Automated scanning control method and system for x-ray flaw detector

Abstract

The application discloses an automatic scanning control method and system for an X-ray flaw detector, and relates to the technical field of detection. The method comprises the following steps: obtaining the characteristics and requirements of a scanning target through interaction, segmenting a scanning domain, reading the specifications of the flaw detector and training an adaptive decision unit, determining a target scanning strategy by traversing the scanning domain, analyzing a pre-control strategy based on the object table and the X-ray source, performing scanning control through numerical control coding and receiving subjective instructions, and simultaneously performing feedback adjustment based on the detector signal check sum. The technical problem that the detection and control of rays lack flexibility and precision and cannot be dynamically optimized according to the characteristics and requirements of different scanning targets in the existing X-ray flaw detection technology is solved. The technical effects of improving detection accuracy and efficiency, avoiding missed detection and false detection, and providing strong support for quality detection in industrial production are achieved by dynamically optimizing ray parameters in real time according to the characteristics and requirements of different scanning targets.

Description

Technical Field

[0001] This application relates to the field of detection technology, and in particular to an automated scanning control method and system for X-ray flaw detectors. Background Technology

[0002] In industrial product quality inspection scenarios, the accuracy and efficiency of X-ray flaw detection are particularly prominent, and the need to optimize flaw detection technology is also more acute. Achieving flexible and accurate flaw detection to better meet the inspection needs of different scanning targets has become a crucial aspect of solving the problem of X-ray flaw detection in industrial products. Traditional X-ray flaw detection technology is often relatively fixed and lacks specificity, relying solely on a single scanning strategy or limited radiation control methods. It lacks sufficient analysis of the characteristics of the scanning target, and lacks in-depth research and utilization of different materials and structures. It is difficult to comprehensively and accurately determine the optimal flaw detection parameters. In the inspection process, there are inflexible situations, leading to inaccurate detection of some complex structures and waste of resources in some simple areas. The formulation of flaw detection schemes is relatively simple and fixed, which cannot well cope with the diverse actual inspection situations in industrial production.

[0003] Currently, in X-ray flaw detection technology, there are technical problems such as a lack of flexibility and precision in the detection and control of radiation, and an inability to dynamically optimize the technology according to the characteristics and needs of different scanning targets. Summary of the Invention

[0004] This application provides an automated scanning control method and system for X-ray flaw detectors. It employs an interactive approach to acquire the characteristics and requirements of the scanning target, segment the scanning domain, read the flaw detector specifications and train an adaptive decision unit, traverse the scanning domain to determine the target scanning strategy, analyze the pre-control strategy using the stage and X-ray source as components, execute scanning control through numerical control coding and receive subjective commands, and simultaneously optimize X-ray parameters dynamically in real time based on detector signal verification and feedback adjustment. This achieves the technical effect of improving detection accuracy and efficiency, avoiding missed and false detections, and providing strong support for quality inspection in industrial production.

[0005] This application provides an automated scanning control method for an X-ray flaw detector, including:

[0006] Based on the basic characteristics and detection requirements of the interactive scanning target, multiple target scanning domains are determined by segmentation. The basic characteristics include geometric and material properties. The specification information of the X-ray flaw detector is read, and an adaptive decision unit is trained under supervision. The adaptive decision unit includes a trajectory decision unit and a ray parameter control decision unit. The multiple target scanning domains are traversed, and scanning decisions and global integration are performed in conjunction with the adaptive decision units to determine the target scanning strategy. Using the stage and X-ray source as scanning collaborative control components, the target scanning strategy is analyzed by off-axis collaborative decomposition to determine the pre-control strategy. The pre-control strategy is numerically encoded and automated scanning control is executed. Subjective control commands are received based on the navigation window, and subjective scanning control is executed. Simultaneously, detection signals are received based on the detector, and scanning fuzzy verification and feedback adjustment management are performed based on the detection signals.

[0007] This application also provides an automated scanning control system for an X-ray flaw detector, including:

[0008] The system comprises the following modules: a target scanning domain determination module, which interacts with the basic characteristics and detection requirements of the target to segment and determine multiple target scanning domains, including geometric and material characteristics; a supervised training module, which reads the specification information of the X-ray flaw detector and supervises the training of an adaptive decision unit, including a trajectory decision unit and a ray parameter control decision unit; a target scanning strategy determination module, which traverses the multiple target scanning domains and, in conjunction with the adaptive decision unit, performs scanning decisions and global integration to determine the target scanning strategy; a pre-control strategy determination module, which uses the stage and X-ray source as scanning collaborative control components to perform off-axis collaborative decomposition analysis on the target scanning strategy to determine the pre-control strategy; a scanning control execution module, which performs numerical control encoding on the pre-control strategy, executes automated scanning control, receives subjective control commands based on the navigation window, and executes subjective scanning control; and a synchronization module, which synchronizes the received detection signals based on the detector and performs scanning fuzzy verification and feedback adjustment management based on the detection signals.

