Magnetic vortex array imaging detection method and detection device for detecting defect of steel plate

Abstract

The invention discloses a magnetic vortex array imaging detection method and a magnetic vortex array imaging detection device for detecting the defect of a steel plate, wherein the method comprises the following steps: acquiring a characteristic parameter and determining an optimal excitation frequency; exciting a sinusoidal alternating current magnetic field and inducing an alternating vortex current; acquiring an induction alternating magnetic signal near a detected area of the detected steel plate; processing the induction alternating magnetic signal and conducting the first differential transformation operation to obtain a transformed differential signal; judging whether the differential signal is less than the preset threshold, if so, judging that no defect exists, otherwise, judging that the defect exists, and extracting an area signal; inputting the area signal into a constructed neural network model to implement defect reverse inversion to obtain a defect profile parameter; and drawing a defect profile according to the defect profile parameter to realize imaging. The method uses a concentric ring type magnetic vortex array detection array to detect the defect, so that the defect of the steel plate is detected at the high accuracy, the detection accuracy is improved, and the defect imaging effect is improved.

Description

technical field [0001] The invention relates to the technical field of non-destructive testing, in particular to a magnetic spin array imaging detection method and a detection device for steel plate defects. Background technique [0002] In non-destructive testing, defect imaging detection is the basis for safety assessment of the tested part. With the development of non-destructive testing technology and the improvement of industrial safety testing standards, the requirements for defect detection sensitivity and imaging accuracy of the tested part are getting higher and higher. , especially for the detection of small-sized defects, since they are often completely covered inside the detection coil, it is particularly difficult to accurately locate and quantify them. [0003] Traditional eddy current testing uses detection coils to achieve signal acquisition. The acquired signals are the accumulated information in the entire coil ring, but it is difficult to quantify and imag...

AI Technical Summary

Problems solved by technology

[0002] In non-destructive testing, defect imaging detection is the basis for safety assessment of the tested part. With the development of non-destructive testing technology and the improvement of industrial safety testing standards, the requirements for defect detection sensitivity and imaging accuracy of the tested part are getting higher and higher. , especially for the detection of small-sized defects, because they are often completely covered inside the detection coil, it is particularly difficult to accurately locate and quantify them

[0003] Traditional eddy current testing uses detection coils to achieve signal acquisition. The acquired signals are the accumulated information in the entire coil ring, but it is difficult to realize the quantification and imaging of defects.

Specifically, some existing detection methods use a single or a small number of magnetic sensor chips instead of detection coils to detect defect signals, but because the number of sensors is small and the chips are arranged inside the excitation coil, what it detects is still the accumulated information in the coil. Only simple quantitative analysis of defects can be carried out. Due to the small amount of detection information that can be obtained, it is difficult to achieve high-precision defect imaging

In related technologies, such as the eddy current detection probe based on the TMR magnetic field sensor array and its detection method, it uses four rectangular coils as the excitation source, and uses a dot matrix and a linear array composed of nine magnetic field sensors to detect defects, but the rectangular coil The circumferential consistency is poor, the amount of defect information that the magnetic field sensor can obtain is small, and the defect imaging effect that can be achieved is not mentioned; another example is the giant magnetoresistance eddy current detection method for welding defects based on the k-proximity algorithm, which uses a rectangular coil and Four giant magnetoresistive sensors realize defect eddy current detection, but they can only detect the presence or absence of weld defects and classify weld types, and cannot realize defect imaging

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