A flow-heat-phase spatiotemporal synchronization visual measurement analysis method, system and device

Abstract

This invention proposes a spatiotemporally synchronized visualization measurement and analysis method, system, and device for flow-heat-phase. The method includes: acquiring a multimodal sensing dataset and performing spatial calibration and alignment; processing the aligned high-speed visual image to obtain a binary phase diagram, combining temporal information to identify and segment it, dividing and merging the liquid phase region, gas phase region, contact line region, and rewetting region to obtain a partitioned result map; identifying and fusing the infrared temperature image, binary phase diagram, and partitioned result map to output a spatiotemporally synchronized visualization measurement phase diagram for flow-heat-phase. By acquiring data to form a dataset and calibrating and aligning it, this invention achieves, for the first time, a precise spatiotemporally synchronized correlation of gas-liquid distribution, temperature field, and heat flow information; combining binary phase diagram generation, intelligent segmentation, and multimodal data fusion technology, it overcomes the limitations of traditional methods and can quantitatively analyze key physical processes under the interaction of multiple bubbles on complex surfaces; the final output phase diagram can reveal the coupling mechanism between the temperature field of the micro-region of the heated surface and the dynamic behavior of bubbles.

Description

Technical Field

[0001] This invention relates to the field of testing technology for heat dissipation devices for high heat flux density electronic devices, and in particular to a method, system, and device for spatiotemporal synchronous visualization measurement and analysis of flow-heat-phase. Background Technology

[0002] Boiling heat transfer, with its extremely high heat transfer efficiency, has been widely used in important engineering fields such as immersion cooling of electronic devices, nuclear reactors, chemical processes, and aerospace thermal management. Its performance is generally characterized by two key parameters: the nucleation boiling heat transfer coefficient and the critical heat flux density. However, the boiling process is an extremely complex process involving multiphase, multiscale, and multi-physics coupling. Simultaneously, phenomena such as bubble nucleation, growth, merging, and detachment occur on the heated surface, accompanied by intense heat and mass transfer processes. For a long time, the lack of experimental methods capable of simultaneously analyzing temperature fields and interface dynamics on spatiotemporal scales has resulted in insufficient understanding of the microscopic mechanisms of boiling heat transfer. This has led existing boiling heat transfer and critical heat flux models to heavily rely on empirical correlations or be limited to idealized single-bubble assumptions, making it difficult to accurately predict the performance of real complex surfaces (such as micro / nanostructured surfaces) under the interaction of multiple bubbles. This, in turn, restricts the rational design and optimization of advanced heat dissipation technologies.

[0003] Traditional research methods typically separate bubble behavior visualization from macroscopic heat transfer measurement. This makes it difficult to accurately correlate the generation, growth, and detachment processes of specific bubbles with the instantaneous changes in the temperature field of micro-regions on the heated surface in both time and space. For example, infrared thermal imaging technology can achieve non-contact, full-field temperature measurement and obtain local heat flux density through inversion. However, its measurement results are affected by the substrate's thermal diffusion effect, resulting in blurred gas-liquid interface signals. Relying solely on heat flux thresholds or gradients to delineate heat transfer regions has limitations such as strong subjectivity and poor accuracy. On the other hand, high-speed visualization techniques based on principles such as total internal reflection can capture surface gas-liquid distribution and contact line morphology with high contrast and accuracy, but they cannot directly provide temperature or heat flux information. This data asynchrony problem limits the quantitative analysis of key physical processes such as local dry spot formation, gas-liquid interface heat transfer, and surface structure enhancement mechanisms. Summary of the Invention

[0004] This invention aims to at least solve the technical problems existing in the prior art, and in particular, it innovatively proposes a method, system and device for synchronous visualization measurement and analysis of flow-heat-phase spatiotemporal.

[0005] To achieve the above-mentioned objectives of this invention, this invention provides a method for simultaneous spatial-temporal visualization measurement and analysis of flow-heat-phase, the method comprising: S1. Simultaneously acquire high-speed visual images, infrared temperature images, pressure data, and temperature data to form a multimodal sensing dataset; S2. Perform spatial calibration and alignment on the multimodal sensing dataset; S3. Obtain a binary phase diagram reflecting the gas-liquid distribution from the aligned high-speed visual image using image processing methods; S4. Based on the binary phase diagram and combined with time-domain information, the high-speed visual image of the boiling heat transfer process is identified and segmented into liquid phase region, gas phase region, contact line region and rewetting region and merged to obtain the partition result map. S5. Recognize the infrared temperature image, binary phase diagram and partition result diagram, and fuse the recognition results to output a flow-thermal-phase spatiotemporal synchronous visualization measurement phase diagram.

[0006] In another aspect, the present invention provides a flow-thermal-phase spatiotemporal synchronous visualization measurement and analysis system, wherein the system is used to execute a flow-thermal-phase spatiotemporal synchronous visualization measurement and analysis method; the system includes: The acquisition module is used to simultaneously acquire high-speed visual images, infrared temperature images, pressure data, and temperature data to form a multimodal sensing dataset. The pulse generation module, connected to the acquisition module, is used to send pulse signals to the acquisition module; The image alignment module, connected to the acquisition module, is used for spatial calibration and alignment of the multimodal sensing dataset; The phase diagram generation module is connected to the image alignment module. It uses image processing methods to obtain a binary phase diagram reflecting the gas-liquid distribution from the aligned high-speed visual image. The region segmentation module, connected to the phase diagram generation module, is used to identify and segment high-speed visual images of the boiling heat transfer process based on the binary phase diagram and combined with time-domain information. The segments are divided into liquid phase region, gas phase region, contact line region and rewetting region and then merged to obtain a partitioned result map. The data fusion and output module, connected to the region segmentation module, is used to identify infrared temperature images, binary phase diagrams, and partitioning result diagrams, and to fuse the identification results to output a flow-thermal-phase spatiotemporal synchronous visualization measurement phase diagram.

