Portable imaging system and method of non-destructive testing

Abstract

A portable imaging system includes an image acquisition module, an imaging module, and a data enhancement module. The image acquisition module is configured to perform A-scan on a target object to generate a plurality of echo signals. The imaging module is configured to obtain A-scan data, B-scan two-dimensional cross-sectional image, C-scan planar distribution image, and point cloud image. The data enhancement module is configured to enhance the plurality of echo signals. A non-destructive testing method is also disclosed.

Description

Technical Field

[0001] This invention relates to an imaging system and a detection method, and more particularly to a portable imaging system based on terahertz, millimeter wave and optical dynamic adjustment of radar transmission power and a method for non-destructive testing using the portable imaging system. Background Technology

[0002] Terahertz imaging technology is a detection technique that uses electromagnetic waves with frequencies ranging from 0.1 THz to 10 THz for imaging. It combines electrical and optical characteristics. Terahertz imaging does not require direct contact and does not cause structural damage to the material under test, thus possessing unique advantages in materials inspection and imaging.

[0003] Terahertz waves have the ability to penetrate non-metallic materials, such as plastics, fibers, ceramics, and composite materials, and can be absorbed and reflected by different materials. Furthermore, through reflection imaging and semi-transparent imaging, terahertz imaging technology can detect the internal structure of materials to identify defects such as cracks and damage, and can also analyze material properties and structure.

[0004] In industries such as rail, aviation, and infrastructure (e.g., cracks in bridges and tunnels), the testing and analysis of materials and structures are particularly important. For example, fatigue cracks in aircraft materials can directly affect the structural integrity and strength of an aircraft. Therefore, each aircraft needs to be inspected every 750 flight hours on average. If cracks in an aircraft are not detected early, they could endanger flight safety.

[0005] Currently, the industry's demand for testing technology mainly focuses on high efficiency, high precision, and ease of operation. Requirements include that the testing system should be able to detect a variety of defects, such as delamination, delamination, dents, cracks, holes, water seepage, melting, and lightning strikes.

[0006] However, current terahertz imaging systems are large, and many of the objects to be inspected are also large components, making inspection difficult and cumbersome. Furthermore, terahertz technology may not be perfect in some detection situations; for example, terahertz technology is more suitable for detecting dents on thin structures, resulting in insufficient detection completeness.

[0007] As can be seen from the above, conventional imaging detection systems need improvement. Summary of the Invention

[0008] The main objective of this invention is to provide a portable imaging system to improve the speed, accuracy, and convenience of structural inspection.

[0009] In one embodiment of the present invention, a portable imaging system is provided, comprising: an image acquisition module including a radar element for performing an A-scan on a target to generate multiple echo signals and obtain multiple A-scan data of the target, wherein the radar element is selected from a group consisting of a terahertz radar element, an Asia-Pacific Hertz radar element, and a millimeter-wave radar element; and an imaging module electrically connected to the image acquisition module for arranging the multiple A-scan data into a cross section to form a B-scan two-dimensional cross-sectional image; and performing multiple B-scans on the B-scan two-dimensional cross-sectional image to obtain... The system comprises: a plurality of B-scan data; combining the plurality of B-scan data into a C-scan planar distribution image; fusing the B-scan two-dimensional cross-sectional image with the C-scan planar distribution image into a point cloud; and a data enhancement module electrically connected to the image acquisition module, for performing the following steps to enhance the plurality of echo signals: introducing sparsity into an echo data model based on the plurality of echo signals to identify sparse features; calculating a sparsity regularization term; adding a total variation constraint; calculating multiple constraints to optimize the echo data model; and iteratively solving using the split Bregman algorithm to generate a super-resolution image.

[0010] In one embodiment of the present invention, the data enhancement module further performs the steps of denoising and regularizing the echo data model.

[0011] In one embodiment of the present invention, an artificial intelligence module is further included, electrically connected to the imaging module, for analyzing the point cloud image.

[0012] In one embodiment of the present invention, a defect marking module is further included, electrically connected to the imaging module, for marking a defect of the target object on the point cloud map to present the location, depth and size of the defect on the target object.

