Multi-view feature-based motor imagery classification method and device, equipment and storage medium

Abstract

The invention is suitable for the technical field of ACFM detection, and provides a detection parameter determination method for ACFM detection of a thick coating, and the method comprises the steps: obtaining the attribute information of an assembly for ACFM detection, and building a simulation model of the assembly for ACFM detection through finite element simulation software according to the attribute information; based on the simulation model, obtaining a defect signal set obtained under the conditions of a preset lift-off height, different detection frequencies and different magnet yoke spans, and determining a change rule of the defect signal based on the defect signal set; acquiring the coating thickness of the workpiece to be detected, and selecting the lift-off height corresponding to the coating thickness as a target lift-off height according to the coating thickness; and determining detection parameters for the to-be-detected workpiece based on a change rule corresponding to the target lift-off height.

Description

Technical Field

[0001] The present application belongs to the field of motion recognition technology, and in particular, relates to a method, device, equipment and storage medium for motion imagery classification based on multi-view features. Background Art

[0002] In the field of nondestructive testing, ACFM technology is widely used due to its high detection sensitivity for surface and near-surface defects of metal materials. This technology generates an alternating magnetic field through the excitation coil, which interacts with the metal workpiece to stimulate eddy currents and generate secondary magnetic fields. By detecting changes in these magnetic fields, defects can be located and evaluated. However, in practical applications, especially when facing metal components with thick coatings, the detection performance of ACFM technology will be significantly affected.

[0003] In traditional ACFM detection systems, the design of the magnetic circuit is crucial to the strength and stability of the detection signal. The magnetic circuit is mainly composed of an excitation coil and a magnetic yoke, and its design needs to consider factors such as magnetic permeability, electrical conductivity, and geometric dimensions. However, when faced with metal components with thick coatings, since the magnetic permeability and electrical conductivity of the coating material may be different from those of the metal being detected, the propagation of the electromagnetic field in the coating is hindered, thereby reducing the sensitivity of the detection signal. In addition, the thick coating will also increase the distance between the probe and the workpiece, that is, the lift-off height, causing the magnetic field strength to decay rapidly according to the inverse square law, further weakening the detection signal and resulting in inaccurate detection.

[0004] Skin effect is another factor that affects the performance of ACFM under thick coating conditions. As the frequency increases, the skin depth decreases, and the electromagnetic field tends to be more concentrated on the surface of the workpiece, resulting in reduced penetration of the electromagnetic field under thick coating conditions. In addition, the presence of thick coatings may also lead to uneven distribution of the electromagnetic field, further affecting the stability and accuracy of the detection signal.

[0005] Therefore, existing ACFM systems often require complex equipment adjustments and a large number of experimental verifications to achieve the best measurement results when dealing with thick coatings. Equipment adjustments and a large number of experimental verifications require a lot of trial and error costs, reduce detection efficiency, and have limited effects in practical applications. Summary of the invention

[0006] The embodiment of the present application provides a method for determining detection parameters for ACFM detection of thick coatings, which addresses the technical problems in the prior art that equipment adjustment and a large number of experimental verifications require a large amount of trial and error costs, reduce detection efficiency, and have limited effects in practical applications.

[0007] The present application embodiment provides a method for determining detection parameters for ACFM detection of thick coatings, the method comprising:

[0008] Acquiring property information of a component for ACFM detection, and establishing a simulation model of the component for ACFM detection by finite element simulation software according to the property information;

[0009] Based on the simulation model, a defect signal set obtained under different detection frequencies and different yoke span conditions at a preset lift-off height is obtained, and a change rule of the defect signal is determined based on the defect signal set;

[0010] Acquiring a coating thickness of a workpiece to be inspected, and selecting a lift-off height corresponding to the coating thickness as a target lift-off height according to the coating thickness;

[0011] An inspection parameter for the workpiece to be inspected is determined based on a variation rule corresponding to the target lift-off height.

[0012] Optionally, the components used for ACFM detection include at least: a U-shaped ferrite yoke, an excitation coil, an experimental workpiece, a lift-off layer and a surrounding air space.

[0013] Optionally, the component for ACFM detection further includes a defect material, the defect material is replaced by air, the size of the defect material is 10 mm×1 mm×10 mm, and the defect material is disposed 10 mm below the center of the U-shaped ferrite yoke.

[0014] Optionally, the step of establishing a simulation model of a component for ACFM detection by finite element simulation software according to the attribute information comprises:

[0015] The finite element simulation software establishes a simulation model of the component for ACFM detection according to the attribute information through mesh division, the mesh division adopts a free tetrahedral mesh, and performs fine processing on the area around the crack of the experimental workpiece in the component for ACFM detection.

