Casting size and type self-adaptive multi-angle X-ray imaging control method and system

Abstract

The invention relates to a casting size and type self-adaptive multi-angle X-ray imaging control method and a casting size and type self-adaptive multi-angle X-ray imaging control system, and relates to the technical field of X-ray nondestructive testing. The system comprises a casting data information acquisition module, a data modeling thickness calculation module, a self-adaptive adjustment module, a central control unit module, an image acquisition and gray level feedback module and an image output module which are connected in sequence. The casting size and type self-adaptive multi-angle X-ray imaging control method and the casting size and type self-adaptive multi-angle X-ray imaging control system are superior to the prior art in the aspects of self-adaptive angle control, real-time gray scale feedback and a closed-loop optimization mechanism, and have the remarkable advantages of high detection precision, high automation degree, good system stability and the like; and a new technical path is provided for intelligent industrial X-ray detection.

Description

Technical Field

[0001] This invention relates to the field of X-ray nondestructive testing technology, and in particular to a multi-angle X-ray imaging control method and system that adapts to the size and type of castings. Background Technology

[0002] With the development of equipment manufacturing, aerospace, and energy heavy industry towards large-scale and integrated production, internal quality control of large-sized and complex castings has become a critical factor affecting product reliability and service life. Traditional industrial X-ray non-destructive testing (Digital Radiography, DR) for large-volume, multi-curved castings mostly employs fixed-angle or limited multi-angle imaging schemes. However, existing castings have complex structures, significant differences in wall thickness, and non-uniform absorption characteristics. Under single-angle or preset-angle imaging conditions, the X-ray transmission path exhibits local overexposure and underexposure, resulting in a significant decrease in the accuracy of internal defect identification and imaging contrast.

[0003] DR systems typically rely on manual experience or fixed templates for exposure and angle control, lacking the ability to adaptively adjust to different casting geometries. When the size, shape, or material of the object being inspected changes, parameters such as X-ray tube voltage, current, focal length, angle, and sampling path need to be reset, a complex process that is difficult to optimize in real time. Moreover, fixed-angle imaging methods are prone to problems such as overlapping local shadows, increased scattering interference, and decreased signal-to-noise ratio when dealing with asymmetrical or multi-cavity castings, affecting the accurate identification of internal defects (such as porosity, shrinkage porosity, and inclusions).

[0004] In recent years, some studies have attempted to improve imaging uniformity through multi-view reconstruction, rotational scanning, or dual-source synchronous imaging. However, these methods mostly rely on preset scanning paths or manual angle selection, failing to dynamically adjust imaging angles and exposure strategies based on the actual workpiece geometry and material absorption characteristics. Complex workpieces face mechanical interference and collision risks during rotational or tilted scanning; without real-time spatial constraints and path optimization mechanisms, system stability and safety are difficult to guarantee. Therefore, it is necessary to research an X-ray inspection control method and system capable of adaptively planning imaging angles and exposure parameters based on the casting's geometry, structural type, and material characteristics. This system should automatically identify the characteristics of the object under test, dynamically optimize multi-angle paths, avoid mechanical interference, balance imaging energy distribution, and achieve high-resolution, multi-view internal defect detection, providing new technical support for intelligent non-destructive testing of large-size integrated castings.

[0005] The most similar implementation to this invention is disclosed in Chinese Patent Application No. 202511170730.0, which discloses a multi-view adaptive X-ray flaw detection method and system for pipelines. This patent targets pipeline wall thickness and weld areas, using multi-view arrangement and scanning paths to adapt to pipeline geometry and welds, with a fixed scene, emphasizing the sensitive angles and trajectories of welds and circumferential welds. Chinese Patent Application No. 202211090534.9 discloses a portable adaptive variable-range and zoom imaging device, system, and control method. This patent application addresses the adaptation of target size and distance changes within a limited space using optical geometry-based variable-range and zoom adaptive control.

