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.

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.

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.

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.

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。

The MFL Testing Methods for Welded Pipes

Steel pipes are categorized into seamless pipes and welded pipes,and particularly the welded pipes’ NDT(Non-Destructive Testing)has been a challenging problem.In the case,on the basis of the presentation of welded pipes,the analysis of its relevant testing key is carried out.Afterwards,the MFL(Magnetic Flux Leakage)methods for longitudinally welded line-pipes and for helically welded pipes are respectively proposed.Meanwhile,their relevant experiments are conducted,and finally the two technologies for the two types of welded pipes are verified well.

计及漏磁的堆栈式超磁致伸缩制动器多物理场耦合建模研究

堆栈式超磁致伸缩制动器(SGMA)因其能量密度高、响应速度快且便于提供稳定的偏置磁场而得到广泛应用。由于永磁体和超磁致伸缩材料相对磁导率极低,磁路中存在明显的磁场空间分布不均匀的现象,磁-机耦合导致其动力学相较于传统结构的制动器更为复杂。为了准确地预测SGMA的输出特性,该文基于有限元仿真搭建了计及漏磁的等效磁路,并结合Jiles-Atherton模型、非线性本构模型及考虑分布特性的结构动力学模型,借助Pspice电路仿真软件建立了超磁致伸缩制动器多物理场耦合动态模型。相较于传统的制动器多场耦合模型,所提模型能够更精准地分析磁路中的漏磁行为,并反映由磁场不均匀引起的力学分布特性。最后搭建制动器输出位移测试平台以验证模型的准确性,模型计算结果与实验结果吻合度良好,证明了所建立模型能有效表征SGMA的输入-输出特性。

基于漏磁内检测的管道焊缝缺陷识别及应对策略研究

漏磁内检测作为焊缝缺陷排查最有效的方法,因焊缝缺陷种类多、评价与修复标准体系复杂,亟须进行研究。基于油气管道漏磁内检测原理和焊缝特点,总结了焊缝、焊缝缺陷的分类及漏磁信号特征,梳理了焊缝缺陷在设计、施工验收、失效评价、响应及修复方面的标准规范,为在役管道焊缝缺陷评价与修复提供参考,也为焊缝缺陷隐患排查及油气管道安全运行提供技术支持。

某输气管道漏磁内检测金属损失缺陷验证检测及评价

某输气管道在首次漏磁内检测时发现2处大于20%WT(Wall Thickness,壁厚)的管道本体缺陷,对缺陷开展了基于内检测数据的开挖验证及检测,并将实测结果和内检测报告结果进行比对来验证内检测器性能规格。结果显示:内检测报告的金属损失缺陷深度比实测值偏小,但在可信度为90%的精度范围内;报告的缺陷长度、宽度及周向定位与实测值间存在偶然性偏差,需进一步扩大开挖验证。采用ASME B31G标准对2处缺陷进行适用性评价,结果表明管道估计维修因子(ERF)均小于1,满足承压能力要求,无须立即修复。

Magnetic Flux Leakage Signal Inversion of Corrosive Flaws Based on Modified Genetic Local Search Algorithm

In this paper,a modified genetic local search algorithm(MGLSA) is proposed.The proposed algorithm is resulted from employing the simulated annealing technique to regulate the variance of the Gaussian mutation of the genetic local search algorithm(GLSA).Then,an MGLSA-based inverse algorithm is proposed for magnetic flux leakage(MFL) signal inversion of corrosive flaws,in which the MGLSA is used to solve the optimization problem in the MFL inverse problem.Experimental results demonstrate that the MGLSA-based inverse algorithm is more robust than GLSA-based inverse algorithm in the presence of noise in the measured MFL signals.

基于单一轴向磁化的钢管高速漏磁检测方法

介绍现有复合磁化漏磁检测方法与装置并分析其局限性:相对螺旋推进的扫查探伤方式限制探伤速度,也难以完成不宜作旋转运动或带直线焊缝的钢管的检测。针对此问题,通过有限元仿真和试验的方法,发现并证实单一轴向磁化下检测钢管上任意方向伤的可能性,尤其是探测钢管上平行于轴向磁感应场的纵向伤的可行性,使得相对直线扫查的探伤成为可能。研究在单一轴向磁化下钢管上纵、横向伤检测信号的特征及其归一化判断;提出一种无需检测探头或钢管旋转的漏磁检测方法并研制出相应的探伤装置,解决无缝钢管生产线上的高速或超高速探伤问题,尤其是自身难以作螺旋推进运动的如连续油管等钢管及焊缝管的直线焊缝上缺陷的快速探伤;同时简化统一传统漏磁检测方法,降低设备成本。