[0013] In one embodiment of the present invention, a material property establishment module is further included, which performs the following steps to establish information on the properties of a single material: setting frequency-modulated continuous wave radar parameters; setting the sweep range and frequency step; using the radar element to perform multiple sweep measurements on a reference material of a single material; collecting echo signals from the reference material to obtain multiple data; and calculating key parameters for each of the multiple data to obtain reference data for the reference material, wherein the key parameters are selected from a group consisting of loss rate, reflection coefficient, real and imaginary parts of dielectric constant, and generating corresponding spectral response curves.

[0014] In one embodiment of the present invention, a material property analysis module is further included, which performs the following steps to analyze the properties of a composite material: setting frequency-modulated continuous wave radar parameters; setting the sweep range and frequency step; performing multiple sweep measurements on a composite material; collecting echo signals from the composite material to obtain multiple raw data of the composite material; preprocessing the multiple data of the composite material, including separating the echo signals of multiple layers of the composite material and estimating the number and thickness of the layers; calculating key parameters of each layer of the composite material to obtain a calculation result, wherein the key parameters are selected from a group consisting of loss rate, reflection coefficient, real and imaginary parts of dielectric constant, and generating corresponding spectral response curves; comparing the calculation result with reference data of a reference material to determine the material properties and thickness of each layer of the composite material; correcting the material properties and the thickness to obtain corrected data; reconstructing the echo signal of the composite material through the corrected data to obtain reconstructed data; and comparing the reconstructed data with the multiple raw data to determine the properties of the composite material.

[0015] In one embodiment of the present invention, a display module is further included, comprising a text display area and an image display area. The text display area is used to display information of the target object to a user in text form, and the image display area is used to display information of the target object to the user in image form, wherein the text display area and the image display area synchronously and correspondingly display specific information of the target object.

[0016] In one embodiment of the present invention, a comparison module is further included, which is used to correspond the point cloud image of the target object to the material properties pre-stored in a database in order to identify the material of the target object.

[0017] In one embodiment of the present invention, the material property is the conductivity of the material.

[0018] To achieve the above objectives, in another embodiment of the present invention, a method for non-destructive testing using the portable imaging system described above is provided, comprising the steps of: performing an A-scan on a target object using an image acquisition module, including performing multi-point scanning on the target object to generate multiple echo signals, thereby obtaining multiple A-scan data of the target object, wherein the radar element is selected from a group consisting of a terahertz radar element, an Asia-Pacific hertz radar element, and a millimeter-wave radar element; arranging the multiple A-scan data into a cross-section using an imaging module to form a B-scan two-dimensional cross-sectional image; and using the imaging module on the B-scan two-dimensional cross-section... Multiple B-scans are performed on a planar image to obtain a plurality of B-scan data; the plurality of B-scan data are combined into a C-scan planar distribution image using an imaging module; the B-scan two-dimensional cross-sectional image and the C-scan planar distribution image are fused into a point cloud map using the imaging module; a data enhancement module is used to enhance the plurality of echo signals, including the following steps: introducing sparsity into an echo data model based on the plurality of echo signals to identify sparse features; calculating a sparsity regularization term; adding a total variation constraint; calculating multiple constraints to optimize the echo data model; and using the split Bregman algorithm to iteratively solve the problem to generate a super-resolution image.

[0019] In one embodiment of the invention, performing an A-scan on the target includes using a radar element to perform a multi-point scan of the target along a line to obtain the plurality of A-scan data.

[0020] In one embodiment of the present invention, the data enhancement module is used to enhance the plurality of echo signals, and the method further includes the steps of denoising and regularizing the echo data model.

[0021] In one embodiment of the present invention, a step is further included: using an artificial intelligence module to analyze the point cloud map.

[0022] In one embodiment of the present invention, a step is further included: using a defect marking module to mark a defect of the target object on the point cloud map to present specific information about the defect on the target object.

[0023] In one embodiment of the present invention, a step is further included: using a comparison module to correspond the point cloud image of the target object to the material properties pre-stored in a database, so as to identify the material of the target object.

[0024] In one embodiment of the present invention, the material property is the conductivity coefficient of the material.

