A pipeline composite defect identification method based on magnetic flux leakage detection

Abstract

The application discloses a pipeline composite defect identification method based on magnetic flux leakage detection, relates to the technical field of pipeline defect detection, and utilizes the characteristics of the radial component of the magnetic flux leakage signal of defects, analyzes the distribution curve of the radial component of the magnetic flux leakage signal of defects, rapidly judges whether the composite pit defects interfere with each other, and further judges whether interference is generated again by combining the size of the ratio E. If formula 1 is satisfied and E>2.5, the two independent pit defects are considered, and the magnetic flux leakage signals do not interfere with each other. If formula 2 is satisfied and 0.5≤E≤2.5, the composite pit defects of the magnetic flux leakage signals interfere with each other. If E<0.5, the composite pit defects are regarded as a large defect, and the method provides help for accurate quantification of subsequent composite defects.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of pipeline defect detection, and in particular to a pipeline composite defect identification method based on magnetic flux leakage detection. BACKGROUND

[0002] In pipeline safety engineering, pipeline detection is a basic method to ensure pipeline safety. Among various types of pipeline detection technologies, magnetic flux leakage detection technology is the most widely used and mature magnetic pipeline defect detection technology, which can obtain the magnetic flux density, i.e., the magnetic flux leakage signal, including the radial component of the magnetic flux density, the axial component of the magnetic flux density, and the circumferential component of the magnetic flux density; wherein the axial direction is along the length of the pipeline, the radial direction is along the direction perpendicular to the inner wall of the pipeline, and the circumferential direction is along the circumference of the pipeline.

[0003] The traditional magnetic flux leakage detection technology cannot accurately identify the composite pit defects of the pipeline during operation, and can only obtain the size and position of the defects according to the magnetic flux leakage signal. However, identifying the composite pit defects of the pipeline has great engineering significance. The peak-to-valley value of the radial component of the magnetic flux density is related to the defect size and the defect distribution form. For the composite pit defects distributed along the axial direction, when the distance between the two pit defects is close or even superimposed, due to the mutual influence of the two pit defects, there are two small peaks with opposite polarity symmetrically distributed between the two characteristic peaks. Analysis shows that this is due to the characteristics of the Bz curve (distribution curve of the radial component of the magnetic flux leakage signal) of the pit defect, which is first negative and then positive. At the middle position, the positive peak of the left pit defect and the negative peak of the right pit defect partially offset, so that the peak value decreases. When the distance between the two pit defects becomes larger and larger, it can be clearly seen that the magnetic field signal characteristics of the two independent pit defects are similar to those of a single defect. At this time, the Bz curve of the composite pit defect presents two obvious characteristic peaks of one negative and one positive, and the signal strength does not change significantly with the increasing distance between the two pit defects. Based on the above analysis, it can be seen that when the two pit defects exist at the same time, the distance between the two pit defects has a significant influence on the magnetic flux leakage field distribution. Therefore, the identification and quantification of the composite pit defects are particularly important in the overall quantification of the pipeline defects. SUMMARY

[0004] In order to overcome the defects in the prior art, the present application provides a pipeline composite defect identification method based on magnetic flux leakage detection, which can meet the overall requirements of composite pit defect identification and quantification.

[0005] To achieve the above purpose, the present application adopts the following technical scheme, comprising:

[0006] A pipeline composite defect identification method based on magnetic flux leakage detection, comprising the following steps:

[0007] S1, obtaining a radial component of a magnetic flux leakage signal of the defect to obtain a distribution curve of the radial component of the magnetic flux leakage signal;

[0008] S2, preliminarily judging the defect according to the distribution curve of the radial component of the magnetic flux leakage signal of the defect:

[0009] In the distribution curve of the radial component of the magnetic flux leakage signal of the defect, there are a maximum peak and a maximum valley; if there are a secondary peak and a secondary valley with opposite polarities and symmetrically distributed between the maximum peak and the maximum valley, the defect is preliminarily judged as a composite defect including two pit defects; if there are no secondary peak and secondary valley with opposite polarities and symmetrically distributed between the maximum peak and the maximum valley, the defect is preliminarily judged as a single pit defect.

[0010] Wherein, the amplitudes of the maximum valley, the secondary peak, the secondary valley and the maximum peak are B z-max1 , B z-max2 , B z-max3 and B z-max4 , respectively.

[0011] S3, further judging the composite defect preliminarily judged as including two pit defects according to the four amplitudes B z-max1 , B z-max2 , B z-max3 and B z-max4 .