[0009] The proposed automated scanning control method and system for X-ray flaw detectors, as described in this application, firstly acquires the characteristics and requirements of the scanning target through interactive methods, segments the scanning domain, reads the flaw detector specifications and trains an adaptive decision-making unit, traverses the scanning domain to determine the target scanning strategy, analyzes the pre-control strategy using the stage and X-ray source as components, performs numerical control coding to execute scanning control and receives subjective commands, and simultaneously optimizes the X-ray parameters in real time based on detector signal verification and feedback adjustment according to the characteristics and requirements of different scanning targets. This achieves the technical effect of improving detection accuracy and efficiency, avoiding missed and false detections, and providing strong support for quality inspection in industrial production. Attached Figure Description

[0010] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments of the present invention will be briefly described below. Flowcharts are used in this application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0011] Figure 1 A flowchart illustrating an automated scanning control method for an X-ray flaw detector provided in an embodiment of this application;

[0012] Figure 2 This is a schematic diagram of the structure of an automated scanning control system for an X-ray flaw detector provided in an embodiment of this application.

[0013] Explanation of reference numerals in the attached diagram: Target scanning domain determination module 10, supervised training module 20, target scanning strategy determination module 30, pre-control strategy determination module 40, scanning control execution module 50, synchronization module 60. Detailed Implementation

[0014] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application.

[0015] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description of this application will be provided in conjunction with the accompanying drawings. The described embodiments should not be considered as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0016] In the following description, references to "some embodiments" describe a subset of all possible embodiments. However, it is understood that "some embodiments" may be the same or different subsets of all possible embodiments and may be combined with each other without conflict. The terms "first" and "second" are used merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only.

[0017] This application provides an automated scanning control method for an X-ray flaw detector, such as... Figure 1 As shown, the method includes:

[0018] Step S100 involves interactively scanning the target's basic characteristics and detection requirements, segmenting the scanning domain to determine multiple target scanning domains. The basic characteristics include geometric and material properties. Specifically, the basic characteristics and detection requirements of the interactively scanned target refer to relevant information acquired and clarified before scanning. The target object to be scanned is selected, the necessary tools and system for interactive scanning are prepared, and the parameters for interactive scanning are set, such as the accuracy of acquiring geometric characteristics and the depth of analysis of material properties. Interactive scanning is then performed to obtain detailed recorded data of the target's geometric characteristics. This detailed recorded data represents the target's shape, size, structure, and other features, and its characteristic is that it describes the target's external morphology. Interactive scanning continues to be performed to obtain recorded data of the target's material properties. This recorded data represents information such as the target's material composition, density, and uniformity, and its characteristic is that it reflects the target's intrinsic material properties. Through the above interactive scanning process, the scanning domain is segmented to determine multiple target scanning domains.

[0019] In one possible implementation, based on the basic characteristics and detection requirements of the interactive scanning target, multiple target scanning domains are determined through scanning domain segmentation. The basic characteristics include geometric and material characteristics. Step S100 further includes step S110, which, based on the basic characteristics, determines a first preset discriminability, segments the scanning target into scanning domains, and determines a first segmentation result. Specifically, the basic characteristics of the scanning target are analyzed. These basic characteristics include geometric characteristics, such as whether the target's shape is regular or irregular, its size, and the complexity of its structure, as well as material characteristics, such as the type of material, its composition, and its uniformity. Based on a comprehensive understanding and evaluation of the basic characteristics, a discriminability standard for segmentation is determined and named the first preset discriminability. The first preset discriminability is similar to a threshold or standard used to distinguish regions with different characteristics within the scanning target. Using a specific segmentation algorithm or method, the scanning target is segmented according to this first preset discriminability. After segmentation, a preliminary segmentation result is obtained, which we call the first segmentation result.

[0020] Step S120: Based on the detection requirements, a second preset discrimination degree is determined, and the scanning target is segmented into a scanning domain to determine a second segmentation result. Specifically, the focus shifts to specific detection requirements, including the type of defect to be detected, such as tiny cracks, internal voids, or uneven material distribution; the required detection accuracy, whether it needs to be accurate to the micrometer or millimeter level; and specific key detection areas, such as critical stress points or areas where problems frequently occur. Based on detailed and specific detection requirements, another discrimination degree standard is determined, namely the second preset discrimination degree. The second preset discrimination degree is specifically set to meet the detection requirements. Based on the second preset discrimination degree, a new round of scanning domain segmentation is performed on the scanning target. After the segmentation is completed, another segmentation result is obtained, which is the second segmentation result.

[0021] Step S130: Fit the first segmentation result and the second segmentation result to determine the multiple target scanning domains. Specifically, the first and second segmentation results obtained above are fitted to find the best matching and coordination method between them. By applying experience and comprehensively considering the characteristics and interrelationships of each region in the two segmentation results, possible duplicate segments and inconsistent parts are eliminated during fitting to achieve a reasonable and effective overall segmentation scheme. Finally, multiple clear target scanning domains are determined through fitting. The scanning domains consider both the basic characteristics of the scanned target and meet specific detection requirements, providing clear and accurate guidance for subsequent precise scanning and flaw detection work. For example, suppose the scanned target is an aircraft engine blade. Based on its basic geometric and material characteristics, a first preset discrimination degree is determined, roughly dividing the blade into regions such as the blade tip, blade body, and blade root, resulting in the first segmentation result. Based on the requirement for detecting common fatigue cracks in the blade, a second preset discrimination degree is determined, further subdividing the key parts where cracks may occur, resulting in the second segmentation result. Then, these two results are fitted to finally determine multiple target scanning domains, such as the high-stress area at the blade tip and specific material joints in the blade body.

