Detection system based on multi-modal imaging

Abstract

The invention provides a detection system based on multi-modal imaging. The detection system can be applied to the technical field of nondestructive detection. The detection system comprises a bearing platform for bearing an object to be detected and acquiring the real-time position of the object to be detected; the optical surface detection module is used for acquiring surface images of the to-be-detected object at different positions; the computed tomography module is used for acquiring internal three-dimensional cross-sectional images of the to-be-measured object at different positions; the synchronous control module is used for synchronously driving the optical surface detection module and the computed tomography module to obtain a surface image and an internal three-dimensional tomographic image while driving the bearing platform to move the to-be-detected object based on a preset track; and the processor is used for carrying out image registration on the surface image and the internal three-dimensional cross-sectional image of the to-be-detected object at the real-time position based on the real-time position of the to-be-detected object, and carrying out data fusion on the surface image and the internal three-dimensional cross-sectional image to obtain a detection result of the to-be-detected object at the real-time position.

Description

Technical Field

[0001] At least one embodiment of this disclosure relates to the field of nondestructive testing technology, and more specifically to a testing system based on multimodal imaging. Background Technology

[0002] Non-destructive and non-contact testing technologies include surface testing and internal testing technologies. However, surface testing and internal testing technologies have the limitation of being single-function and cannot achieve integrated testing of the "surface and interior".

[0003] Surface inspection technology boasts high resolution and high response speed, enabling it to identify micron-level surface defects and accurately detect surface problems such as scratches, dents, cracks, and stains. However, the detection range of surface inspection technology is limited to the surface and shallow areas of an object; it cannot penetrate the surface to obtain internal structural information and cannot identify internal defects such as cavities, inclusions, and delamination.

[0004] Internal inspection technology can reconstruct the internal three-dimensional structure by utilizing differences in material absorption, and can reveal the morphology and location of internal defects. However, the spatial resolution of internal inspection technology is limited by the performance of the X-ray source and the accuracy of the detector, resulting in weak ability to identify micron-sized and smaller surface defects, and it cannot simultaneously achieve rapid localization and accurate characterization of surface defects.

[0005] Therefore, there is an urgent need to provide a detection system that can achieve full-dimensional detection from "surface to interior". Summary of the Invention

[0006] In view of the above problems, this disclosure provides a detection system based on multimodal imaging that can realize full-dimensional detection of "surface-interior".

[0007] According to a first aspect of this disclosure, a detection system based on multimodal imaging is provided. The detection system includes: a support platform for carrying an object to be tested and acquiring the real-time position of the object; an optical surface detection module for acquiring surface images of the object at different positions; a computed tomography (CT) module for acquiring internal three-dimensional tomographic images of the object at different positions; a synchronization control module for simultaneously driving the optical surface detection module and the CT module to acquire the surface images and the internal three-dimensional tomographic images while driving the support platform to move the object based on a preset trajectory; and a processor for: performing image registration on the surface image and the internal three-dimensional tomographic image of the object at the real-time position to obtain the alignment spatial coordinates of the real-time position; and performing data fusion on the surface image and the internal three-dimensional tomographic image based on the alignment spatial coordinates of the real-time position to obtain a detection result of the object at the real-time position.

[0008] According to embodiments of this disclosure, the processor is further configured to: identify surface defects of the object under test based on the surface image; identify internal defects of the object under test based on the internal three-dimensional tomographic image; determine the correlation between the surface defects and the internal defects based on the alignment spatial coordinates of the real-time position, and obtain the detection result of the object under test at the real-time position; the detection result includes the size and structure of the surface defects and the internal defects, as well as the defect determination result.

[0009] According to embodiments of this disclosure, the processor is further configured to: identify the surface defects based on the surface image using an edge detection algorithm.

[0010] According to embodiments of this disclosure, the processor is further configured to: use an edge detection algorithm to determine parameter information of the edge contour of the surface defect based on the surface image.

[0011] According to embodiments of this disclosure, the processor is further configured to: identify the internal defects based on the internal three-dimensional tomographic image using a threshold segmentation algorithm.

[0012] According to an embodiment of this disclosure, the processor is further configured to: determine the correlation between the surface defect and the internal defect based on the alignment spatial coordinates of the real-time position, according to the parameter information of the edge contour of the surface defect and the parameter information of the three-dimensional contour of the internal defect, and obtain the detection result of the object under test at the real-time position.