[0025] In one embodiment of the present invention, a step is further included: using a material property establishment module to establish information on the properties of a single material by performing the following steps: setting frequency-modulated continuous wave radar parameters; setting the sweep range and frequency step; using the radar element to perform multiple sweep measurements on a reference material of a single material; collecting echo signals from the reference material to obtain multiple data; and calculating key parameters for each of the multiple data to obtain reference data for the reference material, wherein the key parameters are selected from a group consisting of loss rate, reflection coefficient, real and imaginary parts of dielectric constant, and generating corresponding spectral response curves.

[0026] In one embodiment of the present invention, a step is further included: using a material property analysis module to analyze the properties of a composite material by performing the following steps: setting frequency-modulated continuous wave radar parameters; setting the sweep range and frequency step; performing multiple sweep measurements on the composite material; collecting echo signals from the composite material to obtain multiple raw data of the composite material; preprocessing the multiple data of the composite material, including separating the echo signals of multiple layers of the composite material and estimating the number and thickness of the layers; calculating key parameters of each layer of the composite material to obtain a calculation result, wherein the key parameters are selected from a group consisting of loss rate, reflection coefficient, real and imaginary parts of dielectric constant and generating corresponding spectral response curves; comparing the calculation result with reference data of a reference material to determine the material properties and thickness of each layer of the composite material; correcting the material properties and the thickness to obtain corrected data; reconstructing the echo signal of the composite material through the corrected data to obtain reconstructed data; and comparing the reconstructed data with the multiple raw data to determine the properties of the composite material.

[0027] The beneficial effects of this invention are as follows: The portable imaging system of this invention, through its portable structure, allows for greater flexibility in the time and location of its application. Furthermore, this portable imaging system can provide a comprehensive detection view by progressively analyzing the raw signal (A-scan), progressing to a cross-sectional view (B-scan), and finally to a frontal image (C-scan), thus facilitating rapid location of problem areas. In addition, by adjusting the weights of sparsity constraints and total variation constraints, the system improves resolution while better recovering the target's contour information. This includes not only improving resolution under noisy conditions but also effectively preserving the geometric contours of important scenes, making it suitable for various radar forward-looking imaging applications. Attached Figure Description

[0028] Figure 1 A block diagram of a portable imaging system according to one embodiment of the present invention; Figure 2This is a schematic diagram of the display interface of a portable imaging system according to an embodiment of the present invention; Figure 3 A flowchart illustrating a method for nondestructive testing using a portable imaging system according to an embodiment of the present invention; and Figure 4 This is a flowchart illustrating a method for enhancing echo signals using a portable imaging system according to an embodiment of the present invention.

[0029] Figure label: 100: Portable imaging system; 1: Image capturing module; 2: Imaging module; 3: Data Augmentation Module; 4: Artificial Intelligence Module; 5: Defect marking module; 6: Compare modules; 7: Material properties module; 8: Material property analysis module; 9: Display module; 91: Text display area; 92: Image display area; S10 to S50: Steps of the method for performing non-destructive testing using the portable imaging system of the present invention; S111 to S115: Steps of a method for enhancing multiple echo signals using a data enhancement module. Detailed Implementation

[0030] The technical solutions of the embodiments of the present invention will now be clearly and completely described with reference to the accompanying drawings. Furthermore, to better illustrate the present invention, numerous specific details are provided in the following detailed embodiments. Those skilled in the art should understand that the present invention can be practiced without certain specific details.

[0031] Unless otherwise stated herein, the singular forms “a” and “the” used in the specification and the appended claims include the numerals. Unless otherwise stated herein, the term “or” used in the specification and the appended claims includes the meaning of “and / or”.

[0032] Reference Figure 1 According to one embodiment of the present invention, a portable imaging system 100 includes: an image capturing module 1, an imaging module 2 and a data enhancement module 3.

[0033] The image acquisition module 1 includes a radar element 11 for performing an A-scan on a target object to generate multiple echo signals, thereby obtaining multiple A-scan data of the target object. The radar element 11 is selected from a group consisting of a terahertz radar element, an Asia-Pacific hertz radar element, and a millimeter-wave radar element, and can generate a carrier wave of 30 to 300 GHz. Preferably, the image acquisition module 1 may also include a camera (e.g., a complementary metal-oxide-semiconductor, CMOS sensor). Specifically, the A-scan is the most basic form of data, providing signal amplitude and depth information at a single point, suitable for quickly measuring material thickness, locating defects at a specific point, and making preliminary judgments about the basic internal conditions of materials. Furthermore, due to its small data volume, the A-scan is suitable for real-time detection and rapid feedback.