[0012] If the four amplitudes B z-max1 , B z-max2 , B z-max3 and B z-max4 satisfy formula 1, it indicates that the magnetic flux leakage signals between the two pit defects in the composite defect do not interfere with each other, i.e. the composite defect is further judged as including two pit defects which do not interfere with each other.

[0013] B z-max2 +B z-max3 >(B z-max1 +B z-max4 )·z% Formula 1

[0014] Wherein, z% is a set proportionality coefficient.

[0015] If the four amplitudes B z-max1 , B z-max2 , B z-max3 and B z-max4 satisfy formula 2, it indicates that the magnetic flux leakage signals between the two pit defects in the composite defect interfere with each other, i.e. the composite defect is further judged as including two pit defects which interfere with each other.

[0016] B z-max2 +B z-max3 ≤(B z-max1 +Bz-max4 )·z% Formula 2

[0017] S4, quantifying the complex defect:

[0018] S41, if the complex defect includes two concave defects that do not interfere with each other, the radii of the two concave defects in the complex defect, i.e. r1 and r2, and the maximum valley value B z-max1 and the maximum peak value B z-max4 of the complex defect are used to quantify the two concave defects in the complex defect respectively;

[0019] S42, if the complex defect includes two concave defects that interfere with each other, the complex defect is quantified in the following way:

[0020] The radii of the two concave defects in the complex defect, i.e. r1 and r2, and the actual center distance D are used to calculate the quantification coefficient E = D / (r1+r2) of the complex defect. The center distance refers to the distance between the centers of the two concave defects;

[0021] If the quantification coefficient E>2.5, the complex defect is considered to include two concave defects that do not interfere with each other, and the two concave defects in the complex defect are quantified respectively according to the way of step S41.

[0022] If the quantification coefficient 0.5≤E≤2.5, the radii of the two concave defects in the complex defect, i.e. r1 and r2, the maximum valley value B z-max1 and the maximum peak value B z-max4 of the complex defect, and the quantification coefficient E are used to quantify the two concave defects in the complex defect respectively;

[0023] If the quantification coefficient 0<E<0.5, the complex defect is considered as a single defect, and the complex defect is quantified as a whole.

[0024] Preferably, in step S4, the radii of the two concave defects in the complex defect, i.e. r1 and r2, and the actual center distance D are obtained according to the distribution curve of the radial component of the magnetic flux leakage signal of the complex defect, in the following specific way:

[0025] The maximum valley in the distribution curve of the radial component of the magnetic flux leakage signal, i.e. point a, and the maximum peak, i.e. point d, are found out;

[0026] Two points with amplitude of 0 in the distribution curve of the radial component of the magnetic flux leakage signal are found out, wherein the point with amplitude of 0 close to the maximum valley, i.e. point a, is point b, and the point with amplitude of 0 close to the maximum peak, i.e. point d, is point c;

[0027] The radius r1 of the first pit defect in the complex defect is the axial distance from point a to point b, the radius r2 of the second pit defect in the complex defect is the axial distance from point c to point d, and the actual center distance D between the two pit defects in the complex defect is the axial distance from point b to point c.

[0028] Preferably, in steps S41 and S42, the quantification of the two pit defects in the complex defect that do not interfere with each other is as follows:

[0029] A plurality of groups of single pit defects with different radii and different depths are simulated, the maximum peak and the maximum trough of the distribution curve of the radial component of the magnetic flux leakage signal of the single pit defect are extracted, and a database of radius-depth-maximum peak value and a database of radius-depth-maximum trough value are respectively constructed;

[0030] The radius r1 of the first pit defect and the maximum trough value B z-max1 are substituted into the database of radius-depth-maximum trough value, and the depth of the first pit defect is obtained by interpolation fitting;

[0031] The radius r2 of the second pit defect and the maximum peak value B z-max4 are substituted into the database of radius-depth-maximum peak value, and the depth of the second pit defect is obtained by interpolation fitting.

