Method and device for detecting defects through magnetic flux leakage

Abstract

The invention provides a magnetic flux leakage defect detection method and device. The device comprises a fixing mechanism, a moving mechanism, a magnetic field excitation device, a magnetic field detection device and a data processing unit. The method comprises the following steps: generating magnetic flux in a local area of a to-be-detected object; moving along the axial direction to collect a first measuring line magnetic field signal; performing circular motion around the to-be-detected object to a next measuring line position; repeatedly collecting until the whole circular scanning is completed; and analyzing the magnetic field signal to determine a suspected defect position. By generating magnetic flux in a local area, power consumption is reduced, and long-time work at a bridge cable pole and the like is facilitated; a multi-sensor differential detection and wave crest recognition algorithm is adopted, so that the defect detection reliability is improved; and the portable wind power generation equipment is combined as continuous power supplement, so that the equipment is lighter and easier to operate, and meanwhile, the detection efficiency and accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of non-destructive testing, and particularly to a method and device for detecting defects by magnetic flux leakage. Background Art

[0002] In bridge engineering, cable-stays are key components for bearing the load of a bridge, and their safety directly affects the overall structural safety of the bridge. Bridge cable-stays are generally composed of multiple strands of steel wires, with a layer of protective material wrapped around the outside. The steel wires are wound by multiple layers of wires. During long-term use, due to uneven stress distribution, material fatigue, and environmental factors, internal wires may break or be damaged. Such internal defects are usually difficult to directly observe from the outside and require specialized detection techniques for identification.

[0003] Currently, magnetic flux detection technology is mainly used for detecting broken wires in steel wires. This technology determines whether there are broken wires by measuring the change in magnetic flux at the cross-section of the steel wires. However, traditional magnetic flux detection technology has obvious deficiencies. First, the traditional method requires the overall magnetization of the cable-stay, so electromagnetic equipment with a large power is needed, which results in a large volume and heavy weight of the equipment and is difficult to operate in the high-altitude working environment of a bridge. Second, since bridge cable-stays are usually located at high altitudes, the on-site power supply conditions are limited, and the continuous operation of high-power equipment is difficult to guarantee, resulting in low detection efficiency or interruption. In addition, the sensitivity of traditional detection methods is limited, and the detection ability for small fractures or early damage inside the cable-stay is insufficient, prone to missed detections.

[0004] In the high-altitude working environment, the power supply problem of the detection equipment is particularly prominent. The cable-stay detection work usually requires the equipment to stay on the bridge for a long time, and the battery capacity is limited. Erecting a temporary power supply line not only increases the operation difficulty but also introduces potential safety hazards. At the same time, the existing detection methods have low positioning accuracy for the defect location, and it often takes multiple repeated detections to determine the accurate location, which not only increases the detection time but also increases the work intensity.

[0005] There is a lack of a portable detection method and device in the prior art that can both meet the requirements of the high-altitude working environment of bridge cable-stays and provide reliable detection results. The difficulty in cable-stay defect detection lies in how to achieve accurate and efficient detection under limited power conditions, while the equipment is easy to operate and can work for a long time. Summary of the Invention

[0006] The purpose of the present invention is to provide a method and device for detecting defects by magnetic flux leakage to solve the problem of how to improve the detection reliability and efficiency.

[0007] To achieve the above technical purpose, the present invention provides a method for detecting defects by magnetic flux leakage, including: Generating magnetic flux in a local area of the object to be detected; Move along the axis of the object to be detected and collect the magnetic field signals on the first measurement line; Make a circular motion around the object to be detected to the next measurement line position; Repeat the collection step until the entire circumference of the object to be detected is scanned; and Analyze the collected magnetic field signals to determine the positions of suspected defects in the object to be detected.

[0008] Optionally, the analysis of the collected magnetic field signals includes: Normalize the collected magnetic field signals; Calculate the local gradient of the magnetic field signals; Calculate the overall fluctuation intensity of the magnetic field signals; and Identify the peaks in the magnetic field signals as the positions of suspected defects.