[0013] According to an embodiment of this disclosure, the optical surface detection module includes: a light source for generating a light beam; a lens for acquiring the light signal generated by the object under test under the illumination of the light beam; and an optical detector for imaging the light signal to obtain the surface image; wherein the surface image includes a three-dimensional surface image; and the light beam includes a laser beam or structured light.

[0014] According to an embodiment of this disclosure, the computed tomography (CT) module includes: a radiation source for generating X-rays; a flat panel detector for detecting the X-ray signal generated by the object under test under the irradiation of the X-rays; and a computed tomography image reconstruction unit for imaging the X-ray signal to obtain the internal three-dimensional tomographic image.

[0015] According to an embodiment of this disclosure, the computed tomography image reconstruction unit is used to image the X signal based on a filtered back projection algorithm to obtain the internal three-dimensional tomographic image.

[0016] According to embodiments of this disclosure, the above-mentioned synchronization control module includes a programmable logic controller.

[0017] According to embodiments of this disclosure:

[0018] (1) The synchronous control module can drive the optical surface detection module and the computed tomography module simultaneously. Based on the movement of the object under test, the surface image and the internal three-dimensional tomographic image can be obtained at the same time, and the detection result of the object under test at the real-time position can be obtained. This can improve the detection efficiency and detection accuracy at the same time, and also reduce the equipment cost.

[0019] (2) The optical surface inspection module and the computed tomography module can be used to perform non-destructive and non-contact inspection of the object under test.

[0020] (3) Using a high-precision carrier platform can obtain the real-time position and high-precision positioning of the object under test, which can improve the image registration accuracy of the surface image and the internal three-dimensional tomographic image at the real-time position, thereby improving the detection accuracy of the detection results. Attached Figure Description

[0021] The foregoing contents, other objects, features, and advantages of this disclosure will become clearer from the following description of embodiments of this disclosure with reference to the accompanying drawings.

[0022] Figure 1 A schematic diagram of a detection system based on multimodal imaging according to an embodiment of the present disclosure is shown. Detailed Implementation

[0023] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0024] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0025] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0026] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0027] The related technologies employ a step-by-step detection mode that combines surface detection and internal detection technologies to achieve "surface-internal" combined detection, but the detection efficiency and accuracy are relatively low.

[0028] First, the step-by-step inspection requires two separate tests, each necessitating independent equipment setup and sample positioning. This time-consuming process does not meet the demands for rapid testing of batch samples. Second, the samples need to be transferred between the two tests, which can easily lead to positional shifts and inaccurate correlations between surface and internal defects, making it impossible to perform correlation analysis between surface and internal defects. Finally, the two tests utilize two separate sets of equipment, occupying space and increasing costs.

[0029] In view of this, this disclosure proposes a detection system based on multimodal imaging, which aims to solve at least one of the above-mentioned technical problems.

[0030] Figure 1 A schematic diagram of a detection system based on multimodal imaging according to an embodiment of the present disclosure is shown.

[0031] like Figure 1 As shown, the detection system based on multimodal imaging includes a support platform 1, an optical surface detection module 2, a computed tomography module 3, a synchronization control module 4, and a processor 5.

[0032] The carrier platform 1 carries the object under test 10 and acquires its real-time position. The optical surface detection module 2 acquires surface images of the object under test 10 at different locations. The computed tomography (CT) module 3 acquires internal three-dimensional tomographic images of the object under test 10 at different locations. The synchronization control module 4 simultaneously drives the optical surface detection module 2 and the CT module 3 to acquire surface images and internal three-dimensional tomographic images while driving the carrier platform 1 to move the object under test 10 according to a preset trajectory.

[0033] The support platform 1 may include a servo drive mechanism and a displacement sensor. The servo drive mechanism can precisely move and rotate along the X, Y, and Z axes, driving the object under test 10 to move along a preset trajectory. The displacement sensor can acquire the real-time position of the object under test 10, providing real-time feedback on the position information of the object under test 10, enabling precise positioning with an accuracy of ±1μm, and ensuring the stability of the position of the object under test 10 during the detection process.

[0034] The optical surface inspection module 2 can acquire surface images of the object 10 at different locations using laser scanning optical surface inspection technology. The optical surface inspection module 2 can also acquire surface images of the object 10 at different locations using machine vision surface inspection technology. The computed tomography (CT) module 3 can acquire internal three-dimensional tomographic images of the object 10 at different locations using CT (Computed Tomography) inspection technology.