管道缺陷漏磁检测的三维有限元仿真分析

为研究运输管道缺陷的漏磁（MFL）信号特征，采用ANSYS软件进行管道缺陷漏磁检测的三维有限元数值仿真。首先建立漏磁检测分析装置的数值模型，进行三维静态情况的数值计算，获得不同缺陷所产生的漏磁信号，然后将这些数据与试验结果进行比较分析。在此基础上，分析缺陷深度、缺陷直径以及传感器提离值对漏磁信号参数的影响。结果表明：磁通密度轴向分量By的幅值能够用于衡量缺陷的深度，可依据By的宽度和磁通密度径向分量Bx的峰峰间距来定量识别缺陷直径；传感器的提离值对缺陷漏磁场的影响很大，为使测得的漏磁信号可靠并能测得深度较小的缺陷，传感器的提离值应设定为1．5～3mm。

油气管道缺陷漏磁在线检测定量识别技术

用有限元软件建模研究了管道缺陷的特征参数与漏磁信号的关系.对漏磁信号进行预处理以消除传感器提离值不同带来的影响,用BP神经网络进行了管道缺陷的定量识别,识别结果的误差<10%.将轴向和径向漏磁信号分别用加权平均和自适应加权平均两种方法进行信号级融合,数据融合后缺陷定量识别的精度和可靠性得到了提高.

应用小生境遗传算法优化导线钢芯断股漏磁检测传感器

输电线路的钢芯铝绞线在运行中可能发生钢芯损伤、断股现象,及时检测和诊断对于保证电网的安全运行具有重要意义。采用巡线机器人对钢芯损伤、断股进行检测是一种具有较好前景的方法。设计一种基于钢芯损伤、断股后形成的漏磁进行检测的传感器,采用48H号钕铁硼稀土永磁铁磁化输电导线钢芯,以永磁铁、导磁体沿导线的径向宽度和轴向长度为变量,以传感器质量作为优化目标,应用搜索能力强、收敛速度快的小生境自适应遗传算法优化传感器的结构尺寸。结果表明,在满足对导线钢芯磁化强度要求下,传感器的质量显著降低,有效提高了巡线机器人的携载能力,且所提方法具有通用性,适用于不同规格导线钢芯断股检测的漏磁传感器设计和优化。

漏磁检测中的缺陷重构方法

漏磁检测技术中的缺陷重构方法是目前漏磁检测缺陷评估的研究热点与难点。在对漏磁检测缺陷重构进行概述的基础上,综述了现有的缺陷重构方法:开环逆向重构法和闭环伪逆重构法,并对这两类方法中常用的逆向模型、前向模型、优化算法及其特点进行了较为详细的介绍。指出了基于数据融合技术、图像处理技术和多缺陷综合评估的缺陷重构方法的研究发展方向。

基于变尺度随机共振的油管漏磁信号检测

为解决大参数微弱信号的识别问题,在研究随机共振基本原理的基础上,提出了变尺度随机共振的概念并给出了实现方法。据此方法对油田抽油管裂纹、通孔、焊缝以及微小锯齿纹4种典型缺陷的漏磁信号进行了分析,并利用多通道数据融合技术减小干扰信号。与原信号波形比较表明,变尺度随机共振波形可有效提高微弱漏磁信号的识别率。

钢管纵向伤高速高精漏磁探伤磁化方法

在钢管螺旋推进漏磁检测扫描中,检测速度越快,要求的检测探靴轴向长度越长,使得扫描覆盖范围超出了均匀磁化区,出现信号不一致的问题。针对钢管纵向伤检测中检测精度与速度相互制约的问题,以保证钢管纵向伤高速检测的信号一致性为目标,采用有限元仿真与实验验证相结合的方法,分析了周向磁化中磁极靴的结构对钢管表面磁场均匀性的影响。在此基础上提出了一种纵向伤漏磁检测磁化方法,扩大了钢管表面的均匀磁场区域,在同样的检测区域内提高了检测信号的一致性。

对接焊缝缺陷漏磁场特征分析及识别研究

为实现钢板对接焊缝存在不同类型缺陷的识别研究,针对铁磁性焊缝的特点,探讨应用漏磁法检测钢板对接焊缝不同类型缺陷。根据漏磁检测(MFL)原理,采用有限元方法(FEM),分别建立钢板对接焊缝中可能存在的裂纹、气孔、未熔合和未焊透等缺陷的三维FEM模型。研究钢板对接焊缝包含以上不同类型缺陷时所产生的漏磁场分布特征,得到漏磁场磁感应强度水平分量和垂直分量相关对比分析曲线。仿真结果表明:漏磁法适用于钢板对接焊缝缺陷的识别研究;根据漏磁场磁感应强度分量的曲线特征,能够实现对焊缝缺陷的分类。

基于漏磁检测数据的缺陷三维重构技术

针对漏磁检测数据可视化研究中存在的技术难点,提出了一套有效的缺陷三维重构方法。首先基于三维有限元神经网络建立漏磁迭代反演模型,构建出与传感器多通道检测数据相对应的缺陷二维断层轮廓序列;然后根据铁磁构件表面腐蚀缺陷断层轮廓的形状特征建立匹配点对,采用线性插值方法实现缺陷相邻断层轮廓间的插值,以克服因传感器数量少对缺陷外形重构精度的影响;最后运用三角形面片将相邻的轮廓线两两连接起来,重构出断层轮廓序列所代表的缺陷三维表面模型。