[0007] In another aspect, the present invention provides a flow-thermal-phase spatiotemporal synchronous visualization measurement and analysis device, the device being used to perform a flow-thermal-phase spatiotemporal synchronous visualization measurement and analysis method; the device includes: The pool boiling experimental chamber is used to contain the experimental working fluid; The substrate integrated module is mounted on the pool boiling test chamber and is transparent to light; The lighting subsystem is used to provide a light source to the substrate integrated module; A high-speed infrared camera is used to acquire infrared temperature images of the substrate integrated module. The first high-speed visible light camera 2 is used to acquire high-speed visual images of the substrate integrated module using a reflector; The second high-speed visible light camera is used to acquire high-speed visual images from the side window of the pool boiling experimental chamber. The second pulse generator is connected to the high-speed infrared camera, the first high-speed visible light camera 2, and the second high-speed visible light camera. The first pulse generator is connected to the high-speed infrared camera, the first high-speed visible light camera 2, the second pulse generator, and the second high-speed visible light camera. The DAQ data acquisition unit is connected to the first pulse generator; Temperature sensor is installed on the pool boiling experimental chamber; A pressure sensor is installed on the pool boiling test chamber.

[0008] The beneficial effects of this invention are as follows: By simultaneously acquiring high-speed visual images, infrared temperature images, and pressure and temperature data to form a multimodal sensing dataset, and through spatial calibration and alignment (such as pixel-level alignment based on the visual transformation matrix), it achieves for the first time a precise spatiotemporal correlation of gas-liquid distribution, temperature field, and heat flux information. Combined with binary phase diagram generation, time-domain information-driven intelligent segmentation of liquid / gas / contact line / rewetting zone, and multimodal data fusion technology, it can quantitatively analyze key physical processes such as local dry spot formation, gas-liquid interface heat transfer, and surface structure enhancement mechanisms under the interaction of multiple bubbles on complex surfaces (such as micro-nano structures), breaking through the limitations of traditional methods that rely on empirical correlations or single-bubble assumptions. The final output of the flow-heat-phase spatiotemporally synchronized visualized measurement phase diagram can intuitively reveal the coupling mechanism between the instantaneous change of temperature field in the micro-region of the heated surface and the dynamic behavior of bubbles, providing high-precision, multi-dimensional experimental support for the rational design and optimization of advanced heat dissipation technologies in fields such as immersion cooling of electronic devices, nuclear reactors, and aerospace thermal management, significantly improving the prediction accuracy of boiling heat transfer and critical heat flux density and its engineering application value.

[0009] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0010] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a flowchart of a spatiotemporal synchronous visualization measurement and analysis method for flow-heat-phase according to Embodiment 1 of the present invention; Figure 2This is a partial structural schematic diagram of a flow-heat-phase spatiotemporal synchronous visualization measurement and analysis device according to Embodiment 3 of the present invention; Figure 3 This is a schematic diagram of all camera signals in Embodiment 3 of the present invention; Figure 4 This is a schematic diagram of the transparent simulated heat source and optical substrate in Embodiment 3 of the present invention; Figure 5 This is a schematic diagram of the integrated module of the pool boiling experimental chamber substrate in Embodiment 3 of the present invention; Figure 6 This is a schematic diagram of the pool boiling experimental chamber in Embodiment 3 of the present invention.

[0011] In the figure: 1. High-speed infrared camera, 2. First high-speed visible light camera, 3. Second high-speed visible light camera, 4. Second pulse generator, 5. First pulse generator, 6. DAQ data acquisition instrument, 7. Illumination subsystem, 8. Flow control valve, 9. Pressure sensor, 10. Temperature sensor, 11. Substrate integrated module, 12. Reflector, 13. Conductive lead, 14. Spring pin, 15. Gold layer, 16. Conductive oxide film, 17. Sapphire optical substrate, 18. O-ring, 19. Pool boiling experimental chamber. Detailed Implementation

[0012] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0013] Example 1 like Figure 1 As shown, a spatiotemporal synchronous visualization measurement and analysis method for flow-heat-phase is presented, the method comprising: S1. Simultaneously acquire high-speed visual images, infrared temperature images, pressure data, and temperature data to form a multimodal sensing dataset; In step S1, it should be noted that the synchronous acquisition achieves precise alignment of the time dimension through a pulse triggering mechanism. Specifically, the first pulse generator 5 and the second pulse generator 4 work together to output a synchronous trigger signal, driving the high-speed infrared camera 1, the first high-speed visible light camera (surface reflection view), and the second high-speed visible light camera 3 (side view) to synchronously acquire image data at a preset frame rate, ensuring that the timestamp error of all visual and infrared images is controlled within the microsecond level. At the same time, the DAQ data acquisition instrument 6 receives the synchronous signal from the pulse generator and synchronously acquires the working fluid pressure data monitored by the pressure sensor 9 and the working fluid body temperature data recorded by the temperature sensor 10, forming a multi-dimensional dataset that includes gas-liquid interface dynamics, temperature field, and macroscopic environmental parameters.

[0014] S2. Perform spatial calibration and alignment on the multimodal sensing dataset; S3. Obtain a binary phase diagram reflecting the gas-liquid distribution from the aligned high-speed visual image using image processing methods; S4. Based on the binary phase diagram and combined with time-domain information, the high-speed visual image of the boiling heat transfer process is identified and segmented into liquid phase region, gas phase region, contact line region and rewetting region and merged to obtain the partition result map. S5. Recognize the infrared temperature image, binary phase diagram and partition result diagram, and fuse the recognition results to output a flow-thermal-phase spatiotemporal synchronous visualization measurement phase diagram.

[0015] In step S5, it should be noted that the identification process includes: (1) Heat flux density inversion: The infrared temperature image is used as the boundary condition and input into the solver; a three-dimensional unsteady heat conduction simulation is performed on the substrate (such as sapphire); the local heat flux density is output into the substrate; combined with the Joule heat input, the heat flux density on the fluid side is calculated to obtain the fluid heat flux density map.

[0016] (2) Regional heat flux density statistics Using the partitioned result map as a mask, the heat flux density values ​​corresponding to the liquid phase region, gas phase region, contact line region, and rewetting region are extracted respectively. Perform pixel-level statistical analysis on each region to calculate its mean heat flux density, variance, probability density distribution, etc.