[0035] The synchronization control module 4 can simultaneously trigger the optical surface detection module 2 and the computed tomography (CT) scanning module 3, enabling simultaneous image acquisition of the object under test 10. This allows the surface image and internal three-dimensional tomographic image of the object under test 10 at its real-time location to be synchronized in time and space. The synchronization control module 4 can be a motion controller or a microcontroller.

[0036] The processor 5 is used to perform image registration between the surface image and the internal three-dimensional tomographic image of the object under test 10 at the real-time position, based on the real-time position of the object under test 10, to obtain the aligned spatial coordinates of the real-time position. Based on the aligned spatial coordinates of the real-time position, the surface image and the internal three-dimensional tomographic image are fused to obtain the detection result of the object under test 10 at the real-time position.

[0037] Based on the real-time position of the object under test 10, the surface image and the internal three-dimensional tomographic image of the object under test 10 at the real-time position are image registered to align the spatial coordinates of the surface image and the internal three-dimensional tomographic image of the object under test 10 at the real-time position, so as to ensure that the information of the surface image at the same position corresponds to the information of the internal three-dimensional tomographic image.

[0038] Alternatively, a world coordinate system can be established at a preset initial position on a preset trajectory for the object 10 under test, and the coordinate systems of the carrier platform 1, optical surface detection module 2, and computed tomography module 3 can be transformed to the world coordinate system. Under the world coordinate system, data fusion is performed based on the real-time position of the object 10 under test, the surface image of the object 10 under test at the real-time position, and the internal three-dimensional tomographic image of the object 10 under test at the real-time position to obtain the detection result of the object 10 under test at the real-time position.

[0039] According to embodiments of this disclosure, non-destructive and non-contact inspection of the object under test can be performed using an optical surface inspection module and a computed tomography (CT) module. Employing a high-precision carrier platform allows for the acquisition of the real-time position and high-precision positioning of the object under test, improving the image registration accuracy between the surface image and the internal three-dimensional tomographic image at the real-time position, thereby enhancing the accuracy of the inspection results. A synchronous control module can synchronously drive the optical surface inspection module and the CT module, simultaneously acquiring the surface image and the internal three-dimensional tomographic image based on a single movement of the object under test, obtaining the inspection result at the real-time position of the object. The object under test does not require a second positioning or two separate measurement processes, simultaneously improving inspection efficiency and accuracy while reducing equipment costs.

[0040] According to embodiments of this disclosure, the processor 5 is further configured to identify surface defects of the object under test 10 based on surface images, and internal defects of the object under test 10 based on internal three-dimensional tomographic images. Based on the aligned spatial coordinates of the real-time position, the correlation between surface defects and internal defects is determined to obtain the detection result of the object under test 10 at the real-time position. The detection result includes the size and structure of the surface and internal defects, as well as the defect determination result.

[0041] Surface defects can be cracks, scratches, pits, burrs, etc., on the surface of the object under test. The size and structure of surface defects can also be identified from the surface image. Based on the size and structure of surface defects, related test items can also be obtained, such as surface roughness, shape and location of surface defects.

[0042] Internal defects can include pores, inclusions, cracks, etc. The size and structure of internal defects can also be identified based on internal three-dimensional tomographic images. Based on the size and structure of internal defects, related detection items can be obtained, such as internal porosity, the shape and location of internal defects.

[0043] The test results can also be used for tolerance analysis. The measured data of dimensional measurements and geometric tolerances can be used to analyze whether the tolerances of a single part are qualified, or whether the cumulative tolerances of multiple parts after assembly lead to excessive assembly clearances.

[0044] According to embodiments of this disclosure, simultaneous identification of surface and internal defects, along with correlation analysis based on image registration, can further improve detection efficiency. Through single-stage localization of the object 10 under test, simultaneous multimodal detection, and automated correlation analysis, defect determination results can be obtained, such as determining whether surface cracks extend into the interior, and other crucial relationships. According to embodiments of this disclosure, the processor 5 is also used to identify surface defects based on the surface image using an edge detection algorithm.

[0045] According to embodiments of this disclosure, the processor 5 is further configured to use an edge detection algorithm to determine parameter information of the edge contour of a surface defect based on a surface image.

[0046] The edge detection algorithm can be a multi-level edge detection algorithm. Processor 5 can perform Gaussian filtering to denoise the surface image, use a multi-level edge detection algorithm to extract the edge contour information of the surface defects, and determine the parameter information of the edge contour of the surface defects, including the length, width, and depth of the edge contour of the surface defects.

