A new measurement system using magnetic flux leakage method in pipeline inspection

被引:94
作者
Ege, Yavuz [1 ]
Coramik, Mustafa [1 ]
机构
[1] Balikesir Univ, Necatibey Fac Educ, Dept Phys, TR-10100 Balikesir, Turkey
关键词
AMR sensors; Crack; Data acquisition; Lab VIEW; Magnetic flux leakage; Non-destructive testing; Pipelines; METAL-SURFACE CRACKS; BARKHAUSEN NOISE; DEFECT DETECTION; MEMORY METHOD; OIL PIPELINE; SIGNALS; STEEL; SIMULATION; SENSORS; STRESS;
D O I
10.1016/j.measurement.2018.03.064
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Today, natural gas and oil, called main energy sources, are transported by pipelines M long distances. Defects (corrosion, cracks, dents) in the buried pipelines can cause loss of life, environmental pollution and economic loss. Recently, devices called "Pipeline Inspection Gauge (PIG)" are used for non-destructive evaluation (NDE) of defects in pipelines. In these devices, the magnetic flux leakage (MFL) technique comes into prominence as the inspection method. However, when the literature is examined, a study that examines the speed variable for defect detection has not been found. In this study, two new PIGs which can be used to investigate the speed variable while determining defects in pipelines are designed. For these new designs, a new magnetic measurement system with KMZ51 AMR sensors is developed. The voltage values of the sensors in the measurement system are saved to the computer by using LabVIEW-based software in sequential order via the NI USB-6210 data acquisition card. This data is also displayed on LCD screens by using MyRIO 1900. In the article, the mechanics of the developed system, its electronics and its software are examined in detail. Moreover, the usability of these new designs in determining pipeline defects are examined through an example experiment result with the Origin analysis program.
引用
收藏
页码:163 / 174
页数:12
相关论文
共 31 条
[1]  
[Anonymous], 1998, KMZ51 MAGNETIC FIELD
[2]   Residual magnetic flux leakage: A possible tool for studying pipeline defects [J].
Babbar, V ;
Clapham, L .
JOURNAL OF NONDESTRUCTIVE EVALUATION, 2003, 22 (04) :117-125
[3]  
Beller M., 2007, Pipeline Inspection Utilizing Ultrasound Technology: On the Issue of Resolution
[4]   MFL signals and artificial neural networks applied to detection and classification of pipe weld defects [J].
Carvalho, A. A. ;
Rebello, J. M. A. ;
Sagrilo, L. V. S. ;
Camerini, C. S. ;
Miranda, I. V. J. .
NDT & E INTERNATIONAL, 2006, 39 (08) :661-667
[5]   ASSESSMENT OF THE MATERIAL STATE OF OIL AND GAS PIPELINES BASED ON THE METAL MAGNETIC MEMORY METHOD [J].
Dubov, A. ;
Kolokolnikov, S. .
WELDING IN THE WORLD, 2012, 56 (3-4) :11-19
[6]   Application of the metal magnetic memory method for detection of defects at the initial stage of their development for prevention of failures of power engineering welded steel structures and steam turbine parts [J].
Dubov, Anatoly ;
Dubov, Alexandr ;
Kolokolnikov, Sergey .
WELDING IN THE WORLD, 2014, 58 (02) :225-236
[7]  
Ege Y., 2016, SIGNAL IMAGE PROCESS, V7, P11
[8]  
Ege Y, 2015, INDIAN J PURE AP PHY, V53, P199
[9]  
Hui Min Kim, 2012, 2012 IEEE International Conference on Automation Science and Engineering (CASE 2012), P624, DOI 10.1109/CoASE.2012.6386507
[10]   Finite element modelling of a circumferential magnetiser [J].
Ireland, RC ;
Torres, CR .
SENSORS AND ACTUATORS A-PHYSICAL, 2006, 129 (1-2) :197-202