[0009] Optionally, the calculation of the local gradient calculates the gradient of each point through first-order differences: ; ; where, in the formula, G A (i, j) and G B (i, j) represent the gradient values at the position (i, j) in matrix A and matrix B respectively; and represent the partial derivatives of matrix A in the x direction and y direction respectively; and represent the partial derivatives of matrix B in the x direction and y direction respectively; A(i, j + 1) - A(i, j) represents the first-order difference of A in the x direction; A(i + 1, j) - A(i, j) represents the first-order difference of A in the y direction; B(i, j + 1) - B(i, j) represents the first-order difference of B in the x direction; B(i + 1, j) - B(i, j) represents the first-order difference of B in the y direction.

[0010] Optionally, the overall fluctuation intensity is calculated through the root mean square value: ; where, in the formula, RMS A and RMS B represent the root mean square values of matrix A and matrix B respectively, measuring the overall fluctuation intensity; M and N represent the number of rows and columns of the matrix respectively; GA(i, j) and GB(i, j) represent the gradient values at the position (i, j); 1 / (M×N) represents the average factor, which is the reciprocal of the total number of points in the matrix.

[0011] Optionally, the identification of the peaks in the magnetic field signals includes: Perform smoothing filtering on the magnetic field signal; Set the peak threshold; and Calculate the distribution range of the peaks.

[0012] Optionally, it further includes: Determine the measuring line and axial position where it is located according to the position of the suspected defect; and Perform a secondary inspection on the wrapped surface of the part with the maximum peak value.

[0013] The present invention also provides a device for detecting magnetic flux leakage defects, including: A fixing mechanism for fixing the device on the object to be detected; A moving mechanism connected to the fixing mechanism, the moving mechanism can move axially along the object to be detected and can make a circular motion around the object to be detected; A magnetic field excitation device arranged at the end of the moving mechanism for generating magnetic flux in a local area of the object to be detected; A magnetic field detection device arranged near the magnetic field excitation device for detecting magnetic field signals; and A data processing unit for processing the data collected by the magnetic field detection device.

[0014] Optionally, the object to be detected is a bridge cable rod, the fixing mechanism is a cable rod fixing ring, the moving mechanism is a telescopic rod, the magnetic field excitation device is a magnetic flux leakage excitation coil, the magnetic field detection device is a magnetic field differential detector, and the magnetic field differential detector includes at least two magnetic field electro-effect detection sensors arranged at intervals.

[0015] Optionally, it further includes a portable wind power generation device for providing power for the device.

[0016] Optionally, the moving mechanism includes a driving device for controlling the axial movement and circular motion of the moving mechanism; the data processing unit includes a data acquisition module and a data analysis module, the data acquisition module is used to record the magnetic field signals on each measuring line, and the data analysis module is used to calculate the magnetic field gradient and identify the magnetic field peaks.

[0017] Compared with the prior art, the present invention has at least the following beneficial effects: The method for detecting magnetic flux leakage defects provided by the present invention generates magnetic flux in a local area of the object to be detected instead of magnetizing the entire cross-section, significantly reducing the power demand; at the same time, through systematic scanning in the axial and circumferential directions and combining multi-dimensional signal analysis methods, it can accurately locate the suspected defect positions, improving the detection reliability and efficiency.

[0018] The device for magnetic flux leakage detection of defects provided by the present invention has the characteristics of being structurally compact and operationally convenient. In particular, by using a portable wind power generation device to provide continuous power supply for the detection device, the problem of difficult power supply in scenarios such as high-altitude bridge cables and poles is solved. The magnetic field differential detector and data processing technology adopted by the device can effectively identify weak magnetic field changes, improve the sensitivity and accuracy of defect detection, and provide a reliable guarantee for the safety monitoring of important facilities such as bridges. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a block diagram of the method steps for magnetic flux leakage detection of defects in an embodiment of the present invention; Figure 2 It is a schematic structural diagram of the device for magnetic flux leakage detection of defects in an embodiment of the present invention; Figure 3 It is a layout diagram of measurement lines in the method for magnetic flux leakage detection of defects in an embodiment of the present invention.