[0017] Multimodal information fusion coding: Construct a four-channel fused image: Channel 1: Temperature Field Channel 2: Heat flux density field Channel 3: Phase Label Channel 4: Area Labels Fusion encoding: Visualize the fused image by encoding it, for example: using background grayscale to represent temperature; overlaying pseudocolor to represent heat flux density; and using contour lines or transparency to distinguish phase and region types.

[0018] Each fused image frame is aligned with the original acquisition timestamp; dynamic videos (.avi / .mp4) or static image sequences (.tiff / .png) are generated. The accuracy of heat flux inversion is verified by comparing the consistency between the partitioned heat flux density and the overall heat flux density and the known single-phase heat transfer coefficient; the partitioned results are manually verified or compared with existing literature data.

[0020] As an optional embodiment of the present invention, optionally, the spatial calibration and alignment of the multimodal sensing dataset in step S2 includes: S201. Spatial calibration of the multimodal sensing dataset, and acquisition of calibration images of visible light and infrared markers from the multimodal sensing dataset; In step S201, it should be noted that the spatial calibration uses a customized high-precision checkerboard calibration plate. Its surface is printed with a circular array of marker points (marker point diameter 2mm, array spacing 5mm, printed with black ink to ensure strong contrast under visible light, and high infrared emissivity material to ensure clear identification in infrared images). The calibration plate is precisely fixed on the measurement area surface of the substrate integrated module so that it completely covers the overlapping field of view of the high-speed visual image and the infrared temperature image. The first pulse generator outputs a synchronous trigger signal to simultaneously start the high-speed visible light camera and the high-speed infrared camera, and acquires at least 15 sets of calibration images in different poses (translation and rotation angles within ±15°), covering the edge and center areas of the field of view, to ensure the robustness and accuracy of subsequent coordinate extraction and transformation matrix calculation.

[0021] S202. Extract the pixel coordinates of the marker points in the high-speed visual image and the infrared temperature image based on the calibration image; In step S202, it should be noted that for high-speed visual images, the findCirclesGrid function in the OpenCV library is used to detect the circular marker array on the calibration board. Combined with the sub-pixel corner detection algorithm (cornerSubPix), the coordinates of the detected markers are refined and optimized to control the positioning accuracy of the pixel coordinates within 0.1 pixels. For infrared temperature images, the contrast between the markers and the background area is first enhanced by the adaptive threshold segmentation algorithm (adaptiveThreshold). Then, the outline rectangle contour of the markers is extracted using the contour detection function (findContours). The geometric center of the contour is calculated as the pixel coordinates of the markers. At the same time, combined with the temperature gradient features of the infrared image, high-temperature pseudo-markers in the non-calibration board area are filtered out to ensure that the extracted marker coordinates are real and valid.

[0022] S203. Calculate the view transformation matrix from marker points in the high-speed visual image to marker points in the infrared temperature image based on pixel coordinates; use the warpPerspective function to calculate the view transformation matrix.

[0023] The calculation process of the view transformation matrix is ​​as follows: First, the pixel coordinates of the marked points in the high-speed visual image and the infrared temperature image are organized into two corresponding point sets. Then, the `findHomography` function in the OpenCV library is used to match these two point sets, and the RANSAC algorithm is used to eliminate possible mismatched points to ensure the robustness of the transformation matrix. Finally, based on the matching results, the `warpPerspective` function is called to generate the view transformation matrix, and it is applied to the resampling operation of the high-speed visual image, thereby achieving accurate spatial alignment between the high-speed visual image and the infrared temperature image. This method can effectively eliminate image distortion caused by differences in camera viewpoints, ensuring the accuracy of subsequent analysis.

[0024] S204. Resample the high-speed visual image based on the view transformation matrix to make the high-speed visual image and the infrared temperature image spatially aligned.

[0025] In step S204, it should be noted that the resampling operation employs a bilinear interpolation algorithm to ensure that the high-speed visual image maintains high resolution and continuity of grayscale information during spatial transformation. The aligned image is then subjected to quality assessment, the alignment error is calculated, and it is verified whether it meets a preset threshold (e.g., pixel-level error less than 0.5 pixels). If it does not meet the threshold, the calibration parameters are readjusted or the calculation process of the view transformation matrix is ​​optimized. Furthermore, after spatial alignment, the pressure and temperature data in the multimodal sensing dataset are further timestamped to ensure the synchronization of all data in the spatiotemporal dimensions.

[0026] As an optional embodiment of the present invention, optionally, obtaining a binary phase diagram reflecting the gas-liquid distribution from the aligned high-speed visual image in step S3 through an image processing method includes: S301. Calculate the time-averaged background image of a high-speed visual image sequence; In step S301, it should be noted that the time-averaged intensity (or minimum value) at each pixel location in the entire high-speed visual image sequence is calculated to construct a background image to eliminate interference from static areas. Specifically, by statistically analyzing the intensity values ​​of corresponding pixels in each frame, the average or minimum value in the time dimension is selected as the pixel value of the background image, thereby effectively separating the dynamic gas-liquid interface information.

[0027] S302. Subtract the time-averaged background image from each frame of high-speed visual image to obtain a high-speed visual image without background. S303. Use an automatic thresholding algorithm to binarize the high-speed visual image without background, distinguish between the gas phase and the liquid phase, and obtain the binarized high-speed visual image. In step S303, it should be noted that the automatic thresholding algorithm uses the Otsu method, which determines the optimal segmentation threshold by maximizing the inter-class variance, thereby achieving accurate differentiation between the gas and liquid phases. This method can dynamically adjust the threshold based on the image's grayscale histogram, adapting to changes in illumination and contrast under different experimental conditions. In the binarized high-speed visual image, the gas phase region is marked in white, and the liquid phase region is marked in black, forming a clear gas-liquid distribution boundary.

[0028] S304. The binarized high-speed visual image is downsampled to the resolution of the infrared temperature image, while retaining grayscale information, to obtain a binary phase diagram reflecting the gas-liquid distribution.