[0022] Step S200: Read the specifications of the X-ray flaw detector and supervise the training of the adaptive decision-making unit, which includes a trajectory decision-making unit and a radiation parameter control decision-making unit. Specifically, this involves reading the specifications of the X-ray flaw detector and supervising the training of the adaptive decision-making unit, which includes a trajectory decision-making unit and a radiation parameter control decision-making unit. Select the model of the X-ray flaw detector to be used, obtain relevant specifications, set training parameters such as accuracy requirements, scanning range, and radiation energy range, and execute the training operation to obtain the preliminary training results of the trajectory decision-making unit. The preliminary training results of the trajectory decision-making unit indicate its ability to plan radiation scanning trajectories under different scanning targets and detection requirements, characterized by precise planning. Continue executing the training operation to obtain the training results of the radiation parameter control decision-making unit. The training results of the radiation parameter control decision-making unit indicate its ability to control radiation parameters, determine the optimal radiation parameters in different materials and detection scenarios, and supervise the entire training process to ensure that the adaptive decision-making unit can operate effectively.

[0023] In one possible implementation, the specification information of the X-ray flaw detector is read, and the adaptive decision unit is trained under supervision. The adaptive decision unit includes a trajectory decision unit and a radiation parameter control decision unit. Step S200 further includes step S210, which reads historical detection data, mines and constructs a detection database. The detection database contains a relative control relationship determined based on material type, radiation intensity and penetration depth, and tube voltage and tube current. The detection database is scalable. Specifically, a large amount of past testing data is retrieved from databases or archives storing historical testing records. This data covers relevant information on different types of materials (such as metals, plastics, ceramics, etc.) when undergoing X-ray testing, including specific parameters such as the intensity of radiation used, penetration depth, tube voltage, and tube current. Data mining techniques and algorithms are used to conduct in-depth analysis and processing of the historical testing data. By mining the potential patterns and relationships within it, a specialized testing database is constructed. This database explicitly includes the relative control relationships determined based on material type, radiation intensity and penetration depth, and tube voltage and tube current. It provides a clear understanding of how to set the required radiation intensity and corresponding tube voltage and tube current for different materials to achieve a specific penetration depth. The testing database is scalable; as new testing data is continuously accumulated and added, the content and relationships in the database can be continuously enriched and improved, making it more accurate and comprehensive.

[0024] Step S220: Using the detection database and the specification information, the X-ray parameter control decision unit is constructed through data-driven training. Specifically, after the detection database is constructed, it is used as an important reference and auxiliary resource to obtain detailed specification information of the X-ray flaw detector, such as the maximum and minimum tube voltage and current range that the equipment can output, as well as parameters such as the equipment's accuracy and stability. Combining the control relationships in the detection database and the flaw detector's specification information, a data-driven training method is adopted. This training method is typically based on a large amount of sample data, allowing the system to automatically learn and optimize parameters to construct a X-ray parameter control decision unit capable of precisely controlling X-ray parameters. Through training and adjustment, the X-ray parameter control decision unit can quickly and accurately provide the optimal X-ray parameter setting scheme based on the input material type, detection requirements, and the actual specifications of the flaw detector, thereby improving the effect and accuracy of X-ray flaw detection. For example, when it is necessary to detect a new type of alloy material, the control relationships of similar materials in the detection database are first used as a reference, and then training is performed in conjunction with the current flaw detector's specification information, enabling the X-ray parameter control decision unit to determine the optimal X-ray parameters suitable for detecting that alloy material.

[0025] Step S300: Traverse the multiple target scanning domains, and combine the adaptive decision-making unit to perform scanning decisions and global integration to determine the target scanning strategy. Specifically, traversing the multiple target scanning domains, combining the adaptive decision-making unit to perform scanning decisions and global integration to determine the target scanning strategy involves selecting the target object to be scanned, preparing the necessary equipment and system for scanning, setting scanning decision parameters such as scanning accuracy, coverage area, and ray parameters, and performing a traversal operation on the multiple target scanning domains to obtain preliminary scanning decision data for each target scanning domain. The preliminary scanning decision data represents a separate scanning plan for each target scanning domain, characterized by its regional specificity. The global integration operation continues to be performed to obtain globally integrated scanning strategy data. The globally integrated scanning strategy data represents the comprehensive planning and coordination of all target scanning domains, determining the final target scanning strategy to guide the efficient execution of the entire scanning process.

