CN114088808A - Pipeline crack visual detection method and system of three-dimensional induced eddy current magnetic field cloud picture - Google Patents
Pipeline crack visual detection method and system of three-dimensional induced eddy current magnetic field cloud picture Download PDFInfo
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Abstract
The invention discloses a pipeline crack visual detection method and a system of a three-dimensional induced eddy current magnetic field cloud picture, wherein the method comprises the following steps: placing a detection probe on a metal pipeline to be detected, wherein the detection probe is used for generating an excitation signal of an eddy magnetic field and measuring the size change of the magnetic field on the surface of the metal pipeline to be detected, and the detection probe comprises two coils and a plurality of magnetic field sensors distributed around the circumferential surface; generating an alternating magnetic field through an exciting coil so as to generate an induced current on the surface of the metal pipeline, acquiring the magnetic induction intensity of a disturbed area on the surface of the metal pipeline to be detected through a magnetic field sensor, and generating a magnetic induction intensity cloud chart according to the magnetic induction intensity and the position of the magnetic field sensor; and carrying out image preprocessing on the generated magnetic induction intensity cloud picture, and removing noise in the magnetic induction intensity cloud picture. The method can realize the visual visualization of the crack defect of the pipeline and improve the accurate evaluation of the defect of the pipeline.
Description
Technical Field
The invention relates to the technical field of nondestructive detection of pipeline cracks, in particular to a pipeline crack visual detection method and system of a three-dimensional induced eddy current magnetic field cloud picture.
Background
With the development of modern industrial technology, metal pipelines play a great role in various fields, and people can not leave various metal pipelines in daily life. Due to long-term use or equipment aging and other reasons, the surface of the metal material is often damaged in different degrees to cause failure, the service performance of the equipment is seriously influenced, and further severe safety accidents such as dangerous goods leakage and explosion can be caused. Therefore, it is important to perform an all-round inspection of the metal pipe to ensure its integrity. The nondestructive testing technology processes and analyzes the change caused by the change of the physical characteristics of the material to obtain the state characteristic related to the quality of the tested object. Eddy current inspection is currently the most common and mature inspection tool in on-line non-destructive inspection applications, using it to detect defects and inspect samples for conditions such as surface cracks, subsurface cracks, and degradation-related defects in pipelines. However, eddy current testing has its own limitations, such as more interference factors and greater lift-off effect. It is difficult to determine the type and shape of a defect at the time of flaw detection, and it is difficult to perform equivalent analysis on the defect. Furthermore, eddy current techniques traditionally rely on variations in the impedance of the pick-up coil. The coil impedance is a comprehensive action result of magnetic field change and other influence factors in a limited interval, one-dimensional information is provided, defects cannot be effectively identified, detection errors are large, and accurate evaluation of the surface defects of the material cannot be realized. Therefore, it is advantageous to measure the magnetic field directly, rather than measuring the time rate of change of the magnetic field. With the continuous improvement of the requirement on the product quality, the response analysis of the defect on the magnetic field signal is urgently needed to be explored, and more useful characteristic information is extracted to establish the quantitative relation between the size of the defect and the surrounding magnetic field. Therefore, the research on the spatial magnetic field detection, the analysis method and the extraction of more feature quantities is a trend to improve the detection accuracy and the eddy current detection.
Disclosure of Invention
Therefore, the pipeline crack visual detection method and system of the three-dimensional induced eddy current magnetic field cloud picture are needed to be provided, the defects existing in the existing electromagnetic detection are overcome, and the detection precision and the intelligent evaluation level are improved.
In order to achieve the purpose, the invention provides a pipeline crack visual detection method of a three-dimensional induced eddy current magnetic field cloud picture, which comprises the following steps:
placing a detection probe on a metal pipeline to be detected, wherein the detection probe is used for generating an excitation signal of an eddy magnetic field and measuring the size change of the magnetic field on the surface of the metal pipeline to be detected, and the detection probe comprises an excitation coil and a plurality of magnetic field sensors distributed around the circumferential surface;
generating alternating current through an exciting coil so as to generate induced current on the surface of the metal pipeline, acquiring the magnetic induction intensity of the current area on the surface of the metal pipeline to be detected through a magnetic field sensor, and generating a magnetic induction intensity cloud chart according to the magnetic induction intensity and the position of the magnetic field sensor;
and carrying out image preprocessing on the generated magnetic induction intensity cloud picture, and removing noise in the magnetic induction intensity cloud picture.
