A multi-modality microwave non-destructive inspection imaging scanning system and method

Abstract

The application discloses a multi-system microwave nondestructive testing and imaging scanning system and method, relates to the technical field of nondestructive testing, and comprises a near-field probe, a single-port vector network analyzer, a plane scanning frame and an upper computer.

Description

Technical Field

[0001] This invention relates to the field of nondestructive testing technology, specifically to a multi-mode microwave nondestructive testing imaging scanning system and method. Background Technology

[0002] Microwave nondestructive testing (NDT) is a nondestructive testing technology that utilizes the interaction between microwaves and the material under test to achieve detection and evaluation. Compared with traditional acoustic, ultrasonic, and X-ray testing technologies, it has many advantages: wide testing coverage, adaptable to various test objects; wide operating frequency, able to match different test objects by adjusting the detection frequency, and strong characterization ability of material density, uniformity, and other parameters; high detection sensitivity, exhibiting strong reflective characteristics to metallic materials; strong penetration ability to non-metallic materials, with a small attenuation coefficient, effectively penetrating dirt, dust layers, dielectric coatings, etc.; adopting a non-contact testing method, eliminating the need for coupling agents, avoiding material contamination, and enabling rapid, continuous, and real-time monitoring; no ionizing radiation, low emission signal power, safe testing, and no electromagnetic damage to the irradiated object; strong environmental adaptability, minimally affected by temperature and air conditions, and applicable in environments with smoke, dust, chemical atmospheres, and high and low temperatures.

[0003] However, existing technologies generally employ dual-port vector network analyzers, or require the construction of complex reference branches including "T" tubes, directional couplers, and short-circuit pistons, or the addition of signal separation and phase adjustment modules to construct interference optical paths. This not only results in numerous system components and high integration difficulty, but also a cumbersome debugging process and significantly increases the production, construction, and maintenance costs of the equipment. In addition, the imaging processing of existing technologies mainly relies on single frequency domain information such as amplitude or phase, failing to fully exploit the rich information such as temporal and spatial coherence contained in broadband sweep data. This leads to limited sensitivity in detecting weak scattering defects and deep defects, making it difficult to identify minute anomalies inside materials. Furthermore, existing technologies have not constructed a collaborative analysis system with multiple imaging modes for different defect types and detection scenarios, resulting in poor adaptability to defects with different characteristics (such as point defects, deep layered defects, and surface microcracks).

[0004] Therefore, we propose an imaging scanning system and method with simple structure and high defect recognition accuracy. Summary of the Invention

[0005] The purpose of this invention is to provide a multi-mode microwave nondestructive testing imaging scanning system and method, which solves the problems of complex structure and low defect recognition in traditional methods.

[0006] This invention is achieved through the following technical solution:

[0007] A multi-mode microwave nondestructive testing imaging scanning system, comprising: A near-field probe is used to transmit microwave signals to the target under test and receive the reflected microwave signals formed by the target under test. The single-port vector network analyzer, as the detection host, has its test port connected to the near-field probe for receiving the reflected microwave signal returned by the near-field probe. It analyzes and calculates the reflected microwave signal within a preset frequency sweep range and demodulates the S11 complex parameters of the target under test. The S11 complex parameters contain amplitude information and phase information. A planar scanning frame is used to carry a near-field probe and moves along the X and Y axes in preset steps according to control commands to achieve point-by-point scanning of the detection plane of the target under test in two-dimensional space. Each stopping position on the movement trajectory of the planar scanning frame is a scanning point, and each scanning point corresponds to a unique two-dimensional space coordinate point. The host computer is connected to both the single-port vector network analyzer and the planar scanning frame. It sends movement control commands to the planar scanning frame and frequency sweep parameter configuration commands to the single-port vector network analyzer. Simultaneously, it receives the S11 complex parameters of each scan point within the frequency sweep range uploaded by the single-port vector network analyzer, constructing a graph containing spatial X-axis, spatial Y-axis, and frequency... The original three-dimensional data matrix of the axis Furthermore, the host computer integrates imaging analysis software.

[0008] Furthermore, the working distance of the near-field probe is less than one wavelength, which is used to acquire subwavelength resolution information of the target under test.

[0009] Furthermore, the imaging analysis software specifically includes: The amplitude imaging module is used to extract the reflection amplitude information of each scan point at a specific frequency from the original three-dimensional data matrix and generate an amplitude image. The phase imaging module is used to extract the reflection phase information of each scan point at a specific frequency from the original three-dimensional data matrix and generate a phase image; The synthetic aperture radar imaging module is used to treat each scanning point as a virtual array element, perform phase compensation and coherent accumulation processing on any point in the imaging area, realize lateral focusing enhancement and generate SAR image; The time-domain reflectometry (TDR) imaging module is used to transform the frequency domain measurement data in the original three-dimensional data matrix to the time domain, obtain the reflection distribution at different depths of the target under test, and generate TDR images.