[0026] Step S400: Using the stage and X-ray source as scanning collaborative control components, perform off-axis collaborative decomposition analysis on the target scanning strategy to determine the pre-control strategy. Specifically, this involves selecting the target object to be scanned, preparing the necessary equipment and conditions for scanning collaborative control, setting relevant control parameters such as the stage's movement speed and accuracy, and the X-ray source's radiation intensity and angle range, and performing the target scanning strategy analysis to obtain preliminary off-axis collaborative decomposition data. This preliminary data represents the decomposition of the target scanning strategy into basic control units related to the stage and X-ray source, characterized by detailed decomposition. Further in-depth collaborative analysis is performed to obtain complete off-axis collaborative decomposition analysis results. These results represent the planning of the stage and X-ray source's collaborative movements along different axes, ultimately determining the pre-control strategy and providing precise guidance for actual scanning operations.

[0027] In one possible implementation, the stage and X-ray source are used as scanning collaborative control components. A misaligned collaborative decomposition analysis is performed on the target scanning strategy to determine the pre-control strategy. Step S400 further includes step S410, which involves determining a first spatial coordinate system centered on the stage and a second spatial coordinate system centered on the X-ray source. Specifically, a three-dimensional spatial coordinate system, called the first spatial coordinate system, is established using the stage as a reference. The origin of this coordinate system is located at a fixed position on the stage, and the directions of the coordinate axes are set according to the actual situation, usually related to the direction of movement of the stage. The position and movement of the stage can be accurately described and calculated in this coordinate system. Another independent three-dimensional spatial coordinate system, the second spatial coordinate system, is established using the X-ray source as a reference. Its origin is located at a specific position on the X-ray source, and the directions of the coordinate axes are also determined according to the characteristics and operational requirements of the X-ray source.

[0028] Step S420: Identify the target scanning strategy and determine a first strategy node. The first strategy node is associated with a first scanning trajectory of the first target scanning domain. The first scanning trajectory is determined based on the domain edge. Specifically, the pre-defined target scanning strategy is analyzed and identified. Within the strategy, a key strategy node, referred to as the first strategy node, is determined. This node is associated with a specific scanning trajectory of the first target scanning domain. The first scanning trajectory does not scan each region sequentially in the traditional order, but is determined based on the edge of the target scanning domain. The scanning trajectory will pass through different positions within the same region multiple times to detect the target more comprehensively and meticulously.

[0029] Step S430: Based on the first spatial coordinate system and the second spatial coordinate system, the first strategy node is allocated to determine a first misaligned cooperative strategy for continuous node control. Specifically, using the previously established first and second spatial coordinate systems, the first strategy node is analyzed. By considering the position, movement, and interrelationship of the stage and X-ray source in the two coordinate systems respectively, the tasks and control requirements involved in the first strategy node are reasonably allocated and coordinated in the two coordinate systems. After allocation and coordination, a first misaligned cooperative strategy that can achieve continuous node control is finally determined. This strategy ensures that during the scanning process, the stage and X-ray source can work collaboratively in different axes to accurately and efficiently scan and detect the target scanning domain according to the predetermined trajectory and requirements. For example, when scanning a complex mechanical part, two spatial coordinate systems are first established. Then, the first strategy node and edge-based scanning trajectory related to a key part of the part are identified. Finally, through allocation in the two coordinate systems, it is determined how to make the stage and X-ray source work collaboratively to achieve accurate scanning of that part, even if the scanning trajectory may pass through different positions of the same area multiple times.

[0030] In one possible implementation, the first strategy node is allocated based on the first spatial coordinate system and the second spatial coordinate system to determine a first misaligned coordinate strategy for continuous node control. Step S430 further includes step S431, which determines control adjustment information for strategy node switching based on the first misaligned coordinate strategy and the second misaligned coordinate strategy. The second misaligned coordinate strategy is a coordinate system allocation strategy determined based on the second strategy node and the second scan trajectory of the second target scan domain. Specifically, considering the first and second misaligned coordinate strategies, each strategy is associated with different strategy nodes and target scan domains. The allocation processing method for each node strategy is the same. When switching from one strategy node to another, adjustments are needed across domains, such as scan trajectory, speed, and ray parameters. Simultaneously, the continuous control state of the stage and ray source in the previous region stage needs to be changed. For example, when switching from the first target scan domain to the second target scan domain, it may be necessary to adjust the direction and speed of the scan trajectory, and change the intensity and wavelength of the ray.

[0031] Step S432: Identify the control adjustment information and determine whether the adjustment threshold is met. Specifically, the determined control adjustment information is identified and analyzed, and the information is compared and judged with a pre-set adjustment threshold. The adjustment threshold is determined comprehensively based on factors such as equipment performance, accuracy requirements, and consideration of equipment lifespan.

[0032] Step S433: If the value exceeds the adjustment threshold, the control adjustment information is converted in multiple steps using the adjustment threshold as a constraint to determine the switching control strategy. Specifically, if the control adjustment information exceeds the adjustment threshold, it means that direct switching may have a significant impact on control accuracy, and may even affect the lifespan of the equipment due to control pulse oscillation. Therefore, the control adjustment information is converted in multiple steps using the adjustment threshold as a constraint. Through gradual and phased adjustments, the final switching control strategy is determined to reduce the adverse effects of switching and ensure the smoothness and accuracy of the scanning process.