[0020] In the figure, 1, fixing mechanism; 2, moving mechanism; 3, magnetic field detection device; 4, magnetic field excitation device. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] The following will describe in more detail a method and device for magnetic flux leakage detection of defects of the present invention with reference to the accompanying drawings, in which the preferred embodiments of the present invention are shown. It should be understood that those skilled in the art can modify the present invention described herein while still achieving the advantageous effects of the present invention. Therefore, the following description should be understood as a broad guidance for those skilled in the art and not as a limitation to the present invention.

[0022] In the following paragraphs, the present invention will be described more specifically by way of example with reference to the accompanying drawings. According to the following description, the advantages and features of the present invention will be clearer. It should be noted that the accompanying drawings are all in a very simplified form and use non-precise scales, only for the purpose of facilitating and clearly assisting in explaining the objectives of the embodiments of the present invention.

[0023] Embodiment 1 An embodiment of the present invention provides a method for magnetic flux leakage detection of defects. Please refer to Figure 1 , including: S1. Generate magnetic flux in a local area of the object to be detected; S2. Move along the axis of the object to be detected and collect the magnetic field signals on the first measurement line; S3. Make a circular motion around the object to be detected to reach the position of the next measurement line; S4. Repeat the collection step until the entire circumference of the object to be detected is scanned; and S5. Analyze the collected magnetic field signals to determine the positions of suspected defects in the object to be detected.

[0024] Specifically, in step S1, a local magnetic flux is generated on the surface of the object to be detected through the magnetic field excitation device 4. Compared with the traditional full-section magnetization, this method only needs to generate magnetic flux in a local area, greatly reducing power consumption.

[0025] In a specific example, the object to be detected can be a bridge cable rod, which is composed of multiple strands of steel strands and is wrapped with a layer of protective material on the outside. The steel strands are wound by multiple wires. In the case of uneven stress, there may be defects such as partial wire breakage or damage. The magnetic field excitation device 4 can be a magnetic flux leakage excitation coil.

[0026] In step S2, move along the axis of the object to be detected and collect the magnetic field signals on the first measurement line. The magnetic field signals are collected by the magnetic field detection device 3.

[0027] In a specific example, the magnetic field detection device 3 is a magnetic field differential detector, which includes at least two magnetic field electro-effect detection sensors arranged at intervals.

[0028] In a specific example, the magnetic field differential detector includes two sensors, denoted as sensor a and sensor b respectively.

[0029] On the first measurement line of the object to be detected, data points are collected at a preset interval Δl, denoted as V a1 (l) and V b1 (l), where the length of the measurement line is L.

[0030] In step S3, make a circular motion around the object to be detected to reach the next measurement line position. After completing the scan of the first measurement line, the moving mechanism 2 makes a circular motion around the object to be detected, moving an arc length of Δr to reach the next measurement line position.

[0031] In this embodiment, the moving mechanism 2 can be a telescopic rod, which is connected to the fixing mechanism 1 and can make a circular motion along the fixing mechanism 1. The fixing mechanism 1 can be a cable rod fixing ring for fixing the device on the object to be detected.

[0032] In step S4, repeat the collection steps until the entire circumference of the object to be detected is scanned. On each measurement line i, data is collected in the same way as the first measurement line, denoted as V ai (l) and V bi (l). A total of n measurement lines are collected until the entire circumference is scanned.

[0033] In step S5, analyze the collected magnetic field signals to determine the positions of suspected defects in the object to be detected. The analysis includes: S5.1, perform normalization processing on the collected magnetic field signals.

[0034] Since the data may have different magnitudes, normalization is required: ; Among them, A'(i, j) and B'(i, j) are normalized to the range of [0, 1]. The A and B matrices are composed of survey line data. A'(i, j) and B'(i, j) respectively represent the values of the normalized matrices A and B at the position (i, j); min(A) and max(A) respectively represent the minimum and maximum values in matrix A; min(B) and max(B) respectively represent the minimum and maximum values in matrix B; the normalization process maps all data to the range of [0, 1], which is convenient for subsequent analysis and comparison.

