Low-frequency electromagnetic detection method for large-scale damage of ferromagnetic materials based on broadband excitation

Abstract

The invention discloses a low-frequency electromagnetic detection method for large-scale damage of ferromagnetic materials based on broadband excitation. Detection direction of the magnetic field signal of low-frequency electromagnetic sensor is determined according to the size of ferromagnetic member detection defect; the reference signal and detection signal acquisition position are selected, fix the distance between sensor and tested part, excite a Chirp signal as a broadband excitation signal to perform broadband excitation low-frequency electromagnetic detection; the computer processes collected broadband detection signal; use the difference of Euclidean distance between reference signal and defect detection signal as a defect characterization parameter to obtain the Euclidean distance curve of different depth defects on the upper and lower surfaces of ferromagnetic components with the detection position. Through the analysis and processing of the low-frequency electromagnetic broadband detection signal, the Euclidean response signal and reference signal under broadband excitation are used to characterize the change of material damage degree, which can effectively reduce the influence of magnetic field skin effect, and is beneficial to the effective characterization of the upper and lower material surface defects of at different depths.

Claims

1. A low-frequency electromagnetic detection method for large-scale damage of ferromagnetic materials based on broadband excitation, comprising the steps of: 1) selecting a piece of ferromagnetic steel plate as a test piece, the ferromagnetic steel plate comprising a surface and an another surface, wherein a thickness of the ferromagnetic steel plate is between 12 mm-16 mm, wherein the surface and the another surface of the ferromagnetic steel plate comprise crack defects of different depths and wherein all of the crack defects have same dimensions except for depth and wherein a maximum one of the depths is less than the thickness of the ferromagnetic steel plate; 2) adjusting a detection direction of a magnetic sensor inside a low-frequency electromagnetic sensor to make the detection direction parallel to the surface of the test piece, wherein a result of the detection result comprises tangential leakage magnetic field strength on the surface of the test piece, wherein magnetic field strength in this direction depends on the defect depth; 3) placing the low-frequency electromagnetic sensor on the surface of the ferromagnetic steel plate so that the low-frequency electromagnetic sensor is in a reference area of the ferromagnetic steel plate that is free of the crack defects, and adjusting a lift-off distance between the low-frequency electromagnetic sensor and the ferromagnetic steel plate to be less than 1 mm; 4) obtaining a reference signal, comprising: adjusting a function generator, the function generator interfaced to a digital oscilloscope and to a power amplifier, to generate an excitation signal comprising a Chirp signal with fixed output voltage and bandwidth for excitation, and activating the power amplifier interfaced to the low-frequency electromagnetic sensor, wherein the low-frequency electromagnetic sensor is interfaced to the digital oscilloscope; simultaneously displaying on the digital oscilloscope the excitation signal and an electromagnetic detection signal detected by the low-frequency electromagnetic sensor at the defect-free reference area of the ferromagnetic steel plate; assigning the electromagnetic detection signal as the reference signal; 5) obtaining defect detection signals, comprising: placing the low-frequency electromagnetic sensor at one side of one of the crack defects; manually controlling a direction the low-frequency electromagnetic sensor is moved along a plurality of detection points so that the moving direction is perpendicular to a longitude of the one crack defect; whenever the low-frequency electromagnetic sensor is placed at one of the detection points, applying the excitation signal to the test piece while simultaneously displaying on the digital oscilloscope the excitation signal and electromagnetic detection signal detected by the low-frequency electromagnetic sensor at that detection point; assigning the electromagnetic detection signals collected at all of the detection points as the defect detection signals; 6) processing the collected reference signal and defect detection signals via a computer, comprising: performing frequency domain analysis on reference signal and each defect detection signal to obtain a spectrum of the reference signal spectrum and a spectrum of the defect detection signal at different ones of the detection points; using Euclidean distance calculation formula to obtain a frequency domain Euclidean distance between the detection signal at each detection point and the reference signal; using the frequency domain Euclidean distance as a defect characteristic parameter to draw a curve of Euclidean distance versus detection position; 7) flipping the test piece and repeating the steps 3) to 6) on the another surface of the test piece comprising obtaining a further curve of Euclidean distance versus detection position based on one or more of the crack defects appearing below the another surface of the test piece; and 8) quantitatively characterizing the crack defects at different depths of the ferromagnetic steel plate based on the Euclidean distance curve and the further Euclidian distance curve, wherein an industrial use of the ferromagnetic steel plate is based on the characterization.