[0033] Step S434: If the control adjustment information is less than or equal to the adjustment threshold, the control adjustment information is used as the switching control strategy. Specifically, if the control adjustment information is less than or equal to the adjustment threshold, it indicates that the impact of direct switching is within an acceptable range, and this control adjustment information is directly used as the switching control strategy without the need for additional multi-step conversion.

[0034] Step S435: Traverse the target scanning strategy, transform and integrate the off-axis coordination strategy and switching control strategy of each strategy node, and determine the pre-control strategy. Specifically, a comprehensive traversal of the entire target scanning strategy is performed. For each strategy node, its corresponding off-axis coordination strategy and switching control strategy are transformed and integrated. Since the distribution processing method of each node strategy is the same, it can be processed according to a unified method. Through integration, a complete pre-control strategy is finally determined, providing accurate and reliable guidance for actual scanning operations. For example, when performing X-ray flaw detection scanning on a complex workpiece, when switching from the first region to the second region, it is found that the control adjustment information exceeds the threshold. Therefore, the scanning parameters are gradually adjusted according to the multi-step conversion method to ensure smooth switching. When switching from the third region to the fourth region, the control adjustment information is within the threshold range, so this information is directly used as the switching control strategy. Traversing the entire scanning strategy and integrating the strategies of all regions yields the final pre-control strategy, ensuring the high-quality completion of flaw detection scanning.

[0035] Step S500: Numerical control (NC) encoding of the pre-control strategy is performed, automated scanning control is executed, and subjective control commands are received based on the navigation window to execute subjective scanning control. Specifically, the pre-control strategy is NC encoded, automated scanning control is executed, and subjective control commands are received based on the navigation window to execute subjective scanning control. The scanning scenario to be applied is selected, the necessary equipment and system for scanning control are prepared, NC encoding parameters are set, such as scanning accuracy, speed range, and X-ray intensity adjustment range, etc., and NC encoding operation is performed to obtain encoded pre-control strategy data. The encoded pre-control strategy data represents the conversion of the pre-control strategy into executable machine instructions. Automated scanning control operation is started, and real-time status data during the automatic scanning process is obtained. The real-time status data during the automatic scanning process represents the automatic operation of the equipment according to the pre-control strategy. Subjective control commands are received based on the navigation window, such as pausing scanning, changing the scanning area, and adjusting scanning parameters. The received subjective control commands represent specific instructions input by the operator according to actual needs. Subjective scanning control operation is executed to obtain scanning result data after subjective control. The scanning result data after subjective control represents the scanning situation after adjustments based on the operator's instructions.

[0036] Step S600: Synchronously receive detection signals based on the detector, and perform scan fuzziness verification and feedback adjustment management based on the detection signals. Specifically, the synchronization involves receiving detection signals based on the detector and performing scan fuzziness verification and feedback adjustment management based on the detection signals. Select the target type to be scanned, prepare the necessary equipment and components for detection, set detection signal receiving parameters such as sensitivity, frequency range, and resolution, execute the detection signal receiving operation to obtain initial detection signal data. The initial detection signal data represents the unprocessed raw signal received by the detector for the first time. Perform scan fuzziness verification based on the received detection signals to obtain verification result data. The verification result data represents the judgment result on the scan clarity and accuracy. Continue to execute the feedback adjustment management operation to obtain adjusted scan state data. The adjusted scan state data represents the new state of the scanning process after feedback adjustment.

[0037] In one possible implementation, synchronous detection signals are received by the detector, and scanning fuzziness verification and feedback adjustment management are performed based on the detection signals. Step S600 further includes step S610, which involves traversing the detection signals and converting them to determine the generated reconstructed scanning target. The reconstructed scanning target is generated and updated based on X-ray detection. Specifically, all detection signals received by the detector are checked and processed one by one. The detection signals are generated after X-rays penetrate the scanning target. Through a specific conversion algorithm and processing procedure, the signals are converted into electrical signals, and these electrical signals are further analyzed and integrated to generate the reconstructed scanning target. The reconstructed scanning target is continuously generated and updated based on the results of X-ray detection, including initialized images, three-dimensional models, etc., which can intuitively present the internal structure and features of the scanning target.

[0038] Step S620: Perform an existence verification of detection elements on the reconstructed scanning target to determine the scanning judgment data. Specifically, perform a detailed existence verification of detection elements on the generated reconstructed scanning target to check whether the preset detection elements (such as specific structures, defect types, etc.) are accurately presented and detected in the reconstructed scanning target. Through verification, obtain the corresponding scanning judgment data to evaluate the quality and completeness of the scan.

[0039] Step S630: If the scan judgment data does not meet the standards, a reflow scan instruction is generated. Specifically, after evaluation, if the scan judgment data is found to be inconsistent with the preset standards, indicating that the scan results are incomplete or incomplete, the system will automatically generate a reflow scan instruction to indicate that the parts that do not meet the requirements need to be rescanned.