[0034] Imaging module 2 is electrically connected to image acquisition module 1 to arrange multiple A-scan data into a cross-section to form a B-scan two-dimensional cross-sectional image. Further, imaging module 2 performs multiple B-scans on the B-scan two-dimensional cross-sectional image to obtain a plurality of B-scan data. Specifically, a B-scan images a cross-section along a scanning path, displaying the depth distribution and approximate shape of defects. This two-dimensional cross-sectional image more intuitively reflects the internal structural features of the inspected object, helping to assess the size and depth distribution of defects, and is suitable for internal inspection scenarios requiring higher resolution. Imaging module 2 also combines the plurality of B-scan data into a C-scan planar distribution image, and fuses the B-scan two-dimensional cross-sectional image and the C-scan planar distribution image into a point cloud map. Specifically, the C-scan provides a defect distribution image across the entire plane, a comprehensive scan of the inspected object, suitable for environments requiring large-scale inspection and quality control, such as locating large-area defects, analyzing material homogeneity, and comprehensively assessing the internal structural condition of the inspected object. The C-scan provides a global view of the inspection data for more in-depth analysis.

[0035] Data augmentation module 3 is electrically connected to image acquisition module 1 and performs the following steps to augment multiple echo signals: introducing sparsity into an echo data model based on multiple echo signals to identify key sparse features of the echo data in the echo data model, removing redundant signals, and enhancing the edge and structural information of the target object to improve the resolution of forward-looking imaging; calculating a sparse regularization term to suppress noise and make the echo data more stable; adding a total variation (TV) constraint to smooth the contours of the target object, making the edge information clearer and avoiding excessive smoothing that leads to loss of detail; calculating multiple constraints to optimize the echo data model, such as applying additional mathematical constraints, including edge preservation, noise suppression, etc., to improve image quality; and using the Split Bregman algorithm for iterative solution to improve image detail while preserving edge features, thereby generating a super-resolution image. Preferably, data augmentation module 3 further performs the following steps: denoising and regularization of the echo data model. Denoising suppresses noise in the echo data model to ensure image clarity and accuracy, while regularization uses mathematical constraints to ensure data stability and consistency. Selectively, after the super-resolution image is generated, the contour and resolution of the super-resolution image are evaluated. If the standards are not met, the sparsity and TV weights are adjusted, and the previous steps are repeated to calculate multiple constraints and iteratively solve using the split Bregman algorithm. This not only improves the resolution but also effectively recovers the contour information of the target object.

[0036] The portable imaging system 100 may also include an artificial intelligence module 4, a defect marking module 5, a comparison module 6, a material property establishment module 7, a material property analysis module 8, and a display module 9.

[0037] The AI ​​module 4 is electrically connected to the imaging module 2 for analyzing point cloud images to quickly identify internal defects, cracks, and abnormalities such as moisture distribution within the target object. Preferably, the AI ​​module 4 can automatically classify defect types, such as cracks and pores, and provide a quantitative assessment of defect severity. The AI ​​module 4 can also perform statistical analysis and generate reports based on the detection results.

[0038] The defect marking module 5 is electrically connected to the imaging module 2 and is used to mark a defect of the target object on a point cloud map to show the location, depth, and size of the defect on the target object. For example, the defect marking module 5 can overlay defect points with color markings on the C-scan and display them to the user through the display module 9 to show information such as the location, size, and type of the defect. The defect marking module 5 can also use 3D modeling technology to reconstruct the target object and dynamically display information such as the depth and structure of the defect of the target object through the display module 9.

[0039] The comparison module 6 is electrically connected to the imaging module 2 to map the point cloud image of the target object to the built-in, pre-stored material properties in a database, thereby automatically identifying the material and number of layers of the target object. Optionally, the material property can be the conductivity coefficient of the material. The conductivity coefficient of each material can serve as a key parameter for distinguishing materials, effectively identifying the differences between metals (e.g., silver, copper, aluminum) and non-metals (e.g., glass, rubber, quartz, etc.), which helps in analyzing composite materials, detecting internal anomalies, or evaluating material properties.