[0029] In step S304, it should be noted that the downsampling operation employs a bilinear interpolation algorithm to ensure that the binarized high-speed visual image maintains boundary sharpness and grayscale accuracy during resolution conversion. The downsampled image is quality-assessed, its spatial alignment error with the infrared temperature image is calculated, and it is verified whether it meets a preset threshold (e.g., pixel-level error less than 0.5 pixels). If not, the downsampling parameters are readjusted or the interpolation algorithm is optimized. Furthermore, after resolution matching is completed, the binary phase diagram undergoes morphological processing, such as erosion and dilation operations, to remove noise and enhance the continuity of gas-liquid distribution boundaries.

[0030] As an optional embodiment of the present invention, optionally, in step S4, based on the binary phase diagram and combined with time-domain information, the high-speed visual image of the boiling heat transfer process is identified and segmented into a liquid phase region, a gas phase region, a contact line region, and a rewetting region, and then merged to obtain a partitioned result image including: S401. Perform OpenCV image processing on the binary phase diagram to obtain the gas phase region; In step S401, it should be noted that the connected component analysis function (connectedComponentsWithStats) from the OpenCV library is used to process the binary phase diagram, extracting all connected white regions as gas phase regions. By calculating the area, perimeter, centroid, and other geometric features of each connected region, gas phase regions that meet the criteria are further filtered and marked to exclude noise interference and small areas as gas phase regions.

[0031] S402. Perform a difference operation on the binary phase diagram to obtain the contact line region; In step S402, it should be noted that the difference operation extracts the dynamically changing regions of the gas-liquid interface by comparing the time series of the binary phase diagram frame by frame. Specifically, pixel-level differences are calculated between the current frame and the previous frame's binary phase diagram, and the regions where grayscale values ​​change are marked as contact line areas. To improve recognition accuracy, morphological operations can be combined with post-processing of the difference results, such as filling small holes through closing operations and using edge detection algorithms (such as the Canny operator) to further enhance the boundary clarity of the contact line. In addition, to eliminate false detections caused by noise or minor fluctuations, an area threshold can be set to filter out excessively small connected regions, ensuring accurate segmentation of the contact line area.

[0032] S403. Based on the binary phase diagram of the current time and the previous time, the pixels that were in the gas phase region in the previous time and the liquid phase region in the current time are identified by logical operation to form a rewetting candidate region, and the pixels that overlap with the contact line region are removed to obtain the rewetting region mask. In step S403, it should be noted that the logical operation extracts the region where the gas phase transitions to the liquid phase as a rewetting candidate region by comparing the binary phase diagram of the current time step with that of the previous time step pixel by pixel. To improve segmentation accuracy, pixels overlapping with the contact line area are further removed to avoid misclassification. Specifically, Boolean logic operations (such as XOR operations) are used to mark pixels that meet the conditions, and morphological erosion operations are combined to remove boundary noise. The final generated rewetting area mask can accurately reflect the dynamic process of liquid re-covering the heated surface, while ensuring that it does not overlap with the contact line area, thereby improving the reliability of the partitioning results.

[0033] S404. Regions not belonging to the gas phase region, contact line region, and rewetting region are defined as liquid phase regions.

[0034] In step S404, it should be noted that the definition of the liquid phase region is achieved through an elimination method. That is, all pixels marked as gas phase region, contact line region, and rewetting region are removed from the binary phase diagram, and the remaining area is the liquid phase region. To ensure the accuracy of the partitioning results, the liquid phase region is further subjected to morphological processing, such as filling any possible small voids through expansion operations and optimizing the continuity of the boundary curve using a smoothing filtering algorithm.

[0035] After completing the above partitioning, the segmentation results of the gas phase region, contact line region, rewetting region, and liquid phase region are merged to generate the final partitioning result map. This result map uses different gray levels or colors to mark each region, facilitating subsequent analysis and visualization.

[0036] This invention provides a spatiotemporal synchronous visualization measurement and analysis method for flow-heat-phase, which can be applied to a testing device. The testing device includes: a high-speed phase distribution imaging unit, a high-speed infrared imaging unit, a transparent simulated heat source and optical substrate, pressure and temperature sensors, a synchronous triggering timing control and signal acquisition module, and a data processing and analysis unit.

[0037] The synchronous trigger timing control and signal acquisition module sends a pulse shutter signal to the high-speed phase distribution imaging unit and the high-speed infrared imaging unit, which is responsible for the synchronous triggering and timing control of high-speed vision and high-speed infrared.

[0038] After receiving the shutter signal, the high-speed phase distribution imaging unit and the high-speed infrared imaging unit send the camera trigger signal to the synchronous trigger timing control and signal acquisition module.

[0039] The synchronous triggering timing control and signal acquisition module receives signals from the high-speed phase distribution imaging unit, the high-speed infrared imaging unit, and the pressure and temperature sensors, and forwards these signals to the data processing and analysis unit. The data processing and analysis unit outputs a flow-thermal-phase spatiotemporal synchronous visualization measurement phase diagram.

[0040] In some embodiments of the first aspect described above, spatial calibration and alignment are performed before boiling. All high-speed cameras and high-speed infrared imaging units are simultaneously activated to capture four marker points located on the back of the substrate. Since these marker points are identifiable under both infrared and visible light, they are captured simultaneously. Image processing software is used to extract the pixel coordinates (uIR, vIR) and (uVis, vVis) of the four marker points from the infrared image and the bottom-view phase image, respectively. The perspective transformation matrix M from the visual image coordinates to the infrared image coordinates is calculated using the cv2.warpPerspective() function. For each frame of the bottom-view phase image, perspective transformation and resampling are performed using the perspective transformation matrix M and the cv2.warpPerspective() function to ensure complete alignment with the field of view and pixel grid of the infrared image. The resampling resolution of the visual image is maintained as an integer multiple of that of the infrared image to preserve its high-resolution information.

[0041] The flow-heat-phase spatiotemporal synchronous visualization measurement phase diagram includes an 8-bit raw image stack of brighter vapor regions and darker liquid regions, recorded by a first high-speed visible light camera 2 through a transparent simulated heat source and an optical substrate.