[0010] Furthermore, the imaging process of the amplitude imaging module is as follows: selecting a single frequency point. Extract the reflection amplitude at this frequency from the original three-dimensional data matrix. The reflection amplitude is then normalized to map it to a grayscale image. .

[0011] Furthermore, the imaging process of the phase imaging module is as follows: selecting a single frequency point. Extract the reflection phase at this frequency from the original three-dimensional data matrix. The reflection phase is then unwrapped, and a phase image is generated from the unwrapped reflection phase. .

[0012] Furthermore, the imaging process of the synthetic aperture radar imaging module is as follows: Each scan point is treated as a virtual array element; For any point within the imaging region Using wavenumber and the distance from the antenna to the focal point Perform phase compensation; The responses of all scan points at that point are coherently summed to generate a SAR image. .

[0013] Furthermore, the formula for calculating the SAR image is as follows:

[0014] In the formula, For wave number, This is the distance from the antenna to the focal point. S11 is the complex parameter in the original three-dimensional data matrix, and For frequency variables, For frequency uptime, This is the lower limit of frequency. It is the imaginary part.

[0015] Furthermore, the imaging process of the time-domain reflectometry imaging module is as follows: For each spatial point in the original three-dimensional data matrix frequency domain data Perform an inverse Fourier transform to obtain the time-domain waveform. ; By selecting a specific time window By selecting the reflection signal within the target depth range, the peak amplitude or energy within that time window is extracted as the pixel value to generate a TDR image. .

[0016] Furthermore, the time window The method for determining it is as follows: Based on the average relative permittivity of the material being tested and target depth range Through the relation:

[0017] Establish a mapping between time and depth, where The speed of light in a vacuum. .

[0018] A multi-mode microwave nondestructive testing imaging scanning method includes the following steps: S1: Set up the system and configure the scanning parameters, including the scanning range, scanning step, and the sweep frequency range of the vector network analyzer; S2: The control plane scanning frame moves the near-field probe point by point, at each coordinate point... At this point, a single-port vector network analyzer is triggered to measure the reflection coefficient S11 parameter of the sample under test, obtaining the original three-dimensional data matrix. ; S3: Read the original three-dimensional data matrix and process it through amplitude imaging algorithm, phase imaging algorithm, synthetic aperture radar imaging algorithm and time domain reflectance imaging algorithm respectively to generate amplitude image, phase image, SAR image and TDR image respectively; S4: Compare and analyze the four generated images to comprehensively identify defects or abnormal areas in the tested sample.

[0019] The technical solution of the present invention has at least the following advantages and beneficial effects: This invention discloses a multi-mode microwave non-destructive testing imaging scanning system and method. It integrates a single-port vector network analyzer with a near-field probe, a planar scanning frame, and a host structure into an integrated testing system. This eliminates the need for complex additional hardware structures such as reference branches, dual-path receivers, and interference optical paths, resulting in a simpler hardware composition and more convenient system integration and debugging operations. This significantly reduces the production and manufacturing costs of the equipment and its subsequent maintenance costs.

[0020] In addition, the upper computer enables coordinated control of the scanning gantry movement and frequency scanning of the detection host, simultaneously completing point-by-point scanning in two-dimensional space and acquiring parameters across the entire frequency band. This makes the detection process more efficient and allows for the rapid construction of a complete data matrix containing both spatial and frequency dimensions, providing comprehensive and accurate raw data support for subsequent multi-mode imaging and improving the defect recognition rate of the imaging images.

[0021] In addition, the imaging analysis software can process the detection data from multiple dimensions such as amplitude, phase, lateral focus, and depth reflection and generate corresponding images, realizing multi-mode imaging analysis. It can fully explore the rich information in the detection data, adapt to the detection needs of different types and depths of defects, and greatly improve the defect detection rate and the adaptability of detection. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the structure of a multi-mode microwave non-destructive testing imaging scanning system according to the present invention; Figure 2 This is a schematic diagram of the amplitude imaging effect of the present invention at a frequency of 9080MHz; Figure 3 This is a schematic diagram of the phase imaging effect of the present invention at a frequency of 9800MHz; Figure 4 This is a schematic diagram of the SAR imaging effect of the present invention at a distance of 12mm; Figure 5 This is a schematic diagram of the TDR imaging effect of the present invention at 1.75ns. Figure 6 This is a schematic diagram of the process of a multi-mode microwave non-destructive testing imaging scanning method according to the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0024] Example 1 like Figure 1 The multi-mode microwave nondestructive testing imaging scanning system shown includes: The near-field probe, as the core transceiver of microwave signals between the system and the target under test, is specifically designed to transmit microwave signals directionally to the target under test and efficiently receive reflected microwave signals formed by internal defects, uneven dielectric constants, or interface reflections of the target under test.