[0040] The material property establishment module 7 is electrically connected to the image acquisition module 1, and is used to perform the following steps to establish the material properties information of a single material: setting frequency-modulated continuous wave (FMCW) radar parameters; setting the sweep range and frequency step, where the sweep range is the sweep time; performing multiple sweep measurements on a reference material of a single material using radar elements; collecting echo signals from the reference material to obtain multiple data points; and calculating key parameters for each data point to obtain reference data for the reference material, where the key parameters are selected from a group consisting of loss rate, reflection coefficient, the real and imaginary parts of dielectric constant, and the corresponding spectral response curves. Preferably, to improve data reliability, the results of multiple measurements are averaged and integrated to remove the influence of random noise. In addition, the standard deviation of the data is calculated to further confirm the stability of the measurement. After processing, all analysis results can be stored in a database to form reference data for the reference material, which can be used for subsequent analysis or matching reference.

[0041] The material property analysis module 8 is electrically connected to the material property establishment module 7, and is used to perform the following steps to analyze the properties of a composite material: setting frequency-modulated continuous wave radar parameters; setting the sweep range and frequency step; performing multiple sweep measurements on a composite material; collecting echo signals from the composite material to obtain multiple raw data of the composite material; preprocessing the multiple data of the composite material, including separating the echo signals of multiple layers of the composite material and estimating the number and thickness of the layers; calculating the key parameters of each layer of the composite material to obtain a calculation result, wherein the key parameters are selected from a group consisting of loss rate, reflection coefficient, real and imaginary parts of dielectric constant, and generating the corresponding spectral response curve; comparing the calculation results (i.e., the parameters of each layer) with the reference data of the reference material to determine the material properties and thickness of each layer of the composite material; correcting the material properties and thickness to obtain corrected data; reconstructing the echo signal of the composite material through the corrected data to obtain reconstructed data; comparing the reconstructed data with multiple raw data to determine the properties of the composite material. Additionally, if the reconstructed data does not meet the requirements after comparison with multiple original data sets, the parameters must be readjusted and the entire process repeated. Disagreements may include the following situations: Layer count or thickness misjudgment: If the layers inside the composite material are not accurately identified during echo signal separation, it may lead to incorrect layer count estimation or thickness calculation deviation. For example, there should be three layers of material, but the system only identifies two layers, or incorrectly identifies extra layers.

[0042] Key parameter calculation deviations: When calculating loss rate, reflection coefficient, and dielectric constant (real and imaginary parts), the parameters may differ significantly from the reference material data due to the influence of the measurement environment or data errors. For example, a certain layer of material should have a specific dielectric constant, but the calculation results show a significant deviation, indicating that there may be an error in the measurement or modeling process.

[0043] Spectral response curve mismatch: The spectral response curve reflects the electromagnetic properties of a material. If it deviates significantly from the data of a reference material, it indicates an error in material property identification or inaccurate test data. For example, it should conform to the typical response of a certain composite material, but the result deviates too much, indicating that the material identification may be incorrect.

[0044] Excessive echo signal reconstruction error: The reconstructed echo signal from the calibrated data should closely match the original measurement data. If a large error exists between the two, it indicates that the analytical model may not have correctly fitted the material's characteristics. For example, the original data may show obvious reflection peaks, but the reconstructed data may fail to reproduce these features.

[0045] Measurement errors or environmental interference: If external environmental factors (e.g., temperature changes, humidity, electromagnetic interference) affect the echo signal during frequency sweep measurements, it may cause data instability, resulting in analysis results that do not match the actual material properties.

[0046] Display module 9 is electrically connected to imaging module 2 and material property analysis module 8, and includes a text display area 91 and an image display area 92. The text display area 91 is used to display information about the properties of the target object or composite material to a user in text format, and the image display area 92 is used to display information about the properties of the target object or composite material to the user in image format. The text display area 91 and the image display area 92 synchronously and correspondingly display specific information about the properties of the target object or composite material. (Refer to...) Figure 2 Specifically, the display module includes a display interface for presenting information to the user, which can be divided into a text display area 91 and an image display area 92. For example, a composite material (i.e., Figure 2 Information about component A in the image display area 91, such as its name, material, size, and quantity, can be displayed as text in the text display area 91, while the image display area 92 can present component A as an image. Preferably, a specific piece of information in the text display area 91 can be simultaneously linked to a corresponding area in the image display area 92 upon selection. For example, the corresponding area can be automatically highlighted, and the corresponding information can be displayed near it. For instance, if one component of component A, carbon fiber, is selected in the text display area 91, the carbon fiber area in the image display area 92 will be highlighted, and the annotation "carbon fiber" will be displayed above the area. This enhances operational accuracy and efficiency, making it particularly suitable for mechanical maintenance and inspection scenarios, significantly reducing human error and improving inspection efficiency.