2. A low-frequency electromagnetic detection method for large-scale damage of ferromagnetic materials based on broadband excitation according to claim 1, further comprising: establishing a theoretical calculation model for low-frequency electromagnetic detection magnetic fields at different frequencies based on a theory of magnetic dipoles, comprising: setting a formula for two dimensional magnetic dipole model associated with surface defects in a magnetized ferromagnetic material in a magnetization field H and the area density of magnetic charge is Q in accordance with: $\begin{array}{cc}{H}_x\left(x,y\right)=\frac{Q}{4{\mathrm{\pi \mu }}_0}\left\{\underset{-h_2}{\overset{-h_1}{\int }}\frac{\left(x+w\right)d{y}^{\prime }}{{\left[\begin{array}{c}{\left(x+w\right)}^2+\\ {\left(y-y^{\prime }\right)}^2\end{array}\right]}^{3/2}}-\underset{-h_2}{\overset{-h_1}{\int }}\frac{\left(x-w\right)d{y}^{\prime }}{{\left[\begin{array}{c}{\left(x-w\right)}^2+\\ {\left(y-y^{\prime }\right)}^2\end{array}\right]}^{3/2}}\right\}& \left(1\right)\\ H_y\left(x,y\right)=\frac{Q}{4{\mathrm{\pi \mu }}_0}\left\{\underset{-h_2}{\overset{-h_1}{\int }}\frac{\left(y-y^{\prime }\right)d{y}^{\prime }}{{\left[\begin{array}{c}{\left(x+w\right)}^2+\\ {\left(y-y^{\prime }\right)}^2\end{array}\right]}^{3/2}}-\underset{-h_2}{\overset{-h_1}{\int }}\frac{\left(y-y^{\prime }\right)d{y}^{\prime }}{{\left[\begin{array}{c}{\left(x-w\right)}^2+\\ {\left(y-y^{\prime }\right)}^2\end{array}\right]}^{3/2}}\right\}& \left(2\right)\end{array}$ wherein, Hx represents a tangential magnetic field intensity, Hy represents a normal magnetic field intensity, x represents an abscissa of an observation point P, y represents an ordinate of the observation point P, μ.sub.o represents a permeability of a vacuum permeability, and h.sub.1 represents an upper surface of a defect buried depth, h.sub.2 represents a buried depth of a bottom surface, w represents half of a defect width, and y′ represents a distance from left and right groove wall micro-line elements d.sub.y to the material surface; wherein relationship between magnetic charge density at depth h below the surface of the test piece and surface magnetic charge density of the test piece can be expressed as: $\begin{array}{cc}\frac{Q_h}{Q_0}=e^{-h\sqrt{\pi f\mu \sigma }}& \left(3\right)\end{array}$ wherein, Qh represents the magnetic charge density at distance h from the test piece surface, Q.sub.0 represents the magnetic charge density at the test piece surface, σ represents a permeability of ferromagnetic material, μ represents a conductivity of ferromagnetic material, and f represents an excitation signal frequency, wherein equivalent magnetic dipole model for low-frequency electromagnetic detection is determined in accordance with: $\begin{array}{cc}{H}_x\left(x,y,f\right)=\frac{Q_0}{4{\mathrm{\pi \mu }}_0}\left\{\underset{-h_2}{\overset{-h_1}{\int }}\frac{e^{-y^{\prime }\sqrt{\pi f\mathrm{\mu \sigma }}}\left(x+w\right)d{y}^{\prime }}{{\left[\begin{array}{c}{\left(x+w\right)}^2+\\ {\left(y-y^{\prime }\right)}^2\end{array}\right]}^{3/2}}-\underset{-h_2}{\overset{-h_1}{\int }}\frac{e^{-y^{\prime }\sqrt{\pi f\mathrm{\mu \sigma }}}\left(x-w\right)d{y}^{\prime }}{{\left[\begin{array}{c}{\left(x-w\right)}^2+\\ {\left(y-y^{\prime }\right)}^2\end{array}\right]}^{3/2}}\right\}& \left(4\right)\\ H_y\left(x,y,f\right)=\frac{Q_0}{4{\mathrm{\pi \mu }}_0}\left\{\underset{-h_2}{\overset{-h_1}{\int }}\frac{e^{-y^{\prime }\sqrt{\pi f\mathrm{\mu \sigma }}}\left(y-y^{\prime }\right)d{y}^{\prime }}{{\left[\begin{array}{c}{\left(x+w\right)}^2+\\ {\left(y-y^{\prime }\right)}^2\end{array}\right]}^{3/2}}-\underset{-h_2}{\overset{-h_1}{\int }}\frac{e^{-y^{\prime }\sqrt{\pi f\mathrm{\mu \sigma }}}\left(y-y^{\prime }\right)d{y}^{\prime }}{{\left[\begin{array}{c}{\left(x-w\right)}^2+\\ {\left(y-y^{\prime }\right)}^2\end{array}\right]}^{3/2}}\right\}& \left(5\right)\end{array}$ wherein the magnetic charge density of low-frequency electromagnetic detection is not uniformly distributed with the increase of defect depth, but with an exponential decay trend, wherein the Euclidean distance characterization parameter E (H.sub.d, H.sub.n) can be calculated by formula (6):
E(H.sub.d,H.sub.n)=√{square root over ((Σ(H.sub.di−H.sub.ni).sup.2))}  (6) wherein, H.sub.d represents the magnetic field strength of an area to be detected, H.sub.n represents the reference magnetic field strength of the reference area, H.sub.di represents the magnetic field strength of the area to be detected at each frequency, and H.sub.ni represents the reference magnetic field strength of the reference area at each frequency.