[0006] The disadvantages of existing technology are: Existing industrial X-ray flaw detection systems suffer from several shortcomings when applied to the inspection of complex castings: They are characterized by fixed angles and a lack of adaptability. Systems typically employ preset single or limited angles for exposure, with detection parameters determined by manual experience. This prevents real-time adjustment of the X-ray source and detector orientation based on the casting's geometry, leading to insufficient or overexposed exposure in localized areas, uneven image grayscale distribution, and loss of detail. Furthermore, they fail to consider variations in casting thickness and material distribution. Traditional systems, based on fixed exposure voltage and time settings, cannot dynamically adjust energy to changes in wall thickness and absorption coefficient, resulting in signal saturation in thick-walled areas, excessive brightness in thin-walled areas, and decreased overall contrast. Angle and energy control are independent, lacking a geometric model-driven joint optimization mechanism, hindering coordinated control. The inspection process lacks real-time feedback and closed-loop correction. Current systems rely on manual analysis and adjustments after exposure, failing to automatically optimize subsequent parameters based on grayscale, signal-to-noise ratio, and other indicators, leading to repeated exposures and low efficiency. Finally, the inspection efficiency and automation level are low, with existing solutions heavily reliant on manual intervention, making them ill-suited for the batch and online inspection needs of large castings.

[0007] In summary, existing technologies struggle to achieve adaptive multi-angle imaging control for different casting sizes and types, limiting further improvements in imaging quality and the level of intelligent inspection. Summary of the Invention

[0008] The present invention aims to solve the technical problems in the prior art by providing a multi-angle X-ray imaging control method and system that adapts to the size and type of castings.

[0009] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows: A multi-angle X-ray imaging control system that adapts to the size and type of castings includes, in sequence: a casting data information acquisition module, a data modeling thickness calculation module, an adaptive adjustment module, a central control unit module, an image acquisition and grayscale feedback module, and an image output module. The system comprises several modules: a casting data acquisition module to collect the dimensions, shape, and material characteristics of the castings and input them into the data modeling and thickness calculation module; a data modeling and thickness calculation module to establish a three-dimensional thickness distribution model; an adaptive adjustment module to calculate the ray energy and projection angle based on the thickness distribution calculation results and transmit the results to the central control unit module; a central control unit module to synchronize the adjustment of spatial position, energy, and exposure parameters; an image acquisition and grayscale feedback module to perform real-time analysis of the detection image after imaging and to feed back the grayscale deviation to the central control unit module for closed-loop correction and adaptive optimization; and an image output module to output clear, grayscale-uniform detection images, enabling multi-angle intelligent imaging detection of castings of different sizes and types.

[0010] In the above technical solution, the central control unit module is equipped with a motion mechanism, an X-ray machine, and a detector, which are used to realize the synchronous adjustment of spatial position, energy, and exposure parameters.

[0011] A multi-angle X-ray imaging control method that adapts to the size and type of castings, applicable to the system described above, includes the following steps: Step S1: Input casting information; The size, type, and material parameters of the object under test are obtained through the casting data information acquisition module, and a basic data model of the casting is established. Step S2: Thickness modeling and feature extraction; The thickness model is based on the formula: Calculate the three-dimensional thickness field distribution; in, For density distribution, The linear attenuation coefficient of the material. The parameter is the energy of the radiation. For the thickness distribution of the casting, Here is the analytical expression for the three-dimensional thickness distribution field. Indicates the direction of ray propagation Indicates perpendicular to the ray direction. Indicates the height direction perpendicular to the ray and the plane of the casting; This stage extracts the geometric and absorption characteristics of the casting structure to provide a basis for subsequent energy regulation; Step S3: Adaptive angle compensation and energy control; The optimal incident radiation is calculated based on the thickness model results, so as to achieve synchronous adjustment of the attitude of the radiation source and the detector. The control strategy follows the optimization objective function: ; in, For the target grayscale distribution, For the measured grayscale distribution, This represents minimization, achieving adaptive exposure by minimizing the difference between the two. Indicates the pixel position in the horizontal and vertical directions; Step S4: Image acquisition and grayscale feedback; After imaging is completed, the image acquisition and grayscale feedback module monitors the image brightness uniformity and contrast in real time, and records grayscale deviations. Feedback is sent to the adaptive adjustment module; Step S5: Gray-scale feedback and closed-loop optimization; Based on the formula: Iterative correction of local energy parameters gradually improves image quality. This indicates the local exposure energy for the next iteration. This represents the local exposure energy in the current iteration. Represents the feedback gain coefficient ， Represents the spatial coordinates of the image plane. Indicates the number of iterations; Step S6: Output image result generation; The image output module generates uniform and contrast-enhanced inspection images, enabling high-precision identification and display of internal defects in castings.