[0040] Step S640: Based on the reflow scan command, perform repeated scan control. Specifically, based on the generated reflow scan command, the scanning process is readjusted and controlled, including adjusting the parameters of the X-ray source, the position and movement of the stage, and the receiving settings of the detector, to ensure that areas that do not meet the standards can be scanned more accurately and comprehensively until the scan results meet the expected standards. For example, when performing flaw detection scanning on a mechanical part, the 3D model of the part is generated by traversing the detection signals as the reconstructed scan target. The detection elements of this model are checked, and if the details of a certain key part are not clear, the data is determined to be substandard, and a reflow scan command is generated. Then, the scanning parameters are readjusted according to the command, and repeated scan control is performed on that part until a satisfactory scan result is obtained.

[0041] In one possible implementation, the existence of detection elements is verified on the reconstructed scanning target to determine the scanning judgment data. Step S620 further includes step S621, which determines the detection elements based on the detection requirements, wherein the detection elements are identified by their respective scanning domains. Specifically, the detection requirements are analyzed according to specific detection requirements, including the types of defects to be detected (such as cracks, porosity, inclusions, etc.), the accuracy requirements for detection, and the areas of focus. Based on the clear detection requirements, the corresponding detection elements are determined. Since the possible types of defects in different structural parts may differ, each detection element is identified by its respective scanning domain. For example, if the detection requirement is to check whether there is a crack in a specific part of a mechanical component, then the detection elements related to the crack will be marked as belonging to the scanning domain of that specific part.

[0042] Step S622: Traverse the detected elements to generate a fuzzy verification library. Specifically, all determined detected elements are traversed one by one. During the traversal, the features, attributes, standards, and other information of each detected element are organized and summarized. The information is integrated to generate a fuzzy verification library for subsequent verification. The library contains detailed specifications and standards for various detected elements so as to compare and verify them with the reconstructed scanning target.

[0043] Step S623: Traverse the fuzzy verification library and perform element matching verification on the reconstructed scanning target. Specifically, the generated fuzzy verification library is traversed. In each traversal, a detection element is extracted from the fuzzy verification library and then subjected to detailed element matching verification with the reconstructed scanning target. This checks whether the reconstructed scanning target contains the features corresponding to the detection element and whether it meets its standards and requirements. By verifying each detection element in the fuzzy verification library, the accuracy and completeness of the reconstructed scanning target are comprehensively evaluated to determine whether the scanning result meets the detection requirements. For example, for the detection of a car engine cylinder block, detection elements such as cylinder wall cracks and internal pores are determined according to the detection requirements, and their respective scanning domains are identified. Then, these detection elements are traversed to generate a fuzzy verification library. Finally, the verification library is traversed to perform element matching verification on the reconstructed cylinder block scanning target to determine whether all the required elements have been detected.

[0044] This application's embodiments employ a method that interactively acquires the characteristics and requirements of the scanning target, segments the scanning domain, reads the flaw detector specifications and trains an adaptive decision unit, traverses the scanning domain to determine the target scanning strategy, analyzes the pre-control strategy using the stage and X-ray source as components, performs numerical control coding to execute scanning control and receives subjective commands, and simultaneously performs detector signal verification and feedback adjustment. This achieves the technical effect of improving detection accuracy and efficiency, avoiding missed and false detections, and providing strong support for quality inspection in industrial production by dynamically optimizing X-ray parameters in real time according to the characteristics and requirements of different scanning targets.

[0045] In the above text, refer to Figure 1 An automated scanning control method for an X-ray flaw detector according to an embodiment of the present invention is described in detail. Next, reference will be made to... Figure 2 An automated scanning control system for an X-ray flaw detector is described according to an embodiment of the present invention.

[0046] The automated scanning control system for an X-ray flaw detector according to embodiments of the present invention addresses the technical problems in existing X-ray flaw detection technology, namely the lack of flexibility and precision in radiation detection and control, and the inability to dynamically optimize based on the characteristics and requirements of different scanning targets. By dynamically optimizing radiation parameters in real time according to the characteristics and requirements of different scanning targets, the system achieves the technical effect of improving detection accuracy and efficiency, avoiding missed and false detections, and providing strong support for quality inspection in industrial production. The automated scanning control system for an X-ray flaw detector includes: a target scanning domain determination module 10, a supervised training module 20, a target scanning strategy determination module 30, a pre-control strategy determination module 40, a scanning control execution module 50, and a synchronization module 60.

[0047] The target scanning domain determination module 10 is used to interactively scan the basic characteristics and detection requirements of the target, and to perform scanning domain segmentation to determine multiple target scanning domains. The basic characteristics include geometric characteristics and material characteristics.

[0048] The supervised training module 20 is used to read the specification information of the X-ray flaw detector and supervise the training of the adaptive decision unit, which includes a trajectory decision unit and a ray parameter control decision unit.

[0049] The target scanning strategy determination module 30 is used to traverse the multiple target scanning domains, combine the adaptive decision unit, perform scanning decisions and global integration, and determine the target scanning strategy.

[0050] The pre-control strategy determination module 40 is used to perform off-axis collaborative decomposition analysis on the target scanning strategy using the stage and X-ray source as scanning collaborative control components, and determine the pre-control strategy.

[0051] The scanning control execution module 50 is used to perform numerical control encoding on the pre-control strategy, execute automated scanning control, receive subjective control instructions based on the navigation window, and execute subjective scanning control.