[0032] Preferably, in step S42, the quantification of the two pit defects in the complex defect that interfere with each other is as follows:

[0033] A plurality of groups of complex defects with different quantification coefficients are simulated, the complex defects are composed of two pit defects with known radii, known depths, and known center distances, the maximum peak and the maximum trough of the distribution curve of the radial component of the magnetic flux leakage signal of the complex defect are extracted, and a database of quantification coefficient-radius of the first pit defect-depth of the first pit defect-maximum trough value and a database of quantification coefficient-radius of the second pit defect-depth of the second pit defect-maximum peak value are respectively constructed;

[0034] The radius r1 of the first pit defect, the maximum trough value B z-max1 , and the quantification coefficient E are substituted into the database of quantification coefficient-radius of the first pit defect-depth of the first pit defect-maximum trough value, and the depth of the first pit defect is obtained by interpolation fitting;

[0035] The radius r2 of the second pit defect, the maximum peak value B z-max4 , and the quantification coefficient E are substituted into the database of quantification coefficient-radius of the second pit defect-depth of the second pit defect-maximum peak value, and the depth of the second pit defect is obtained by interpolation fitting.

[0036] Preferably, in step S42, the composite defect is regarded as a single defect, and the overall quantification method of the composite defect is:

[0037] According to the distribution curve of the radial component of the magnetic flux leakage signal of the composite defect, the maximum trough point a and the maximum peak point d in the distribution curve of the radial component of the magnetic flux leakage signal are found, and the axial distance between the point a and the point d is the length L of the composite defect.

[0038] A plurality of groups of single defects with different lengths and different depths are simulated, the maximum trough value of the distribution curve of the radial component of the magnetic flux leakage signal of the single defect is extracted, and a length-depth-maximum trough value database is constructed.

[0039] The length L and the maximum trough value B of the composite defect are substituted into the length-depth-maximum trough value database, and the depth of the composite defect is obtained by interpolation fitting. z-max1

[0040] Preferably, in step S3, the set proportion coefficient z% is 95%.

[0041] The present application has the advantages that:

[0042] (1) The present application uses the characteristics of the radial component of the magnetic flux leakage signal of the defect, and according to the calculation of formula 1 and formula 2, it is quickly judged whether it is a composite pit defect interfering with each other, and then it is further confirmed whether interference is generated according to the size of the ratio E. If formula 1 is satisfied and E>2.5, it is considered as two independent pit defects, and the magnetic flux leakage signals do not interfere with each other; if formula 2 is satisfied and E≤2.5, it is a composite pit defect interfering with each other; if E<0.5, the composite pit defect is regarded as a large defect, which provides help for the accurate quantification of the subsequent composite defect.

[0043] (2) Compared with the conventional defect depth quantification method, the quantification method proposed in the present application adds the quantification coefficient E, which can reduce the error of the defect depth quantification compared with the conventional quantification method, greatly improve the accuracy of the composite pit defect depth quantification, and meet the overall requirements of the composite pit defect identification and quantification.

[0044] (3) The present application considers the critical case of the nearest center distance of the two pit defects without interfering with each other, and finds the maximum distance of the two pit defects as a composite defect. This method is not affected by the mutual interference of the pit defect signals, and can accurately identify and quantify the composite pit defect, which provides great help for the detection and evaluation of the pipeline composite defect. BRIEF DESCRIPTION OF DRAWINGS

[0045] Figure 1 It is a pipeline composite defect identification method flow chart based on magnetic flux leakage detection.

[0046] Figure 2 ​The distribution curve of the radial component of the magnetic flux leakage signal for the composite pit defect with left / right pit radius of 3 / 3 mm and center distance of 6 mm, 9 mm, 12 mm, 15 mm and 21 mm, respectively.

[0047] Figure 3 The fitting curve of the different center distances of the composite pit defect and the amplitude of the radial component of the magnetic flux leakage signal, wherein, Figure 3 a is the fitting curve of the composite pit defect with left / right pit radius of 2 / 7 mm, Figure 3 b is the fitting curve of the composite pit defect with left / right pit radius of 3 / 7 mm, Figure 3 c is the fitting curve of the composite pit defect with left / right pit radius of 4 / 7 mm, Figure 3 d is the fitting curve of the composite pit defect with left / right pit radius of 5 / 7 mm, Figure 3 e is the fitting curve of the composite pit defect with left / right pit radius of 6 / 7 mm, Figure 3 f is the fitting curve of the composite pit defect with left / right pit radius of 7 / 7 mm.

[0048] Figure 4 The relationship diagram of the single pit defect with different radii and different depths and the amplitude of the radial component of the magnetic flux leakage signal.

[0049] Figure 5 The relationship diagram of the composite defect with different quantization coefficients and the amplitude of the radial component of the magnetic flux leakage signal. DETAILED DESCRIPTION

[0050] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0051] As shown in FIG. Figure 1 A pipeline composite defect identification method based on magnetic flux leakage detection, comprising the following steps:

[0052] S1, obtaining the radial component of the magnetic flux leakage signal of the defect to obtain the distribution curve of the radial component of the magnetic flux leakage signal.