Further, the method also comprises the following steps:
and moving the detection probe and the position of the circuit board above the support plate, and recording the position of the circuit board on the surface of the metal pipeline.
Furthermore, the exciting coil comprises an outer coil and an inner coil, the outer coil is an arc coil coaxial with the metal pipeline to be detected, and the inner coil is a rectangular coil.
Further, different magnetic induction intensities in the magnetic induction intensity cloud chart correspond to different colors.
Further, the method also comprises the following steps: inputting the preset magnetic induction intensity cloud pictures of different defect cracks of the pipeline into a deep learning model for deep learning, calling the deep learning model after deep learning to perform feature matching on the magnetic induction intensity cloud pictures after noise removal, and identifying the surface defects of the metal pipeline to be detected.
Further, the pre-processing comprises processing, defogging, contrast enhancement or lossless amplification by a two-dimensional maximum entropy segmentation method.
The invention provides a pipeline crack visual detection system of a three-dimensional induced eddy current magnetic field cloud picture, which comprises a memory and a processor, wherein the memory is stored with a computer program, and the computer program realizes the steps of the method according to any one of the embodiments of the invention when being executed by the processor.
Different from the prior art, the technical scheme adopts the technical scheme that after the probe double coils generate the excitation current, a variable magnetic field is generated, a disturbance eddy current magnetic field caused by the surface defects of the pipeline is obtained through the magnetic field sensor, and finally a magnetic induction intensity cloud picture is generated. Therefore, the visual visualization of the crack defect of the pipeline can be realized through the image of the magnetic induction intensity cloud chart, and the accurate evaluation of the pipeline defect is improved.
Drawings
FIG. 1 is a schematic view of the probe of the present invention;
FIG. 2 is a model cloud of magnetic induction intensity of the surface of a pipeline under different-orientation cracks;
FIG. 3 is a model cloud of the magnetic induction intensity of the surface of the pipeline under the cracks with different lengths;
FIG. 4 is a model cloud chart of magnetic induction intensity of the surface of a pipeline under different depth cracks;
FIG. 5 is a y-direction magnetic induction intensity cloud chart of the pipeline under different depth cracks.
Detailed Description
To explain technical contents, structural features, and objects and effects of the technical solutions in detail, the following detailed description is given with reference to the accompanying drawings in conjunction with the embodiments.
Referring to fig. 1 to 5, the present embodiment provides a method and a system for visually detecting a pipeline crack by using a three-dimensional induced eddy current magnetic field cloud. In the implementation process, a double-coil non-contact detection probe is placed above the metal pipeline and used for generating an excitation signal of an eddy current magnetic field and measuring the size change of the surface magnetic field of a measured object. Fig. 1 is a schematic diagram of the structure of a probe, which is composed of two exciting coils, a detection sensor and a metal pipe to be detected. The outer coil of the probe is an arc coil coaxial with the pipeline, and the inner coil is a rectangular coil. The upper and lower arc radiuses of the arc-shaped coil are respectively 24mm and 35mm, the width is 40mm, and the thickness is 1 mm; the length of the rectangular coil in the probe is 38mm, the width of the rectangular coil is 30mm, the height of the rectangular coil is 17mm, and the thickness of the rectangular coil is 1 mm. The inner surface of the circular arc coil is just attached to the outer surface of the rectangular coil. The inner and outer radii of the metal pipe are 10mm and 15mm, respectively. The number of turns of the two coils is 200 turns, and the conductivity of the coil leads is 6 multiplied by 107S/m, cross-sectional area of 1X 10-6m2The excitation current is 10A, and the frequency is 200 Hz. Because the magnetic field value on the surface of the pipeline is collected during actual measurement, a cylindrical supporting plate coaxial with the pipeline is designed between the arc coil and the pipeline and used for collecting magnetic induction intensity distribution on the three-dimensional cylindrical section. Above the cylindrical support plate is a designed circuit board which can be rotated in the circumferential direction on the cylindrical support plate and also can be moved in the axial direction above the support plate. The automatic movement of the cylindrical supporting plate can be realized by connecting a mechanical arm which can be fixed on the surface of the metal pipeline to be measured to the supporting plate, and the recording of the position of the cylindrical supporting plate on the surface of the metal pipeline is realized by recording the movement position of the mechanical arm. The circuit board is provided with a plurality of magnetic field sensors in parallel and in sequence, and the magnetic field sensors are used for detecting the change condition of the magnetic field and converting the change condition into electric signals. The circuit board is also provided with a signal interface circuit for connecting the sensor, the power supply and an external device. The circuit board is installed on cylindrical backup pad, can provide with the pipeline surface fixed, stable unchangeable lift from the height.
