Defects in most structures can be generated not only on outside but also on inside or on the back-side during the manufacturing or construction process. Also they cause the growth of defects due to operation of various complex environments and structures will be destroyed eventually. In order to improve the reliability of the structure, the detection and size-estimation of defects should be investigated. In this paper, as an extension of previous studies on surface defects, two-dimensional artificial backside cracks (blind cracks) into paramagnetic material were evaluated by using the same aluminum probe. The potential drop at the defect position is distributed in the n-shape in the case of the back defect, which is different from results of the surface defect (u-shape). The potential drops at the defect position are measured with the largest value. The potential drop ratio (Vcmax/Vs) for the defective position is used as a parameter to predict the thickness (l) of defect position.

Most structures require high reliability to ensure safety and soundness. The materials used for these structures are not only defective in the manufacturing process and construction process, but also cause generation and progress of defects due to operation of various complex use environments. In order to improve the reliability of the structure, it is very important to detect and estimate the defect size. The method of evaluating these defects without damaging the structure is a non-destructive method. In this paper, an aluminum probe of AC potential drop(ACPD) method is applied to the evaluation of two-dimensional artificial defects in ferromagnetic materials. Since the potential drop of the defect end is larger than that of the sound area, the defect can be detected and its position can be clearly confirmed, and the potential drops are changed according to the depth of the defect. The potential drop ratio (Vjmax/Vs) of the defective area has a large value for the defect. The relationship between the potential drop ratio (Vjmax/Vs) of 10 kHz and the defect depth can reduce the error in predicting the depth.