[0035] Specifically: ; Among them, {n / 2} is the integer part of n / 2. The reason for continuing to splice 1, 2,..., {n / 2} after the matrix n serial number is that the object to be detected is circular, avoiding recognition deviation caused by defects appearing near the survey line.

[0036] S5.2, Calculate the local gradient of the magnetic field signal. Use the first-order difference to calculate the gradient of each point: ; Among them: ; Among them, in the formula, G A (i, j) and G B (i, j) respectively represent the gradient values at the position (i, j) of matrices A and B; and respectively represent the partial derivatives of matrix A in the x and y directions; and respectively represent the partial derivatives of matrix B in the x and y directions; A(i, j + 1) - A(i, j) represents the first-order difference of A in the x direction; A(i + 1, j) - A(i, j) represents the first-order difference of A in the y direction; B(i, j + 1) - B(i, j) represents the first-order difference of B in the x direction; B(i + 1, j) - B(i, j) represents the first-order difference of B in the y direction.

[0037] The gradient matrices GA and GB represent the fluctuation intensity at each position.

[0038] S5.3, Calculate the overall fluctuation intensity of the magnetic field signal. Use the root mean square (RMS) to measure the overall fluctuation intensity: ; Among them, in the formula, RMSA and RMS B represent the root mean square values of matrix A and matrix B respectively, measuring the overall fluctuation intensity; M and N represent the number of rows and columns of the matrix respectively; GA(i, j) and GB(i, j) represent the gradient values at position (i, j) respectively; 1 / (M×N) represents the average factor, which is the reciprocal of the total number of points in the matrix.

[0039] S5.4. Identify the peaks in the magnetic field signal as the suspected defect positions. A peak is a local maximum point that satisfies: ; Among them, the peak identification is based on the local maximum principle. A(i, j)>A(i - 1, j), A(i, j)>A(i + 1, j), A(i, j)>A(i, j - 1), A(i, j)>A(i, j + 1) mean that the value at position (i, j) is greater than the values at its four adjacent positions above, below, left, and right; the judgment conditions for B(i, j) are similar, jointly realizing that the detected is a true local maximum point rather than a fluctuation caused by noise.

[0040] Since noise may affect peak identification, the following additional steps are required: S5.4.1. Perform smoothing filtering on the magnetic field signal. Use Gaussian filtering to remove local high-frequency noise: ; Among them, A s (i, j) and B s (i, j) represent the values of the smoothed filtered matrix A and matrix B at position (i, j) respectively; ω(m, n) represents the Gaussian weight function; m and n are the relative coordinates of the filtering window, ranging from -k to k.

[0041] Gaussian weight: ; Usually, σ≈1.5 is selected for smoothing.

[0042] S5.4.2. Set the peak threshold. The screening criteria for peaks are: ; Among them, μA, σA are the mean and standard deviation of A s (i,j), μB and σB are the mean and standard deviation of matrix B s respectively; α is an adjustment parameter, usually taking the value of 1.5, which is used to select peaks within a certain range above the mean.

[0043] S5.4.3. Calculate the distribution range of peaks. The distribution range of peaks can be determined by the region growing algorithm: Take the local maximum point (i, j) as the seed point; If the adjacent points satisfy , then they are classified into the same peak region; Calculate the center point, area, and average height of each peak region.

[0044] In the formula, |As(i', j') - As(i, j)| < ε means that the difference between the adjacent point and the seed point is less than the threshold ε, which is used to determine the boundary of the peak region.

[0045] Further, it further includes the step: S6. Determine the measuring line and axial position where the suspected defect is located according to the position of the suspected defect.

[0046] According to the matrix position where the peak is located, it is possible to determine which measuring line the defect is located on and which axial position on the measuring line.

[0047] S7. Perform a secondary inspection on the wrapped surface of the part with the maximum peak value.

[0048] Select the part with the maximum signal peak value and perform a more detailed inspection to confirm the defect situation. For bridge cables and poles, it may be necessary to cut open the wrapped surface to check whether the steel strands are broken or damaged.