[0047] Optionally, as mentioned above, display module 9 can also be used to present various information to the user, such as the signal map of scan A, the echo map of the scan section of scan B, the horizontal profile of scan C, 3D point cloud model, and inspection report.

[0048] Optionally, display module 9 may also include a function selection and control area and a data analysis area (not shown). The function selection and control area provides users with operational options such as switching analysis modes, adjusting power, controlling accessories, and measurement functions, thus providing system flexibility and high operability. The function selection and control area also supports intelligent inspection and manual calibration, improving inspection accuracy. Depth and thermal image range settings allow for customized data ranges based on inspection needs. The data analysis area supports multi-mode data visualization, including A-scan, B-scan, and C-scan, presenting inspection results from different dimensions. The data analysis area also provides 3D point cloud modeling capabilities, reconstructing the three-dimensional structure of the target object, and incorporates data analysis and conversion, as well as AI object recognition technology, to quickly identify defects and generate accurate inspection reports.

[0049] Reference Figure 3 According to another embodiment of the present invention, a method for nondestructive testing using a portable imaging system as described above includes the steps of: S10: Using an image capturing module to perform an A-scan on a target, including multi-point scanning of the target to generate multiple echo signals, thereby obtaining multiple A-scan data of the target, wherein the radar element is selected from a group consisting of a terahertz radar element, an Asia-Pacific hertz radar element and a millimeter-wave radar element.

[0050] S20: An imaging module is used to arrange multiple A-scan data into a cross-section to form a B-scan two-dimensional cross-sectional image. Specifically, performing an A-scan on a target involves using radar elements to scan the target at multiple points along a line to obtain multiple A-scan data.

[0051] S30: Use the imaging module to perform multiple B-scans on the B-scan two-dimensional cross-sectional image to obtain multiple B-scan data; S40: Use the imaging module to combine multiple B-scan data into a C-scan planar distribution image; S50: Use the imaging module to fuse the B-scan two-dimensional cross-sectional image and the C-scan planar distribution image into a point cloud map.

[0052] The method also includes step S11: enhancing multiple echo signal systems using a data enhancement module, referring to... Figure 4 The detailed steps are as follows: S111: Introduce sparsity to a single-echo data model based on multiple echo signals to identify sparse features; S112: Calculate the sparse regularization term; S113: Add total variation constraint; S114: Compute multiple constraints to optimize the echo data model; and S115: Use the split Bregman algorithm iteratively to generate a super-resolution image.

[0053] Preferably, using a data enhancement module to enhance multiple echo signals also includes the steps of denoising and regularizing the echo data model.

[0054] Optionally, the method also includes a step of: using a material property building module to establish information on the properties of a single material by performing the following steps: setting frequency-modulated continuous wave radar parameters; setting the sweep range and frequency step; performing multiple sweep measurements on a reference material of a single material using radar elements; collecting echo signals from the reference material to obtain multiple data points; and calculating key parameters for each of the multiple data points to obtain reference data for the reference material, wherein the key parameters are selected from a group consisting of loss rate, reflection coefficient, real and imaginary parts of dielectric constant, and generating corresponding spectral response curves.

[0055] Optionally, the method further includes a step of using a material property analysis module to analyze the properties of a composite material by performing the following steps: setting frequency-modulated continuous wave radar parameters; setting the sweep range and frequency step; performing multiple sweep measurements on the composite material; collecting echo signals from the composite material to obtain multiple raw data of the composite material; preprocessing the multiple data of the composite material, including separating the echo signals of multiple layers of the composite material and estimating the number and thickness of the layers; calculating key parameters for each layer of the composite material to obtain a calculation result, wherein the key parameters are selected from a group consisting of loss rate, reflection coefficient, real and imaginary parts of dielectric constant, and generating corresponding spectral response curves; comparing the calculation result with reference data of a reference material to determine the material properties and thickness of each layer of the composite material; correcting the material properties and thickness to obtain corrected data; reconstructing the echo signal of the composite material from the corrected data to obtain reconstructed data; and comparing the reconstructed data with multiple raw data to determine the properties of the composite material.