[0025] The core design features are supplemented as follows: This near-field probe adopts a modular design, consisting of multiple probe elements, each with a different frequency range. This allows the near-field probe to select probe elements with different frequency ranges based on the material properties of the target object (such as relative permittivity and thickness). In this embodiment, multiple probe elements covering the 6GHz~20GHz frequency band are selected, adaptable to common detection objects such as non-metallic composite materials and ceramic coatings. Simultaneously, the working distance of the near-field probe is strictly controlled, set to 0.5mm~2mm in this embodiment, ensuring it is less than the wavelength of the medium at the corresponding frequency within the preset sweep frequency range—taking the mid-frequency of 13GHz within the sweep frequency range as an example, the corresponding medium wavelength is:

[0026] in The speed of light in a vacuum. The average relative permittivity of the material being tested is 4 in this embodiment. The working distance of the probe is much smaller than this wavelength, which allows it to directly couple the evanescent wave of the target surface, effectively breaking through the diffraction limit of far-field imaging. This enables the acquisition of subwavelength resolution information of the target, accurately capturing fine structural features and micro-defects with dimensions between 0.1mm and 1mm, solving the problem that traditional far-field imaging cannot identify micro-defects. In addition, the probe front end is equipped with an anti-interference shielding layer, which can effectively reduce the interference of external electromagnetic signals on the transmitted and received signals, improving the stability and accuracy of signal acquisition.

[0027] The single-port vector network analyzer, as the detection host, establishes a stable communication connection between its test port and the near-field probe through a low-loss coaxial cable. Its core function is to receive the reflected microwave signal returned by the near-field probe and perform professional analysis and calculation on the reflected microwave signal within a preset frequency sweep range, and finally demodulate the S11 complex parameters of the target under test. Specifically, the single-port vector network analyzer in this embodiment has a sweep frequency range of 6GHz to 20GHz, a sweep point count of 1024, and an intermediate frequency bandwidth of 1kHz to ensure the frequency resolution and signal stability of the sweep signal, enabling it to accurately capture subtle changes in reflected signals at different frequencies. The S11 complex parameter contains both amplitude and phase information. The amplitude information reflects the intensity of the reflected signal and is directly related to the dielectric constant, defect size, and depth of the target object. A larger amplitude value indicates a stronger reflected signal and more pronounced reflection characteristics of the corresponding defect or interface. The phase information reflects the phase shift of the microwave signal from emission to reflection and is highly sensitive to minute changes in the dielectric constant and defect depth of the tested material, making it a core parameter for identifying shallow, subtle defects.

[0028] Compared to traditional dual-port vector network analyzers, the single-port hardware architecture used in this embodiment eliminates the need for complex reference branches such as "T"-tubes, directional couplers, and short-circuit pistons. It also eliminates the need for additional signal separation and phase adjustment modules to construct the interference optical path, significantly simplifying the system hardware composition. This not only reduces manufacturing costs but also simplifies hardware debugging, eliminating the need for complex branch calibrations by specialized technicians; ordinary operators can complete the equipment debugging and operation. Furthermore, this vector network analyzer features real-time data upload capabilities, transmitting the S11 complex parameters of each scan point to the host computer in real time, ensuring the timeliness and completeness of data acquisition.

[0029] The planar scanning frame is used to fix and support the near-field probe. It adopts a high-precision ball screw transmission structure and can make precise translational movements along the X and Y axes according to the control commands issued by the host computer, so as to realize the two-dimensional spatial point-by-point scanning of the detection plane of the target under test.

[0030] In this embodiment, the effective scanning range of the planar scanning frame is set to 0mm~100mm (X-axis) × 0mm~100mm (Y-axis). The scanning step can be flexibly adjusted according to the detection accuracy requirements. It is set to 2mm for routine detection and can be adjusted to 0.5mm for high-precision detection. The positioning accuracy of the scanning frame can reach ±0.01mm, ensuring the positioning accuracy of each scanning point. Its positioning accuracy directly determines the spatial resolution of the subsequent imaging. The smaller the step and the higher the positioning accuracy, the denser the distribution of scanning points, the higher the spatial resolution of the imaging, and the clearer the fine contours of the defects can be presented.