[0049] The method for detecting defects by magnetic flux leakage provided in this embodiment can comprehensively capture the defect information on the surface and inside of the object to be detected by generating magnetic flux in the local area of the object to be detected and adopting a scanning strategy combining the axial direction and the circumference. This method consumes less power and is suitable for environments with difficult power supply; through multi-sensor differential detection and complex data processing algorithms, the reliability of defect detection is improved; by using peak recognition and analysis techniques, the defect position can be accurately located, providing precise guidance for subsequent maintenance. It is particularly suitable for the detection of structures such as bridge cables and poles where it is difficult to directly observe the internal state.

[0050] Embodiment 2 The embodiment of the present invention provides a device for detecting defects by magnetic flux leakage. Please refer to Figure 2 , the device for detecting defects by magnetic flux leakage includes: a fixing mechanism 1, a moving mechanism 2, a magnetic field excitation device 4, a magnetic field detection device 3, and a data processing unit.

[0051] The fixing mechanism 1 is used to fix the device on the object to be detected. In this embodiment, when the object to be detected is a bridge cable and pole, the fixing mechanism 1 is a cable and pole fixing ring. The cable and pole fixing ring can firmly fix the device at a specific position of the cable and pole, realizing the stability of the device position during the detection process.

[0052] The moving mechanism 2 is connected to the fixed mechanism 1, and the moving mechanism 2 can move axially along the object to be detected and can perform a circular motion around the object to be detected. In this embodiment, the moving mechanism 2 is a telescopic rod. The telescopic rod can be shortened and elongated, facilitating the device to scan along the axial direction of the object to be detected. At the same time, the telescopic rod can perform a circular motion along the fixed ring, facilitating the scanning of the entire side surface of the object to be detected. In a specific example, the moving mechanism 2 includes a driving device for controlling the axial movement and circular motion of the moving mechanism 2.

[0053] The driving device can adopt driving methods such as motors, stepper motors or servo motors to achieve precise control, which belongs to the common means of those skilled in the art and will not be elaborated herein.

[0054] The magnetic field excitation device 4 is arranged at the end of the moving mechanism 2 for generating magnetic flux in a local area of the object to be detected. In this embodiment, the magnetic field excitation device 4 is a magnetic flux leakage excitation coil. The magnetic flux leakage excitation coil is closely attached to the surface of the object to be detected to generate local magnetic flux. Since it is not necessary to magnetize the entire cross-section of the object to be detected, the power of the magnetic flux leakage excitation coil is relatively small. Compared with the traditional full cross-section magnetization, the weight of the device is significantly reduced.

[0055] In a specific example, the magnetic flux leakage excitation coil can be wound with a copper wire with 500 - 1000 turns and a wire diameter of 0.5 - 1.0 mm. The specific parameters can be adjusted according to the material and size of the object to be detected, which belongs to the common means of those skilled in the art and will not be elaborated herein.

[0056] The magnetic field detection device 3 is arranged near the magnetic field excitation device 4 for detecting magnetic field signals. In this embodiment, the magnetic field detection device 3 is a magnetic field differential detector, and the magnetic field differential detector includes at least two magnetic field electro-effect detection sensors arranged at intervals. When the amplitude of the alternating magnetic field is strong, the voltage peak output by the magnetic field electro-effect detection sensor is relatively high, corresponding to the appearance of magnetic flux leakage characteristics.

[0057] In a specific example, the magnetic field electro-effect detection sensor can adopt Hall elements, magnetoresistive sensors, giant magnetoresistive sensors or tunnel magnetoresistive sensors, etc. Different sensors have different sensitivities and applicable ranges, and the appropriate sensor type can be selected according to specific application requirements.

[0058] The data processing unit is used to process the data collected by the magnetic field detection device 3. In this embodiment, the data processing unit includes a data acquisition module and a data analysis module. The data acquisition module is used to record the magnetic field signals on each measurement line, and the data analysis module is used to calculate the magnetic field gradient and identify the magnetic field peaks. The data processing unit can process the collected data in real time or store the data for offline analysis. In a specific example, the data processing unit can adopt an embedded processor such as ARM, DSP, etc., and cooperate with necessary storage and communication modules to implement the functions of data acquisition, processing, and transmission.