[0053] S2, according to the distribution curve of the radial component of the magnetic flux leakage signal of the defect, preliminarily judging the defect:

[0054] In the distribution curve of the radial component of the leakage magnetic signal of the defect, there are maximum peaks and maximum troughs. If there are secondary peaks and troughs with opposite polarity and symmetrical distribution between the maximum trough and the maximum peak, the defect is initially identified as a composite defect including two pit defects. If there are no secondary peaks and troughs with opposite polarity and symmetrical distribution between the maximum trough and the maximum peak, the defect is initially identified as a single pit defect.

[0055] Among them, the amplitudes of the maximum trough, the second peak, the second trough, and the maximum peak are B, respectively. z-max1 B z-max2 B z-max3 B z-max4 .

[0056] like Figure 2 As shown, based on the distribution curve of the radial component of the leakage magnetic signal of the composite defect, the radii r1 and r2 of the two pit defects in the composite defect and the actual center distance D are obtained, as follows:

[0057] Find the maximum trough (point a) and maximum peak (point d) in the distribution curve of the radial component of the leakage magnetic signal;

[0058] Find the two points with an amplitude of 0 in the distribution curve of the radial component of the leakage magnetic signal. The point with an amplitude of 0 near the maximum trough (point a) is point b, and the point with an amplitude of 0 near the maximum peak (point d) is point c.

[0059] The radius r1 of the first pit in the composite defect is the axial distance from point a to point b, the radius r2 of the second pit in the composite defect is the axial distance from point c to point d, and the actual center distance D between the two pits in the composite defect is the axial distance from point b to point c.

[0060] S3, based on these four amplitudes B z-max1 B z-max2 B z-max3 B z-max4 Further assessment is needed for the composite defect initially identified as including two pit defects:

[0061] If these four amplitudes B z-max1 B z-max2 B z-max3 B z-max4 If Equation 1 is satisfied, it means that the leakage magnetic signal between the two pit defects in the composite defect does not interfere with each other, that is, the composite defect is further determined to include two non-interfering pit defects:

[0062] B z-max2 +B z-max3 >(B z-max1 +B z-max4 Formula 1

[0063] wherein z% is a set proportion coefficient;

[0064] If the four amplitudes B z-max1 , B z-max2 , B z-max3 , B z-max4 satisfy formula 2, it indicates that the leakage magnetic signal between the two pit defects in the composite defect produces interference, i.e., the composite defect is further determined to include two mutually interfering pit defects:

[0065] B z-max2 +B z-max3 ≤(B z-max1 +B z-max4 )·z% formula 2

[0066] In this embodiment, the set proportion coefficient z% is 95%.

[0067] S4, quantifying the composite defect:

[0068] S41, if the composite defect includes two mutually non-interfering pit defects, the two mutually non-interfering pit defects in the composite defect are quantified according to the radii r1 and r2 of the two mutually non-interfering pit defects and the maximum valley value B z-max1 and the maximum peak value B z-max4 of the composite defect, respectively;

[0069] S42, if the composite defect includes two mutually interfering pit defects, the quantification manner of the composite defect is:

[0070] According to the radii r1 and r2 of the two pit defects in the composite defect and the actual center distance D, the quantification coefficient E=D / (r1+r2) of the composite defect is calculated;

[0071] If the quantification coefficient E>2.5, the composite defect is regarded as including two mutually non-interfering pit defects, and the two mutually non-interfering pit defects in the composite defect are quantified according to the manner of step S41, respectively;

[0072] If the quantification coefficient 0.5≤E≤2.5, the two mutually interfering pit defects in the composite defect are quantified according to the radii r1 and r2 of the two mutually interfering pit defects in the composite defect, the maximum valley value B z-max1 and the maximum peak value B z-max4 of the composite defect, and the quantification coefficient E, respectively;

[0073] If the quantification coefficient 0<E<0.5, the composite defect is regarded as a single defect, and the composite defect is quantified as a whole.

[0074] In steps S41 and S42, the quantification method of the two non-interfering pit defects in the composite defect is as follows:

[0075] A plurality of groups of single pit defects with different radii and different depths are simulated, the maximum peak and the maximum trough of the distribution curve of the radial component of the magnetic flux leakage signal of the single pit defect are extracted, and a database of radius-depth-maximum peak value and a database of radius-depth-maximum trough value are respectively constructed;

[0076] The radius r1 of the first pit defect and the maximum trough value B z-max1 are substituted into the database of radius-depth-maximum trough value, and the depth of the first pit defect is obtained by interpolation fitting method.