[0031] The planar scanning frame moves along a line-by-line scanning pattern. Each stationary position on the moving trajectory is a scanning point, and each scanning point corresponds to a unique two-dimensional spatial coordinate point. The number and distribution of scanning points are determined by the scanning range and scanning step. For example, in this embodiment, a 2mm step and a 100mm×100mm scanning range are used, forming a total of 51×51 scanning points, fully covering the detection area of ​​the target. The scanning frame is also equipped with a probe attitude adjustment mechanism, which can adjust the tilt angle of the near-field probe according to the surface flatness of the target, ensuring that the probe remains parallel to the surface of the target and that the working distance of the probe at each scanning point is consistent, avoiding signal acquisition errors caused by distance deviation. In addition, the scanning frame has an emergency stop and reset function, which can quickly stop operation and reset to the initial position when the equipment malfunctions or after the detection is completed, improving the safety and convenience of equipment operation.

[0032] The host computer, an industrial-grade computer, establishes bidirectional communication connections with the single-port vector network analyzer and the planar scanning frame via Ethernet, serving as the main control unit of the system to realize the control, data processing, and imaging analysis of the entire detection process.

[0033] On the one hand, the host computer has built-in dedicated control software that can send movement control commands to the planar scanning frame to precisely control its movement trajectory, step distance, and dwell time. Simultaneously, it sends sweep frequency parameter configuration commands to the single-port vector network analyzer, including sweep frequency range, number of sweep points, intermediate frequency bandwidth, and measurement speed. All parameters can be flexibly set according to the size, material properties, and testing requirements of the target object, and support parameter saving and recall, facilitating subsequent testing of similar samples and improving testing efficiency. On the other hand, the host computer receives the S11 complex parameters of each scan point within the sweep frequency range uploaded by the single-port vector network analyzer in real time. High-speed data caching technology ensures stable storage and rapid retrieval of massive amounts of data. In this embodiment, 51×51 scan points are used, with each scan point including 1024 frequency points of S11 parameters. Based on this data, a spatial X-axis, spatial Y-axis, and frequency... The original three-dimensional data matrix of the axis Each element of this matrix corresponds to a specific scan point. Specific frequency The S11 complex parameters are the raw data foundation for all subsequent imaging processing. The matrix data is stored in binary format, facilitating rapid access and processing by subsequent algorithms. Furthermore, the host computer integrates imaging analysis software developed on the MATLAB platform, which boasts excellent compatibility and scalability. This software provides a stable platform for the operation of multi-mode imaging algorithms, supporting simultaneous and individual operation of four imaging modes, allowing for flexible selection based on detection requirements.

[0034] In addition, the imaging analysis software specifically includes: The amplitude imaging module is used to extract the reflection amplitude information of each scanning point at a specific frequency point from the original three-dimensional data matrix and generate an amplitude image. Its core function is to intuitively present the distribution characteristics of the strong reflection interface inside the target being measured. The imaging process of this module is as follows: First, based on the defect type and material properties of the target object, the optimal single frequency point is selected through broadband pre-scanning. In this embodiment, the polytetrafluoroethylene sheet (relative permittivity) is targeted. =2.1) detection, selected The frequency point falls within the preset sweep frequency range (6GHz~20GHz) of the single-port vector network analyzer, and the difference in S11 parameter amplitude between the defect area and the blank area is largest at this frequency, ensuring the highest contrast of the amplitude image; subsequently, the reflection amplitude of each scan point at this frequency is accurately extracted from the original three-dimensional data matrix. Since the reflection amplitude varies considerably between different scanning points (typically ranging from 0 to 1), the extracted reflection amplitude is normalized to facilitate intuitive image observation and defect identification. The amplitude value is mapped to a grayscale range of 0 to 255 to eliminate interference caused by differences in signal amplitude. Finally, the normalized reflection amplitude is mapped into a grayscale amplitude image. The intensity of grayscale values ​​corresponds to the strength of reflection amplitude. A higher grayscale value (closer to white) indicates a stronger reflection amplitude, corresponding to highly reflective interfaces within the target object (such as metal-nonmetal interfaces or material delamination). A lower grayscale value (closer to black) indicates a weaker reflection amplitude, corresponding to areas with uniform internal structure within the target object. Amplitude images can quickly identify the contours and locations of highly reflective defects (such as large cracks, delamination, and metallic impurities) within the target object. Specifically, for example... Figure 2 The diagram shown illustrates the amplitude imaging effect at a frequency of 9080MHz.

