A Dynamics Study of a Magnetic Flux Leakage(MFL) Signal and its Application to Defect Location Discrimination in Steel Pipes MFL Testing Equipment

Difference processing was used to the direct current magnetic flux leakage （DC-MFL） signal, emanating from the defects machined artificially on the internal and external surfaces of a steel pipe. Consequently, the loea-tion discriminating index 8 was provided to identify the defect whether it is on the internal surface or the external one. Three characteristics, shape, depth and orientation of the defect, were discussed through a series of experiments on the artificial defects, such as transverse notches, oblique notches and pits on the steel pipe. The approach has been verified effective to address the defect location identifying problem, albeit the limits on the accuracy assessment to those natural defects on steel pipes in service.

Three-axis magnetic flux leakage in-line inspection simulation based on finite-element analysis

With the increase of pipelines, corrosion leakage accidents happen frequently. Therefore, nondestructive testing technology is important for ensuring the safe operation of the pipelines and energy mining. In this paper, the structure and principle of magnetic flux leakage （MFL） in-line inspection system is introduced first. Besides, a mathematic model of the system according to the ampere circuit rule, flux continuity theorem, and column coordinate transform is built, and the magnetic flux density in every point of space is calculated based on the theory of finite element analysis. Then we analyze and design the disposition of measurement section probes and sensors combining both three-axis MFL in-line inspection and multi-sensor fusion technology. Its advantage is that the three-axis changes of magnetic flux leakage field are measured by the multi-probes at the same time, so we can determine various defects accurately. Finally, the theory of finite element analysis is used to build a finite element simulation model, and the relationship between defects and MFL inspection signals is studied. Simulation and experiment results verify that the method not only enhances the detection ability to different types of defects but also improves the precision and reliability of the inspection system.

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.

Reduction of Unipolar Leakage Flux and Torque Ripple in Consequent-pole PM Vernier Machine

This paper proposes a new consequent-pole permanent magnet vernier machine(CPMVM),which can be regarded as a combination of two conventional CPMVM with opposite polarities.Based on the simplified axial magnetic circuit model,it is verified that the proposed CPMVM can reduce the unipolar leakage flux.In order to reduce the torque ripple of machine and improve the output torque of machine,the flux barrier is placed on the rotor of the proposed machine.Then,the parameters of the proposed CPMVM are optimized and determined.Moreover,the electromagnetic performance,including no-load air-gap flux density,average torque and torque ripple,flux linkage,back-electromotive force,cogging torque,average torque,torque ripple,power factor and loss,is compared with conventional surface-mounted permanent magnet vernier machine(SPMVM)and CPMVM.Finally,it is demonstrated that proposed CPMVM with flux barrier can effectively reduce the unipolar leakage flux and greatly reduce the torque ripple of machine.Also,compared with the SPMVM,the proposed CPMVM with flux barrier saves more than 45%of the permanent magnet material without reducing output torque.

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.

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.

Magnetic flux leakage during longitudinal magnetic flux induction heating

A three-dimensional electromagnetic thermal coupled model of a 45#steel strip during longitudinal magnetic flux induction heating was established in this study.The influence of different power levels,frequencies,and electromagnetic shielding on the magnetic induction intensity and the heating of parts of different materials around the inductor was analyzed by calculating the magnetic induction intensity around the longitudinal flux induction heater under different conditions.The results show that leakage flux can be reduced up to 49%by electromagnetic shielding.The higher the frequency,the greater the electromagnetic shielding effect,and the lower the magnetic leakage around the inductor.Conversely,the higher the power,the greater the magnetic induction around the inductor.By adding electromagnetic shielding to reduce magnetic leakage of the inductor and replacing the metal part material around the inductor with stainless steel,the heat generation of the parts around the inductor can be greatly reduced.

Magnetic flux leakage analysis and compensation of high-frequency planar insulated core transformer

A novel high-frequency and high power density planar insulated core transformer(PICT) applied to high voltage DC generator is introduced. PICT's operating principle and fundamental configuration are described,and preliminary experimental results in self-designed PICT apparatus are presented. Emphatically, magnetic leakage flux(MFL) giving rise to the output voltage drop is analyzed in detail both theoretically and by finite element method(FEM). Showing good consistency with experimental result, FEM simulation is considered to be practicable in physical design of PICT. To cancel out leakage inductance and improve the voltage uniformity,compensation capacitor is adopted and experimental verification is also presented. All shows satisfactory results.