[0077] The radius r2 of the second pit defect and the maximum peak value B z-max4 are substituted into the database of radius-depth-maximum peak value, and the depth of the second pit defect is obtained by interpolation fitting method.

[0078] In step S42, the quantification method of the two interfering pit defects in the composite defect is as follows:

[0079] A plurality of groups of composite defects with different quantification coefficients are simulated, the composite defect is composed of two pit defects with known radius, known depth and known center distance, the maximum peak and the maximum trough of the distribution curve of the radial component of the magnetic flux leakage signal of the composite defect are extracted, and a database of quantification coefficient-radius of the first pit defect-depth of the first pit defect-maximum trough value and a database of quantification coefficient-radius of the second pit defect-depth of the second pit defect-maximum peak value are respectively constructed.

[0080] The radius r1 of the first pit defect, the maximum trough value B z-max1 and the quantification coefficient E are substituted into the database of quantification coefficient-radius of the first pit defect-depth of the first pit defect-maximum trough value, and the depth of the first pit defect is obtained by interpolation fitting method.

[0081] The radius r2 of the second pit defect, the maximum peak value B z-max4 and the quantification coefficient E are substituted into the database of quantification coefficient-radius of the second pit defect-depth of the second pit defect-maximum peak value, and the depth of the second pit defect is obtained by interpolation fitting method.

[0082] In step S42, the composite defect is regarded as a single defect, and the overall quantification method of the composite defect is as follows:

[0083] According to the distribution curve of the radial component of the magnetic flux leakage signal of the composite defect, the maximum trough point a and the maximum peak point d in the distribution curve of the radial component of the magnetic flux leakage signal are found, and the axial distance between the point a and the point d is the length L of the composite defect.

[0084] Simulate multiple sets of single defects with different lengths and depths, extract the maximum trough value from the distribution curve of the radial component of the leakage magnetic signal of a single defect, and construct a database of length-depth-maximum trough value;

[0085] The length L and maximum trough value B of the composite defect are... z-max1 Substitute the data into the database of length-depth-maximum trough value, and obtain the depth of the composite defect through interpolation fitting.

[0086] Example 1

[0087] In this embodiment, based on the basic principle of magnetic flux leakage detection technology, the finite element method was used, and the ANSYS electromagnetic field simulation software was employed to simulate the magnetic flux leakage signal of composite pit defects in pipelines.

[0088] Two three-dimensional finite element models of pit defects are established along the axial direction of the pipe to form a three-dimensional finite element model of composite pit defects in the pipe. In this embodiment, a total of 21 composite pit defects are set. The depth of the left and right pits is fixed, and the radii of the left and right pits, i.e., the cross-sectional radii, are 2 / 2mm, 2 / 3mm, 2 / 4mm, 2 / 5mm, 2 / 6mm, 2 / 7mm, 3 / 3mm, 3 / 4mm, 3 / 5mm, 3 / 6mm, 3 / 7mm, 4 / 4mm, 4 / 5mm, 4 / 6mm, 4 / 7mm, 5 / 5mm, 5 / 6mm, 5 / 7mm, 6 / 6mm, 6 / 7mm, and 7 / 7mm, respectively. By changing the center distance between the two pit defects in each composite pit defect, the distribution curves of the radial component of the leakage magnetic field signal of each composite pit defect under different center distances are obtained.

[0089] For example, for a composite pit defect with a left / right pit radius of 2 / 2 mm, the center distance between the two pit defects is set to 4 mm, 6 mm, 8 mm, 10 mm, 12 mm, 14 mm, and 16 mm respectively; for a composite pit defect with a left / right pit radius of 3 / 4 mm, the center distance between the two pit defects is set to 7 mm, 10 mm, 13 mm, 16 mm, 19 mm, 22 mm, and 25 mm respectively; and for a composite pit defect with a left / right pit radius of 4 / 6 mm, the center distance between the two pit defects is set to 10 mm, 14 mm, 18 mm, 22 mm, 26 mm, 30 mm, 34 mm, and 38 mm respectively.

[0090] like Figure 2 As shown, the radial component distribution curves of the leakage magnetic field signal are obtained for a composite pit defect with left / right pit radii of 3 / 3 mm, when the center distances are 6 mm, 9 mm, 12 mm, 15 mm and 21 mm respectively.