[0059] In addition, the device may further include a portable wind power generation device, which is used to provide power for the device. There is natural ventilation above the bridge all year round. Using the wind power generation device can supplement electrical energy for the detection device when it is on standby, and improve the working time of the device above the bridge. In a specific example, the portable wind power generation device can adopt a small wind turbine, and cooperate with necessary voltage stabilizing and energy storage devices to provide continuous and stable power supply for the detection device.

[0060] During the operation of the device, first fix the device on the object to be detected through the fixing mechanism 1, start the magnetic field excitation device 4 to generate magnetic flux, and then control the moving mechanism 2 to move along the axis of the object to be detected, and collect the magnetic field signals on the first measurement line through the magnetic field detection device 3. After completing the scanning of the first measurement line, the moving mechanism 2 makes a circular motion around the object to be detected to the next measurement line position, and repeats the collection step until the scanning of the entire circle is completed. Finally, the data processing unit analyzes the collected magnetic field signals to determine the position of the suspected defect.

[0061] The device for detecting magnetic flux leakage defects provided in this embodiment adopts the principle of local magnetization, which greatly reduces the power demand; through the collaborative work of the fixing mechanism 1 and the moving mechanism 2, it realizes the omnidirectional scanning of the object to be detected; uses the portable wind power generation device to solve the power supply problem, and is suitable for working in high-altitude environments such as bridges for a long time; adopts the magnetic field differential detection technology to improve the detection sensitivity and anti-interference ability; the data processing unit can perform complex signal analysis to accurately identify the defect position. The overall design is light and practical, and is especially suitable for structures such as bridge cables and poles that are difficult to access and detect.

[0062] Embodiment Three Based on Embodiment One and Embodiment Two, this embodiment provides an example description for the detection of bridge cables and poles.

[0063] Bridge cable rods are generally composed of multiple strands of steel wire ropes, with a layer of protective material wrapped around the outside. Due to the multi-layer winding of the steel wire ropes, the force distribution may be uneven, and in extreme cases, the steel wires may break or be damaged. The local fracture of the steel wire rope is difficult to detect externally and requires special detection methods for diagnosis.

[0064] The traditional method for detecting bridge cable rods diagnoses broken wires in the steel wire ropes by the difference in magnetic flux, but there are problems such as difficult power supply and bulky and difficult-to-operate equipment on bridge cable rods. The magnetic flux leakage detection method and device provided in this embodiment only generate magnetic flux for local steel wires and require less power consumption. At the same time, by arranging a portable wind power generation device under the equipment, continuous replenishment is provided for the power supply to ensure long-term stay and work on bridge cable rods.

[0065] In specific operations, first fix the cable rod fixing ring on the bridge cable rod, and then drive the magnetic flux leakage excitation coil and the magnetic field differential detector to move along the axial direction of the cable rod through the telescopic rod to collect magnetic field signals. Please refer to Figure 3 , after completing the first measurement line Ⅰ, the telescopic rod makes a circular motion around the cable rod to the next position to perform the second measurement line Ⅱ, and then the telescopic rod makes a circular motion around the cable rod to the next position, and so on until the entire circumference is scanned.

[0066] Data processing includes steps such as signal normalization, gradient calculation, fluctuation intensity calculation, and peak recognition. Through these processes, the possible fracture or damage positions of the steel wire ropes in the cable rod can be identified. For the part with the largest peak value, the cable rod wrapping surface can be cut open for inspection to see if repair is needed.

[0067] This method can accurately detect the broken wire defects in the steel wire ropes, with high detection sensitivity and low false alarm rate. Compared with the traditional method, the detection efficiency is increased by about 30%, the equipment weight is reduced by about 50%, and the power consumption is reduced by about 60%.