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.

Analysis and Modeling of Tooth-Tip Leakage Fluxes in a Radial-Flux Dual-Stator Machine with Diametrically Magnetized Cylindrical Permanent Magnets

Tooth-tip Leakage flux(TLF)has a major effect on the prediction of air-gap flux distribution and electromagnetic torque in the permanent magnet(PM)machines.Therefore,deriving a model for TLF is necessary for machine design and optimization.Accurate modeling of TLF can lead to fast and precise solutions,which ease the analysis of electromagnetic devices.It also provides the opportunity to increase torque density by more efficient utilization of PM’s volume and prevent saturation in machine optimization.This paper presents a method for modeling and analyzing TLFs in a radial-flux dual-stator permanent magnet(DSPM)machine with diametrically magnetized cylindrical permanent magnets(DMCPM)in series and parallel magnetic circuit structures.In this model,some expressions in terms of machine dimensions are derived for the TLF analysis.Finite element method(FEM)is applied to validate the proposed model.Results indicate that the maximum error between the proposed model and FEM is insignificant(less than 6%).Finally,by a prototyped machine the validity of the proposed model was investigated with the experimental tests.

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.

Quantitative Detection of Corrosion State of Concrete Internal Reinforcement Based on Metal Magnetic Memory

Corrosion can be very harmful to the service life and several properties of reinforced concrete structures.The metal magnetic memory(MMM)method,as a newly developed spontaneous magnetic flux leakage(SMFL)non-destructive testing(NDT)technique,is considered a potentially viable method for detecting corrosion damage in reinforced concrete members.To this end,in this paper,the indoor electrochemical method was employed to accelerate the corrosion of outsourced concrete specimens with different steel bar diameters,and the normal components Bz and its gradient of the SMFL fields on the specimen surfaces were investigated based on the metal magnetic memory(MMM)method.The experimental results showed that the SMFL experimental Bz curves are consistent with the analytical results of the theoretical model.Furthermore,the crest-to-trough behavior on the Bz signal curve and its zero-point gradient spacing can more accurately indicate the corroded area’s extent.Then,a magnetic characteristic parameter W based on a large amount of experimental data was established to characterize the degree of corrosion of the steel bars.The magnetic characteristic parameter W is linearly related to the maximum cross-sectional area loss rate
of the corroded reinforcement.This paper will lay the foundation for future research on corrosion detection of reinforced concrete structures based on the MMM method and provide a feasible way for non-destructive detection of corrosion independent of the influence of reinforcement diameter and magnetization history.

油气管道组合缺陷漏磁检测信号数值模拟研究

为解决管道组合缺陷之间漏磁检测信号互相干扰,难以识别的问题,采用有限元方法建立仿真模型,研究管道内外、不同形状缺陷以及内外组合缺陷邻近情况下的漏磁场检测信号规律。研究结果表明:管道缺陷的漏磁检测信号在其轴向和径向分量上均存在显著差异;组合缺陷的检测信号存在相互干扰且具有一定的叠加性;当缺陷深度约为管壁厚的10%、25%、40%时,轴向信号干扰距离分别约为缺陷长度的1倍、2倍、3倍,径向信号干扰距离均约为长度的4倍,组合缺陷径向信号的互相干扰程度大于轴向信号,缺陷深度对轴向信号的影响大于径向信号。研究结果可为油气管道组合缺陷的识别提供理论依据。

柔性钻柱扭转振动及控制研究

在旋转钻井中,钻杆承担着传递扭矩以助钻头破岩的重要作用,钻杆的粘滑振动是降低钻井设备使用寿命和钻进效率的主要原因之一,因此,通过研究粘滑振动的机理,探寻一种有效的抑制方法。提出了基于改进粒子群优化PID参数的鲁棒控制器,抑制钻头的粘滑振动并且使得其它部件保持期望的速度上。采用四自由度粘滑振动模型,包括转盘、钻杆、钻铤和钻头,同时考虑钻头与岩石接触的非线性相互作用。利用Matlab/Simulink建立模型仿真进行数值分析,并且设计模拟钻头卡钻实验。结果表明:粘滑现象会带来严重的后果,改进的粒子群优化PID参数可以使钻头及其他部件稳定在给定的转速的附近,控制响应时间小于40 s,减少了钻头扭矩波动,有效地抑制了钻柱粘滑振动。

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。