[0047] According to embodiments of this disclosure, the processor 5 is also configured to identify internal defects based on internal three-dimensional tomographic images using a threshold segmentation algorithm.

[0048] The threshold segmentation algorithm can be an adaptive threshold segmentation algorithm. The processor 5 can use the adaptive threshold segmentation algorithm to extract the three-dimensional contour of the internal defect from the internal three-dimensional tomographic image and determine the parameter information of the three-dimensional contour of the internal defect. The parameter information of the three-dimensional contour of the internal defect includes the volume and equivalent diameter of the three-dimensional contour of the internal defect.

[0049] According to an embodiment of this disclosure, the processor 5 is further configured to align spatial coordinates based on the real-time position, determine the correlation between surface defects and internal defects based on the parameter information of the edge contour of the surface defect and the parameter information of the three-dimensional contour of the internal defect, and obtain the detection result of the object under test 10 at the real-time position.

[0050] According to embodiments of this disclosure, the optical surface inspection module 2 may include a light source, a lens, and an optical detector. The light source is used to generate a light beam; the lens is used to acquire the light signal generated by the object under test under the illumination of the light beam; and the optical detector is used to image the light signal to obtain a surface image. The surface image may also be a three-dimensional surface image. The light beam may be a laser beam or a structured light beam. Three-dimensional surface imaging of the object under test can be performed using lasers, structured light, or other methods, such as laser scanning detection methods and machine vision detection methods, to obtain a three-dimensional surface image.

[0051] In one example, the optical surface detection module 2 may include a laser 21, a lens, and an optical detector.

[0052] Laser 21 is used to generate a laser beam, which can be used as an excitation source. The laser beam can be visible light or infrared light. A lens is used to acquire the light signal generated by the object under test 10 under the illumination of the laser beam, such as the reflected or scattered signal generated on the surface of the object under test 10 under the illumination of the laser beam. An optical detector is used to image the light signal to obtain a surface image. The optical detector can be a CCD (Charge-Coupled Device) image sensor. The optical surface detection module 2 may also include an image acquisition card.

[0053] According to embodiments of this disclosure, a focused laser beam can improve the resolution of surface defects and enhance the acquisition accuracy of micron-level surface scratches and dents. The optical surface detection module can achieve high resolution and fast response, accurately identifying surface defects such as scratches, dents, cracks, and stains on the surface of the object under test.

[0054] According to embodiments of the present disclosure, the computed tomography (CT) module 3 may include a radiation source, a flat panel detector 31, and a computed tomography image reconstruction unit.

[0055] The X-ray source is used to generate X-rays. The X-ray source can be a microfocus X-ray source, with a focal point of 5 μm, and the X-ray energy can be adjusted within the range of 50 kV to 450 kV. A flat panel detector 31 is used to detect the X-ray signal generated by the object 10 under X-ray irradiation. The flat panel detector 31 can be an X-ray detector, with pixels of 100 μm. A computed tomography (CT) image reconstruction unit is used to image the X-ray signal to obtain an internal three-dimensional tomographic image.

[0056] The computed tomography (CT) module 3 can be a CT detection module. The CT module utilizes CT detection technology to penetrate objects using X-rays or gamma rays, and reconstructs the object's internal three-dimensional structure by leveraging the differences in radiation absorption by different materials. This allows for a clear visualization of the morphology and location of defects within the object.

[0057] According to embodiments of this disclosure, a computed tomography image reconstruction unit is used to image an X signal based on a filtered back projection algorithm to obtain an internal three-dimensional tomographic image.

[0058] According to embodiments of this disclosure, the clarity of internal three-dimensional tomographic images can be improved by using a microfocus X-ray source and a filtered back projection algorithm, and it can also be adapted to the penetration requirements of different materials.

[0059] According to embodiments of this disclosure, the synchronization control module 4 may be a programmable logic controller.

[0060] The programmable logic controller (PLC) is electrically connected to the carrier platform 1, the optical surface inspection module 2, and the computed tomography (CT) scanning module 3, enabling their coordinated operation. This allows for synchronous temporal driving of the carrier platform 1, synchronous triggering of the optical surface inspection module 2 and the CT scanning module 3, and synchronous spatial positioning of the two modules. The PLC's synchronization error is less than the equipment positioning error, effectively solving the timing deviation problem in the step-by-step detection mode and ensuring that surface images and internal 3D tomographic images are acquired synchronously at the same time and location.