[0068] In summary, the magnetic flux leakage detection defect method and device provided by the present invention, while improving the detection sensitivity and accuracy, significantly reduce the energy consumption and equipment weight, improve the operation convenience, and provide a practical and efficient technical solution for the field of structural safety monitoring.

[0069] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these changes and modifications.

Claims

1. A method for detecting defects by magnetic flux leakage, characterized in that: include: Generate magnetic flux to the local area of ​​the object to be detected; Move along the axial direction of the object to be detected to collect the magnetic field signal on the first measuring line; Make circular motion around the object to be detected to the next measuring line position; Repeat the acquisition steps until the entire circumference of the object to be detected is scanned; as well as The acquired magnetic field signal is analyzed to determine the location of the suspected defect in the object to be inspected.

2. The method according to claim 1, characterized in that: The magnetic field signal collected by the analysis includes: Performing normalization processing on the collected magnetic field signal; Calculate the local gradient of the magnetic field signal; Calculate the overall fluctuation strength of the magnetic field signal; and Identify peaks in the magnetic field signal as suspected defect locations.

3. The method according to claim 2, characterized in that The local gradient is calculated by first-order difference to calculate the gradient of each point: ； ； Among them, G in the formula A (i, j) and G B (i, j) represents the gradient value at position (i, j) in matrix A and matrix B respectively; and Respectively represent the partial derivatives of matrix A in the x-direction and y-direction; and denote the partial derivatives of matrix B in the x-direction and y-direction respectively; A(i, j+1) - A(i, j) denotes the first-order difference of A in the x-direction; A(i+1, j) - A(i, j) denotes the first-order difference of A in the y-direction; B(i, j+1) - B(i, j) denotes the first-order difference of B in the x-direction; B(i+1,j) - B(i, j) denotes the first-order difference of B in the y-direction.

4. The method according to claim 2, characterized in that: The overall volatility intensity is calculated by the RMS value: ； Among them, RMS in the formula A and RMS B They represent the root mean square values ​​of matrix A and matrix B, respectively, which measure the overall fluctuation intensity; M and N represent the number of rows and columns of the matrix, respectively; GA(i, j) and GB(i, j) represent the gradient value at position (i, j), respectively; 1 / (M×N) represents the average factor, which is the inverse of the total number of points in the matrix.

5. The method according to claim 2, characterized in that: The identifying of the peaks in the magnetic field signal comprises: Perform smoothing and filtering on magnetic field signals; Setting a peak threshold; and Calculate the distribution range of the peaks.

6. The method according to claim 1, characterized in that Also includes: Determine the measurement line and axial position based on the location of the suspected defect; and Perform a secondary inspection of the wrapping surface at the location with the largest peak.

7. A device for detecting magnetic flux leakage defects, characterized in that: include: A fixing mechanism, used for fixing the device on the object to be detected; A moving mechanism connected to the fixing mechanism, wherein the moving mechanism can move axially along the object to be detected and can make a circular motion around the object to be detected; A magnetic field excitation device disposed at the end of the moving mechanism, used to generate magnetic flux in a local area of ​​the object to be detected; A magnetic field detection device disposed near the magnetic field excitation device, for detecting a magnetic field signal; as well as A data processing unit is used to process the data collected by the magnetic field detection device.

8. The device according to claim 7, characterized in that The object to be detected is a bridge cable, the fixing mechanism is a cable fixing ring, the moving mechanism is a telescopic rod, the magnetic field excitation device is a leakage magnetic excitation coil, the magnetic field detection device is a magnetic field differential detector, and the magnetic field differential detector includes at least two magnetic field electric effect detection sensors arranged at intervals.

9. The device according to claim 7, characterized in that Also included is a portable wind power generating device for providing power to the apparatus.

10. The device according to claim 7, characterized in that The mobile mechanism includes a driving device for controlling the axial movement and circular motion of the mobile mechanism; the data processing unit includes a data acquisition module and a data analysis module, the data acquisition module is used to record the magnetic field signal on each measuring line, and the data analysis module is used to calculate the magnetic field gradient and identify the magnetic field peak.

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