The primary goal of this research is to investigate the effect of defect on the fatigue-induced magnetic behavior of a ferromagnetic steel. Uniaxial cyclic loading tests on X70 pipeline steel were carried out with various stress levels. The variation of the magnetic signals surrounding the specimen was detected by two fluxgate magnetometers. The results indicated that the evolution of the magnetic field at defect shows significant differences compared to the smooth area. The evolutions of the magnetic fields similar in the first two stages, however, in the third stage, the magnetic field at defect changed both in the amplitude of magnetic field and the shape of the hysteresis loops. The experiment results proposed a feasible non-destructive testing method for pipeline steels.
With the development of the world offshore oil industry, submarine pipelines are widely used in deep-sea oil and natural gas exploitation. Yet corrosion defects are often found in pipelines. Corrosion is one of the main causes of accidents in the oil and gas industry. Corrosion can lead to local damage to the pipeline and result in stress concentrations. Additionally, due to the existence of vortex-induced vibration (VIV) (Williamson and Govardhan, 2004) and suspended span (Zakeri, 2009), submarine pipelines are prone to fatigue damage, especially in the defect areas. Hence, it is important to detect these defects timely with non-destructive testing methods.
Structural Health Monitoring (SHM) technology can sense and predict a series of factors detrimental to structure such as structural defects, damage, deformation, and corrosion. The main purpose of pipeline monitoring is to identify the location of corrosion defects, assess defects accurately and predict the residual life of the pipeline. Common NDE techniques are magnetostrictive sensors (MSSs) technique (Cheong, Jung and Kim, 2006; Luo, Rose and Kwun, 2004; Jia, Liu, Wang, Liu and Ge, 2011), distributed fiber sensors technique (Rajeev, Kodikara, Chiu and Kuen, 2013; Thien, Chiamori, Ching, Wait and Park, 2008), electromagnetic acoustic transducers (EMATs) technique (Hirao and Ogi, 1999; Zhao, Varma, Mei, Ayhan and Kwan, 2005), guided waves method (Cawley, Cegla and Galvagni, 2012 ; Harley, Ying, Moura, Oppenheim, Sobelman and Garrett, 2012), ultrasonic sensors technique (Ying et al., 2013 ; Michaels, Cobb and Michaels, 2004) and so on.