[0035] The phase imaging module extracts the reflection phase information of each scan point at a specific frequency from the original 3D data matrix to generate a phase image. Its core advantage is its high sensitivity to minute differences in dielectric constant and depth variations, enabling it to capture shallow, subtle defects that are difficult to detect in amplitude images. Further explanation is as follows: In the specific implementation process, a single frequency point is selected... Unlike the amplitude imaging module, this embodiment selects... At this frequency, the change in reflection phase is most pronounced and the phase curve is stable, which reduces the difficulty of phase unwrapping and improves the accuracy of phase imaging. Subsequently, the reflection phase of each scanning point at this frequency is extracted from the original three-dimensional data matrix. Because microwave signals undergo phase changes during propagation and reflection. The periodic changes cause the reflection phase to exist. Entanglement phenomenon (i.e., phase value exceeds) If the range of reflections is too wide (with repetitions or jumps), it will seriously affect the accuracy of the imaging and fail to truly reflect the defect characteristics of the target being measured. Therefore, it is necessary to unwrap the extracted reflection phase.

[0036] In this embodiment, the least squares method is used for phase unwrapping. By constructing a phase gradient matrix, the interference caused by phase entanglement is eliminated, and the unwrapped reflection phase data is mapped to a grayscale range of 0~255 to generate a phase image. In a phase image, the grayscale values ​​correspond to the magnitude of the phase; the greater the phase change, the more pronounced the difference in grayscale values. Because shallow, minute defects (such as surface microcracks or shallow debonding) can cause minute changes in the dielectric constant of the tested material, leading to significant changes in the reflection phase, these changes are difficult to capture in amplitude images. Therefore, phase images can accurately capture these shallow, minute defects, compensating for the limitations of amplitude imaging and improving the comprehensiveness of defect detection; specifically... Figure 3 The diagram shown illustrates the phase imaging effect at a frequency of 9800MHz.

[0037] The synthetic aperture radar imaging module treats each scanning point as a virtual array element, performs phase compensation and coherent accumulation processing on any point within the imaging area, achieves lateral focusing enhancement, and generates SAR images. Its core function is to improve lateral imaging resolution and clearly present the detailed features of point defects and edge defects. In the specific implementation process, each scanning point of the planar scanning frame is first regarded as a virtual array element, and a virtual synthetic aperture array is constructed. The number of virtual array elements is consistent with the number of scanning points (51×51 in this embodiment), and the distribution of virtual array elements is consistent with the spatial distribution of scanning points; for any focal point within the imaging area... First, calculate the distance from each virtual element (i.e., each scan point) to the focal point. ,distance The calculation formula is:

[0038] in The coordinates of the scan point, This is the working distance between the near-field probe and the surface of the target being measured (1 mm in this embodiment).

[0039] Subsequently, using wavenumber and distance Phase compensation is performed, where the wavenumber ( The operating frequency of the microwave signal is 13 GHz, which is the center frequency of the sweep frequency range in this embodiment. (The speed of light in a vacuum) The purpose of phase compensation is to eliminate the phase shift caused by the path difference between different virtual array elements and the focal point, and to ensure that the signals of all virtual array elements are superimposed in phase at the focal point.

[0040] Then, the responses of all scan points at the focal point (i.e., the corresponding S11 complex parameters) are coherently accumulated. This coherent accumulation process enhances the signal strength at the focal point, suppresses clutter interference, and ultimately generates a SAR image. The calculation formula is:

[0041] In the formula, For wave number, This is the distance from the antenna to the focal point. S11 is the complex parameter in the original three-dimensional data matrix, and For frequency variables, For frequency uptime, This is the lower limit of frequency. The imaginary part is used. In this embodiment, SAR imaging processing significantly improves the lateral resolution compared to amplitude imaging and phase imaging (0.5mm~1mm), thus clearly presenting the detailed features of point defects and edge defects, solving the problem of insufficient lateral resolution in traditional imaging modes. Furthermore, the SAR imaging module supports flexible selection of the focus area, allowing for localized focusing on suspected defect areas to further enhance the presentation of defect details; specifically, as shown... Figure 4 The image shown is a schematic diagram of the SAR imaging effect at a distance of 12mm.

[0042] The time-domain reflectometry (TDR) imaging module transforms the frequency-domain measurement data in the original three-dimensional data matrix to the time domain, acquires the reflectance distribution at different depths of the target under test, and generates TDR images. Its core advantage is its high longitudinal resolution, which can clearly identify the defect distribution at different depths of the target under test. The specific implementation process consists of three steps: The first step is to process each spatial point in the original 3D data matrix. frequency domain data Perform an inverse Fourier transform to convert the frequency domain data into the corresponding time domain waveform. —Due to the spectral leakage problem in the original frequency domain data, Hanning window weighting processing is required before inverse Fourier transform to reduce the interference caused by spectral leakage and ensure the accuracy of the time domain waveform. Each peak in the time domain waveform corresponds to the reflection signal of different interfaces or defects of the target under test. The time of peak appearance is related to the propagation time of the reflection signal. The longer the propagation time, the deeper the corresponding defect.