[0016] Optionally, the step of determining the detection parameters for the workpiece to be detected based on the change rule corresponding to the target lift-off height includes:

[0017] When the target lift-off height is 10 mm, the detection parameters for the workpiece to be detected are determined based on the variation rule corresponding to the target lift-off height of 10 mm: a rated detection frequency of 5 KHz and a yoke span of 30 mm.

[0018] Optionally, the step of obtaining a defect signal set obtained under different detection frequencies and different yoke span conditions at a preset lift-off height based on the simulation model includes:

[0019] Through the single variable method, based on the simulation model, a defect signal set obtained under different detection frequencies and different yoke span conditions at a preset lift-off height is obtained.

[0020] On the other hand, the present application provides a detection parameter determination device for thick coating ACFM detection, the device comprising:

[0021] A data acquisition module, used to obtain attribute information of components used for ACFM detection, and to establish a simulation model of the components used for ACFM detection through finite element simulation software according to the attribute information;

[0022] An experimental module, for obtaining a defect signal set obtained under different detection frequencies and different yoke span conditions at a preset lift-off height based on the simulation model, and determining a change rule of the defect signal based on the defect signal set;

[0023] A matching module, used for obtaining the coating thickness of the workpiece to be inspected, and selecting a lift-off height corresponding to the coating thickness as a target lift-off height according to the coating thickness;

[0024] The parameter determination module is used to determine the detection parameters for the workpiece to be detected based on the change law corresponding to the target lift-off height.

[0025] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0026] By acquiring the attribute information of the components used for ACFM detection, and establishing a simulation model of the components used for ACFM detection through finite element simulation software based on the attribute information; obtaining a set of defect signals obtained under different detection frequencies and different yoke span conditions at a preset lift-off height based on the simulation model, and determining the variation law of the defect signal based on the defect signal set; obtaining the coating thickness of the workpiece to be detected, and selecting a lift-off height corresponding to the coating thickness as the target lift-off height based on the coating thickness; determining the detection parameters for the workpiece to be detected based on the variation law corresponding to the target lift-off height. Establishing a simulation model through finite element simulation software, analyzing the effects of different detection frequencies and yoke spans on defect signals, and determining the optimal probe parameter combination, the sensitivity of ACFM detection technology under thick coating conditions is significantly improved, the number of experiments is reduced, the time for parameter selection is shortened, and the efficiency of the detection process is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0028] Figure 1 It is a flow chart of a method for determining detection parameters for thick coating ACFM detection provided by an embodiment of the present application;

[0029] Figure 2 It is a simulation model diagram of a detection method for ACFM detection of thick coatings provided in one embodiment of the present application;

[0030] Figure 3 It is a detection flow chart of a detection method for thick coating ACFM detection provided by another embodiment of the present application. DETAILED DESCRIPTION

[0031] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0032] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0033] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0034] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0035] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0036] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0037] like Figure 1 As shown, the present application provides a method for determining detection parameters for thick coating ACFM detection, the method comprising:

[0038] S101, acquiring attribute information of a component used for ACFM detection, and establishing a simulation model of the component used for ACFM detection by using finite element simulation software according to the attribute information;

[0039] S102, obtaining a defect signal set obtained under different detection frequencies and different yoke span conditions at a preset lift-off height based on the simulation model, and determining a change rule of the defect signal based on the defect signal set;

[0040] S103, obtaining the coating thickness of the workpiece to be inspected, and selecting a lift-off height corresponding to the coating thickness as a target lift-off height according to the coating thickness;

[0041] S104: Determine detection parameters for the workpiece to be detected based on a change rule corresponding to the target lift-off height.

[0042] By acquiring the attribute information of the components used for ACFM detection, and establishing a simulation model of the components used for ACFM detection through finite element simulation software based on the attribute information; obtaining a set of defect signals obtained under different detection frequencies and different yoke span conditions at a preset lift-off height based on the simulation model, and determining the variation law of the defect signal based on the defect signal set; obtaining the coating thickness of the workpiece to be detected, and selecting a lift-off height corresponding to the coating thickness as the target lift-off height based on the coating thickness; determining the detection parameters for the workpiece to be detected based on the variation law corresponding to the target lift-off height. Establishing a simulation model through finite element simulation software, analyzing the effects of different detection frequencies and yoke spans on defect signals, and determining the optimal probe parameter combination, the sensitivity of ACFM detection technology under thick coating conditions is significantly improved, the number of experiments is reduced, the time for parameter selection is shortened, and the efficiency of the detection process is improved.