[0056] Although the present invention has been disclosed with reference to preferred embodiments, it is not intended to limit the invention. Any person skilled in the art may make various modifications and alterations without departing from the spirit and scope of the invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A portable imaging system, characterized in that, Include: An image acquisition module includes a radar element for performing an A-scan on a target to generate multiple echo signals and obtain multiple A-scan data of the target, wherein the radar element is selected from a group consisting of a terahertz radar element, an Asia-Pacific hertz radar element and a millimeter-wave radar element. An imaging module, electrically connected to the image acquisition module, is used to arrange multiple A-scan data into a cross section to form a B-scan two-dimensional cross-sectional image; perform multiple B-scans on the B-scan two-dimensional cross-sectional image to obtain a plurality of B-scan data; combine the plurality of B-scan data into a C-scan planar distribution image; and fuse the B-scan two-dimensional cross-sectional image and the C-scan planar distribution image into a point cloud map; and A data enhancement module, electrically connected to the image acquisition module, is used to perform the following steps to enhance the multiple echo signals: Sparsity is introduced into a single-echo data model based on these multiple echo signals to identify sparse features; Calculate the sparse regularization term; Add total variation constraints; Calculate multiple constraints to optimize the echo data model; and The split Bregman algorithm is used iteratively to generate a super-resolution image.

2. The portable imaging system as described in claim 1, characterized in that, The data enhancement module also performs the following steps: denoising and regularizing the echo data model.

3. The portable imaging system as described in claim 1, characterized in that, It also includes an artificial intelligence module electrically connected to the imaging module for analyzing the point cloud image.

4. The portable imaging system as described in claim 1, characterized in that, It also includes a defect marking module electrically connected to the imaging module, used to mark a defect of the target object on the point cloud map to show the location, depth and size of the defect on the target object.

5. The portable imaging system as described in claim 1, characterized in that, It also includes a material property establishment module, electrically connected to the image acquisition module, for performing the following steps to establish material property information for a single material: Set the parameters for the frequency modulated continuous wave radar; Set the sweep range and frequency step; The radar element is used to perform multiple frequency sweep measurements on a reference material of a single material; Collect echo signals from the reference material to obtain multiple data points; as well as The key parameters of each of the complex data points are calculated to obtain the reference data of the reference material, wherein the key parameters are selected from a group consisting of loss rate, reflection coefficient, real and imaginary parts of dielectric constant, and the corresponding spectral response curves.

6. The portable imaging system as described in claim 5, characterized in that, It also includes a material property analysis module, electrically connected to the material property establishment module, used to perform the following steps to analyze the properties of a composite material: Set the parameters for the frequency modulated continuous wave radar; Set the sweep range and frequency step; A composite material is subjected to multiple frequency sweep measurements; Collect echo signals from the composite material to obtain multiple raw data of the composite material; The multiple data points of the composite material are preprocessed, including the echo signals of the multiple layers of the composite material and the estimation of the number and thickness of the layers; The key parameters of each layer of the composite material are calculated to obtain a calculation result, wherein the key parameters are selected from a group consisting of loss rate, reflection coefficient, real and imaginary parts of dielectric constant, and the corresponding spectral response curves. The calculation results are compared with the baseline data of the reference material to determine a material property and a thickness of each layer of the composite material; Correct the material properties and the thickness to obtain correction data; The echo signal of the composite material is reconstructed using the correction data to obtain reconstructed data; and The reconstructed data is compared with the plurality of original data to determine the properties of the composite material.

7. The portable imaging system as described in claim 6, characterized in that, It also includes a display module electrically connected to the material property analysis module, including a text display area and an image display area. The text display area is used to display information about the properties of the composite material to a user in text form, and the image display area is used to display information about the properties of the composite material to the user in image form. The text display area and the image display area synchronously and correspondingly display specific information about the properties of the composite material.