[0042] The first high-speed visible light camera 2 experiences a distortion in the width of its surface dimensions per frame due to its tilted viewing angle. This distortion can be corrected by performing a perspective transformation using four marker points on the surface. The markers can be viewed simultaneously on both the high-speed visible light and infrared images and are used for spatial alignment of the two images.

[0043] The pixel density of the mapping domain of the high-speed visible light camera is selected to be three times that of the high-speed infrared camera 1, in order to retain the high-resolution information obtained by the high-speed visible light camera.

[0044] Calculate the temporal average intensity (or minimum value) at each pixel location in the entire image stack sequence to obtain the average background image. This background image reflects uneven illumination and the inhomogeneity of the substrate itself. Subtract the background image from each frame to obtain an image with enhanced contrast and uniform illumination.

[0045] After background subtraction, the Otsu automatic global thresholding algorithm is applied to the image to automatically determine the optimal threshold and binarize the image. Pixels with gray levels above the threshold are defined as 1 (white, representing the gas phase), and pixels with gray levels below the threshold are defined as 0 (black, representing the liquid phase), resulting in a binary phase diagram P(x,y,t). The binary phase diagram is downsampled to the resolution of an infrared image, but an averaging method is used during sampling to make the pixel values ​​floating-point numbers (between 0 and 1), thus preserving high-resolution information.

[0046] The heat transfer region identification of the image is performed as described above, that is, for each frame of binary phase diagram P, the following image operation is performed.

[0047] Based on the data image results, the boiling heat transfer process image is divided into four regions: liquid region, contact line region, vapor region, and rewetting region.

[0048] Vapor phase mask V: Using a circular structuring element with a radius of 2 pixels, the image P is eroded three times in succession. The white area of ​​each bubble is shrunk inward by approximately 4 pixels. The result is denoted as erode(Pt), representing the pure vapor phase region V, thus removing the blurred edges of the gas-liquid interface. Vt = erode(Pt) Where erode() is the erode function, and Vt and Pt are the time-related binary phase diagram matrices of V and P; Contact line region mask I: Using the same structuring element and number of iterations, dilate the image Pt to obtain dilate(Pt), and calculate the contact line region: It = dilate(Pt) − erode(Pt) Rewetting Region Mask R: Distinguishing between single-phase liquid and rewetting regions involves using temporal information about bubble footprint movement. Rewetting occurs after a bubble detaches or moves, covering a hot surface previously occupied by vapor with cold liquid. Therefore, pixels that were in the gas phase in the previous moment and are currently in the liquid phase are identified. Using two phase maps that are slightly separated in time (a few frames), the following binary operation can be used to identify regions that were previously occupied by vapor and then covered by liquid: Ri0t=[Pit−δt|Pi t]−Pi t Here, Ri0t represents the initial estimate of pixel values ​​in the rewetting region, the subscript i indicates a single pixel, the symbol | indicates a bitwise OR operation, and the superscript t indicates the time for acquiring the phase map. δt represents the region selected that will affect recognition.

[0049] The initial candidate region may overlap with the contact line region (because the contact line also moves). Overlapping regions are eliminated using a pixel-by-pixel logical AND operation: Rit=Ri0t−Ri0t&Iit The '&' symbol represents the logical AND operator. This yields the final rewetting area mask Rit. Liquid phase mask L: All regions not divided into V, I, and R are ordinary liquid phase regions.

[0050] The intelligent partitioning result image is obtained by merging the four masks (L, I, V, R) onto a single image and labeling them with different colors.

[0051] Compared with the prior art, the beneficial effects of this embodiment are: 1. Multiphysics field spatiotemporal strict synchronization coupling test method A test method integrating hardware-level synchronization and software post-processing is proposed, achieving precise temporal and spatial coupling between the transient temperature field and the dynamic gas-liquid interface distribution field during boiling. High temporal synchronization accuracy: Through hardware triggering design, not only is high frame rate exposure synchronization between cameras with different frame rates achieved, but more importantly, the "zero-frame alignment" problem in pre-triggered recording mode is solved, ensuring that the multimodal data sequence begins at the same physical moment when capturing any transient event, laying the foundation for accurately establishing causal relationships. High spatial data coupling quality: A spatial calibration method based on physical marker points is adopted, achieving pixel-level precise registration between infrared and visual images, eliminating spatial misalignment errors caused by differences in field of view, viewing angle, and lens distortion, enabling reliable pixel-by-pixel correlation analysis of the temperature field and phase distribution field.

[0052] 2. Highly integrated system with strong scalability and reliability The system integrates heating, temperature measurement, and visualization substrates into a single unit, avoiding the impact of additional packaging on measurement accuracy. The entire synchronous control logic is implemented in hardware using an external pulse generator, ensuring stability and reliability, independence from the camera's internal software clock, and strong anti-interference capabilities. Furthermore, the system's design framework is not only suitable for pool boiling research but can also be adapted for studying other phase change heat transfer processes such as flow boiling and condensation with minor adjustments. It provides an unprecedented and comprehensive experimental dataset for in-depth research on local heat flux density inversion, interfacial heat and mass transfer mechanisms, and dry spot dynamics.

[0053] Example 2 A flow-thermal-phase spatiotemporal synchronous visualization measurement and analysis system is provided, which is used to execute the flow-thermal-phase spatiotemporal synchronous visualization measurement and analysis method; the system includes: The acquisition module is used to simultaneously acquire high-speed visual images, infrared temperature images, pressure data, and temperature data to form a multimodal sensing dataset. The pulse generation module, connected to the acquisition module, is used to send pulse signals to the acquisition module; The image alignment module, connected to the acquisition module, is used for spatial calibration and alignment of the multimodal sensing dataset; The phase diagram generation module is connected to the image alignment module. It uses image processing methods to obtain a binary phase diagram reflecting the gas-liquid distribution from the aligned high-speed visual image. The region segmentation module, connected to the phase diagram generation module, is used to identify and segment high-speed visual images of the boiling heat transfer process based on the binary phase diagram and combined with time-domain information. The segments are divided into liquid phase region, gas phase region, contact line region and rewetting region and then merged to obtain a partitioned result map. The data fusion and output module, connected to the region segmentation module, is used to identify infrared temperature images, binary phase diagrams, and partitioning result diagrams, and to fuse the identification results to output a flow-thermal-phase spatiotemporal synchronous visualization measurement phase diagram.