[0043] In a possible implementation manner, the components for ACFM detection include at least: a U-shaped ferrite yoke, an excitation coil, an experimental workpiece, a lift-off layer, and a surrounding air domain.

[0044] In a possible implementation, the component for ACFM detection further includes a defect material, the defect material is replaced by air, the size of the defect material is 10 mm×1 mm×10 mm, and the defect material is disposed 10 mm below the center of the U-shaped ferrite yoke.

[0045] In a possible implementation, the step of establishing a simulation model of a component for ACFM detection by using finite element simulation software according to the attribute information includes:

[0046] The finite element simulation software establishes a simulation model of the component for ACFM detection according to the attribute information through mesh division, the mesh division adopts a free tetrahedral mesh, and performs fine processing on the area around the crack of the experimental workpiece in the component for ACFM detection.

[0047] For example, Figure 2 As shown in the figure, the finite element simulation software COMSOL is used for modeling and analysis. The model is mainly composed of a U-shaped ferrite yoke, an excitation coil, a workpiece to be tested, a lift-off layer and an outer air domain. The coil is rectangular in shape, with 150 turns and a 0.1A sinusoidal current. The defective material is replaced by air, with a size of 10mm×1mm×10mm (length×width×depth), located in the center of the yoke, and the lift-off layer, i.e., the distance from the bottom of the yoke to the workpiece is 10mm. Some material properties are shown in Table 1.

[0048] In the meshing part, the U-shaped ferrite and the excitation coil were divided into conventional networks. For other domains in the tested steel plate except the crack, the free tetrahedron network division was adopted. The core of the meshing is to refine the network around the crack, and this part also adopts the free tetrahedron network division method. It effectively improves the detection accuracy and resource utilization.

[0049] Table 1 Material properties

[0050]

[0051] In a possible implementation, the step of determining the detection parameters for the workpiece to be detected based on the change rule corresponding to the target lift-off height includes:

[0052] When the target lift-off height is 10 mm, the detection parameters for the workpiece to be detected are determined based on the variation rule corresponding to the target lift-off height of 10 mm: a rated detection frequency of 5 KHz and a yoke span of 30 mm.

[0053] For example, when a U-shaped yoke is selected, the magnetic lines of force follow the principle of minimum loop to complete the closure between the two legs of the yoke. Therefore, the distance between the two legs of the yoke (span) is appropriately increased so that more magnetic lines of force can reach the surface of the workpiece and increase the sensitivity of the detection result. In order to explore the influence of the span of the yoke on the detection result, on the basis of the above-mentioned optimal frequency, the lift-off is fixed to 10mm. The initial span is selected as 5mm, and the stepping interval is 5mm until the span is selected as 50mm. The frequency is selected as 5KHz for simulation research, and the magnetic field distortion rate under different spans is obtained. It can be seen from the magnetic field distortion rate under different spans that the distortion rate increases with the increase of the span, and reaches the maximum value at a span of about 30 to 35mm, that is, the maximum value is obtained at the peak of the magnetic field intensity wave, and the detection effect is the best. The signal distortion rate does not change much between the span of 30 and 40mm, and the distortion rate tends to decrease after the span is 40mm, that is, the span should not be too large. From the above analysis, it can be seen that the detection sensitivity is highest when the span of 30mm is selected at a frequency of 5KHz.

[0054] In a possible implementation manner, the step of obtaining a defect signal set obtained under different detection frequencies and different yoke span conditions at a preset lift-off height based on the simulation model includes:

[0055] Through the single variable method, based on the simulation model, a defect signal set obtained under different detection frequencies and different yoke span conditions at a preset lift-off height is obtained.

[0056] In a possible implementation, Figure 3As shown, the present application provides a detection parameter determination device for thick coating ACFM detection, the device comprising:

[0057] The data acquisition module 201 is used to obtain the attribute information of the components used for ACFM detection, and to establish a simulation model of the components used for ACFM detection through finite element simulation software according to the attribute information;

[0058] The experimental module 202 is used to obtain a defect signal set obtained under different detection frequencies and different yoke span conditions at a preset lift-off height based on the simulation model, and determine a change rule of the defect signal based on the defect signal set;

[0059] A matching module 203 is used to obtain the coating thickness of the workpiece to be inspected, and select a lift-off height corresponding to the coating thickness as a target lift-off height according to the coating thickness;

[0060] The parameter determination module 204 is used to determine the detection parameters for the workpiece to be detected based on the change rule corresponding to the target lift-off height.