[0012] The present invention has the following beneficial effects: Assuming the pipeline system is inspected as a cylinder or a regular pipe, this invention can automatically calculate the optimal shooting angle based on geometric features and material absorption characteristics, adapting to personalized inspections of castings of different sizes and shapes, and significantly improving radiographic uniformity.

[0013] This invention updates the angle and energy distribution in real time during the imaging process, achieving self-learning optimization, while the pipeline system only relies on a preset algorithm path, resulting in a delayed feedback response.

[0014] This invention can achieve a more uniform exposure distribution and a higher contrast image through grayscale closed-loop feedback and multi-parameter synchronous adjustment, supporting online detection and mass production; the patented technology in the background technology still requires manual intervention and offline reconstruction.

[0015] In summary, the multi-angle X-ray imaging control method and system for adaptive casting size and type of the present invention is superior to the prior art in terms of adaptive angle control, real-time grayscale feedback and closed-loop optimization mechanism. It has significant advantages such as high detection accuracy, high degree of automation and good system stability, and provides a new technical path for intelligent industrial X-ray inspection. Attached Figure Description

[0016] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0017] Figure 1 This is a schematic diagram of the structure of the multi-angle X-ray imaging control system for adaptive casting size and type of the present invention.

[0018] Figure 2 This is a flowchart illustrating the steps of the multi-angle X-ray imaging control method for adaptive casting size and type according to the present invention.

[0019] Figure 3 This is a schematic diagram of geometric relationships and angle definitions.

[0020] Figure 4 This is a schematic diagram of the angle optimization and feedback adjustment curve.

[0021] The reference numerals in the figure are: 1- Casting data acquisition module; 2- Data modeling and thickness calculation module; 3- Adaptive adjustment module; 4- Central control unit module; 5- Image acquisition and grayscale feedback module; 6- Image output module; 401 - Motion mechanism; 402 - X-ray machine; 403 - Detector. Detailed Implementation

[0022] The inventive concept of this invention is as follows: The present invention relates to a multi-angle X-ray imaging control method and system that adapts to casting size and type. By introducing key technologies such as casting size and type recognition, thickness field modeling, multi-angle optimization planning, and energy zoning control, the system can automatically generate the optimal combination of imaging angles and exposure energy allocation scheme based on the geometry and material properties of the casting. By constructing a candidate angle set and a multi-objective optimization model, and combining it with a real-time image feedback and correction mechanism, adaptive detection control for different castings is achieved, thereby significantly improving imaging uniformity, contrast, and defect identification accuracy, and reducing repeated exposures and manual adjustment steps.

[0023] The core of the multi-angle X-ray imaging control method and system for adaptive casting size and type of the present invention lies in the closed-loop control mechanism of casting information recognition, geometric modeling, angle planning, energy regulation and image feedback optimization, which realizes adaptive adjustment and multi-angle collaborative optimization of X-ray imaging parameters, thereby improving the detection accuracy and imaging uniformity of internal defects in complex castings.

[0024] The present invention will now be described in detail with reference to the accompanying drawings.

[0025] like Figure 1As shown, the multi-angle X-ray imaging control system for casting size and type adaptively of the present invention mainly consists of the following modules connected in sequence: casting data information acquisition module 1, data modeling thickness calculation module 2, adaptive adjustment module 3, central control unit module 4, image acquisition and grayscale feedback module 5, and image output module 6. The casting data information acquisition module 1 is used to collect the size, shape, and material characteristics of the casting and input them to the data modeling thickness calculation module 2. The data modeling thickness calculation module 2 is used to establish a three-dimensional thickness distribution model. The adaptive adjustment module 3 is used to perform energy mapping calculation and angle planning based on the thickness distribution calculation results, respectively calculating the X-ray energy and projection angle, and transmitting the results to the central control unit module 4. The central control unit module 4 includes a motion mechanism 401, an X-ray machine 402, and a detector 403, which are used to synchronously adjust the spatial position, energy, and exposure parameters, respectively. The image acquisition and grayscale feedback module 5 is used to perform real-time analysis of the detected image after imaging, feeding back the grayscale deviation to the central control unit module 4 to achieve closed-loop correction and adaptive optimization. Image output module 6 is used to output clear, grayscale-uniform inspection images to achieve multi-angle intelligent imaging inspection of castings of different sizes and types.