[0091] Due to the signal characteristics of the radial component of the magnetic flux leakage signal, four amplitudes will appear on the curve of the radial component of the magnetic flux leakage signal of each composite pit defect, which are marked as B z-max1 , B z-max2 , B z-max3 and B z-max4 from left to right, i.e. the amplitudes of the maximum trough, the secondary peak, the secondary trough and the maximum peak. Among them, B z-max2 and B z-max3 are most affected by signal interference; B z-max1 and B z-max4 will also be affected to a lesser extent, but can be ignored in the identification of composite pit defects.

[0092] If the four amplitudes B z-max1 , B z-max2 , B z-max3 and B z-max4 satisfy formula 1, it means that the magnetic flux leakage signals of the two pit defects do not interfere with each other, i.e. they can be regarded as two separate pit defects:

[0093] B z-max2 +B z-max3 ≥(B z-max1 +B z-max4 )·95% formula 1

[0094] If the four amplitudes B z-max1 , B z-max2 , B z-max3 and B z-max4 satisfy formula 2, it means that the magnetic flux leakage signals of the two pit defects interfere with each other, i.e. they constitute a composite pit defect:

[0095] B z-max2 +B z-max3 ≤(B z-max1 +B z-max4 )·95% formula 2

[0096] According to the above conditions, scatter plots are generated for each group of amplitudes and corresponding different center distances, and it can be found that different center distances and the amplitudes of the radial component have a nonlinear exponential relationship. Nonlinear fitting is performed on the scatter plot, which satisfies the following formula 3:

[0097] y=A1·exp(-x / t1)+y0 formula 3

[0098] Wherein, x is the center distance between the two pit defects, y is B z-max2 +B z-max3 , A1, t1, y0 are fitting coefficients.

[0099] To better explain the method of the present application, the present embodiment is described in detail below in combination with the drawings, and the corresponding y values at different center distances are listed respectively for the left / right pit radius of 2 / 7 mm, 3 / 7 mm, 4 / 7 mm, 5 / 7 mm, 6 / 7 mm and 7 / 7 mm of the composite pit defect, and the fitting results of each group of data are shown in Table 1. Figure 3

[0100] The critical peak-to-valley value yt of each composite pit defect is calculated as yt=(B z-max1 +B z-max4 )·95%. The critical value yt is substituted into the formula fitted for each group of data to obtain the critical center distance Dt between the two pit defects at the critical peak-to-valley value yt of the composite pit defect. The specific data are shown in Table 1.

[0101] Table 1

[0102]

[0103] As can be seen from the data in Table 1, when the sum of the radii of the two pit defects in the composite pit defect, i.e., r1+r2, is larger, the peak-to-valley value B z-max1 +B z-max4 of the radial component of the magnetic flux leakage signal of the composite pit defect is larger, the critical peak-to-valley value yt is larger, and the critical center distance Dt is also larger. However, the ratio E of the critical center distance Dt to the sum of the radii of the composite pit defect r1+r2 is almost unchanged and is stable at about 2.5. Therefore, it can be obtained that if the ratio E is greater than 2.5, the two pit defects are considered as two separate defects, and the magnetic flux leakage signals of the two pit defects are independent and do not interfere with each other. If the ratio E is less than 2.5, the two pit defects constitute a composite pit defect, and the magnetic flux leakage signals generated by the two pit defects interfere with each other, the polarity of the magnetic flux leakage signal at the center position of the composite pit defect is opposite, and the magnetic flux leakage signals cancel each other out, which may generate a small wave peak and a small wave valley, thereby affecting the accuracy of defect quantification.

[0104] Therefore, according to the characteristics of the radial component of the magnetic flux leakage signal of the defect and the calculation according to the formula 1 and the formula 2, it is quickly judged whether it is a composite pit defect, and then it is confirmed again whether interference is generated according to the size of the ratio E. If the formula 1 is satisfied, it is considered as two independent pit defects, the magnetic flux leakage signals do not interfere with each other, and E>2.5. If the formula 2 is satisfied, it is a composite pit defect, the magnetic flux leakage signals interfere with each other, and E≤2.5. The method provides help for the accurate quantification of subsequent composite defects.

[0105] According to the judgment method of the composite pit defect described above, whether it is a composite pit defect is judged, and then the radius r1, the radius r2 and the actual center distance D of the two pit defects are analyzed according to the characteristics of the radial component of the magnetic flux leakage signal to obtain the coefficient E. ​

[0106] wherein, Figure 2 For example, the radius r1 of the left pit defect is the axial distance from point a to point b, the radius r2 of the right pit defect is the axial distance from point c to point d, and the actual center distance D of the two pit defects is the axial distance from point b to point c.

