基于磁通门磁力计的油气管道多缺陷智能识别分类方法研究  

Intelligent identification and classification methods of oil and gas pipeline defects by fluxgate magnetometry

作　　者：万勇[1] 王永智 杨勇[3] 刘超[3] 戴永寿[1] WAN Yong;WANG Yongzhi;YANG Yong;LIU Chao;DAI Yongshou(College of Oceanography and Space Informatics,China University of Petroleum, Qingdao 266580, China;College of Control Science and Engineering, China University of Petroleum, Qingdao 266580, China;Sinopec Shengli Oilfield Technology Testing Center, Dongying 257000, China)

机构地区：[1]中国石油大学(华东)海洋与空间信息学院,山东青岛266580 [2]中国石油大学(华东)控制科学与工程学院,山东青岛266580 [3]中国石化股份胜利油田分公司技术检测中心,山东东营257000

出　　处：《哈尔滨工程大学学报》2021年第9期1321-1329,共9页Journal of Harbin Engineering University

基　　金：国家重点研发计划(2016YFC0802302).

摘　　要：为保障管道的正常运行并及时对管道缺陷进行防治,本文基于金属磁记忆检测技术的原理,利用磁通门磁力计采集了管道漏磁信号,计算并选取多种特征量,包括磁感应强度峰峰值、最大值、最小值、平均值、能量、面积、梯度最大值、梯度平均值、小波包能量。使用协同表示分类方法、传统支持向量机方法和改进支持向量机方法建立了多种管道缺陷分类模型,其中最优模型缺陷的识别率达到了99.5130%,模型训练加识别时间仅3.55 s。结果表明:模型对管道腐蚀缺陷、弯管应力集中缺陷以及焊缝应力集中缺陷的识别是有效的。本研究可应用于实际油田管道分类,并为缺陷分类领域的研究提供一定的参考。Ensuring the normal operation of pipelines and preventing pipeline defects before they occur are important tasks in oilfields.Metal magnetic memory detection technology may be especially helpful in these endeavors.In this paper,a fluxgate magnetometer is first used to collect pipeline magnetic flux leakage signals.Then,various characteristic quantities,including magnetic induction peak,maximum value,minimum value,average value,energy,area,maximum gradient,average gradient,and wavelet packet energy,are calculated,and the most representative properties are selected.Finally,three methods,namely,the collaborative representation classification method,the traditional support vector machine method,and the improved support vector machine method,are employed to establish several pipeline defect classification models.The defect recognition rate of the optimal model could reach 99.5130%,with the model training and recognition time being only 3.55 s.Results show that the optimal model can effectively identify pipeline corrosion and defects,as well as bend and weld stress concentration defects.This study may be applied to actual oilfield pipeline classification and provides a reliable reference for future research on defect classification.

关 键 词：金属磁记忆 支持向量机 协同表示分类 管道缺陷 腐蚀 焊缝 应力集中 分类 

分 类 号：TE973[石油与天然气工程—石油机械设备]