Research on Magnetic Flux Leakage Detection Method for Subsea Pipeline

The intelligent pig based on the (MFL) is frequently used for in-line inspection of transportation pipelines. The article discusses the key technology of an MFL tool that includes the sensors structure, the constitution of tool hardware, software and the analysis method of MFL signal.

Evaluation of Surface Cracks Using Magnetic Flux LeakageTesting

The magnetic field distribution characteristics of surface cracks with various widths are discussed based on finite element (FEM) results. The crack depth was 0.20 mm, the width range was from 0.02 to 1.00 mm. The results showed that crack width and lift-off (the distance between surface and sensor) will influence signals. Discussed in this paper is the influence of various lift-off parameters on the peak to peak values of the normal component in magnetic flux leakage testing. The effects can be applied to evaluate surface breaking cracks of different widths and depths. An idea is presented to smooth narrow, sharp crack tips using alternating current (AC) field magnetization.

Magnetic Flux Leakage Course of Inner Defects and Its Detectable Depth

As a promising non-destructive testing(NDT)method,magnetic flux leakage(MFL)testing has been widely used for steel structure inspection.However,MFL testing still faces a great challenge to detect inner defects.Existing MFL course researches mainly focus on surface-breaking defects while that of inner defects is overlooked.In the paper,MFL course of inner defects is investigated by building magnetic circuit models,performing numerical simulations,and conducting MFL experiments.It is found that the near-surface wall has an enhancing effect on the MFL course due to higher permeability of steel than that of air.Further,a high-sensitivity MFL testing method consisting of Helmholtz coil magnetization and induction coil with a high permeability core is proposed to increase the detectable depth of inner defects.Experimental results show that inner defects with buried depth up to 80.0 mm can be detected,suggesting that the proposed MFL method has the potential to detect deeply-buried defects and has a promising future in the field of NDT.

Influence of Slot Defect Length on Magnetic Flux Leakage

A key issue, which influences the applications of magnetic flux leakage testing, is defect quantification. There have been many research on the relationship between width, depth and magnetic flux leakage of slot defect. However, the length factor is often ignored. The relationship between characteristics of defect leakage field and defect length was investigated. The magnetic flux leakages of a series of plate specimens with the same width, same depth and different length slot defects were tested under the same magnetizing conditions. Testing results show that defect length is an important parameter needed to consider in quantifying defects.

Coefficients de-noising with wavelet transform for magnetic flux leakage data obtained from oil pipeline

This paper considers the problem of noise cancellation for the magnetic flux leakage (MFL) data obtained from the inspection of oil pipelines. MFL data is contaminated by various sources of noise, and the noise can considerably reduce the detectability of flaw signals in MFL data. This paper presents a new de-noising approach for removing the system noise contained in the MFL data by using the coefficients de-noising with wavelet transform. Experimental results are presented to demonstrate the advantages of this de-noising approach over the conventional wavelet de-noising method.

Numerical analysis and experimental research on detection of welding defects in pipelines based on magnetic flux leakage

Regular inspection of long-distance oil and gas pipelines plays an important role in ensuring the safe transportation of oil and gas,and inspection on welding defects is an important part of the inspection process.Magnetic flux leakage(MFL)is an electromagnetic non-destructive testing technique which has been commonly utilized to detect welding defects in pipelines.In the present study,Maxwell electro-magnetic simulation software was used to carry out numerical study on the welding defects in pipelines,including incomplete penetration and undercut.TheФ406 pipeline with a wall thickness of 7 mm was selected as the study case to establish the numerical model.Setting the life-off value at 1 mm,the distribution of magnetic leakage field was investigated for pipeline without defect,pipeline with incomplete penetration defect and pipeline with undercut defect respectively,the characteristic values describing the depth and width of defects were found.Furthermore,quantified equations which can be used to describe the defect depth were proposed.Finally,experimental research was carried out to validate the effectiveness of the numerical model,and the experimental results showed good consistence with the numerical calculation results.The research results indicate that,it is technically feasible and reliable to diagnose the incomplete penetration and undercut welding defects in pipelines using MFL.

Quantitative Interpretation for the Magnetic Flux Leakage Testing Data Based on Neural Network

In order to interpret the magnetic flux leakage (MFL) testing data quantitatively and size the defects accurately, some defect profiles inversion methods from the MFL signals are studied on the basis of the neural network.Because the wavelet ba- sis function neural network (WBFNN) has good accuracy in the forward calculation and the radial basis function neural network (RBFNN) has reliable precision in the inversion modeling respectively,a new neural network scheme combining WBFNN and RBFNN is presented to solve the nonlinear inversion problem for the MFL data and reconstruct the defect shapes.And such details as the choice of wavelet basis function,the initialization of the weight value and the input normalization are analyzed,the train- ing and testing algorithm for the network are also studied.The inversion results demonstrate that the proposed network scheme has good reliability to interpret the MFL data for some defects.