[0107] If the two pit defects do not constitute a composite pit defect, E≥2.5, according to the conventional defect quantification method, the relationship between the leakage magnetic signal component amplitudes B z-max1 and B z-max4 corresponding to the defect depth h is used to estimate the defect depth, as shown in Figure 4 .

[0108] If the two pit defects constitute a composite pit defect, 0.5≤E≤2.5 (E is less than 0.5, which can be regarded as two defects merging into one large defect). If the conventional method is used to quantify the composite pit defect (as shown in Figure 4 ), there will be a large error. Through a large amount of sample data feedback, the smaller E is, the stronger the signal interference is, the larger the quantification error of the composite pit defect is, and the defect depth is overestimated. Because the radial amplitude is disturbed to different degrees when the composite pit defect exists, and the signal center baseline changes due to the disturbance, the zero point is offset, resulting in a certain error in the defect radius and the center distance, which affects the quantification of the defect depth. Therefore, E is one of the main references for the quantification of the defect depth. When quantifying the composite pit defect, we consider the changes of the leakage magnetic signal radial component amplitudes B z-max1 and B z-max4 together with the defect radius r, the defect depth h, and the quantification coefficient E as independent variables. When quantifying the depth of the composite pit defect, the purpose of adding the quantification coefficient E is to reduce the error in the quantification of the defect depth relative to the conventional quantification method. The quantification relationship of the composite pit defect is obtained by fitting a four-dimensional image through interpolation, as shown in Figure 5 .

[0109] The results of the embodiment show that, compared with the conventional defect depth quantification method, the method proposed in the present application can greatly improve the accuracy of the quantification of the depth of the composite pit defect, and can meet the overall requirements of the identification and quantification of the composite pit defect.

[0110] The above is only a preferred embodiment of the present application, and is not intended to limit the present application. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for identifying composite defects of a pipeline based on magnetic flux leakage detection, characterized in that, The method comprises the following steps: S1, obtaining a radial component of a magnetic flux leakage signal of a defect to obtain a distribution curve of the radial component of the magnetic flux leakage signal; S2, preliminarily judging the defect according to the distribution curve of the radial component of the magnetic flux leakage signal of the defect: In the distribution curve of the radial component of the magnetic flux leakage signal of the defect, there are a maximum peak and a maximum valley; if there are a secondary peak and a secondary valley with opposite polarities and symmetrically distributed between the maximum peak and the maximum valley, the defect is preliminarily judged as a composite defect comprising two pit defects; If there are no secondary peak and secondary valley with opposite polarities and symmetrically distributed between the maximum peak and the maximum valley, the defect is preliminarily judged as a single pit defect; Wherein, the amplitude of the maximum trough, the secondary peak, the secondary trough and the maximum peak is B z-max1 , B z-max2 , B z-max3 , B z-max4 ; S3, according to this four amplitude B z-max1 , B z-max2 , B z-max3 , B z-max4 Further determination is made on the complex defect preliminarily determined to include two pit defects: If the four amplitudes B z-max1 , B z-max2 , B z-max3 , B z-max4 satisfy formula 1, it indicates that the leakage magnetic signals between the two pit defects in the composite defect do not interfere with each other, i.e. the composite defect is further determined to include two pit defects that do not interfere with each other: B z-max2 +B z-max3 >(B z-max1 +B z-max4 )·z% Formula 1 Wherein z% is a set proportion coefficient; If the four amplitudes B z-max1 , B z-max2 , B z-max3 , B z-max4 satisfy formula 2, it indicates that the leakage magnetic signal between the two pit defects in the complex defect produces interference, that is, the complex defect is further determined to include two mutually interfering pit defects: B z-max2 +B z-max3 ≤(B z-max1 +B z-max4 )·z% Equation 2 S4, quantifying the composite defect: S41, if the composite defect consists of two non-interfering pit defects, then based on the radii r1 and r2 of the two non-interfering pit defects in the composite defect, and the maximum trough value B of the composite defect... z-max1 and maximum peak value B z-max4 Quantify two non-interfering pit defects in a composite defect separately. S42, if the composite defect comprises two pit defects interfering with each other, the quantification mode of the composite defect is: According to the radii r1 and r2 of the two pit defects in the composite defect and the actual center distance D, a quantification coefficient E of the composite defect is calculated, E=D / (r1+r2); the center distance refers to the distance between the centers of the two pits; If the quantification coefficient E>2.5, the composite defect is regarded as comprising two pit defects not interfering with each other, and the two pit defects not interfering with each other in the composite defect are quantified according to the mode of step S41; If the quantization coefficient E is 0.5≤E≤2.5, then according to the radii r1, r2 of the two mutually interfering pit defects in the complex defect, the maximum valley value B of the complex defect z-max1 and the maximum peak value B z-max4 and the quantization coefficient E, the two mutually interfering pit defects in the complex defect are quantized respectively; If the quantification coefficient 0<E<0.5, the composite defect is regarded as a single defect, and the composite defect is quantified as a whole.