[0052] The synchronization module 60 is used to synchronize the detection signals received by the detector and to perform scanning fuzzy verification and feedback adjustment management based on the detection signals.

[0053] The specific configuration of the target scanning domain determination module 10 will be described in detail below. As mentioned above, based on the basic characteristics and detection requirements of the interactive scanning target, multiple target scanning domains are determined by scanning domain segmentation. The basic characteristics include geometric characteristics and material characteristics. The target scanning domain determination module 10 further includes: a first segmentation result determination unit, which is used to determine a first preset distinguishability based on the basic characteristics, and to perform scanning domain segmentation on the scanning target to determine a first segmentation result; a second segmentation result determination unit, which is used to determine a second preset distinguishability based on the detection requirements, and to perform scanning domain segmentation on the scanning target to determine a second segmentation result; and multiple target scanning domain determination units, which are used to fit the first segmentation result and the second segmentation result to determine the multiple target scanning domains.

[0054] The specific configuration of the supervised training module 20 will be described in detail below. As mentioned above, the specification information of the X-ray flaw detector is read, and the adaptive decision-making unit is trained under supervision. The adaptive decision-making unit includes a trajectory decision-making unit and a radiation parameter control decision-making unit. The supervised training module 20 further includes: a database construction unit, which is used to read historical detection data, mine and construct a detection database, wherein the detection database contains a relative control relationship determined based on material type, radiation intensity and penetration depth, tube voltage and tube current, and the detection database is expandable; and a data-driven training unit, which is used to assist the detection database, combined with the specification information, in constructing the radiation parameter control decision-making unit through data-driven training.

[0055] The specific configuration of the pre-control strategy determination module 40 will be described in detail below. As mentioned above, the stage and X-ray source are used as scanning collaborative control components. The target scanning strategy is analyzed by misalignment collaborative decomposition to determine the pre-control strategy. The pre-control strategy determination module 40 further includes: a spatial coordinate system determination unit, which is used to determine a first spatial coordinate system centered on the stage and a second spatial coordinate system centered on the X-ray source; a target scanning strategy identification unit, which is used to identify the target scanning strategy, determine a first strategy node, and a first scanning trajectory of the first strategy node and the first target scanning domain, wherein the first scanning trajectory is determined based on the domain edge; and a node allocation unit, which is used to allocate the first strategy node based on the first spatial coordinate system and the second spatial coordinate system to determine a first misalignment collaborative strategy for continuous node control.

[0056] The node allocation unit is used to allocate the control of the first strategy node based on the first spatial coordinate system and the second spatial coordinate system, and to determine the first misaligned coordination strategy for continuous node control. The node allocation unit further includes: a control adjustment information determination subunit, which is used to determine control adjustment information for strategy node switching based on the first misaligned coordination strategy and the second misaligned coordination strategy, wherein the second misaligned coordination strategy is a coordinate system allocation strategy determined based on the second strategy node and the second scan trajectory of the second target scan domain; and an adjustment threshold determination subunit, which is used to identify the control adjustment information. The system first determines whether the adjustment threshold is met; then it uses a switching control strategy determination subunit, which, if the threshold is greater than the adjustment threshold, performs multi-step transformation on the control adjustment information to determine the switching control strategy; a control adjustment information determination subunit, which, if the control adjustment information is less than or equal to the adjustment threshold, uses the control adjustment information as the switching control strategy; and a target scanning strategy traversal subunit, which traverses the target scanning strategy, transforms and integrates the off-axis coordination strategy and the switching control strategy of each strategy node to determine the pre-control strategy.

[0057] The specific configuration of the synchronization module 60 will be described in detail below. As mentioned above, synchronization is based on the detector receiving detection signals, and scanning fuzziness verification and feedback adjustment management are performed based on the detection signals. The synchronization module 60 further includes: a detection signal traversal unit, which is used to traverse the detection signals and convert and determine the generated reconstructed scanning target, wherein the reconstructed scanning target is generated and updated based on ray detection; an existence verification unit, which is used to perform detection element existence verification on the reconstructed scanning target and determine the scanning judgment data; a reflow scanning instruction generation unit, which is used to generate a reflow scanning instruction if the scanning judgment data does not meet the standard; and a scanning control unit, which is used to perform repeated scanning control based on the reflow scanning instruction.

[0058] The existence verification unit for the reconstructed scanning target, which performs existence verification of detection elements to determine scanning judgment data, further includes: a detection element determination subunit, which determines detection elements based on the detection requirements, wherein the detection elements are identified by their respective scanning domains; a fuzzy verification library generation subunit, which traverses the detection elements to generate a fuzzy verification library; and a fuzzy verification library traversal subunit, which traverses the fuzzy verification library to perform element matching verification on the reconstructed scanning target.

[0059] The automated scanning control system for X-ray flaw detectors provided in the embodiments of the present invention can execute the automated scanning control method for X-ray flaw detectors provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0060] Although this application makes various references to certain modules in the system according to the embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. The various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of this invention.

