A method, device and storage medium for improving imaging quality of wheel defect detection

Abstract

The present application relates to the technical field of defect detection, and discloses a method, equipment and storage medium for improving wheel defect detection imaging quality, the method comprising the following steps: acquiring a set of emission angles, an array element set and a plane wave echo array signal of a corresponding wheel detection area, grid processing the detection area, determining the effective plane wave echo and the emission angle corresponding to the grid point, the ratio of the defect depth to the aperture width of the grid point, screening the array element set and the set of emission angles in the plane wave echo array signal to determine the boundary array element and the boundary angle range corresponding to the grid point and perform equidistance scattering mapping to obtain a solution space, using a chaotic evolutionary optimization algorithm to optimize the solution space to obtain an optimal emission angle subset, and using the plane wave echo corresponding to the optimal emission angle subset to perform coherent plane wave compound imaging to obtain a defect visualization image. The present application improves imaging quality with small sample data, shortens imaging time and ensures defect detection accuracy.

Description

Technical Field

[0001] This invention relates to the field of defect detection technology, specifically a method, device, and storage medium for improving the imaging quality of wheel defect detection. Background Technology

[0002] Over long-term use, train wheels may develop internal defects such as cracks and inclusions due to fatigue, threatening train safety. Therefore, it is necessary to regularly inspect train wheels using ultrasonic testing equipment to ensure their safe operation.

[0003] Plane wave ultrasound imaging technology covers the entire imaging area with a single transmission. The principle of plane wave imaging is that an array of ultrasonic transducers, in a single excitation, causes each element to simultaneously emit ultrasonic signals with the same or linearly delayed manner, forming a plane wavefront that appears to be infinitely extended. As this plane wave propagates through the medium, it can simultaneously illuminate the entire imaging area, thus receiving echo information covering the entire field of view after a single transmission. This method enables high frame rate imaging.

[0004] Because signal propagation at a single angle is subject to obstruction and attenuation, the detection signal may be blocked by multiple defects or attenuated during propagation, resulting in the obstructed target being undetectable. Therefore, plane waves with all angles are currently used to solve the problems of multiple defect obstruction and signal attenuation by using different angles to improve imaging quality. However, traditional all-angle composites require a large amount of raw sample data, resulting in long imaging time and poor imaging quality. Summary of the Invention

[0005] The purpose of this invention is to provide a method, device, and storage medium for improving the imaging quality of wheel defect detection, so as to solve the existing technical problems.

[0006] The technical solution of this invention is: A method for improving the imaging quality of wheel defect detection includes the following steps: Acquire the plane wave echo array signal of the detection area of ​​the corresponding wheel, including the emission angle set, array element set, and the corresponding wheel. The detection area is gridded according to a preset aperture width threshold. The directionality of the plane wave echo corresponding to each grid point is determined. Threshold filtering is performed based on the directionality of the plane wave echo to determine the effective plane wave echo and its corresponding effective emission angle. The grid point corresponding to the effective emission angle is then determined. F Value, the F The value is the ratio of defect depth to hole width; Based on certainty F The values ​​are used to filter the array element set and transmission angle set in the plane wave echo array signal to determine the boundary array element and boundary angle range corresponding to each grid point; The boundary array elements and boundary angle range are equidistantly mapped to obtain the solution space. Taking the emission angle of each array element as an individual, a fitness function oriented towards the main lobe and side lobe angle constraints is constructed based on the angle position encoding. The chaotic evolutionary optimization algorithm is used to find the optimal subset of emission angles in the solution space. Coherent plane wave composite imaging is performed using the plane wave echoes corresponding to the optimal emission angle subset to obtain a visual image of the defect.