By analyzing the distribution condition of the cylindrical surface induced eddy current magnetic field near the defect and adopting a proper image processing means, the accurate evaluation of the pipeline surface crack can be realized. The visual pipeline crack detection method based on the three-dimensional induced eddy current magnetic field cloud picture comprises the following steps:
1. placement of test probes
And according to the radius of the pipeline to be detected, reasonably selecting a matched detection probe to ensure that the arc coil and the pipeline are coaxial. The arc coil and the rectangular coil respectively generate induced currents which are different in direction and are uniformly distributed on the surface of the pipeline. In the measuring process, the probe exciting coil is kept static, and after the magnetic field acquisition of the region covered by the probe is finished, the probe exciting coil moves to the next detection region. The detection probe collects the magnetic field on the outer surface of the pipeline according to a preset path, and the detection path can be collected along the axial direction of the pipeline firstly and then collected along the axial direction of the pipeline again through the rotation of the probe. Of course, it is also possible to perform circumferential acquisition first, and then perform circumferential acquisition by changing the position in the axial direction.
2. Establishing correlation between surface magnetic induction and spatial position
The cylindrical support plate below the probe is coaxially arranged with the pipeline and is kept in a relatively static state with the coil. A movable elongate circuit board is arranged between the cylindrical support plate and the coil, and a plurality of magnetic field sensor arrays are uniformly distributed on the circuit board, and the magnetic field sensors are arranged on the circuit board according to the axial direction. One side of the circuit board is provided with a row of interface circuits for connecting the sensor with an external circuit. During measurement, when the probe coil reaches a certain area and is kept still, the circuit board firstly scans in two directions along the circumferential direction. After the circumferential direction scanning is finished, the circuit board moves to the next position along the axial direction so as to avoid a detection dead zone between two adjacent magnetic field sensors. Then, the circuit board is scanned bi-directionally along the circumferential direction. The steps are repeated until the scanning of the whole area covered by one position of the probe is finished.
After each scanning, the magnetic induction intensity of the surface of the pipeline is measured through signal processing such as subsequent amplification and filtering. Collecting the magnetic field in the space around the pipe is not enough to analyze the position, orientation and other information of the defect. The moving device of the auxiliary probe circuit board must record the actual position of the magnetic field sensor at the same time to establish the correlation between the magnetic induction intensity and the spatial position. The actual position of each sensor in the sensor array is determined by the rotational position of the coil, the rotational position of the circuit board above the support plate, and the position of each sensor in the array.
3. Construction of magnetic induction intensity cloud picture
A magnetic field sensor on the circuit board corresponds to the magnetic field distribution of a small part of area, and the magnetic field distribution of the area scanned at one time can be obtained by splicing the magnetic fields acquired by all the sensors on a graph. And expressing the magnetic induction intensities with different sizes by corresponding colors, so as to establish a cloud picture of the surface of the pipeline. The selected display colors of the magnetic induction intensities of different levels and how the colors are arranged between each level are very important. And proper color contrast is selected, which is beneficial to improving the defect resolution of the magnetic induction intensity cloud picture. In this embodiment, for example, the magnetic induction intensity may be represented by gradually changing from red to yellow to green and then to blue. The magnetic induction intensity cloud pictures around the pipeline can be composed of a plurality of graphs in different areas, and the same position can also be composed of four cloud pictures in three axial directions and a magnetic induction intensity mode. The step can be realized by software, the measurement result is input into the software, and the required magnetic induction intensity cloud picture is obtained through a preset algorithm and a sensor array distribution rule.
4. Image pre-processing
The directly acquired magnetic induction intensity cloud map is not enough to be used for realizing detection and state evaluation of defects such as cracks, and the images must be properly processed. For the convenience of subsequent processing, it is necessary to first remove noise generated by environmental factors and the like. Corresponding to the detection of the surface cracks of the pipeline, edge points can be extracted by adopting a certain method, and then a certain threshold value, such as a two-dimensional maximum entropy segmentation method, is set, so that a new binary image is established. And subsequently, clear crack characteristics are obtained through certain thinning. In addition, a deep learning technology can be adopted to carry out various optimization treatments such as defogging, contrast enhancement, lossless amplification and the like on the cloud images with less ideal quality, and more clear images can be reconstructed.