[0043] The second step is to determine the average relative permittivity of the material being tested. and target depth range Through the relation:

[0044] Establish a precise mapping between time and depth to determine the corresponding time window. —In this embodiment, the material being tested is a polytetrafluoroethylene sheet (PTFE sheet). The target depth ranges from 0.5mm to 5mm. Substituting these values ​​into the formula yields the following result. , Therefore, the time window is set to This time window allows for precise selection of reflected signals within the target depth range, effectively eliminating clutter interference such as surface reflection (time less than 5.4ns) and multiple reflections (time greater than 54ns), thereby improving the signal-to-noise ratio of the time domain signal.

[0045] The third step is to extract the peak amplitude or energy of the time-domain waveform within the time window as the pixel value of that scanning point to generate a TDR image. The grayscale value of a TDR image corresponds to the magnitude of the peak amplitude. The larger the peak amplitude, the higher the grayscale value, and the stronger the reflection intensity of the corresponding defect. The vertical axis of the TDR image corresponds to the defect depth, and the horizontal axis corresponds to the spatial coordinates of the scan point. The depth distribution of the defect can be intuitively presented through the TDR image. The vertical resolution can reach 0.05mm, which can clearly identify deep defects (such as layered defects with a depth of 3mm to 5mm), making up for the shortcomings of amplitude imaging and phase imaging in accurately identifying deep defects.

[0046] Furthermore, TDR imaging has two major advantages: ① High vertical resolution: Vertical resolution is determined by the sweep bandwidth B. This system supports a maximum sweep bandwidth of 20GHz. =2.1 materials (such as polytetrafluoroethylene). This is sufficient to distinguish defect layers of different depths.

[0047] ② Clutter Suppression: Through time-gating, clutter such as surface reflections and multiple reflections can be effectively eliminated, retaining only the target depth signal, significantly improving the signal-to-noise ratio; and specifically as follows... Figure 5 The image shown is a schematic diagram of the TDR imaging effect at 1.75ns.

[0048] These four modules operate independently yet collaboratively, processing the original 3D data matrix from different dimensions to generate corresponding detection images. It is important to note that... Figure 2 The yellow area represents the background, and the blue area represents the target being measured. Figure 2 The two blue areas within the yellow region represent the target object, while the rest is the background. Figures 4-5 The blue area represents the background, and the yellow area represents the target being measured.

[0049] Example 2 Based on the aforementioned multi-mode microwave nondestructive testing imaging scanning system, this embodiment also provides a multi-mode microwave nondestructive testing imaging scanning method, such as... Figure 6 As shown, the specific steps include supplementing detailed operational details, parameter setting basis, and exception handling methods to ensure the operability of the method: S1: Set up the system and configure the scanning parameters, including the scanning range, scanning step, and the sweep frequency range of the vector network analyzer; Specifically, the hardware connection and communication debugging of the near-field probe, single-port vector network analyzer, planar scanning frame, and host computer are completed according to the above system composition. During hardware connection, a low-loss coaxial cable is used between the near-field probe and the single-port vector network analyzer to ensure that the signal loss during transmission is less than 0.5dB. The host computer is connected to the vector network analyzer and the planar scanning frame via Ethernet, with a unified IP address range set to ensure smooth communication. During debugging, no-load debugging is performed first, i.e., without placing the target under test, the system is started to perform frequency sweeping and scanning to check the operating status of each component, ensuring that the planar scanning frame moves smoothly, the vector network analyzer acquires signals normally, and the host computer receives data stably. Then, load debugging is performed by placing a standard sample with known defects to verify the system's detection accuracy and imaging effect. If the imaging is blurry or the data is abnormal, the probe working distance, sweep frequency parameters, or scanning step are adjusted until the system operates normally. After debugging, the scanning parameters and frequency sweep parameters are set through the host computer. The scanning parameters include the scanning range and scanning step, while the frequency sweep parameters are the frequency sweep range, number of frequency sweep points, and intermediate frequency bandwidth of the single-port vector network analyzer. The parameter settings must strictly match the size, material properties, and detection requirements of the target being measured to avoid detection errors caused by parameter mismatch.