2. The method according to claim 1, wherein, In step S4, according to the distribution curve of the radial component of the magnetic flux leakage signal of the composite defect, the radii r1 and r2 of the two pit defects in the composite defect and the actual center distance D are obtained, and the specific mode is as follows: Find the maximum valley point a and the maximum peak point d in the distribution curve of the radial component of the magnetic flux leakage signal; Find two points with an amplitude of 0 in the distribution curve of the radial component of the magnetic flux leakage signal, wherein the point with an amplitude of 0 close to the maximum valley point a is point b, and the point with an amplitude of 0 close to the maximum peak point d is point c; The radius r1 of the first pit defect in the composite defect is the axial distance from point a to point b, the radius r2 of the second pit defect in the composite defect is the axial distance from point c to point d, and the actual center distance D between the two pit defects in the composite defect is the axial distance from point b to point c.

3. The method according to claim 2, wherein, In steps S41 and S42, the quantification mode of the two pit defects not interfering with each other in the composite defect is: A plurality of groups of single pit defects with different radii and different depths are simulated, the maximum peak and the maximum valley of the distribution curve of the radial component of the magnetic flux leakage signal of the single pit defect are extracted, and a database of radius-depth-maximum peak value and a database of radius-depth-maximum valley value are respectively constructed; The radius r1 of the first pit defect is compared with the maximum valley value B z-max1 The depth of the first pit defect is obtained by an interpolation fitting method through the database of radius-depth-maximum valley value. The radius r2 of the second pit defect is compared with the maximum wave crest value B z-max4 The depth of the second pit defect is obtained by the interpolation fitting method by substituting the radius-depth-maximum wave crest value database.

4. The method according to claim 2, wherein, In step S42, the quantification mode of the two pit defects interfering with each other in the composite defect is: The complex defects of multiple sets of different quantization coefficients are simulated, the complex defects are composed of two pit defects with known radius, known depth and known center distance, the maximum peak and the maximum trough of the distribution curve of the radial component of the magnetic flux leakage signal of the complex defects are extracted, and a database of quantization coefficient-first pit defect radius-first pit defect depth-maximum trough value and a database of quantization coefficient-second pit defect radius-second pit defect depth-maximum peak value are respectively constructed; The radius r1 of the first pit defect, the maximum valley value B z-max1 The quantization coefficient E is substituted into the database of quantization coefficient-radius of the first pit defect-depth of the first pit defect-maximum valley value, and the depth of the first pit defect is obtained by an interpolation fitting method. The radius r2 of the second pit defect, the maximum peak value B z-max4 The quantization coefficient E is substituted into the database of quantization coefficient-second pit defect radius-second pit defect depth-maximum peak value, and the depth of the second pit defect is obtained by interpolation fitting.

5. The method of claim 2, wherein the method further comprises: In step S42, the complex defect is regarded as a single defect, and the overall quantization mode of the complex defect is: According to the distribution curve of the radial component of the magnetic flux leakage signal of the complex defect, the maximum trough, i.e., point a, and the maximum peak, i.e., point d, of the distribution curve of the radial component of the magnetic flux leakage signal are found, and the axial distance between the point a and the point d is the length L of the complex defect; Multiple sets of single defects with different lengths and different depths are simulated, the maximum trough value of the distribution curve of the radial component of the magnetic flux leakage signal of the single defect is extracted, and a database of length-depth-maximum trough value is constructed; The length L, the maximum valley value B of the complex defect are measured by using the optical microscope and the surface profiler. z-max1 The length-depth-maximum valley value database is substituted, and the depth of the complex defect is obtained by the interpolation fitting method.

6. The method of claim 1, wherein the method is characterized by, In step S3, the set proportion coefficient z% is 95%.

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