[0007] Further, the directionality of the plane wave echo corresponding to each grid point is determined, including the following steps: Acquire sound velocity, ultrasonic probe excitation frequency, signal bandwidth, array element width, and emission angle; The directivity at different emission angles is determined based on the following formula: , in, , λ min For the minimum effective wavelength, For the speed of sound, f c To excite the frequency, For signal bandwidth, D ( θ () represents the directionality at different launch angles. θ For the launch angle, W The width of the array element.

[0008] Furthermore, based on the directionality of the plane wave echo, threshold screening is performed to determine the valid plane wave echo and its corresponding valid transmission angle, including the following steps: The directionality of the plane wave echo is compared with a -3dB threshold. Plane wave echoes with a directionality greater than the -3dB threshold are considered valid plane wave echoes. The effective plane wave echo corresponds to the transmission angle of the effective transmission angle.

[0009] Furthermore, the corresponding grid points are determined based on the following formula. F value, , in, F For the effective launch angle F value, For the effective launch angle.

[0010] Furthermore, based on the determined F The values ​​are filtered through the array element set and transmission angle set in the plane wave echo array signal to determine the boundary array element and boundary angle range corresponding to each grid point, including the following steps: Obtain the defect depth detected by the full array element; Based on the defect depth and effective emission angle detected by the full array element F The value determines the width of the receiving aperture; Based on the receiving aperture width value, the boundary array elements are determined by intercepting array elements within the aperture width on the horizontal plane where the array elements are set. Within the boundary array elements, selection is performed based on the effective emission angle to determine the boundary angle range.

[0011] Furthermore, an equidistant dispersion mapping is performed on the boundary array elements and the boundary angle range to obtain the solution space, including the following steps: The position of each individual in the chaotic evolution optimization algorithm is encoded by applying boundary constraints to the endpoints of the array and a fixed constraint to the total length of the array. At the same time, the dimension is set as the total number of array elements minus the number of degrees of freedom corresponding to the preset boundary constraints, so as to obtain the continuous position sequence of the individual. The continuous position sequence of individuals is processed according to a preset equal-distance discrete interval, and transformed into a discrete array selection vector. The discrete array selection vector is then mapped to the coordinate axis of the solution space and converted into the form of array element index to realize the discretized expression of array element selection variables. The spatial position of the array elements is associated with the angular response of the array pattern. The array pattern function is determined based on the element weights, element positions, wavenumbers and emission angles to achieve angular position encoding, thus obtaining the solution space.

[0012] Furthermore, coherent plane wave composite imaging is performed using the plane wave echoes corresponding to the selected optimal emission angle subset to obtain a visual image of the defect, including the following steps: The speed of sound, the emission angle of the plane wave emitted by the array element, and the longitudinal coordinates of the scattering point in the imaging area are obtained to determine the first transmission time of the plane wave emitted by the array element to the scattering point. The sound velocity, the position of the array element, and the lateral and longitudinal coordinates of the scattering point in the imaging area are obtained to determine the second transmission time of the plane wave emitted by the array element back to the array element via the scattering point. The total transmission delay time of the plane wave is determined by superimposing the first transmission time and the second transmission time. Based on the total propagation delay of the plane wave, the position of the array element, and the lateral and longitudinal coordinates of the scattering point in the imaging area, the echo amplitude at the scattering point is determined. The echo amplitude at all scattering points of the emission angle set and array element set is calculated based on the delay time. The echo amplitudes are then superimposed to obtain the amplitude at the scattering point of the coherent plane wave composite imaging algorithm. The various amplitude values ​​are combined and input into the processing unit for imaging to obtain a visual defect map of the detected area.

[0013] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the above-described method for improving the imaging quality of wheel defect detection.

[0014] The present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, performs the above-described method for improving the imaging quality of wheel defect detection.

[0015] Compared with existing technologies, the present invention provides a method, device, and storage medium for improving the imaging quality of wheel defect detection, the advantages of which are: 1. By dividing the detection area into grids, the directionality of the plane wave echo corresponding to each grid point is determined. F Value, based on F Value filtering removes emission angles and array elements that contribute little to the current grid point, retaining only the data within the effective range, reducing the amount of data that needs to be processed, thereby shortening the imaging time.