5. Evaluation of pipe defects
And finally, fast inversion of information such as defect depth, area and position is carried out, and accurate, automatic and intelligent nondestructive detection of the pipeline defect is really realized. The deep learning has particularly good effect on feature extraction and positioning. Based on deep learning, a convolution network is established, the characteristics of data are automatically searched by the network, the network is continuously adjusted by self according to a certain rule to realize the identification of the surface defects of the pipeline, the defect of manually extracting the characteristics is avoided, and the accuracy of evaluating the pipeline defects is improved. The magnetic induction intensity cloud pictures of different defect cracks of the preset pipeline can be input into the deep learning model for deep learning, the deep learning model after the deep learning is called to perform feature matching on the magnetic induction intensity cloud pictures after the noise is removed, and the surface defects of the metal pipeline to be detected are identified.
The following describes different crack defects. According to the electromagnetic induction principle, when an exciting coil which is provided with alternating current is close to the upper part of the pipeline, the surface of the pipeline generates induced eddy current. The magnitude of the induced eddy currents is not only related to the excitation current, but also necessarily related to the state parameters of the pipe. When a crack exists on the surface of the pipeline, the current which is originally uniformly distributed is damaged by the crack, and the induced current can change the original path and reselect the path to pass through. The change of direction and magnitude of the eddy current will cause the change of the magnetic field in the space around the eddy current. Therefore, by measuring the change of the eddy magnetic field in the space around the pipeline, the change of the eddy in the pipeline can be deduced, and the surface and near-surface conditions of the pipeline can be further evaluated.
The magnetic field outside the pipe is practically equal to the vector sum of the source field generated by the exciting current and the eddy current field generated by the induced current. Changes in the eddy current field result in changes in the magnetic field, and thus pipe defects can be predicted to some extent from changes in the magnetic field at a point around the crack. However, in practice, the measurement points have certain randomness, and if the measurement points are not properly selected, missed detection or false detection occurs. Of course, one or more special straight lines can be selected as the detection path, but there are still many disadvantages for the cylindrical curved surface such as the pipeline. In addition, another major factor is that the actual defects are morphologically different and have irregularities, and the measurement of individual points and lines alone does not reveal complete information about the defect. Therefore, for accurate and comprehensive quantitative evaluation of the pipeline defects, it is very important to select a proper detection surface. The method adopts a cylindrical surface which is coaxial with the outer surface of the pipeline as a research object, and the three-dimensional magnetic field in the area can comprehensively reflect the change caused by the defect of the pipeline in any direction. If the magnetic induction intensity value can be converted into an image which can be visually displayed, whether the pipeline has defects or not can be judged more conveniently and directly, and accurate information of the defects can be obtained.
(1) Evaluation of different orientation cracks
Under the excitation of the double coils, the magnetic induction intensity model on the three-dimensional cylindrical surface above the pipeline is obtained through calculation of COMSOL software and is shown in fig. 2, wherein (a) - (d) in fig. 2 respectively show cloud charts formed by the magnetic induction intensity model on the cylindrical surface when no crack, a transverse crack, a longitudinal crack and a 45-degree oblique crack exist on the surface of the pipeline. The longitudinal crack size was 12mm × 1mm × 1mm (length × width × depth), and the transverse crack size was 40 ° × 1mm × 1mm (central angle × width × depth). Different colors of the cloud represent magnetic induction intensities with different magnitude values. By measuring the magnetic induction intensity distribution rule of the region, a magnetic induction intensity model cloud picture and a three-dimensional magnetic induction intensity component cloud picture are obtained, and the position information of the pipeline crack is analyzed from the image, so that the visualization of the crack is realized.
