Pulsed Remote Field Eddy Current Testing (PRFECT) attracts the attention in the testing of ferromagnetic pipes because of its continuous spectrum. This paper simulated the practical PRFECT of pipes by using ANSYS software and employed Least Squares Support Vector Regression (LSSVR) to extract the zero-crossing time to analyze the pipe thickness. As a result, a secondary peak is found in zero-crossing time when transmitter passed by a defect. The secondary peak will lead to wrong quantification and the localization of defects, especially when defects are found only at the transmitter location. Aiming to eliminate the secondary peaks, double sensing coils are set in the transition zone and Wiener deconvolution filter is applied. In the proposed method, position dependent response of the differential signals from the double sensing coils is calibrated by employing zero-mean normalization. The methods proposed in this paper are validated by analyzing the simulation signals and can improve the practicality of PRFECT of ferromagnetic pipes.
In the non-destructive testing of ferromagnetic pipes based on remote field eddy currents, an array of sensing coils is often used to detect local defects. While testing, the image that is obtained by sensing coils exhibits a ghost-image, which originates from both the transmitter and sensing coils passing over the same defects in pipes. Ghost-images are caused by transmitters and lead to undesirable assessments of defects. In order to remove ghost-images, two pickup coils are coaxially set to each other in remote field. Due to the time delay between differential signals tested by the two pickup coils, a Wiener deconvolution filter is used to identify the artificial peaks that lead to ghost-images. Because the sensing coils and two pickup coils all receive the same signal from one transmitter, they all contain the same artificial peaks. By subtracting the artificial peak values obtained by the two pickup coils from the imaging data, the ghost-image caused by the transmitter is eliminated. Finally, a relatively highly accurate image of local defects is obtained by these sensing coils. With proposed method, there is no need to subtract the average value of the sensing coils, and it is sensitive to ringed defects.
Remote Field Eddy Current Testing (RFECT) has broad applications in ferromagnetic pipe testing due to the same testing sensitivity to inner and outer wall defects. However, how to quantify wall thickness in the RFECT of pipes is still a big problem. According to researchers’ studies, a linear relationship exists between the wall thickness, permeability and conductivity of a pipe and the phase of the RFECT signal. Aiming to quantify wall thickness by using this linear function, it is necessary to further study the effects of pipe permeability and conductivity on the phase of the RFECT signal. When the product value of the permeability and the conductivity of a pipe remains constant, the univariate analysis and Finite Element Analysis (FEA) are employed to analyze the variations among the phase of the RFECT signal caused by different couples of permeability and conductivity. These variations are calibrated by using a nonlinear fitting method. Moreover, Multi-Frequency Eddy Current Testing (MFECT) is applied to inverse the permeability and conductivity of a pipe to compensate for the quantification analysis of wall thickness. The methods proposed in this paper are validated by analyzing the simulation signals and can improve the practicality of RFECT of ferromagnetic pipes.
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