3. A low-frequency electromagnetic detection method for large-scale damage of ferromagnetic materials based on broadband excitation according to claim 1, further comprising: providing a system that comprises the function generator, the power amplifier, the digital oscilloscope, a stabilized current power supply and the low-frequency electromagnetic sensor; dividing an output port of the function generator into two channels, one channel connected to a second channel of the digital oscilloscope for displaying broadband excitation signals comprising the excitation signal and the other channel connected to the input port of the power amplifier; and connecting an output end of the power amplifier to an input end of the low-frequency electromagnetic sensor, connecting an output end of the low-frequency electromagnetic sensor to a first channel of the digital oscilloscope for displaying the electromagnetic signal detected by the low-frequency electromagnetic sensor, and positive and negative poles of the stabilized current power supply respectively to two power supply input terminals of low-frequency electromagnetic sensor for supplying power for the magnetic sensor inside the low-frequency electromagnetic sensor.

Description

DESCRIPTION OF DRAWINGS

(1) FIG. 1 is a cross-sectional view of a rectangular slot two-dimensional magnetic dipole model;

(2) FIG. 2 is a Euclidean distance defect characterization flowchart;

(3) FIG. 3 is a low-frequency electromagnetic detection system diagram; wherein: 1. Function generator, 2. Power amplifier, 3. Digital oscilloscope, 4. Stabilized current power supply, 5. Low frequency electromagnetic sensor;

(4) FIG. 4a is a schematic diagram of upper surface defects scanning and detecting;

(5) FIG. 4b is a schematic diagram of lower surface defects scanning and detecting;

(6) FIG. 5a is diagram showing characterization results of broadband Euclidean distance on the upper surface defect;