8. The portable imaging system as described in claim 1, characterized in that, It also includes a display module electrically connected to the imaging module, comprising a text display area and an image display area. The text display area is used to display information about the target object to a user in text form, and the image display area is used to display information about the target object to the user in image form, wherein the text display area and the image display area synchronously and correspondingly display specific information about the target object.

9. The portable imaging system as described in claim 1, characterized in that, It also includes a comparison module electrically connected to the imaging module, used to match the point cloud image of the target object with the material properties pre-stored in a database in order to identify the material of the target object.

10. The portable imaging system as described in claim 6, characterized in that, This material property refers to its electrical conductivity.

11. A method for nondestructive testing using the portable imaging system as described in claim 1, characterized in that, Includes the following steps: An A-scan is performed on a target using an image capture module, including multi-point scanning of the target to generate multiple echo signals, thereby obtaining multiple A-scan data of the target, wherein the radar element is selected from a group consisting of a terahertz radar element, an Asia-Pacific hertz radar element and a millimeter-wave radar element. An imaging module is used to arrange the multiple A-scan data into a cross section to form a B-scan two-dimensional cross-sectional image; Using this imaging module, multiple B-scans are performed on the B-scan two-dimensional cross-sectional image to obtain multiple B-scan data; Using this imaging module, the multiple B-scan data are combined into a C-scan planar distribution image; Using this imaging module, the two-dimensional cross-sectional image of the B scan and the planar distribution image of the C scan are fused into a point cloud map; The process involves using a data enhancement module to enhance the multiple echo signals, including the following steps: Sparsity is introduced into a single-echo data model based on these multiple echo signals to identify sparse features; Calculate the sparse regularization term; Add total variation constraints; Calculate multiple constraints to optimize the echo data model; and The split Bregman algorithm is used iteratively to generate a super-resolution image.

12. The method as described in claim 10, characterized in that, Performing an A-scan on a target involves using a radar element to scan the target at multiple points along a line to obtain multiple A-scan data.

13. The method as described in claim 10, characterized in that, Using the data enhancement module to enhance the multiple echo signals also includes the steps of denoising and regularizing the echo data model.

14. The method as described in claim 10, characterized in that, It also includes a step: using an artificial intelligence module to analyze the point cloud map.

15. The method as described in claim 10, characterized in that, It also includes a step: using a defect marking module to mark a defect of the target object on the point cloud map to present specific information about the defect on the target object.

16. The method as described in claim 10, characterized in that, It also includes a step of using a comparison module to match the point cloud image of the target object with the material properties stored in a database in order to identify the material of the target object.

17. The method as described in claim 16, characterized in that, This material property refers to its electrical conductivity.

18. The method as described in claim 10, characterized in that, It also includes a step: using a material property building module to build information on the material properties of a single material by performing the following steps: Set the parameters for the frequency modulated continuous wave radar; Set the sweep range and frequency step; The radar element is used to perform multiple frequency sweep measurements on a reference material of a single material; Collect echo signals from the reference material to obtain multiple data points; as well as The key parameters of each of the complex data points are calculated to obtain the reference data of the reference material, wherein the key parameters are selected from a group consisting of loss rate, reflection coefficient, real and imaginary parts of dielectric constant, and the corresponding spectral response curves.

19. The method as described in claim 10, characterized in that, It also includes a step: using a material property analysis module to analyze the properties of a composite material by performing the following steps: Set the parameters for the frequency modulated continuous wave radar; Set the sweep range and frequency step; A composite material is subjected to multiple frequency sweep measurements; Collect echo signals from the composite material to obtain multiple raw data of the composite material; The multiple data points of the composite material are preprocessed, including the echo signals of the multiple layers of the composite material and the estimation of the number and thickness of the layers; The key parameters of each layer of the composite material are calculated to obtain a calculation result, wherein the key parameters are selected from a group consisting of loss rate, reflection coefficient, real and imaginary parts of dielectric constant, and the corresponding spectral response curves. The calculation results are compared with the baseline data of the reference material to determine the material properties and thickness of each layer of the composite material; Correct the material properties and the thickness to obtain correction data; The echo signal of the composite material is reconstructed using the correction data to obtain reconstructed data; and The reconstructed data is compared with the plurality of original data to determine the properties of the composite material.

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