[0050] S2: Control the planar scanning frame to move the near-field probe point by point. The host computer sends a movement control command to the planar scanning frame to control it to move the near-field probe along the X-axis and Y-axis point by point to the scanning point (xi, yi) according to the preset steps, and accurately locate at each scanning point. The positioning dwell time is set to 10ms to ensure that the vector network analyzer has enough time to complete the signal acquisition and analysis of the scanning point. At each coordinate point At the target location, the host computer triggers a single-port vector network analyzer via Ethernet. The vector network analyzer emits microwave signals according to preset sweep parameters, which are directed onto the target by a near-field probe. The near-field probe receives the reflected microwave signals from the target and transmits them back to the vector network analyzer. The vector network analyzer performs amplitude and phase analysis and calculation on the reflected microwave signals, demodulating the S11 complex parameters of the scan point across the entire sweep frequency range. The measurement time for the S11 parameters at each frequency point is set to 5ms to ensure measurement accuracy. If the S11 parameter acquisition at a certain scan point fails (e.g., abnormal signal amplitude or phase change), the system will automatically reacquire the parameters at that scan point. If three consecutive acquisitions fail, the host computer will issue an alarm. The operator can check the probe working distance, cable connection, or the position of the target, and continue testing after troubleshooting. After all scan points have been tested, the S11 complex parameters of all scan points are uploaded to the host computer in real time via Ethernet. The host computer uses a high-speed data processing algorithm to construct a graph containing spatial X-axis, spatial Y-axis, and frequency parameters. The original three-dimensional data matrix of the axis The data is validated, and abnormal data is removed to ensure its integrity and accuracy.

[0051] S3: Read the original three-dimensional data matrix and process it using amplitude imaging algorithm, phase imaging algorithm, synthetic aperture radar imaging algorithm and time domain reflectance imaging algorithm respectively. The host computer calls the imaging analysis software to read the original three-dimensional data matrix constructed in step S2. First, the data is preprocessed (including noise reduction and normalization) to remove abnormal data caused by external interference and improve imaging quality. Subsequently, the amplitude imaging module, phase imaging module, synthetic aperture radar imaging module, and time domain reflectance imaging module are activated respectively. Each module processes the raw data according to its corresponding algorithm logic, generating amplitude images, phase images, SAR images, and TDR images. The four modules can run simultaneously, with a processing time of approximately 30 seconds, or they can run individually, allowing for flexible selection based on detection requirements.

[0052] In addition, the generated images are stored in BMP format and support operations such as image zooming in and out and grayscale adjustment, making it easy for operators to observe defect details. At the same time, the imaging software automatically records the imaging parameters of each image (such as frequency points, scanning steps, phase unwrapping algorithms, etc.), which facilitates the traceability and comparison of subsequent detection results.

[0053] S4: Compare and analyze the four generated images to comprehensively identify defects or abnormal areas in the tested sample.

[0054] Specifically, operators will conduct a collaborative comparative analysis of the generated amplitude images, phase images, SAR images, and TDR images, combining the characteristics of different imaging modes to extract defect information of the target under test: amplitude images are used to identify the outline and location of large defects with strong reflections (such as delamination and metallic impurities); phase images are used to identify the distribution of shallow and minute defects (such as surface microcracks and shallow debonding); SAR images are used to accurately present the lateral outline and detailed features of defects, and determine the size and shape of defects; TDR images are used to clearly identify the depth distribution of defects and determine the depth location of defects.

[0055] By cross-validating and supplementing multiple images, detection errors caused by a single imaging mode can be effectively eliminated, enabling precise localization, morphological recognition, and depth determination of defects or abnormal areas in the tested sample. For example, if a microcrack with a depth of 2mm and a width of 0.3mm exists in a tested sample, the amplitude image shows a blurred defect outline, the phase image clearly shows the distribution range of the defect, the SAR image accurately presents the width and shape of the defect, and the TDR image clearly shows the depth of the defect as 2mm. Through comparative analysis of these four images, the various characteristics of the defect can be comprehensively and accurately grasped. After the inspection is completed, the host computer can automatically generate an inspection report, including information such as the four imaging images, defect location, defect size, and inspection parameters, facilitating the archiving of inspection results and subsequent analysis.