Key technique of a detection sensor for coal mine wire ropes

Wire ropes,employed extensively in coal mine hoists and transportation systems are subject to damage due to wear,corrosion and fatigue.The extent of damage and the carrying capacity of ropes are closely related to the sense of safety by staff and equipments.Magnetic flux leakage detection method(MFL),as an effective method,is these days widely used in detection of broken strands of wire ropes.In order to improve the accuracy of detection of flaws in wire ropes by magnetic flux leakage(MFL),the effect of the distance between a sensor and the surface of a wire rope(i.e.,lift-off) on detection by magnetic flux leakage was in-vestigated.An analysis of the main principles for the choice of lift-off is described by us and a new method that improves the structure of the detector is proposed from the point of view of the design of a magnetic circuit,to restrain the impact of fluctuations of sensor lift-off.The effect of this kind of method is validated by simulation and computation.The results show that the detection sensitivity is markedly increased by this method.Furthermore,the signal-to-noise ratio(SNR) can be increased by over 28%.This method will lend itself to offer reliable scientific information to optimize the structure of excitation devices and improve the accuracy of MFL detection.

Speed Measurement Feasibility by Eddy Current Effect in the High-Speed MFL Testing

It is known that eddy current effect has a great influence on magnetic flux leakage testing(MFL).Usually,contacttype encoder wheels are used to measure MFL testing speed to evaluate the effect and further compensate testing signals.This speed measurement method is complicated,and inevitable abrasion and occasional slippage will reduce the measurement accuracy.In order to solve this problem,based on eddy current effect due to the relative movement,a speed measurement method is proposed,which is contactless and simple.In the high-speed MFL testing,eddy current induced in the specimen will cause an obvious modification to the applied field.This modified field,which is measured by Hall sensor,can be utilized to reflect the moving speed.Firstly,the measurement principle is illustrated based on Faraday’s law.Then,dynamic finite element simulations are conducted to investigate the modified magnetic field distribution.Finally,laboratory experiments are performed to validate the feasibility of the proposed method.The results show that Bmz(r1)and Bmx(r2)have a linear relation with moving speed,which could be used as an alternative measurement parameter.

一种基于单轴向充磁永磁环励磁的钢丝绳无损检测方法

为提高钢丝绳缺陷检测能力,简化励磁结构,提出一种基于单个轴向充磁永磁环励磁的钢丝绳无损检测方法。通过分析钢丝绳缺陷在单个轴向充磁永磁环励磁方法下产生的漏磁场,得到该方法能通过漏磁场感知缺陷运动方向的结论。在此基础上,利用COMSOL软件对该励磁方式进行有限元建模,通过仿真计算缺陷处漏磁的分布,验证了结论的正确性,分析了影响漏磁场的因素,并结合霍尔元件性能参数,给出了传感器的最佳布置位置。最后,通过设计信号调理电路,结合3D打印实现传感器结构,完成了实验平台搭建。仿真结果表明,对于同一缺陷,基于该励磁方式产生的最大漏磁场明显大于传统方式。实验结果表明,对于10 mm粗的钢丝绳,当霍尔元件布置的提离值为3 mm和8 mm时,均能够通过缺陷处漏磁信号感知钢丝绳运动方向。

拱顶储罐罐顶缺陷漏磁检测技术研究

针对拱顶储罐在长期使用过程中,罐顶因环境因素和储存介质的影响造成内外壁腐蚀损伤而严重威胁储罐安全运行的问题,对拱顶储罐罐顶进行了缺陷漏磁检测技术研究。建立了罐顶漏磁检测三维模型,并采用有限元分析方法对该模型进行求解;分析不同影响因素对漏磁信号特征的影响,通过对漏磁场峰值的拟合,得到了不同影响因素对罐顶缺陷漏磁场的影响规律。结果表明,外壁半球形缺陷漏磁检测信号峰值与缺陷半径符合线性拟合规律,内壁半球形缺陷漏磁检测信号峰值与缺陷半径符合二次拟合规律,加强肋处形成的漏磁检测信号与缺陷检测信号波形相反。通过试验验证了漏磁检测方法能有效检测储罐罐顶的缺陷,并能确定缺陷的深度和位置。

油气管道漏磁数据处理和缺陷识别量化方法的研究进展

漏磁法是最稳定的无损在线检测技术之一,用于评估油气管道的健康状况。从通道基线校正、异常值判别、数据缺口的恢复和滤波四个方面阐述了漏磁数据预处理的方法和步骤;结合漏磁数据缺陷的峰谷值等显性特征,总结了不同特征提取方法下缺陷信号的本质特征;介绍了基于支持向量机、神经网络、图像处理和形态学等方法构建缺陷反演模型。最后,从数据预处理和缺陷识别量化两方面展望了漏磁信号处理未来的研究方向。

