漏磁场信号,进行处理和转化为漏磁场云图,从信号和云图两者来分析漏磁场,提出了缺陷漏磁场的干扰消除方法、影响因素补偿技术和缺陷漏磁场图像的截取,并分别获得较好的效果,分析了缺陷定性和定量识别的方法,研究了缺陷外形参数量化的方法,得出了缺陷外形量化的数学模型,试验验证缺陷识别的效果,证明整个过程和方法有效可行,大大提高了管道缺陷检测和量化的精度。
The magnetic flux leakage （MFL） detection instrument for pipeline was used to detect and identify the underground oil-gas pipe erosion defects. The hardware, sampling and signal processing of the instrument were described. Some man-made defects were fabricated on the pipeline of 273 mm diameter, and MFL signals of defects were collected and processed, then transformed to the MFL map. The MFL field was analyzed with the MFL signal and map. The interference eliminating method, the technique of compensation for influential factors and the extraction of defect MFL signal or map from the background were put forward with good effect. The qualitative and quantitative recognition methods of erosion defects were analyzed. The quantitative description of defect shape was studied and the mathematical models of defect recognition were obtained. The results show that the whole process and methods are effective, and the precision of defect detection and quantization has been increased.
出处
《钢铁》
CAS
CSCD
北大核心
2006年第4期62-65,70,共5页
Iron and Steel
关键词
漏磁场
管道
腐蚀缺陷
图像
识别
magnetic flux leakage field
pipeline
erosion defect
image
recognition
