摘要
漏磁检测技术是油气管道损伤检测中最常用的方法之一。其是一种利用磁敏传感器检测漏磁信号进而探测管道缺陷的无损检测技术。首先介绍了漏磁检测的原理和操作流程,而后综述了近年来漏磁检测技术在信号预处理、异常识别以及缺陷量化3方面取得的重要成果。其中,重点介绍了基于深度学习的异常识别和缺陷量化方法,并分析了这些方法存在的不足。最后,对管道漏磁检测的未来发展进行了展望。
Magnetic flux leakage detection technology is one of the most commonly used methods for damage detection in oil and gas pipelines.It is a nondestructive testing technology that uses magnetic sensors to detect magnetic flux leakage signals and then detect pipeline defects.This paper first briefly introduced the principle and operation process of magnetic flux leakage testing,and then summarized the important achievements of magnetic flux leakage testing technology in signal preprocessing,anomaly recognition,and defect quantification in recent years.Among them,anomaly recognition and defect quantification were the key points in the magnetic flux leakage detection process.The focus was on introducing deep learning based anomaly recognition and defect quantification methods,and then analyzing the current shortcomings of these methods.Finally,the future development of pipeline magnetic flux leakage testing was prospected.
作者
左万君
戴西斌
吴昌玉
ZUO Wanjun;DAI Xibin;WU Changyu(Jiangxi General Inspection and Certification Institute of Special Equipment Inspection and Testing,Nanchang 330000,China)
出处
《无损检测》
CAS
2024年第3期56-63,共8页
Nondestructive Testing
关键词
无损检测
漏磁检测
神经网络
异常识别
缺陷量化
nondestructive testing
magnetic flux leakage testing
neural network
abnormal identification
defect quantification