(7) FIG. 5b is a diagram showing characterization results of broadband Euclidean distance on the lower surface defect.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

(8) The present invention will be further described below in conjunction with preferred embodiment:

(9) The implementation process includes the following steps:

(10) Construction of the Experimental System:

(11) The system used in the present invention is built based on in FIG. 3, including a function generator 1, a power amplifier 2, a digital oscilloscope 3, a stabilized current power supply 4 and a low-frequency electromagnetic sensor 5. First, divide the output port of the function generator 1 into two channels, one connected to the second channel of digital oscilloscope 3 for displaying broadband excitation signals, and the other connected to the input port of the power amplifier 2 for magnetizing DUT. Then, output end of the power amplifier 2 is connected to the input end of the low-frequency electromagnetic sensor 5, and its output end is connected to the first channel of the digital oscilloscope 3 for displaying the electromagnetic signal detected by the low-frequency electromagnetic sensor 5. Finally, the positive and negative poles of stabilized current power supply 4 are respectively connected to the two power supply input terminals of low-frequency electromagnetic sensor 5 for supplying the power for magnetic sensor inside low-frequency electromagnetic sensor 5.

(12) Magnetic sensor detection direction selection: the test piece is 20# low carbon steel plate, a 620×400×12 mm commonly used ferromagnetic material. The steel plate has four standard artificial defects with 25 mm long and 4 mm wide, the depth of these four defects are 4.8 mm, 6.0 mm, 7.2 mm and 9.6 mm. Since the width of the defect is equal and depth is different, the detection direction of magnetic sensor is adjusted to be parallel to the tangential direction on the surface of tested steel plate, so that the electromagnetic detection signal is more sensitive to depth.

(13) Sensor parameter selection: Place the sensor on defect-free side and defective side of the tested steel plate surface, manually control the sensor to maintain a lift-off distance of 1 mm from steel plate surface. Adjust the function generator, set excitation signal to a broadband Chirp signal, control the voltage to 3V, and the frequency bandwidth to 0-150 Hz.

(14) Electromagnetic testing experiment: Place the sensor in non-defective reference area, turn on the power amplifier, and use digital oscilloscope to record and collect the non-defective reference signal. According to FIG. 4a and FIG. 4b, select a 30 mm linear distance perpendicular to the length of defect to make the sensor moves from left to right within the selected linear distance during detect. The detection step length is controlled to 1 mm, and the detection speed changes manually. Use digital oscilloscope to record the excitation signal and electromagnetic detection signal of a single position, and store the defect detection signal of 31 points during movement.

(15) The computer processes the collected reference signals and the defect detection signals. First, perform frequency domain analysis on the reference signal and each detection signal to obtain reference signal spectrum and detection signal spectrum at different positions. Then Euclidean distance calculation formula (6) is used to obtain the frequency domain Euclidean distance between detection signal and reference signal at each detection point, and the distance is used as the defect characteristic parameter to draw the curve of Euclidean distance of the surface defect at different depths with the detection position (As shown in FIG. 5a) and the curve of the Euclidean distance between the lower surface defects and the detection position (as shown in FIG. 5b).

(16) Analysis of experimental results: the depth of each defect and the position of the defect is known. It can be seen from FIG. 5a and FIG. 5b that the peaks in two figures can be judged, and the application of broadband excitation low-frequency electromagnetic detection method can effectively distinguish different depth defects on the upper and lower surfaces of steel plate. For four defects with equal width and different depth, the Euclidean distance detection amplitude on the upper surface is 169.2, 193.0, 212.4, 224.3; the Euclidean distance detection amplitude on the lower surface is 65.36, 75.11, 84.38, 89.33. The detection amplitude of each defect on the upper and lower surfaces is quite different, and the defect separation rate is higher.

(17) While the invention has been particularly shown and described as referenced to the embodiments thereof, those skilled in the art will understand that the foregoing and other changes in form and detail may be made therein without departing from the spirit and scope of the invention.

REFERENCE

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