[0061] The synchronous control module can control the high-precision carrier platform to move according to a preset trajectory, while simultaneously triggering the image acquisition of the optical surface detection module and the X-ray emission and signal reception of the computed tomography module, ensuring that surface imaging and internal imaging are synchronized in time and space.

[0062] In one embodiment, the detection process using a detection system based on multimodal imaging is as follows.

[0063] The sample to be tested is placed on the support platform, and the initial position of the sample is calibrated by the displacement sensor of the support platform to determine the detection area.

[0064] Determine the preset trajectory of the support platform. Set the acquisition frequency of the optical surface detection module, which can be in the range of 50 frames / second to 100 frames / second. Set the X-ray emission frequency of the CT detection module, which can be in the range of 1 Hz to 5 Hz.

[0065] The synchronous control module drives the carrier platform to move the object under test according to a preset trajectory while simultaneously driving the optical surface detection module and the CT detection module to obtain surface images and internal three-dimensional tomographic images.

[0066] Based on the real-time position of the object under test, the processor performs image registration between the surface image and the internal 3D tomographic image of the object at that real-time position to obtain the aligned spatial coordinates of the real-time position. Based on these aligned spatial coordinates, the surface image and the internal 3D tomographic image are fused to obtain the detection result of the object at its real-time position.

[0067] After the inspection is completed, the support platform is reset and the object under test is removed. Surface images from different locations, internal 3D tomographic images, image registration data, and inspection results are stored in the processor's data storage module, generating an inspection report for subsequent traceability.

[0068] In one example, the object under test can be a semiconductor chip with dimensions of 10mm × 10mm × 0.5mm, and the required detection accuracy is at the micrometer level. It is necessary to detect scratches and bumps on the surface of the object under test, as well as internal voids and bonding failures.

[0069] The preset trajectory of the support platform is determined to be a rotary scanning trajectory, with a scanning speed of 5 mm / s and a rotation of 360°. The wavelength of the laser beam in the optical surface detection module is set to 532 nm, the spot size of the laser beam is 10 μm, and the acquisition frequency is 100 frames / second. The energy of the X-rays in the CT detection module is set to 80 kV, and the X-ray emission frequency is 5 times / second. The pixel size of the flat panel detector 31 is set to 100 μm.

[0070] Two scratches were identified as surface defects. The first scratch has an edge contour length of 200 μm and a width of 15 μm. The second scratch has an edge contour length of 350 μm and a width of 15 μm. One cavity was identified as an internal defect. The diameter of the cavity's three-dimensional contour is 80 μm. The determination can be made by judging whether the positions of the two scratches and the cavity are the same or coincident, and by judging whether the grayscale values ​​of the two scratches and the cavity are similar. For example, this can be used to determine that surface defects and internal defects of a semiconductor chip are unrelated.

[0071] If a step-by-step detection mode is used, obtaining the detection result takes 75 seconds. Using the detection system based on multimodal imaging in this application embodiment, the detection result is obtained in 36 seconds, improving the detection efficiency by 52%, and the detection accuracy meets the micron-level requirements of semiconductor chips.

[0072] In one example, the object under test can be a carbon fiber composite component with dimensions of 500mm × 300mm × 20mm, requiring large-scale inspection and correlation analysis. Surface cracks and dents, as well as internal delamination and inclusions, need to be detected.

[0073] The preset trajectory of the support platform is determined to be a helical scanning trajectory, with a scanning speed of 2 mm / s and a rotation of 360°. The wavelength of the laser beam in the optical surface detection module is set to 532 nm, it is a green laser, the laser beam spot size is 10 μm, and the acquisition frequency is 50 frames / second. The energy of the X-rays in the CT detection module is set to 160 kV, and the X-ray emission frequency is 1 Hz. The pixel size of the flat panel detector 31 is set to 100 μm.

[0074] A surface defect is identified as a crack. The length of the surface crack's edge contour is 5 mm. An internal defect is identified as having two layers. The first layer has a thickness of 0.2 mm. The second layer has a thickness of 0.3 mm. The determination can be made by judging whether the surface crack and internal defect are located at the same or overlapping points, whether they are significantly different from their surroundings, and whether their grayscale values ​​are similar. For example, it can be determined that a surface crack in a carbon fiber composite component extends internally and connects to a single layer.