[0016] 2. By using a chaotic evolutionary optimization algorithm based on equidistant dispersion mapping to perform sparse optimization on plane wave echoes, it is possible to reduce imaging sample data while ensuring imaging quality. This can improve imaging efficiency and detection stability while ensuring defect detection accuracy. Attached Figure Description

[0017] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0018] The following is combined Figure 1 The specific embodiments of the present invention will be described in detail below. In the description of the invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature; in the description of the invention, unless otherwise stated, "a plurality of" means two or more.

[0019] Example like Figure 1 As shown, this embodiment of the invention provides a method for improving the imaging quality of wheel defect detection, including the following steps: S1. Acquire multi-angle plane wave echo array signals.

[0020] Specifically, an array-type ultrasonic transducer is used to acquire multi-angle plane wave echo array signals from train wheels. For subsequent processing, it is necessary to record the emission angle set and array element set of the array-type ultrasonic transducer, and to record the plane wave echo array signal of the corresponding wheel detection area under a specific array element set and emission angle set.

[0021] S2. The detection area is gridded according to the preset aperture width threshold. The directionality of the plane wave echo corresponding to each grid point is determined. Threshold filtering is performed based on the directionality of the plane wave echo to determine the effective plane wave echo and its corresponding effective emission angle. The corresponding grid point is determined based on the effective emission angle. F Value, the F The value is the ratio of defect depth to aperture width.

[0022] Specifically, the detection area is divided into several square grids. The side length of the square grid is usually set to the range of 0.0005mm to 0.0015mm. When the side length is below 0.0005mm, the computational load is greater but the effect is not improved. When the range is above 0.0015mm, the imaging quality of the defect will decrease significantly, specifically in that the defect boundary is more blurred. In practice, the side length of the square grid can be set to 0.001mm, and each grid line intersection point is used as an independent grid point, with each grid point representing a defect.

[0023] Specifically, determining the directionality of the plane wave echo corresponding to each grid point includes the following steps: First, obtain the sound velocity, the excitation frequency of the ultrasonic probe, and the signal bandwidth. Then, calculate the minimum effective wavelength using the following formula. λ min : , in, λ min For the minimum effective wavelength, For the speed of sound, f c To excite the frequency, This refers to the signal bandwidth.

[0024] Obtain the element width and emission angle, and determine the directivity of different emission angles based on the minimum effective wavelength, element width, and emission angle using the following formula: , in, D ( θ () represents the directionality at different launch angles. θ For the launch angle, W The width of the array element. λmin It is the minimum effective wavelength.

[0025] Specifically, threshold screening based on the directionality of plane wave echoes to determine valid plane wave echoes and their corresponding valid transmission angles includes the following steps: The effective emission angle is determined using a -3dB threshold method. , , , in, For an effective launch angle, For the launch angle, This is the absolute value of the receiving angle.

[0026] Substituting the obtained effective launch angle into the following formula yields the corresponding effective launch angle. F value: , in, F For the effective launch angle F value, For the effective launch angle.

[0027] S3, based on deterministic F The values ​​are used to filter the array element set and transmission angle set in the plane wave echo array signal to determine the boundary array element and boundary angle range corresponding to each grid point.

[0028] Specifically, due to F This value is also known as the ratio of defect depth to aperture width, and is therefore important in determining the effective emission angle. corresponding F After that, the defect depth detected by the full array element is obtained.

[0029] The receiving aperture width value is determined by reverse calculation using the following formula: , in, F For the effective launch angle F value, d f The depth of the defect detected by the full array element. D f This is the width value of the receiving aperture.

[0030] Based on the receiving aperture width value, array elements within the aperture width are selected on the horizontal plane where array elements are set to determine the boundary array elements. Within the boundary array elements, the effective transmission angle is used for screening to determine the boundary angle range.

