[1] Shi, Y., Zhang, C., Li, R., Cai, M., & Jia, G., (2015). Theory and application of magnetic flux leakage pipeline detection. Sensors, 15(12), 31036-31055.
[2] Wang, Z. D., Gu, Y., & Wang, Y. S., (2012). A review of three magnetic NDT technologies. Journal of Magnetism and Magnetic Materials, vol. 324, 382-388.
[3] Usarek, Z., & Warnke, K., (2017). Inspection of gas pipelines using magnetic flux leakage technology. Advances in Materials Science, 17.3, 37-45.
[4] Gao, Y., Tian, G. Y., Li, K., Ji, J., Wang, P., & Wang, H., (2015). =Multiple cracks detection and visualization using magnetic flux leakage and eddy current pulsed thermography=. Sensors and Actuators A: Physical, 234, 269-281.
[5] Li, E., Kang, Y., Tang, J., & Wu, J., (2018). A new micro magnetic bridge probe in magnetic flux leakage for detecting micro-cracks. Journal of Nondestructive Evaluation, 37(3), 46.
[6] Kim, J. W., & Park, S., (2018). Magnetic flux leakage sensing and artificial neural network pattern recognition-based automated damage detection and quantification for wire rope non-destructive evaluation. Sensors, 18(1), 109.
[7] Li, Y., Wilson, J., & Tian, G. Y., (2007). Experiment and simulation study of 3D magnetic field sensing for magnetic flux leakage defect characterisation. NDt & E international, 40(2), 179-184.
[8] Antipov, A. G., & Markov, A. A., (2014). Evaluation of transverse cracks detection depth in MFL rail NDT. Russian Journal of Nondestructive Testing, 50(8), 481-490.
[9] Kim, J. W., Park, J., Yu, B. J., & Park, S., (2016). MFL Sensing based NDE Technique for Defect Detection of Railway Track. 8th European Workshop on Structural Health Monitoring (EWSHM 2016). Bilbao, Spain.
[10] Terada, Y., Yamashita, M. I. T. S. U. G. U., Tamehiro, H., & Ayukawa, N., (1997). Development of API X100 UOE line pipe. Nippon steel technical report, 72, 47-52.
[11] Sherif, E. S. M., Almajid, A. A., Khalil, K. A., Junaedi, H., & Latief, F. H., (2013). Electrochemical studies on the corrosion behavior of API X65 pipeline steel in chloride solutions. International journal of electrochemical science, 8, 9360-9370.
[12] Hashemi, S. H., (2011). Strength–hardness statistical correlation in API X65 steel. Materials Science and Engineering A, 528, 1648-1655.
[13] Hashemi, S. H., & Mohammadyani, D., (2012). Characterisation of weldment hardness, impact energy and microstructure in API X65 steel. International Journal of Pressure Vessels and Piping, 98, 8-15.
[14] El-Danaf, E., Baig, M., Almajid, A., Alshalfan, W., Al-Mojil, M., & Al-Shahrani, S., (2013). Mechanical, microstructure and texture characterization of API X65 steel. Materials & Design, 47, 529-538.
[15] Mirzaee, A., Kahrobaee, S., & Ahadi Akhlaghi, I., (2020). Non-destructive determination of microstructural/mechanical properties and thickness
variations in API X65 steel using magnetic hysteresis loop and artificial neural networks. Nondestructive Testing and Evaluation, 35(2), 190-206.
[16] Sahebalam, A., Kashefi, M., & Kahrobaee, S., (2014). Comparative study of eddy current and Barkhausen noise methods in microstructural assessment of heat treated steel parts. Nondestructive Testing and Evaluation, 29(3), 208-218.
[17] Ahmadzade-Beiraki, E., Kahrobaee, S., Kashefi, M., Akhlaghi, I. A., & Mazinani, M., (2020). Quantitative Evaluation of Deformation Induced Martensite in Austenitic Stainless Steel Using Magnetic NDE Techniques. Journal of Nondestructive Evaluation, 39(1), 1-9.