[0054] The flow-heat-phase spatiotemporal synchronous visualization measurement and analysis system in Embodiment 2 above is used to execute the flow-heat-phase spatiotemporal synchronous visualization measurement and analysis method. The specific details of each module are the specific components in Embodiment 3, so they will not be described in detail here.

[0055] Example 3 like Figures 2 to 6 As shown, a flow-thermal-phase spatiotemporal synchronous visualization measurement and analysis device is used to execute a flow-thermal-phase spatiotemporal synchronous visualization measurement and analysis method; the device includes: The boiling chamber 19 is used to contain the experimental medium. The boiling chamber 19 includes a substrate integration module and a flow control valve 8. A transparent simulated heat source and an optical substrate are integrated on the substrate integration module and mounted at the bottom of the boiling chamber 19. The substrate is connected to a PEEK support by spring pins 14 and sealed to the substrate integration module using O-rings 18. The module is sealed to the bottom of the boiling chamber using another O-ring 18. The flow control valve 8 is mounted at the top of the boiling chamber 19. The boiling chamber 19 is made of PEEK material, providing insulation and chemical stability, and is tightly enclosed from the outside, containing the experimental medium inside.

[0056] like Figure 6 As shown, the pool boiling experimental chamber 19 has a rectangular structure with transparent windows on its side. The substrate integration module 11 is mounted on the pool boiling test chamber 19 and is transparent to light; The substrate integration module 11 includes: A transparent simulated heat source and optical substrate are mounted on the boiling chamber 19. The transparent simulated heat source and optical substrate are composed of a high-transmittance substrate in the infrared and visible light bands. Preferably, the substrate material includes at least silicon and its composites, glass, sapphire, calcium fluoride, etc. A functional transparent conductive thin film is prepared on the upper surface of the substrate by vapor deposition or electron beam evaporation.

[0057] Preferably, the vapor deposition or electron beam evaporation process includes at least: physical vapor deposition (PVD), chemical vapor deposition (CVD), and electron beam evaporation.

[0058] Preferably, the functional transparent conductive film includes at least: oxide film systems, such as indium tin oxide (ITO), aluminum-doped zinc oxide (AZO), fluorine-doped tin oxide (FTO), etc.; metal film systems, such as gold (Au), silver (Ag), aluminum (Al), etc.; polymer film systems, such as polyaniline, polypyrrole, etc.; and nanomaterial film systems, such as silver nanowires, carbon nanotubes, etc.

[0059] The transparent simulated heat source and optical substrate have at least three functions: first, a transparent conductive heating function, which can generate a uniform and controllable heat flux on its upper surface when a DC or pulsed current is applied to the substrate, simulating a heating element; second, as an infrared radiation source and temperature sensing surface, which has high emissivity or opacity for mid- and long-wave infrared radiation, and its own temperature distribution can be directly obtained by measuring the infrared radiation it emits; and third, as an optical observation window, which maintains high transparency in the visible light band, allowing high-resolution transmission or reflection optical observation from the back of the substrate.

[0060] Transparent simulated heat source and optical substrate include: A sapphire optical substrate 17 is disposed on a pool boiling experimental chamber 19; like Figure 5 As shown, the sapphire optical substrate 17 is mounted at the bottom of the pool boiling experimental chamber 19 for use in... It provides high light transmittance and high temperature resistance, ensuring uniform heat distribution and high-quality optical imaging during experiments. The surface of the sapphire optical substrate 17 is precision polished to reduce light scattering and refraction errors, thereby improving the acquisition accuracy of high-speed visual images and infrared temperature images.

[0061] A conductive oxide film 16 is disposed on a sapphire optical substrate 17; like Figure 5As shown, a conductive oxide film 16 covers the sapphire optical substrate 17, forming a transparent simulated heat source to provide uniform heating during experiments. The conductive oxide film 16 is made of a material with high conductivity and high light transmittance, which can generate stable heat when energized, while allowing visible and infrared light to pass through, ensuring that the acquisition of high-speed visual images and infrared temperature images is not interfered with.

[0062] Gold layer 15 is provided at both ends of conductive oxide film 16.

[0063] like Figure 5 As shown, the gold layer 15 is positioned at both ends of the conductive oxide film 16, forming a stable current path to ensure the uniformity and controllability of the heating process. The gold layer 15 possesses excellent conductivity and chemical stability, enabling it to maintain its functional properties for extended periods at high temperatures. The sapphire optical substrate 17, the conductive oxide film 16, and the gold layer 15 together constitute the core structure of the transparent simulated heat source, providing a reliable thermal environment for the experiment. This design not only meets the experimental requirements for high-temperature conditions but also takes into account the high-precision requirements of optical imaging, allowing for the simultaneous and non-interfering acquisition of high-speed visual images and infrared temperature images.

[0064] Spring pin 14 is disposed on the transparent simulated heat source and optical substrate; like Figure 5 As shown, the spring pin 14 is connected to the gold layer 15 via elastic contact, ensuring stable current transmission to the conductive oxide film 16, thereby achieving precise heating control of the transparent simulated heat source. The spring pin 14 is made of a highly elastic material, which can maintain good contact performance in multiple experiments, avoiding uneven heating problems caused by poor contact.

[0065] The conductive lead 13 is connected at one end to the spring pin 14 and at the other end to the pool boiling experimental chamber 19. O-ring 18 is disposed at the bottom of the transparent simulated heat source and the optical substrate.

[0066] The lighting subsystem 7 is used to provide a light source to the substrate integration module 11; The illumination subsystem 7 in this embodiment is a high-brightness LED light source with an optimized wavelength range to meet the acquisition requirements of high-speed visual images and infrared temperature images. The illumination subsystem 7 projects light uniformly onto the surface of the substrate integrated module 11 via an optical fiber beam guide, ensuring consistent illumination intensity and eliminating shadow interference in the experimental area. Furthermore, the illumination subsystem 7 is equipped with an adjustable light attenuator, which dynamically adjusts the light intensity according to experimental conditions, thereby avoiding image quality problems caused by overexposure or underexposure. The light source design of this system also considers thermal management, incorporating a built-in cooling fan and temperature control module to extend the lifespan of the light source and ensure stability during the experiment. The high-brightness LED light source should contain at least monochromatic light such as red light and composite light such as white light. Preferably, the high-brightness LED light source is positioned on the side of the high-speed visible light camera imaging subsystem, or it enters the high-speed visible light camera imaging subsystem through a high-reflectivity front surface mirror.