[0061] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application. In some cases, the actions or steps described in this application can be performed in a different order than that shown in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. An automated scanning control method for an X-ray flaw detector, characterized in that, The method includes: Based on the basic characteristics and detection requirements of the interactive scanning target, multiple target scanning domains are determined by scanning domain segmentation. The basic characteristics include geometric characteristics and material characteristics. Read the specification information of the X-ray flaw detector and supervise the training of the adaptive decision unit, which includes a trajectory decision unit and a ray parameter control decision unit; By traversing the multiple target scanning domains and combining them with the adaptive decision-making unit, scanning decisions are made and the entire domain is integrated to determine the target scanning strategy; Using the stage and X-ray source as scanning collaborative control components, the target scanning strategy is subjected to off-axis collaborative decomposition analysis to determine the pre-control strategy. The pre-control strategy is numerically encoded, automated scanning control is executed, and subjective control commands are received based on the navigation window to execute subjective scanning control. Synchronous detection signals are received by the detector, and scanning fuzzy verification and feedback adjustment management are performed based on the detection signals. The method of performing misaligned collaborative decomposition analysis on the target scanning strategy includes: A first spatial coordinate system is determined with the stage as the center, and a second spatial coordinate system is determined with the X-ray source as the center; Identify the target scanning strategy, determine a first strategy node, and the first strategy node and the first scanning trajectory of the first target scanning domain are determined based on the domain edge; Based on the first spatial coordinate system and the second spatial coordinate system, the first strategy node is allocated to determine the first misaligned cooperative strategy for node control continuity. The method of performing misaligned collaborative decomposition analysis on the target scanning strategy includes: Based on the first misaligned axis coordination strategy and the second misaligned axis coordination strategy, control adjustment information for strategy node switching is determined, wherein the second misaligned axis coordination strategy is a coordinate system allocation strategy determined based on the second strategy node and the second scan trajectory of the second target scan domain; Identify the control adjustment information and determine whether the adjustment threshold is met; If the value is greater than the adjustment threshold, the control adjustment information is subjected to multi-step conversion with the adjustment threshold as a constraint to determine the switching control strategy; If the control adjustment information is less than or equal to the adjustment threshold, the control adjustment information will be used as the switching control strategy. The target scanning strategy is traversed, and the off-axis coordination strategy and switching control strategy of each strategy node are transformed and integrated to determine the pre-control strategy. The scanning fuzzy verification based on the detection signal includes: The detection signals are traversed, and the generated reconstructed scanning target is determined by transformation, wherein the reconstructed scanning target is generated and updated based on ray detection; The existence of detection elements is verified on the reconstructed scanning target to determine the scanning judgment data; If the scan judgment data does not meet the standard, a reflow scan instruction is generated; Based on the aforementioned reflux scan command, repeated scan control is performed.

2. The automated scanning control method for an X-ray flaw detector as described in claim 1, characterized in that, The step of segmenting the scan domain to determine multiple target scan domains includes: Based on the fundamental characteristics, a first preset distinguishability is determined, and the scanning target is segmented into scanning domains to determine the first segmentation result. Based on the detection requirements, a second preset distinguishability is determined, the scanning target is segmented into a scanning domain, and a second segmentation result is determined. The first segmentation result and the second segmentation result are fitted together to determine the plurality of target scanning regions.

3. The automated scanning control method for an X-ray flaw detector as described in claim 1, characterized in that, The adaptive decision-making unit includes a ray parameter control decision-making unit, comprising: Historical detection data is read, and a detection database is constructed. The detection database contains a relative control relationship determined based on material type, radiation intensity and penetration depth, and tube voltage and tube current. The detection database is also expandable. Using the detection database and the specification information as a supplement, the ray parameter control decision unit is constructed through data-driven training.

4. The automated scanning control method for an X-ray flaw detector as described in claim 1, characterized in that, The existence verification of detected elements for the reconstructed scan target includes: Based on the aforementioned detection requirements, detection elements are determined, wherein each detection element is identified by its assigned scan domain. Traverse the detected elements to generate a fuzzy verification library; The fuzzy verification library is traversed to perform element matching verification on the reconstructed scanning target.

5. An automated scanning control system for an X-ray flaw detector, characterized in that, The system is used to implement the automated scanning control method for an X-ray flaw detector as described in any one of claims 1-4, the system comprising: The target scanning domain determination module is used to interactively scan the basic characteristics and detection requirements of the target, and to divide the scanning domain to determine multiple target scanning domains. The basic characteristics include geometric characteristics and material characteristics. The supervised training module is used to read the specification information of the X-ray flaw detector, and the supervised training adaptive decision unit includes a trajectory decision unit and a ray parameter control decision unit. The target scanning strategy determination module is used to traverse the multiple target scanning domains, combine the adaptive decision unit, perform scanning decisions and global integration, and determine the target scanning strategy. A pre-control strategy determination module is used to perform off-axis collaborative decomposition analysis on the target scanning strategy, using the stage and X-ray source as scanning collaborative control components, to determine the pre-control strategy. The scanning control execution module is used to perform numerical control encoding on the pre-control strategy, execute automated scanning control, and receive subjective control instructions based on the navigation window to execute subjective scanning control. A synchronization module is used to synchronize the detection signals received by the detector and to perform scanning fuzzy verification and feedback adjustment management based on the detection signals.

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