[0031] S4. Perform equidistant dispersion mapping on the boundary array elements and boundary angle range to obtain the solution space. Taking the emission angle of each array element as an individual, construct a fitness function based on angle position encoding that is oriented towards the angle constraints of the main lobe and side lobe. Use the chaotic evolutionary optimization algorithm to find the optimal subset of emission angles in the solution space.

[0032] The chaotic evolution optimization algorithm aims to reduce sidelobe peak values ​​and compress main lobe width. It uses Logistic mapping to generate chaotic sequences to complete population initialization, chaotic crossover, and chaotic mutation. Its implementation process is as follows: The commonly used formula for the chaotic mapping Logistic mapping is as follows: , in, For the first Chaos value in the next iteration For control parameters, when The state indicates that the system is completely chaotic. The core process of the algorithm is a loop of "initialization → chaotic perturbation → evolution operation → termination judgment".

[0033] First, the objective optimization problem is transformed into a single-objective function optimization in a continuous space using binary encoding, so that the algorithm can proceed. Then, the objective function is set: or Decision variables: Variable constraints: , Traditional evolutionary algorithms initialize the population with random numbers, which can easily lead to uneven distribution of individuals; chaotic initialization generates the population through "chaotic sequence → variable mapping", which ensures traversability.

[0034] For each decision variable dimension Generate a logistic mapping with a length of chaotic sequence . For individual indexes, For the dimension index, randomly initialize the first chaotic value: , Among these, it is necessary to avoid c =0 or c =1, otherwise the sequence degenerates. Iterative generation of subsequent chaotic values: , Chaotic sequence A linear mapping from the (0,1) interval to the actual constraint interval of the decision variables. The initial population was obtained. , of which The first individual The variables are: , in Indicates the number of iterations At that time, individual The One variable.

[0035] Then, the fitness function is set as the criterion for "evaluating the quality of individuals," and designed according to the optimization objective as follows: , After calculating the fitness of all individuals, record the globally optimal individual in the initial population. and global optimal fitness : , , Crossover is a "genetic recombination" process. Traditional crossover uses random numbers to select crossover sites, while chaotic crossover uses chaotic sequences to control the crossover strength, enhancing diversity and reorganizing the population. Individuals are randomly divided into Yes; generates chaotic crossover factors.

[0036] For each pair of individuals, generate one chaotic value using a Logistic mapping. : , in, These are control parameters.

[0037] Offspring are generated through crossover, and all dimensions of each pair of individuals are considered. Generate two offspring using the following formula. and , , , When random number If the crossover is performed, it will be executed; otherwise, the crossover will not be executed, and the parent generation will be preserved.

[0038] Mutation is a process of "gene mutation." Traditional mutation uses random perturbation, while chaotic mutation uses chaotic sequences to generate perturbation amplitudes, avoiding excessive perturbation. Each individual in the population is selected. Generate random numbers ,like If so, then the mutation will be performed on that individual.

[0039] For the individuals requiring mutation, generate chaotic mutation factors to generate chaotic sequences. Mapped to Interval: , For the individual's first Each variable is updated using the following formula: , in, This is the disturbance coefficient, used to control the intensity of variation, and is typically taken as 0.1~0.2. Exceeding If so, then it is truncated to the boundary value.

[0040] Retain high-quality individuals and eliminate low-quality individuals to ensure the overall quality of the population improves. Use a more stable elite retention strategy for selection. Merge the parent and offspring populations to obtain a population of [size missing]. A temporary population; sort the temporary population in descending order of fitness, and select the top... The individual with the highest fitness is selected to form the iteration. new population Calculate the fitness of the new population; if there are individuals with fitness exceeding [a certain threshold], [further action is taken]. Then update the global optimum: , , Iteration terminates: when The algorithm terminates when the change in the global optimal fitness is less than a threshold. The algorithm terminates after K generations (e.g., K=10), as shown in the formula: .