The technical effects are as follows: the magnetic induction intensity mode cloud chart is distributed more uniformly without cracks, and no obvious shadow is generated, as shown in figure 2 (a). Due to the fact that the double coils are excited and excitation parameters of the two coils are inconsistent, the obtained magnetic induction intensity cloud picture is integrally distributed in an inclined state and forms an included angle with an actual pipeline. At the moment, the magnetic induction intensity cloud pictures are symmetrically distributed, blue areas are arranged on two sides of the cloud pictures to indicate that the areas have the lowest magnetic induction intensity, and the pictures are displayed in dark colors due to the fact that the colors of the pictures are black and white; inwards along the blue area, two approximately parallel light-colored areas exist, and the magnetic induction intensity in the two light-colored areas is higher; and a red area is arranged inside the cloud picture to show that the magnetic induction intensity of the part is highest, and the picture is displayed in a darker color due to the black and white color. When a crack exists on the pipeline, the original regular magnetic field distribution on the magnetic induction intensity model cloud picture is broken, a very obvious 'shadow' is generated at the position corresponding to the crack, and the 'shadow' reflected in the picture is basically consistent with the position of the crack, as shown in fig. 2(b) - (d). The phenomenon proves that when the double coils are excited together, whether the pipeline has cracks or not is judged by detecting whether the magnetic induction intensity cloud pictures on the upper cylindrical surface of the pipeline have the shadows or not, and information such as the positions and the directions of the cracks can be accurately obtained. In addition, the coil can be directly placed above the pipeline for measurement regardless of whether the crack is longitudinal or oblique, and the limiting conditions that the coil is rotated or repeatedly adjusted to ensure that the direction of the induced current is vertical to the direction of the crack are not needed. The 'shadow' in the cloud picture is the visual embodiment of the pipeline crack, and the 'visualization' of the crack is realized.
(2) Evaluation of different length cracks
Under the excitation of the double coils, the crack length is changed, and the magnetic induction intensity mode cloud chart of the outer cylindrical surface of the pipeline is shown in fig. 3, wherein fig. 3(a) - (d) show that the longitudinal crack length is respectively 10mm, 12mm, 15mm and l8 mm. The technical effects are as follows: according to the four groups of magnetic induction intensity models, the following conclusion can be obtained that the change of the surface cracks of the pipeline does not change the overall distribution rule of the magnetic induction intensity on the cylindrical surface, and the overall distribution of the cloud pictures shown in the figures 3(a) to (d) is consistent. Secondly, along with the change of the length of the crack on the surface of the pipeline, the affected area of the eddy current on the surface of the pipeline is changed, the 'shadow' corresponding to the crack is changed, and the change trend is consistent with the change of the actual crack. Comparing the length unit on the right side of the graph, the shadow length in the cloud picture can be found to be the length of the pipeline crack actually, and therefore the length information of the pipeline surface crack and the defect can be accurately evaluated according to the length change rule of the shadow length in the cloud picture. In the same way, the width information of the crack can also be obtained through the width change rule of the shadow in the cloud picture.
(3) Evaluation of different depth cracks
Crack depth is another defect information of interest. Under the excitation of the double coils, other conditions are not changed, and only the crack depth is changed, and the corresponding magnetic induction intensity cloud charts are shown in fig. 4, wherein fig. 4(a) - (d) show that the longitudinal crack depth is 1mm, 2mm, 3mm and 3.5mm respectively.
The technical effects are as follows: as can be seen from the analysis of fig. 4, the change in the depth of the crack not only reflects the "shadow" portion corresponding to the crack, but also has a certain influence on the magnetic induction around the crack. As the depth of the crack increases, the ambient magnetic induction decreases significantly. The magnetic induction intensity around the crack is weakened, so that the crack detection effect is unfavorable, and the shadow is blurred to a certain extent and is not obvious in boundary with the periphery. Although the 'shadow' corresponding to the crack is not very obvious, the crack depth can be evaluated according to the change rule of the 'shadow'. As the crack depth increases, the size of the magnetic induction intensity mode in the region of the crack region decreases significantly. The reason for the reduced magnetic induction of this region can still be explained by the principle of eddy current field. The phenomena shown in fig. 4(a) - (d) occur due to the increase of the depth of the crack, which leads to the increase of the eddy magnetic field in the space around the pipe, thereby causing the decrease of the overall magnetic field.
As the depth of the crack increases, the "shadow" corresponding to the crack becomes more blurred, which is disadvantageous for practical detection, and other means can be used for auxiliary analysis. FIG. 5 is a y-direction magnetic induction cloud under the effect of different depth cracks, wherein FIGS. 5(a) - (d) also show longitudinal crack depths of 1mm, 2mm, 3mm and 3.5mm, respectively. By analyzing the cloud pattern shown in fig. 5, it can be seen that the y-direction magnetic induction cloud pattern does not show the crack "shadow" shown in fig. 3, and therefore, the crack cannot be mainly evaluated by using the cloud pattern. However, as the depth of the crack increases, the image thereof also shows a certain regular change. In fig. 5(a), the positions of two "blue regions" (the center positions of two similar light-colored circular ring regions, and the outer sides of the circular rings are red) are high on the left and low on the right, and the relative positions of the two "blue regions" are changed from fig. 5 (b). The deeper the crack depth, the relatively higher the "blue region" on the right in the cloud. The two "blue areas" shown in FIG. 5(d) have changed to low left and high right. Furthermore, as the crack depth increases, the lateral distance between the two "blue zones" also becomes wider and wider. Therefore, the crack depth can be judged through the magnetic induction intensity model cloud picture, and then the complementary analysis is carried out by combining the y-direction magnetic induction intensity cloud picture.
