金属管道裂纹的金属磁记忆定量化评价方法研究
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摘要
管道运输在现代化工业中占据及其重要的位置,由于腐蚀、磨损、意外损伤等导致的管道泄露造成了很大的损失,各国都对管道无损检测都给予了充分重视。管道存在应力集中是导致事故的主要根源。传统的无损检测方法没有办法对应力集中进行有效检测。金属磁记忆检测技术作为一种新的无损检测方法,在应力集中以及裂纹检测方面具有很多优点。
本文介绍了金属磁记忆检测机理、检测系统的硬件和软件设计、以及金属磁记忆检测的定量化方法研究。检测系统的硬件主要由MSP430单片机,HMC1021Z型磁阻传感器,以及周边信号调理电路组成。软件设计包括单片机程序设计以及PC机上使用Matlab对数据进行处理的程序设计。检测系统的工作流程是：首先,通过传感器模块对实验板进行检测,检测到的信号经过信号调理电路变成MSP430单片机可以采集的信号,继而单片机A／D端口进行数据采集,并通过串行接口发送到PC终端。最后,使用Matlab软件对采集到的数据进行处理。
本课题实验部分内容分两步进行,第一部分是对金属实验板进行检测。使用激光线切割的方法在实验板上预置了不同类型的裂纹,并通过振动的方法消除裂纹边缘处的残余应力。利用搭建好的金属磁记忆检测电路对实验板上不同类型的裂纹进行磁信号采集,在提取预置裂纹的原始磁信号基础上,对信号进行微分并归一化处理。而后,计算过零点峰峰值的梯度,并将该值作为检测缺陷／应力集中区的新的特征值。第二部分是验证实验,通过对金属管道裂纹进行检测,达到验证该特征值能否检测不同类型试件上裂纹／应力集中的目的。分析比较结果表明：过零点两端峰峰值梯度能够明显表征缺陷位置,并且具有良好的幅值一致性。由此得出结论,实验搭建的系统可以实现实验目的,同时过零点峰峰值比重可以作为金属磁记忆检测定量化分析的特征值。
Pipeline transportation which can cause large losses for its leaks occupies an important position in modern industry. As stress concentration is a major reason of damage incidents, countries give non-destructive testing of the pipeline full attention. However, the traditional method is not effective. Metal Magnetic Memory (MMM) has many advantages in case of testing and monitoring the crack.
This paper introduces the MMM theory, design of detection system in hardware and software, and the quantitative analysis of MMM. The hardware of testing system includes MSP430, HMC1021Z magnetoresistive sensor, and the match signal processing circuit. The software design of testing system contains the design of MCU programming, and Matlab Data processing programming. The detection system working flow is:the signal which is processed by the conditioning circuit after detected by sensor module on test board, is collected by MSP430 microcontroller, then sent to the PC through serial interface, and finally, processed by Matlab data processing program.
This experiment is carried out in two steps. The first step is to detect the metal plate preferences of different types of cracks by laser beam cutting method and being eliminate residual stress by vibration method. The magnetic signal around crack is collected by the testing system, and then processed in differential and scale. The new feature is found by calculating the gradient value on both sides of zero. The second step is to verify weather this new feature is effective on different work piece through testing the pipe which has pre-cracks. New feature has great consistency in testing different work piece. Therefore, the gradient value on both sides of zero can be the new feature in MMM quantitative analysis.
本文介绍了金属磁记忆检测机理、检测系统的硬件和软件设计、以及金属磁记忆检测的定量化方法研究。检测系统的硬件主要由MSP430单片机,HMC1021Z型磁阻传感器,以及周边信号调理电路组成。软件设计包括单片机程序设计以及PC机上使用Matlab对数据进行处理的程序设计。检测系统的工作流程是：首先,通过传感器模块对实验板进行检测,检测到的信号经过信号调理电路变成MSP430单片机可以采集的信号,继而单片机A／D端口进行数据采集,并通过串行接口发送到PC终端。最后,使用Matlab软件对采集到的数据进行处理。
本课题实验部分内容分两步进行,第一部分是对金属实验板进行检测。使用激光线切割的方法在实验板上预置了不同类型的裂纹,并通过振动的方法消除裂纹边缘处的残余应力。利用搭建好的金属磁记忆检测电路对实验板上不同类型的裂纹进行磁信号采集,在提取预置裂纹的原始磁信号基础上,对信号进行微分并归一化处理。而后,计算过零点峰峰值的梯度,并将该值作为检测缺陷／应力集中区的新的特征值。第二部分是验证实验,通过对金属管道裂纹进行检测,达到验证该特征值能否检测不同类型试件上裂纹／应力集中的目的。分析比较结果表明：过零点两端峰峰值梯度能够明显表征缺陷位置,并且具有良好的幅值一致性。由此得出结论,实验搭建的系统可以实现实验目的,同时过零点峰峰值比重可以作为金属磁记忆检测定量化分析的特征值。
Pipeline transportation which can cause large losses for its leaks occupies an important position in modern industry. As stress concentration is a major reason of damage incidents, countries give non-destructive testing of the pipeline full attention. However, the traditional method is not effective. Metal Magnetic Memory (MMM) has many advantages in case of testing and monitoring the crack.