[0041] Since traditional chaotic evolutionary optimization algorithms are difficult to apply directly to the optimization of sparse elements in ultrasonic phased arrays, a chaotic evolutionary optimization algorithm strategy based on equidistant dispersion mapping is proposed. The individual positions of continuous chaotic evolutionary optimization algorithms are converted into element index forms through equidistant dispersion mapping, realizing the discretized expression of element selection variables. Then, an angle position encoding mechanism is introduced to associate the angular response of the array radiation pattern with the spatial position of the elements, and the angular constraints of the main lobe and side lobe regions are given special consideration in the fitness evaluation, thereby enhancing the directionality of the optimization. Simultaneously, by limiting the search range of individual updates, the element positions are adjusted only within a local candidate window, avoiding large-scale invalid jumps and improving convergence efficiency. Finally, this method can achieve sidelobe suppression and beam performance optimization under the conditions of element number and sparsity constraints.

[0042] Specifically, the position of an individual in the chaotic evolutionary optimization algorithm is encoded as follows: .

[0043] Where dim is the dimension of the solution space, which is determined to satisfy the constraints. d 1=0, d N = L , L The sum of the spacing between all array elements. Let be the total number of array elements, therefore the dimension of the solution space is dim = N - 2. The position of the angle can then be expressed as... .

[0044] The continuous positions of individuals in the chaotic evolutionary optimization algorithm are discretized using the following discretization formula: , in, This represents the position of an individual after discretization; the position of an individual is the position of an array element.

[0045] The distance between each array element is Based on the characteristics of equidistant dispersion, we can conclude that... , , in, x d i It is the first i The index of each array element, .

[0046] The first i Dimensional position mapping to the first i On the solution space coordinate axes of dimension , the solution space coordinate axes are represented as follows: , , in, This represents the selectable angle positions during the first iteration. ; Indicates the first t The available angle positions during each iteration.

[0047] After discretizing the array element positions, the array element indices are represented as array selection vectors: , The constraints on the array elements are: , in, It can be either 0 or 1; a value of 1 indicates that it is referenced, and a value of 0 indicates that it is not referenced. This represents the total number of array elements.

[0048] Then, an angle position encoding mechanism is introduced to establish a correlation between the angle response of the array pattern and the spatial position of the array elements. The array pattern function is represented as follows: , in, For the array element weights, For the position of the array element, For wave number, θ The launch angle.

[0049] After obtaining the angular position code, the fitness function suitable for this target is proposed as follows: , in, For different angles and positions.

[0050] To restrict the range of individual updates in the chaotic evolutionary optimization algorithm, the individual update formula is as follows: , For the first The individual in the first The position at the next iteration; For the first i The individual in the first t The position updated at +1 iteration; r The random coefficient is usually a random number between 0 and 1, used to control the step size or degree of influence of an individual moving closer to the optimal individual; In the first t At the next iteration, the position of the best individual in the current population; t This represents the current iteration number.

[0051] S5. Perform coherent plane wave composite imaging using the plane wave echoes corresponding to the optimal emission angle subset to obtain a visual image of the defect. Specifically, this includes the following steps: The transmission delay time of different array elements is calculated based on different deflection angles to achieve wavefront deflection. The launch delay time for each array element is: , in, For the first The launch delay time of each array element Let be the emission angle of the plane wave emitted by the array element. x n For the first n The position of each array element c The speed of sound.

[0052] The number of launch angles is The total number of array elements in the ultrasonic transducer is , No. The position of each element is The launch angle is When the probe is in the receiving plane wave mode, the transmission angle is... A plane wave is emitted, and the plane wave reaches the scattering point ( x , z The first transmission time is: , in, z The vertical coordinates of the scattering point in the imaging region. Let be the emission angle of the plane wave emitted by the array element. c The speed of sound.

