Analysis of Mechanical Properties of Welds by Magnetic Memory Detection
[1]
Zu Ruili, Key Laboratory of Nondestructive Testing of Ministry of Education, Nanchang Hangkong University, Nanchang, China.
[2]
Ren Shangkun, Key Laboratory of Nondestructive Testing of Ministry of Education, Nanchang Hangkong University, Nanchang, China.
[3]
Zhao Zhenyan, Key Laboratory of Nondestructive Testing of Ministry of Education, Nanchang Hangkong University, Nanchang, China.
[4]
Ren Xianzhi, Key Laboratory of Nondestructive Testing of Ministry of Education, Nanchang Hangkong University, Nanchang, China.
In order to detecting the mechanical properties of steel weld quality quickly and accurately, the method of detecting the weld quality of low carbon steel by magnetic memory detection technology is studied. Tensile test and magnetic signal measurement of different welding current welding specimens were carried out, and the defect detection analysis were carried out by using ray detection technique. Studying the relationship between the change of magnetic memory signal during tensile process and the yield strength and tensile strength of low carbon steel welds. The results show that the specimens with different welding current have different mechanical properties, and the specimens with different yield strength and tensile strength have different characteristics of magnetic memory signals. It is found that the mechanical properties of low-carbon steel welds can be effectively determined by using the two-parameter information fusion technology based on the basic principle of metal magnetic memory detection technology and the average magnetic signal information and magnetic signal gradient information under different stress. The research results can provide reference for the application of magnetic memory detection technology in the quality evaluation of carbon steel weld quality.
Nondestructive Testing, Magnetic Memory Detection, Weld Quality, Average Magnetic Signal, Magnetic Signal Gradient
[1]
Ren J L, Wang D S, Song K. Influence of Stress State on Magnetic Memory Signal [J]. Journal of Aeronautical, 2007, 28 (3): 724-728.
[2]
Leng J C, Xing H Y, Zhou G Q, et al. Dipole modelling of metal magnetic memory for V-notched plates [J]. Insight: Non-Destructive Testing and Condition Monitoring, 2013, 55 (9): 98-503.
[3]
Liorzou F, Phelps B, Atherton D L. Macroscopic models of magnetization [J]. IEEE Transactions on Magnetics, 2000, 36 (2): 418-428.
[4]
Li C, Dong L, Wang H, et al. Metal magnetic memory technique used to predict the fatigue crack propagation behavior of 0.45%C steel [J]. Journal of Magnetism & Magnetic Materials, 2016, 405: 50-157.
[5]
Kolokolnikov, Anatoly Dubov, Oleg Steklov. Assessment of welded joints stress–strain state in-homogeneity before and after post weld heat treatment based on the metal magnetic memory method [J]. Welding in the World, 2016: -8.
[6]
Dubov A A, Kolokolnikov M S. Assessment of the Material State of Oil and Gas Pipelines Based on the Metal Magnetic Memory Method [J]. Welding in the World Le Soudage Dans Le Monde, 2012, 56 3-4): 1-19.
[7]
Dubov A A. Principle features of metal magnetic memory method and inspection tools as compared to known magnetic NDT methods [C]// World Conference on Nondestructive Testing. 2006: 034-1037.
[8]
Liu H G, Zhang W M, Wang Z X. Research on Welding Defect Detection Technology Based on Magnetic Memory Method [J]. Journal of Beijing Institute of Technology, 2007, 27 9): 11-814.
[9]
Qiu X J, Li W S, Bai S W. Neural Network Identification of Metal Magnetic Memory Signals for Welding Cracks [J]. Journal of Welding, 2008, 29 3): 3-16.
[10]
Qiu X J, Li W S, Yan C Y. Recognition Method of Macro Welding Crack Based on Metal Magnetic Memory [J]. China Mechanical Engineering, 2007, 18 (12): 1475-1478.
[11]
Dubov A, Dubov A, Kolokolnikov S. 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]. Welding in the World Le Soudage Dans Le Monde, 2014, 58 (2): 225-236.
[12]
Kolokolnikov S, Dubov A, Steklov O. Assessment of welded joints stress–strain state inhomogeneity before and after post weld heat treatment based on the metal magnetic memory method [J]. Welding in the World, 2016, 60 (4): 1-8.
[13]
Xu K S, Chou X Q, Jiang H. 20 steel welding defect magnetic memory signal analysis [J]. Journal of Welding, 2016, 37 (3): 13-16.
[14]
Long F F, Gao G Z, Zhang X Y. Research on Crack Magnetic Memory Testing Technology in Plate and Weld [J]. Nondestructive testing, 2016, 38 (11): 27-29.
[15]
Tian X Y. Effect of welding current on microstructure and properties of Q235 steel welded joint [J]. Foundry Technology, 2014 (8).