[0067] A high-speed infrared camera 1 is used to acquire infrared temperature images of the substrate integrated module 11; The first high-speed visible light camera 2 is used to acquire high-speed visual images of the substrate integrated module 11 using the reflector 12; The second high-speed visible light camera 3 is used to acquire high-speed visual images from the side window of the boiling experimental chamber 19. The second high-speed visible light camera 3 records the macroscopic growth, detachment, and movement of bubbles from the side through the side window, providing supplementary multi-angle analysis. Its imaging principle is based on the difference in refractive index between the gas-liquid phases and the substrate: when the surface is covered by vapor (low refractive index), total internal reflection or high reflection easily occurs, and the camera receives high light intensity; when covered by liquid (high refractive index), light intensity is transmitted or scattered, and the camera receives low light intensity. This results in a high-contrast gas-liquid binary phase distribution map.

[0068] The frame rate of a high-speed visible light camera is usually set to an integer multiple of the frame rate of the high-speed infrared camera in a high-speed infrared imaging unit in order to obtain more refined interface dynamics information.

[0069] The second pulse generator 4 is connected to the high-speed infrared camera 1, the first high-speed visible light camera 2, and the second high-speed visible light camera 3. The second pulse generator 4 receives the shutter signal of the high-speed infrared imaging unit transmitted by the first pulse generator 5, and uses it as a gate signal to activate its output.

[0070] When the trigger button for the second pulse generator 4 is manually pressed, the second pulse generator 4 will only activate upon receiving an exposure signal from the infrared camera. Once the exposure signal arrives, a very precise delay, slightly less than the infrared frame period (e.g., for 500Hz, with a frame period of 2ms, the delay can be set to 1.98ms), is then generated as a short pulse as a "global storage trigger" signal. This ensures that frame 0 in the high-speed visible light camera always coincides with the frame of the high-speed infrared camera image.

[0071] This ensures that regardless of whether the manual start button for the second pulse generator 4 is pressed, the stored trigger signal is always emitted just before the start of the next infrared exposure. Since the exposures of all cameras are locked to the infrared exposure reference, this stored trigger signal guarantees that the "frame 0" images saved by all cameras were acquired within the same infrared exposure cycle, achieving strict "zero-frame alignment." The length of the pre-trigger buffer can be set according to actual needs.

[0072] The first pulse generator 5 is connected to the high-speed infrared camera 1, the first high-speed visible light camera 2, the second pulse generator 4, and the second high-speed visible light camera 3. DAQ data acquisition unit 6 is connected to the first pulse generator 5; like Figure 2 As shown, the high-speed infrared camera 1, the first high-speed visible light camera 2, and the second high-speed visible light camera 3 are precisely synchronized to ensure that the acquired infrared temperature images and high-speed visual images remain consistent in the time dimension. The first pulse generator 5 and the second pulse generator 4 work together to send high-precision time synchronization signals to each camera, thereby achieving accurate acquisition of the multimodal sensing dataset. In addition, the DAQ data acquisition instrument 6 is responsible for recording pressure and temperature data in real time during the experiment and integrating them with the image data to form a complete spatiotemporal synchronized data stream. The light source intensity of the illumination subsystem 7 can be automatically adjusted according to the experimental stage, and in conjunction with the exposure parameter optimization of the high-speed infrared camera 1 and the visible light camera, it effectively avoids image distortion caused by uneven illumination.

[0073] The synchronous trigger timing control and signal acquisition module includes a second pulse generator 4, a first pulse generator 5, and a DAQ data acquisition instrument.

[0074] The second pulse generator 4, the first pulse generator 5, the high-speed visible light camera imaging subsystem, the high-speed infrared imaging unit, and the DAQ data acquisition instrument are connected via BNC. When the high-speed infrared imaging unit is exposed, the shutter signal of the active high-speed infrared imaging unit is sent to the input of the first pulse generator. The first pulse generator creates six uniform timing pulses for each received pulse, which serve as exposure trigger signals for the two high-speed visible light cameras in the high-speed visible light camera imaging subsystem to activate the shutters of the high-speed visible light cameras.

[0075] All cameras continuously record data to an allocated pre-trigger memory buffer before triggering the input. An external trigger signal saves the recorded frames in the allocated pre-trigger memory buffer and continues recording to the post-trigger memory buffer. The buffer length is appropriately set to capture the heater's step change in response to thermal input and subsequent steady-state periodic transient response. Recorded frames include a certain number of pre-trigger frames, frame 0, and all post-trigger frames. Manually inputting the trigger signal cannot guarantee 0-frame alignment for both high-speed visible light and high-speed infrared cameras. A different delay can be enforced by referencing another pulse generator until all cameras capture simultaneously.

[0076] Temperature sensor 10 is installed on the pool boiling experimental chamber 19; Pressure sensor 9 is installed on the pool boiling test chamber 19.

[0077] As another optional embodiment of the present invention, the pool boiling test chamber 19 may also be provided with a flow regulating valve 8.

[0078] In this embodiment, the flow regulating valve 8 is installed on the top of the boiling test chamber 19 to regulate the flow rate and direction of the experimental working fluid, thereby precisely controlling the flow field distribution during the boiling heat transfer process.

[0079] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for simultaneous spatiotemporal visualization measurement and analysis of flow-heat-phase, characterized in that, The method includes: Simultaneously acquire high-speed visual images, infrared temperature images, pressure data, and temperature data to form a multimodal sensing dataset; Spatial calibration and alignment are performed on the multimodal sensing dataset; The aligned high-speed visual image is used to obtain a binary phase diagram reflecting the gas-liquid distribution through image processing methods; Based on the binary phase diagram and combined with time-domain information, the high-speed visual image of the boiling heat transfer process is identified and segmented into liquid phase region, gas phase region, contact line region and rewetting region and then merged to obtain a partitioned result image. The infrared temperature image, binary phase diagram, and partitioning result diagram are identified, and the identification results are fused to output a flow-thermal-phase spatiotemporal synchronous visualization measurement phase diagram.