[0026] like Figure 2 As shown, the multi-angle X-ray imaging control method for adaptive casting size and type of the present invention is applicable to the above-mentioned system, and the method includes the following steps: Step S1: Input casting information (size, type, material); The casting data information acquisition module 1 acquires the size, type and material parameters of the object under test and establishes the basic data model of the casting. Step S2: Thickness Modeling With feature extraction; Moving on to the thickness modeling and feature extraction stage, the thickness model is based on the formula: , Calculate the three-dimensional thickness field distribution; in, For density distribution, The linear attenuation coefficient of the material. For the radiation energy parameter, For the thickness distribution of the casting, Here is the analytical expression for the three-dimensional thickness distribution field. Indicates the direction of ray propagation Indicates perpendicular to the ray direction. This indicates the height direction perpendicular to the ray and the plane of the casting.

[0027] This stage extracts the geometric and absorption characteristics of the casting structure to provide a basis for subsequent energy regulation.

[0028] Step S3: Adaptive angle compensation and energy control; Entering the adaptive angle compensation stage, the optimal incident angle is calculated based on the thickness model results. This enables synchronous adjustment of the attitude of the X-ray source and detector 403; The control strategy follows the optimization objective function: ; in, For the target grayscale distribution, For the measured grayscale distribution, This represents minimization, achieving adaptive exposure by minimizing the difference between the two. Indicates the pixel position in the horizontal and vertical directions; Step S4: Image acquisition and grayscale feedback; After imaging is completed, the image acquisition and grayscale feedback module 5 monitors the image brightness uniformity and contrast in real time, and records the grayscale deviation. Feedback is sent to the control system (adaptive adjustment module 3); Step S5: Gray-scale feedback and closed-loop optimization; Entering the grayscale feedback and closed-loop optimization stage, according to the formula: , Iterative correction of local energy parameters gradually improves image quality. This indicates the local exposure energy for the next iteration. This represents the local exposure energy in the current iteration. Represents the feedback gain coefficient ， Represents the spatial coordinates of the image plane. Indicates the number of iterations; Step S6: Output image result generation; After multiple rounds of optimization, the image output module 6 generates a uniform and contrast-enhanced detection image, enabling high-precision identification and display of internal defects in the casting.

[0029] like Figure 3 As shown in the diagram, the geometric relationship and angle definition illustrate the spatial layout and geometric constraints between the X-ray machine 402, detector 403, and the casting under test. The system establishes a three-dimensional Cartesian coordinate system with the center of the casting as the origin. The x-axis points towards detector 403, the y-axis represents the horizontal rotation direction, and the z-axis is the vertical direction. The X-rays emitted by the X-ray machine 402 pass through different thickness regions of the casting under test and reach detector 403, forming an incident angle during propagation. The incident angle, representing the angle between the ray and the system normal, is a core parameter for multi-angle imaging control, and it is related to the thickness distribution of the casting being measured. Together, they determine the local energy decay law, which satisfies the Beer-Lambert law: ; in, The intensity of the incident ray, The linear attenuation coefficient is... The intensity of the transmitted rays is also represented by the grayscale signal acquired by the detector. The system dynamically adjusts the incident angle. The distance between the X-ray source and detector 403 enables adaptive irradiation of regions with different thicknesses: the incident angle is automatically increased for thick-walled regions to enhance the penetration depth, while the angle is decreased for thin-walled regions to avoid overexposure. This geometric relationship and angle definition provide the mathematical basis for the multi-angle adaptive control algorithm (i.e., adaptive adjustment module 3) of this invention, enabling the system to intelligently plan the optimal imaging path based on the casting size, type, and material distribution, thereby achieving balanced imaging energy, improved contrast, and enhanced defect visualization.