[0056] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A multi-mode microwave non-destructive testing imaging scanning system, characterized in that, include: A near-field probe is used to transmit microwave signals to the target under test and receive the reflected microwave signals formed by the target under test. The single-port vector network analyzer, as the detection host, has its test port connected to the near-field probe for receiving the reflected microwave signal returned by the near-field probe. It analyzes and calculates the reflected microwave signal within a preset frequency sweep range and demodulates the S11 complex parameters of the target under test. The S11 complex parameters contain amplitude information and phase information. A planar scanning frame is used to carry a near-field probe and moves along the X and Y axes in preset steps according to control commands to achieve point-by-point scanning of the detection plane of the target under test in two-dimensional space. Each stopping position on the movement trajectory of the planar scanning frame is a scanning point, and each scanning point corresponds to a unique two-dimensional space coordinate point. The host computer is connected to both the single-port vector network analyzer and the planar scanning frame. It sends movement control commands to the planar scanning frame and frequency sweep parameter configuration commands to the single-port vector network analyzer. Simultaneously, it receives the S11 complex parameters of each scan point within the frequency sweep range uploaded by the single-port vector network analyzer, constructing a graph containing spatial X-axis, spatial Y-axis, and frequency... The original three-dimensional data matrix of the axis Furthermore, the host computer integrates imaging analysis software; The imaging analysis software specifically includes: The amplitude imaging module is used to extract the reflection amplitude information of each scan point at a specific frequency from the original three-dimensional data matrix and generate an amplitude image. The phase imaging module is used to extract the reflection phase information of each scan point at a specific frequency from the original three-dimensional data matrix and generate a phase image; The synthetic aperture radar imaging module is used to treat each scanning point as a virtual array element, perform phase compensation and coherent accumulation processing on any point in the imaging area, realize lateral focusing enhancement and generate SAR image; The time-domain reflectometry (TDR) imaging module is used to transform the frequency domain measurement data in the original three-dimensional data matrix to the time domain, obtain the reflection distribution at different depths of the target under test, and generate TDR images.

2. The multi-mode microwave non-destructive testing imaging scanning system according to claim 1, characterized in that: The near-field probe operates at a distance less than one wavelength and is used to acquire subwavelength resolution information of the target being measured.

3. The multi-mode microwave nondestructive testing imaging scanning system according to claim 1, characterized in that: The imaging process of the amplitude imaging module is as follows: selecting a single frequency point. Extract the reflection amplitude at this frequency from the original three-dimensional data matrix. The reflection amplitude is then normalized to map it to a grayscale image. .

4. The multi-mode microwave nondestructive testing imaging scanning system according to claim 1, characterized in that: The imaging process of the phase imaging module is as follows: selecting a single frequency point. Extract the reflection phase at this frequency from the original three-dimensional data matrix. The reflection phase is then unwrapped, and a phase image is generated from the unwrapped reflection phase. .

5. The multi-mode microwave nondestructive testing imaging scanning system according to claim 1, characterized in that: The imaging process of the synthetic aperture radar imaging module is as follows: Each scan point is treated as a virtual array element; For any point within the imaging region Using wavenumber and the distance from the antenna to the focal point Perform phase compensation; The responses of all scan points at that point are coherently summed to generate a SAR image. .

6. The multi-mode microwave non-destructive testing imaging scanning system according to claim 5, characterized in that: The formula for calculating the SAR image is: In the formula, For wave number, The distance from the antenna to the focal point. S11 is the complex parameter in the original three-dimensional data matrix, and For frequency variables, For frequency uptime, This is the lower limit of frequency. It is the imaginary part.

7. The multi-mode microwave non-destructive testing imaging scanning system according to claim 1, characterized in that: The imaging process of the time-domain reflectometry imaging module is as follows: For each spatial point in the original three-dimensional data matrix frequency domain data Perform an inverse Fourier transform to obtain the time-domain waveform. ; By selecting a specific time window By selecting the reflection signal within the target depth range, the peak amplitude or energy within that time window is extracted as the pixel value to generate a TDR image. .

8. The multi-mode microwave nondestructive testing imaging scanning system according to claim 7, characterized in that: The time window The method for determining it is as follows: Based on the average relative permittivity of the material being tested and target depth range Through the relation: Establish a mapping between time and depth, where The speed of light in a vacuum. .

9. A multi-mode microwave nondestructive testing imaging scanning method, applied to the system described in any one of claims 1-8, characterized in that, Includes the following steps: S1: Set up the system and configure the scanning parameters, including the scanning range, scanning step, and the sweep frequency range of the vector network analyzer; S2: The control plane scanning frame moves the near-field probe point by point, at each coordinate point... At this point, a single-port vector network analyzer is triggered to measure the reflection coefficient S11 parameter of the sample under test, obtaining the original three-dimensional data matrix. ; S3: Read the original three-dimensional data matrix and process it through amplitude imaging algorithm, phase imaging algorithm, synthetic aperture radar imaging algorithm and time domain reflectance imaging algorithm respectively to generate amplitude image, phase image, SAR image and TDR image respectively; S4: Compare and analyze the four generated images to comprehensively identify defects or abnormal areas in the tested sample.

Images