The invention provides a pipeline crack visual detection system of a three-dimensional induced eddy current magnetic field cloud picture, which comprises a memory and a processor, wherein a computer program is stored in the memory, and the computer program realizes the steps of the method when being executed by the processor. The storage medium of the present embodiment may be a storage medium provided in an electronic device, and the electronic device may read the content of the storage medium and achieve the effects of the present invention. The storage medium may also be a separate storage medium, which is connected to the electronic device, and the electronic device may read the content of the storage medium and implement the method steps of the present invention. The system adopts the probe double coils to generate exciting current so as to generate a variable magnetic field, obtains a disturbance eddy magnetic field caused by the surface defects of the pipeline through the magnetic field sensor and finally generates a magnetic induction intensity cloud picture. Therefore, the visual visualization of the crack defect of the pipeline can be realized through the image of the magnetic induction intensity cloud chart, and the accurate evaluation of the pipeline defect is improved.
It should be noted that, although the above embodiments have been described herein, the invention is not limited thereto. Therefore, based on the innovative concepts of the present invention, the technical solutions of the present invention can be directly or indirectly applied to other related technical fields by making changes and modifications to the embodiments described herein, or by using equivalent structures or equivalent processes performed in the content of the present specification and the attached drawings, which are included in the scope of the present invention.
Claims (7)
1. A pipeline crack visual detection method of a three-dimensional induced eddy current magnetic field cloud picture is characterized by comprising the following steps:
placing a detection probe on a metal pipeline to be detected, wherein the detection probe is used for generating an excitation signal of an eddy magnetic field and measuring the size change of the magnetic field on the surface of the metal pipeline to be detected, and the detection probe comprises an excitation coil and a plurality of magnetic field sensors distributed around the circumferential surface;
generating alternating current through an exciting coil so as to generate induced current on the surface of the metal pipeline, acquiring the magnetic induction intensity of the current area on the surface of the metal pipeline to be detected through a magnetic field sensor, and generating a magnetic induction intensity cloud chart according to the magnetic induction intensity and the position of the magnetic field sensor;
and carrying out image preprocessing on the generated magnetic induction intensity cloud picture, and removing noise in the magnetic induction intensity cloud picture.
2. The visual pipeline crack detection method based on the three-dimensional induced eddy current magnetic field cloud picture as claimed in claim 1, further comprising the steps of:
and moving the detection probe and the position of the circuit board above the support plate, and recording the position of the circuit board on the surface of the metal pipeline.
3. The visual pipeline crack detection method based on the three-dimensional induced eddy current magnetic field cloud picture as claimed in claim 1, wherein the visual pipeline crack detection method comprises the following steps: the exciting coil comprises an outer coil and an inner coil, the outer coil is an arc coil coaxial with the metal pipeline to be detected, and the inner coil is a rectangular coil.
4. The visual pipeline crack detection method based on the three-dimensional induced eddy current magnetic field cloud picture as claimed in claim 1, wherein the visual pipeline crack detection method comprises the following steps: and different magnetic induction intensities in the magnetic induction intensity cloud pictures correspond to different colors.
5. The visual pipeline crack detection method based on the three-dimensional induced eddy current magnetic field cloud picture as claimed in claim 1, further comprising the steps of: inputting the preset magnetic induction intensity cloud pictures of different defect cracks of the pipeline into a deep learning model for deep learning, calling the deep learning model after deep learning to perform feature matching on the magnetic induction intensity cloud pictures after noise removal, and identifying the surface defects of the metal pipeline to be detected.
6. The visual pipeline crack detection method based on the three-dimensional induced eddy current magnetic field cloud picture as claimed in claim 1, wherein the visual pipeline crack detection method comprises the following steps: the pre-processing comprises processing, defogging, contrast enhancement or lossless amplification by adopting a two-dimensional maximum entropy segmentation method.
7. The utility model provides a visual detecting system of pipeline crackle of three-dimensional induction eddy current magnetic field cloud picture which characterized in that: comprising a memory, a processor, said memory having stored thereon a computer program which, when being executed by the processor, carries out the steps of the method according to any one of claims 1 to 6.
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