[0030] like Figure 4 The angle optimization and feedback adjustment curve shown illustrates the angle correction amount of the system under closed-loop control. With grayscale deviation The dynamic variation with the number of iterations. The horizontal axis represents the number of feedback control iterations, and the vertical axis represents the correction amount. Solid line. The dotted line indicates the correction range during angle adjustment. This indicates the trend of image grayscale error. In the initial stage, due to uneven image brightness distribution, the grayscale deviation is large, resulting in a significant angle correction by the system. As feedback control iterates, the grayscale deviation gradually decreases, the correction rapidly decays and stabilizes, eventually converging to zero, indicating that the system has reached the optimal pose and exposure balance state. Figure 4 Reflects the formula (in, Indicates the angle attenuation factor. This indicates the angle correction amount for the next iteration. This represents the angle correction amount for the current iteration. The convergence characteristics of the feedback gain coefficient (representing the feedback gain coefficient) verify that the multi-angle X-ray imaging control method for casting size and type proposed in this invention can achieve real-time optimization of X-ray source attitude and imaging grayscale, thereby improving image contrast and defect recognition accuracy.

[0031] The multi-angle X-ray imaging control method and system for casting size and type adaptive of the present invention is superior to the prior art in terms of adaptive angle control, real-time grayscale feedback and closed-loop optimization mechanism. It has significant advantages such as high detection accuracy, high degree of automation and good system stability, and provides a new technical path for intelligent industrial X-ray inspection.

[0032] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A cast size and type adaptive multi-angle X-ray imaging control system, characterized by, It comprises successively connected: foundry data information acquisition module (1), data modeling thickness calculation module (2), self-adaptive adjustment module (3), central control unit module (4), image acquisition and gray feedback module (5) and image output module (6); Wherein, the foundry data information acquisition module (1) is used to collect the size, shape and material characteristics of the casting, and is input to the data modeling thickness calculation module (2);The data modeling thickness calculation module (2) is used to establish a three-dimensional thickness distribution model;The self-adaptive adjustment module (3) is used to calculate the radiation energy and projection angle according to the thickness distribution calculation result, and the result is transmitted to the central control unit module (4);The central control unit module (4) is used to realize the synchronous adjustment of spatial position, energy and exposure parameter;The image acquisition and gray feedback module (5) is used to analyze the detection image in real time after imaging, and the gray deviation is fed back to the central control unit module (4), realizing closed loop correction and adaptive optimization;The image output module (6) is used to output clear and gray balanced detection image, realizing multi-angle intelligent imaging detection of different size and type castings.

2. The cast size and type adaptive multi-angle X-ray imaging control system according to claim 1, characterized in that, The central control unit module (4) is provided with motion mechanism (401), X-ray machine (402) and detector (403) respectively for realizing synchronous adjustment of spatial position, energy and exposure parameter.

3. A method for controlling multi-angle X-ray imaging with casting size and type adaptation, applicable to the system of claim 1, characterized in that, The method comprises the following steps: Step S1: foundry information input; The size, type and material parameters of the measured object are obtained by the foundry data information acquisition module (1), and the basic data model of the casting is established; Step S2: thickness modeling and feature extraction; The thickness model is calculated using the formula: to calculate the three-dimensional thickness field distribution; wherein, is the density distribution, is the material linear attenuation coefficient, is the ray energy parameter; is the casting thickness distribution, is the analytical expression of the three-dimensional thickness distribution field, denotes the direction of the ray propagation, denotes the direction perpendicular to the ray, denotes the direction perpendicular to the height of the ray and the casting plane; This stage extracts the geometric and absorption characteristics of the casting structure, providing a basis for subsequent energy regulation; Step S3: adaptive angle compensation and energy control; According to the thickness model result, the optimal incidence is calculated, and the posture of the radiation source and the detector (403) is adjusted synchronously; The control strategy follows the optimization objective function: ； wherein, is a target gray scale distribution, is a measured gray scale distribution, denotes minimization, adaptive exposure is achieved by minimizing the difference between the two, denotes horizontal and vertical direction pixel positions; Step S4: image acquisition and gray feedback; After the imaging is completed, the image acquisition and gray feedback module (5) monitors the image brightness uniformity and contrast index in real time, and feeds back the gray deviation to the adaptive adjustment module (3). Step S5: gray feedback and closed loop optimization; According to the formula: , the local energy parameter is iteratively corrected to gradually improve the image quality. local exposure energy of the next iteration, local exposure energy of the current iteration, feedback gain coefficient ， image plane space coordinate, n iteration number; Step S6: output image result generation; The detection image of uniformization and contrast enhancement is generated by the image output module (6), realizing high precision identification and display of the internal defects of the casting.

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