改进Canny算子的小管径弯头漏磁缺陷图像量化方法

弯头作为管道的重要组成部件,受流体冲刷侵蚀等形成的缺陷对其安全运行构成威胁。漏磁检测是管道缺陷检测的有效技术,缺陷的精确量化具有重要意义。为了研究小管径弯头不同位置缺陷图像规律,并提高缺陷量化精度,提出一种改进Canny算子的小管径弯头漏磁缺陷图像量化方法。通过建立小管径弯头漏磁内检测仿真模型,分析了弯头不同位置处金属损失缺陷的图像规律。采用形态滤波和OTSU优化Canny算子,结合图像处理方法构建了缺陷图像量化模型,并对弯头不同位置缺陷深度量化做修正处理。实验结果表明,弯头不同位置缺陷在图像上呈现出明显的差异性,量化模型对缺陷长度和宽度的量化具有较高的精度,误差均小于2 mm。缺陷深度的量化误差较大,修正后深度量化的精度为86.34%,满足金属损失缺陷量化精度需求。该方法可实现缺陷漏磁图像量化处理,对管道漏磁缺陷量化具有一定意义。

多通道钢丝绳的漏磁检测信号融合方法

分析了现有钢丝绳漏磁检测系统中存在的损伤信号幅值较小、前端多个磁敏元件处理方式较为简单等问题,提出了一种钢丝绳漏磁检测系统中的多通道信号融合方法。首先从磁敏元件阵列的角度出发,提出了多种磁敏元件阵列方式;其次从信号处理模拟电路的角度出发,设计了多通道信号融合硬件电路;最后,针对钢丝绳进行了实际测试,验证了此方法的可行性。

低压输气管道水驱漏磁内检测可行性研究

本文以解决低压输气管道漏磁内检测时检测器速度过快为目的,提出了以气驱改为水驱的方式进行漏磁内检测的方法,本文首先阐述了漏磁内检测原理及局限、低压输气管道漏磁内检测难点及策略,然后从前期准备、漏磁检测及流程恢复三方面展开阐述了低压输气管道气驱改为水驱漏磁内检测的关键环节,并通过实际工程案例验证了低压输气管道水驱漏磁内检测流程的可靠性,为低压输气管道漏磁内检测提供了一种新思路。

基于局部椭圆变形的长输管道内检测的实践应用

论述了基于局部椭圆变形的长输管道,在无法实施局部换管的特定条件下如何实施内检测工作的应用实践。通过对漏磁检测设备的连接臂、皮碗法兰和探头进行改造,提升了检测设备在3D(内径)弯管处的通过能力,实现了不发生卡球事故的安全目标。通过对现场实测数据和内检测报告数据的分析比对,验证了内检测数据量化精度达到Rosen公司标准。为今后在长输管道局部椭圆变形及其他变形的特定条件下,实施内检测工作积累了实践经验,为类似管道的内检测、技术管理和安全运营提供了一定的借鉴作用。

运载火箭电磁阀漏磁特性量化研究与极性检测系统设计

传统的运载火箭电磁阀极性测试往往通过“耳听手摸”的方式,故存在漏检误检、测试记录不可量化及数据追溯、无法精准判读、测试效率低等问题;因此对运载火箭典型姿控电磁阀开展了漏磁性能的测量与量化分析,掌握阀体各部位漏磁场分布规律、漏磁场随距离衰减变化规律、电磁阀之间漏磁场相互影响情况,并提出了一种非接触式的可视化电磁阀极性检测系统设计方法,采用三冗余敏感探头采编设计保证极性检测准确性,经试验测试验证,实现了无需精确安装即可100%检测电磁阀动作及时序动作精准判读,提升了电磁阀极性检测能力和测试效率;该系统已成功应用于大型运载火箭的总装测试流程中,对于提升运载火箭自动化测试水平具有重要意义。

基于注意力特征融合的漏磁缺陷识别方法

针对漏磁缺陷识别率低、检测速度慢等问题,提出了一种基于注意力特征融合的漏磁缺陷识别方法。所提算法以CenterNet为基础进行修改,主干网络选取了一种轻量级网络PP-LCNet,相较于现在流行的主干特征提取网络既保证了低计算量又保证了高精度。采用注意力网络CBAM主动学习低层特征中的重要信息并与高层特征进行融合,使模型同时获得低层细粒度信息与高层语义信息,进而提升小缺陷识别的准确率。结果表明,当IOU大于0.5时,所提算法的准确率为94.3%,推理时间为9.6 ms。

原油储罐泄漏检测技术研究

原油储罐在复杂的内外部环境中最容易出现的失效形式是底板穿孔从而导致原油泄漏。文章介绍了声发射方法和漏磁扫描方法应用于储罐底板的泄漏检测。两种方法都可以评估与定位底部材料的损伤及底板材料的微泄漏。文章介绍了原油储罐泄漏检测原理,分析了现场检测过程,对同一具原油储罐进行声发射和漏磁扫描检测后,对两种方法的检测结果进行分析与经济性对比,进而给出该储罐的完整性评估,并提出储罐的检修意见。