[0053] Signal scattering point ( x , z When it is returned, the first The second transmission time received by each array element is: , in, z The vertical coordinates of the scattering point in the imaging region. It is the first The position of each array element c For the speed of sound, This represents the lateral coordinates of the scattering point within the imaging region.

[0054] The transmission angle can be obtained by superimposing the first transmission time and the second transmission time. The total propagation delay of the plane wave is: , No. Each element deflects at a plane wave angle of . The received signal at that time is The scattering point is then calculated based on the total transmission delay time. The amplitude at that point is: , Calculate all based on delay time From various angles and All scattering points of each array element ( x , z The echo amplitude at the point is calculated by superimposing the echo amplitudes to obtain a composite signal, which is the amplitude at the scattering point obtained by the coherent plane wave composite imaging algorithm. for: , A visual defect map of the detected area is obtained by combining the various amplitudes and imaging them in the processing unit.

[0055] It should be noted that the processing unit can be an onboard computer.

[0056] In summary, this invention provides a method for improving the imaging quality of wheel defect detection, based on coherent plane-wave compounding (CPWC) combined with chaotic evolutionary optimization (CEO) for high-quality visualization imaging. This method performs sparsity optimization on the acquired plane wave echo data using the chaotic evolutionary optimization algorithm and incorporates adaptive... F The method can autonomously determine the selected angle based on the directionality of different echo angles, and select angles suitable for different depths for composite imaging. The resulting imaging effect is comparable to that of full-angle imaging. This method can complete imaging with less data, significantly shortening the imaging time and meeting the technical requirements of real-time imaging. At the same time, this composite imaging method effectively overcomes the limitations of single-angle detection, and can more clearly and accurately present the shape, size, and orientation information of defects inside train wheels.

[0057] In another embodiment of the present invention, a computer device is also provided, including a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the steps in the method embodiment for improving the imaging quality of wheel defect detection. Specific implementation methods can be found in the method embodiment, and will not be repeated here.

[0058] In another embodiment of the present invention, a non-transitory computer-readable storage medium containing instructions is also provided, on which a computer program is stored. For example, a memory containing instructions that can be executed by a processor of a computer device to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc. When the computer program is executed by the processor, it can implement the steps in the embodiments of the method for improving the imaging quality of wheel defect detection. Specific implementation methods can be found in the method embodiments, which will not be repeated here.

[0059] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart. Figure 1One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0060] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0061] These computer program instructions can also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0062] The above-disclosed embodiments are merely preferred embodiments of the present invention. However, the embodiments of the present invention are not limited thereto, and any variations that can be conceived by those skilled in the art should fall within the protection scope of the present invention.

Claims

1. A method for improving the imaging quality of wheel defect detection, characterized in that, Includes the following steps: Acquire the plane wave echo array signal of the detection area of ​​the corresponding wheel, including the emission angle set, array element set, and the corresponding wheel. The detection area is gridded according to a preset aperture width threshold. The directionality of the plane wave echo corresponding to each grid point is determined. Threshold filtering is performed based on the directionality of the plane wave echo to determine the effective plane wave echo and its corresponding effective emission angle. The grid point corresponding to the effective emission angle is then determined. F Value, the F The value is the ratio of defect depth to hole width; Based on certainty F The values ​​are used to filter the array element set and transmission angle set in the plane wave echo array signal to determine the boundary array element and boundary angle range corresponding to each grid point; The boundary array elements and boundary angle range are equidistantly mapped to obtain the solution space. Taking the emission angle of each array element as an individual, a fitness function oriented towards the main lobe and side lobe angle constraints is constructed based on the angle position encoding. The chaotic evolutionary optimization algorithm is used to find the optimal subset of emission angles in the solution space. Coherent plane wave composite imaging is performed using the plane wave echoes corresponding to the optimal emission angle subset to obtain a visual image of the defect. Determining the directionality of the plane wave echo corresponding to each grid point includes the following steps: Acquire sound velocity, ultrasonic probe excitation frequency, signal bandwidth, array element width, and emission angle; The directionality at different launch angles is determined based on the following formula; ,in, , λ min For the minimum effective wavelength, For the speed of sound, f c To excite the frequency, For signal bandwidth, D ( θ () represents the directionality at different launch angles. θ For the launch angle, W The width of the array element; Threshold screening based on the directionality of plane wave echoes to determine valid plane wave echoes and their corresponding valid transmission angles includes the following steps: The directivity of the plane wave echo is compared with a -3dB threshold. Plane wave echoes with a directivity greater than the -3dB threshold are considered valid plane wave echoes. The transmission angle corresponding to the valid plane wave echo is the valid transmission angle. The corresponding grid points are determined based on the following formula. F value; ,in, F For the effective launch angle F value, For the effective launch angle.