[0061] An embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: acquiring attribute information of a component for ACFM detection, and establishing a simulation model of the component for ACFM detection through finite element simulation software based on the attribute information; acquiring a set of defect signals obtained under different detection frequencies and different yoke span conditions at a preset lift-off height based on the simulation model, and determining a variation law of the defect signal based on the defect signal set; acquiring a coating thickness of a workpiece to be detected, and selecting a lift-off height corresponding to the coating thickness as a target lift-off height based on the coating thickness; and determining the detection parameters for the workpiece to be detected based on the variation law corresponding to the target lift-off height.

[0062] An embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the following steps are implemented: obtaining attribute information of a component used for ACFM detection, and establishing a simulation model of the component used for ACFM detection through finite element simulation software based on the attribute information; obtaining a set of defect signals obtained under different detection frequencies and different yoke span conditions at a preset lift-off height based on the simulation model, and determining a change law of the defect signal based on the defect signal set; obtaining the coating thickness of the workpiece to be detected, and selecting a lift-off height corresponding to the coating thickness as a target lift-off height based on the coating thickness; and determining the detection parameters for the workpiece to be detected based on the change law corresponding to the target lift-off height.

[0063] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0064] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0065] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0066] In the embodiments provided in the present application, it should be understood that the disclosed devices / network equipment / terminal equipment and methods can be implemented in other ways. For example, the device / network equipment / terminal equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0067] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0068] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for determining detection parameters for ACFM detection of thick coatings, characterized in that: The method comprises: Acquiring property information of a component for ACFM detection, and establishing a simulation model of the component for ACFM detection by finite element simulation software according to the property information; Based on the simulation model, a defect signal set obtained under different detection frequencies and different yoke span conditions at a preset lift-off height is obtained, and a change rule of the defect signal is determined based on the defect signal set; Acquiring a coating thickness of a workpiece to be inspected, and selecting a lift-off height corresponding to the coating thickness as a target lift-off height according to the coating thickness; An inspection parameter for the workpiece to be inspected is determined based on a variation rule corresponding to the target lift-off height.

2. A method for determining detection parameters for thick coating ACFM detection as claimed in claim 1, characterized in that: The components used for ACFM detection at least include: a U-shaped ferrite yoke, an excitation coil, an experimental workpiece, a lift-off layer and a peripheral air domain.

3. A method for determining detection parameters for thick coating ACFM detection as claimed in claim 2, characterized in that: The component for ACFM detection also includes a defect material, which is replaced by air. The defect material has a size of 10 mm×1 mm×10 mm and is arranged 10 mm below the center of the U-shaped ferrite yoke.

4. A method for determining detection parameters for thick coating ACFM detection as claimed in claim 1, characterized in that: The step of establishing a simulation model of a component for ACFM detection by finite element simulation software according to the attribute information comprises: The finite element simulation software establishes a simulation model of the component for ACFM detection according to the attribute information through mesh division, the mesh division adopts a free tetrahedral mesh, and performs fine processing on the area around the crack of the experimental workpiece in the component for ACFM detection.

5. A method for determining detection parameters for thick coating ACFM detection as claimed in claim 1, characterized in that: The step of determining the detection parameters for the workpiece to be detected based on the change rule corresponding to the target lift-off height includes: When the target lift-off height is 10 mm, the detection parameters for the workpiece to be detected are determined based on the variation rule corresponding to the target lift-off height of 10 mm: a rated detection frequency of 5 KHz and a yoke span of 30 mm.

6. A method for determining detection parameters for thick coating ACFM detection as claimed in claim 1, characterized in that: The step of obtaining a defect signal set obtained under different detection frequencies and different yoke span conditions at a preset lift-off height based on the simulation model comprises: Through the single variable method, based on the simulation model, a defect signal set obtained under different detection frequencies and different yoke span conditions at a preset lift-off height is obtained.

7. A detection parameter determination device for thick coating ACFM detection, characterized in that: The device comprises: A data acquisition module, used to obtain attribute information of components used for ACFM detection, and to establish a simulation model of the components used for ACFM detection through finite element simulation software according to the attribute information; An experimental module, for obtaining a defect signal set obtained under different detection frequencies and different yoke span conditions at a preset lift-off height based on the simulation model, and determining a change rule of the defect signal based on the defect signal set; A matching module, used for obtaining the coating thickness of the workpiece to be inspected, and selecting a lift-off height corresponding to the coating thickness as a target lift-off height according to the coating thickness; The parameter determination module is used to determine the detection parameters for the workpiece to be detected based on the change law corresponding to the target lift-off height.

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