[0075] If a step-by-step detection method is used, obtaining the detection result takes 20 minutes. Using the multimodal imaging-based detection system of this application embodiment, the detection result is obtained in 15 minutes, improving the detection efficiency by 25%, and providing key correlation data for the safety assessment of carbon fiber composite components.

[0076] The processor may include a data fusion and analysis unit. This unit may include a data storage module, an image registration module, and a defect analysis module. The data storage module stores surface images of surface defects output by the optical surface inspection module and internal three-dimensional tomographic images output by the CT inspection module. The image registration module establishes a spatial coordinate correspondence between the surface image and the internal three-dimensional tomographic image based on displacement data from a high-precision bearing platform, thus achieving image registration. The defect analysis module identifies the location, size, and shape of surface defects using edge detection algorithms such as the Canny algorithm, identifies the location, volume, and type of internal defects using threshold segmentation algorithms, and analyzes the correlation between surface and internal defects based on the registered coordinate relationship, such as whether surface cracks extend into the interior.

[0077] In another embodiment, the non-destructive, non-contact testing process includes the following steps.

[0078] Step 1: Sample preprocessing and localization.

[0079] The object to be tested is placed on a high-precision carrier platform. The initial position of the object to be tested is calibrated by the displacement sensor of the carrier platform to determine the detection area. The synchronous control module presets the movement trajectory of the high-precision carrier platform (such as spiral scanning trajectory or linear scanning trajectory), the image acquisition frequency of the optical surface detection module (50 frames / second to 100 frames / second), and the X-ray emission frequency of the CT detection module (1 frame / second to 5 times / second) according to the size of the object to be tested and the detection requirements.

[0080] Step 2: Simultaneously initiate multimodal detection, i.e., simultaneously acquire surface images and X-ray detection images (internal three-dimensional tomographic images).

[0081] The synchronous control module sends control signals to drive the high-precision carrier platform to move along a preset trajectory; at the same time, it triggers the laser emitter of the optical surface detection module to emit lasers, and the CCD image sensor collects image signals of the surface of the object under test at a preset frequency and transmits them to the data fusion and analysis unit.

[0082] Meanwhile, the micro-focus X-ray source of the CT detection module emits X-rays at a preset frequency. After penetrating the object under test, the X-rays are received by the flat panel detector. The detector converts the X-ray signals into electrical signals and transmits them to the CT image reconstruction unit. The reconstruction unit generates internal three-dimensional tomographic images of the object under test in real time and transmits them to the data fusion and analysis unit of the processor.

[0083] Step 3: Data fusion and defect analysis (image registration).

[0084] The image registration module of the data fusion and analysis unit aligns the spatial coordinates of the surface image with the internal three-dimensional tomographic image based on the real-time displacement data of the high-precision bearing platform, ensuring that the surface information and internal information at the same location correspond one-to-one.

[0085] The defect analysis module processes the surface image: it removes noise by Gaussian filtering, extracts the edge contours of surface defects using the Canny algorithm, and calculates parameters such as the length, width, and depth of the defects.

[0086] The internal three-dimensional tomographic image is processed by using an adaptive threshold segmentation algorithm to distinguish between defective and normal regions, extracting the three-dimensional contour of the internal defect, and calculating parameters such as the defect volume and equivalent diameter.

[0087] Finally, based on the registered coordinate relationship, the defect analysis module determines whether there is a correlation between surface defects and internal defects, such as whether surface cracks are connected to internal cavities, and generates an inspection report that includes surface defects, internal defects, and their correlation.

[0088] Step 4: End of testing and sample removal.

[0089] After the test is completed, the synchronous control module controls the high-precision bearing platform to reset, removes the object to be tested, and the data storage module automatically saves all image data and analysis results during the test process for easy traceability and review.

[0090] The multimodal imaging-based detection system of this application provides real-time feedback on the position of the object under test, allowing for real-time viewing of surface and internal three-dimensional tomographic images of the object from any location. The object does not require two separate positioning operations, nor two separate measurement operations: one for surface defects and one for internal defects. System registration can be performed at the initial position of the object. The sample only needs to be fixed on the support platform, and can rotate while scanning along a preset trajectory. After the optical surface detection module and the computed tomography module simultaneously acquire data, a registered image is generated. The physical coordinate systems of the optical surface detection module and the computed tomography module are fixed.