2. The method for improving the imaging quality of wheel defect detection according to claim 1, characterized in that, Based on certainty F The values ​​are filtered through the array element set and transmission angle set in the plane wave echo array signal to determine the boundary array element and boundary angle range corresponding to each grid point, including the following steps: Obtain the defect depth detected by the full array element; Based on the defect depth and effective emission angle detected by the full array element F The value determines the width of the receiving aperture; Based on the receiving aperture width value, the boundary array elements are determined by intercepting array elements within the aperture width on the horizontal plane where the array elements are set. Within the boundary array elements, selection is performed based on the effective emission angle to determine the boundary angle range.

3. The method for improving the imaging quality of wheel defect detection according to claim 1, characterized in that, The solution space is obtained by performing equidistant dispersion mapping on the boundary array elements and the boundary angle range, including the following steps: The position of each individual in the chaotic evolution optimization algorithm is encoded by applying boundary constraints to the endpoints of the array and a fixed constraint to the total length of the array. At the same time, the dimension is set as the total number of array elements minus the number of degrees of freedom corresponding to the preset boundary constraints, so as to obtain the continuous position sequence of the individual. The continuous position sequence of individuals is processed according to a preset equal-distance discrete interval, and transformed into a discrete array selection vector. The discrete array selection vector is then mapped to the coordinate axis of the solution space and converted into the form of array element index to realize the discretized expression of array element selection variables. The spatial position of the array elements is associated with the angular response of the array pattern. The array pattern function is determined based on the element weights, element positions, wavenumbers and emission angles to achieve angular position encoding, thus obtaining the solution space.

4. The method for improving the imaging quality of wheel defect detection according to claim 1, characterized in that, Coherent plane wave composite imaging is performed using the plane wave echoes corresponding to the selected optimal emission angle subset to obtain a visual image of the defect, including the following steps: The speed of sound, the emission angle of the plane wave emitted by the array element, and the longitudinal coordinates of the scattering point in the imaging area are obtained to determine the first transmission time of the plane wave emitted by the array element to the scattering point. The sound velocity, the position of the array element, and the lateral and longitudinal coordinates of the scattering point in the imaging area are obtained to determine the second transmission time of the plane wave emitted by the array element back to the array element via the scattering point. The total transmission delay time of the plane wave is determined by superimposing the first transmission time and the second transmission time. Based on the total propagation delay of the plane wave, the position of the array element, and the lateral and longitudinal coordinates of the scattering point in the imaging area, the echo amplitude at the scattering point is determined. The echo amplitude at all scattering points of the emission angle set and array element set is calculated based on the delay time. The echo amplitudes are then superimposed to obtain the amplitude at the scattering point of the coherent plane wave composite imaging algorithm. The various amplitude values ​​are combined and input into the processing unit for imaging to obtain a visual defect map of the detected area.

5. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the method for improving the imaging quality of wheel defect detection as described in any one of claims 1 to 4.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it can perform the method for improving the imaging quality of wheel defect detection as described in any one of claims 1 to 4.

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