This paper introduces the MMM theory, design of detection system in hardware and software, and the quantitative analysis of MMM. The hardware of testing system includes MSP430, HMC1021Z magnetoresistive sensor, and the match signal processing circuit. The software design of testing system contains the design of MCU programming, and Matlab Data processing programming. The detection system working flow is:the signal which is processed by the conditioning circuit after detected by sensor module on test board, is collected by MSP430 microcontroller, then sent to the PC through serial interface, and finally, processed by Matlab data processing program.
This experiment is carried out in two steps. The first step is to detect the metal plate preferences of different types of cracks by laser beam cutting method and being eliminate residual stress by vibration method. The magnetic signal around crack is collected by the testing system, and then processed in differential and scale. The new feature is found by calculating the gradient value on both sides of zero. The second step is to verify weather this new feature is effective on different work piece through testing the pipe which has pre-cracks. New feature has great consistency in testing different work piece. Therefore, the gradient value on both sides of zero can be the new feature in MMM quantitative analysis.
引文
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[2]袁方.成品油管道输送的优势及发展[J].石油库与加油站,2006.15(4)：38-39
[3]Gerhard MOOK, Jouri SIMONIN, Wolf Dieter FEIST. Detection and Characterization of Magnetic Anomalies in Gas Turbine Disks[J]. ECNDT 2006.4(13):15-17
[4]宋小春,黄松岭,赵伟.天然气长输管道裂纹的无损检测方法[J].天然气工业,2007,7(7)：103-106.
[5]庾莉萍.我国油气管道运营安全管理存在的问题及保障措施[J].石油规划设计,2007.18(2)：13
[6]刘贵民.无损检测技术[M].北京：国防工业出版社,2006：67-80
[7]刘富顺,汤明.无损检测基础[M].北京：北京航空航天大学出版社,2002：140-160
[8]范向红,王少华,那晶。我国管道漏磁检测技术及其成就[J].石油工业技术督,2007(4)：55-56
[9]徐丽,张幸红,韩杰才.射线检测在复合材料无损检测中的应用[J].无损检测,2004,26(9)：450-456
[10]Howell,M LA Journal of the I Corr ST[J]. Industial Corrosion,1986,4(6):3-7
[11]王丽,冯蒙丽,丁红胜,白世武,刘方明.金属磁记忆检测的原理和应用[J],物理测试2007,3(25)：2
[12]仲维畅.铁磁性物体在地磁场中的自发“运动磁化”[J].无损探伤,2004,28(5)：9-10
[13]黄松岭,李路明.用金属磁记忆方法检测应力分布[J].无损检测,2002,24(5)：212-214
[14]张卫民,董韶平,等.磁记忆法检测方法及其应用研究[J].北京理工大学学报,2003,23(8)：330-333
[15]Nick Fost. Pipline coating faults evaluated[J]. Anti-corrosion Method&Materials,1986, 33(10):7-13
[16]D. C. Jile, S Hariharan, MK Devine. Magnescope:A Portable Magnetic Inspection System for Evaluation of Steel Structures and Components [J]. IEEE Trans. On Magnetics,1990,26(5):2577-2579
[17]M. K. Devine, D. C. Jile. Composition Dependence of the Magnetomechanical Effect and Magnetostriction [J]. IEEE. Trans. On Magnetics,1996,32(5):4740-4742
[18]M. J. Sablik, D. C. Jile. Modeling Effects of Varying Torsion in Magnetized Steel [J]. IEEE Transactions on Magnetics,2000,36(5):3248-3250
[19]Y. H. Chen, D. C. Jile. The magnetomechanical Effect under Torsional Stress in a Cobalt Ferrite Composite [J]. IEEE Transactions on Magnetics,2001,37(4):3069-3072
[20]Jerzy Kaleta. Magnetovision as a Tool for Investigation of Fatigue Process of Ferromagnetics[C]. SAE Brasil International Conference on Fatigue,2002,10(22):27-35
[21]T. Sukegawa. Magnetic Nondestructive Evaluation of Ferromagnetic Steel Due to Mechanical Loading[J]. Electromagnetic Nondestructive Evaluation IOS Press,2002,5(7): 135-142
[22]仲维畅.金属磁记忆法诊断的理论基础[J].无损检测,2001,23(10)：424-426
[23]温伟刚,萨殊利.金属磁记忆检测的机理及实现[J].北方交通大学学报,2002,26(4)：67-70
[24]丁辉,张寒,李晓红,文习山.磁记忆检测裂纹类型缺陷的理论模型[J].无损检测,2002,2(5)：78-80
[25]李路明,黄松岭,等.缺陷长度对漏磁场的影响[J].科学技术与工程,2002,2(4)：52-53
[26]李路明,王晓凤,黄松岭磁记忆现象和地磁场的关系[J].无损检测,2003,25(8)：387-389
[27]周俊华,雷银照.正磁致伸缩铁磁性材料磁记忆现象的理论探讨[J].郑州大学学报,2003,24(3)：101-105
[28]张卫民,刘红光.中低碳钢静拉伸时磁记忆效应的实验研究[J].北京理工大学学报,2004,24(7)：571-574
[29]张卫民,刘红光,等.低碳钢扭转过程弱磁信号变化及金属磁记忆效应[J].北京理工大学学报,2005,25(11)：1003-1007
[30]张卫民,刘红光,等.高强度钢磨削时的金属磁记忆现象初探[J].兵工学报,2005,26(3)：375-378
[31]于凤云,张川绪,吴淼.放置方向对磁记忆检测信号的影响[J].煤矿机械,2005,10(21)：149-151
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