[0091] The detection mode of the detection system based on multimodal imaging in this application embodiment is one-time positioning and synchronous detection, which enables surface defects and internal defects to be identified at the same time, reducing the detection time by more than 50% and meeting the needs of rapid detection of batch samples.

[0092] The detection system based on multimodal imaging in this application embodiment is based on a high-precision carrier platform and synchronous control, which enables the positioning accuracy of surface defects and internal defects to reach ±10μm and ±50μm respectively, and can achieve precise correlation.

[0093] The multimodal imaging-based detection system of this application uses one system to replace two sets of equipment, reducing costs and saving detection site resources. The multimodal imaging-based detection system of this application features fully automated control, reducing human error. Utilizing adjustable energy of the laser beam and X-rays, it can be adapted to different materials such as metals, plastics, and composite materials, and can be applied in fields such as semiconductors, aerospace, and automotive manufacturing.

[0094] The detection system based on multimodal imaging in this application utilizes multimodal imaging non-destructive and non-contact detection, which involves "single positioning, synchronous detection, and surface-internal defect correlation analysis," to improve detection efficiency and accuracy, reduce equipment investment costs, and solve the problems of low efficiency, poor accuracy, and high cost in existing step-by-step detection methods.

[0095] Those skilled in the art will understand that the features described in the various embodiments of this disclosure can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. In particular, the features described in the various embodiments of this disclosure can be combined and / or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0096] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. A detection system based on multimodal imaging, characterized in that, The detection system includes: A support platform is used to support the object to be tested and to obtain the real-time position of the object to be tested. An optical surface detection module is used to acquire surface images of the object under test at different locations; A computed tomography (CT) module is used to acquire internal three-dimensional tomographic images of the object under test at different locations; The synchronous control module is used to simultaneously drive the optical surface detection module and the computed tomography module to obtain the surface image and the internal three-dimensional tomographic image while driving the carrier platform to move the object under test according to a preset trajectory. Processor, used for: Based on the real-time position of the object under test, image registration is performed on the surface image and the internal three-dimensional tomographic image of the object under test at the real-time position to obtain the aligned spatial coordinates of the real-time position; and Based on the aligned spatial coordinates of the real-time location, the surface image and the internal three-dimensional tomographic image are fused to obtain the detection result of the object under test at the real-time location.

2. The detection system according to claim 1, characterized in that, The processor is also used for: Identify surface defects of the object under test based on the surface image; Identify internal defects of the object under test based on the internal three-dimensional tomographic image; Based on the alignment spatial coordinates of the real-time position, the correlation between the surface defect and the internal defect is determined, and the detection result of the object under test at the real-time position is obtained. The detection results include the size and structure of the surface defects and the internal defects, as well as the defect determination results.

3. The detection system according to claim 2, characterized in that, The processor is also used for: The surface defects are identified based on the surface image using an edge detection algorithm.

4. The detection system according to claim 3, characterized in that, The processor is also used for: Using an edge detection algorithm, the parameter information of the edge contour of the surface defect is determined based on the surface image.

5. The detection system according to claim 4, characterized in that, The processor is also used for: The internal defects are identified based on the internal three-dimensional tomographic image using a threshold segmentation algorithm.

6. The detection system according to claim 5, characterized in that, The processor is also used for: Based on the alignment space coordinates of the real-time position, and according to the parameter information of the edge contour of the surface defect and the parameter information of the three-dimensional contour of the internal defect, the correlation between the surface defect and the internal defect is determined, and the detection result of the object under test at the real-time position is obtained.

7. The detection system according to claim 1, characterized in that, The optical surface detection module includes: A light source used to produce light beams; A lens is used to collect the light signal generated by the object under test under the illumination of the light beam; An optical detector is used to image the light signal to obtain the surface image; The surface image includes a three-dimensional surface image; the light beam includes a laser beam or structured light.

8. The detection system according to claim 1, characterized in that, The computed tomography module includes: A radiation source used to generate X-rays; A flat panel detector is used to detect the X-ray signal generated by the object under test under the irradiation of the X-rays; The computed tomography image reconstruction unit is used to image the X signal to obtain the internal three-dimensional tomographic image.

9. The detection system according to claim 8, characterized in that, The computed tomography image reconstruction unit is used to image the X signal based on a filtered back projection algorithm to obtain the internal three-dimensional tomographic image.

10. The detection system according to any one of claims 1 to 9, characterized in that, The synchronization control module includes a programmable logic controller.

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