2. The method for simultaneous spatial-temporal visualization measurement and analysis of flow-heat-phase as described in claim 1, characterized in that, Step S2 involves spatial calibration and alignment of the multimodal sensing dataset, including: Spatial calibration is performed on the multimodal sensing dataset, and calibration images of visible light and infrared marker points are obtained from the multimodal sensing dataset; Based on the calibration image, the pixel coordinates of the marker points in the high-speed visual image and the infrared temperature image are extracted respectively; Calculate the visual transformation matrix from the marker point in the high-speed visual image to the marker point in the infrared temperature image based on the pixel coordinates; The high-speed visual image is resampled based on the visual transformation matrix, so that the high-speed visual image and the infrared temperature image are spatially aligned.

3. The method for simultaneous spatial-temporal visualization measurement and analysis of flow-heat-phase as described in claim 2, characterized in that, The warpPerspective function is used to calculate the view transformation matrix.

4. The method for simultaneous spatial-temporal visualization measurement and analysis of flow-heat-phase as described in claim 1, characterized in that, Obtaining a binary phase diagram reflecting the gas-liquid distribution includes: Calculate the time-averaged background image of a high-speed visual image sequence; Subtract the time-averaged background image from each frame of the high-speed visual image to obtain a background-free high-speed visual image. The high-speed visual image without background is binarized using an automatic thresholding algorithm to distinguish between the gas phase and the liquid phase, thus obtaining the binarized high-speed visual image. The binarized high-speed visual image is downsampled to the resolution of an infrared temperature image while retaining grayscale information to obtain a binary phase diagram reflecting the gas-liquid distribution.

5. The method for simultaneous spatial-temporal visualization measurement and analysis of flow-heat-phase as described in claim 1, characterized in that, The obtained partitioned result image includes: The binary phase diagram is processed using OpenCV to obtain the gas phase region; Perform a difference operation on the binary phase diagram to obtain the contact line region; Based on the binary phase diagram of the current time and the previous time, the pixels that were in the gas phase region in the previous time and the liquid phase region in the current time are identified by logical operation to form a rewetting candidate region. The pixels that overlap with the contact line region are removed to obtain the rewetting region mask. The region that does not belong to the gas phase region, contact line region, and rewetting region is defined as the liquid phase region.

6. A spatiotemporal synchronous visualization measurement and analysis system for flow-heat-phase, characterized in that, The system is used to execute the spatiotemporal synchronous visualization measurement and analysis method for flow-thermal-phase as described in any one of claims 1 to 5; the system includes: The acquisition module is used to simultaneously acquire high-speed visual images, infrared temperature images, pressure data, and temperature data to form a multimodal sensing dataset. A pulse generation module, connected to the acquisition module, is used to send pulse signals to the acquisition module; An image alignment module, connected to the acquisition module, is used to perform spatial calibration and alignment on the multimodal sensing dataset; The phase diagram generation module is connected to the image alignment module and uses image processing methods to obtain a binary phase diagram reflecting the gas-liquid distribution from the aligned high-speed visual image. The region segmentation module, connected to the phase diagram generation module, is used to identify and segment the high-speed visual image of the boiling heat transfer process based on the binary phase diagram and combined with time-domain information, dividing it into liquid phase region, gas phase region, contact line region and rewetting region and merging them to obtain a partitioned result map. The data fusion and output module is connected to the region segmentation module and is used to identify the infrared temperature image, binary phase diagram and partition result diagram, and fuse the identification results to output a flow-thermal-phase spatiotemporal synchronous visualization measurement phase diagram.

7. A flow-heat-phase spatiotemporal synchronous visualization measurement and analysis device, characterized in that, The apparatus is used to perform the spatiotemporal synchronous visualization measurement and analysis method for flow-thermal-phase as described in any one of claims 1 to 5; the apparatus comprises: The pool boiling experimental chamber (19) is used to contain the experimental working fluid; The substrate integration module (11) is disposed on the pool boiling test chamber (19) and has light transmittance; The lighting subsystem (7) is used to provide a light source to the substrate integration module (11); A high-speed infrared camera (1) is used to acquire infrared temperature images of the substrate integrated module (11); The first high-speed visible light camera (2) is used to acquire high-speed visual images of the substrate integrated module (11) using a reflector (12); The second high-speed visible light camera (3) is used to collect high-speed visual images from the side window of the pool boiling experimental chamber (19); The second pulse generator (4) is connected to the high-speed infrared camera (1), the first high-speed visible light camera (2), and the second high-speed visible light camera (3); The first pulse generator (5) is connected to the high-speed infrared camera (1), the first high-speed visible light camera (2), the second pulse generator (4), and the second high-speed visible light camera (3); The DAQ data acquisition unit (6) is connected to the first pulse generator (5); A temperature sensor (10) is installed on the pool boiling test chamber (19); A pressure sensor (9) is installed on the pool boiling test chamber (19).

8. The flow-heat-phase spatiotemporal synchronous visualization measurement and analysis device as described in claim 7, characterized in that, The pool boiling test chamber (19) is also equipped with a flow regulating valve (8).

9. The flow-heat-phase spatiotemporal synchronous visualization measurement and analysis device as described in claim 7, characterized in that, The substrate integration module (11) includes: A transparent simulated heat source and optical substrate are disposed on the pool boiling experimental chamber (19); A spring pin (14) is disposed on the transparent simulated heat source and optical substrate. The conductive lead (13) is connected at one end to the spring pin (14) and at the other end to the pool boiling test chamber (19); An O-ring (18) is disposed at the bottom of the transparent simulated heat source and the optical substrate.

10. The flow-heat-phase spatiotemporal synchronous visualization measurement and analysis device as described in claim 9, characterized in that, The transparent simulated heat source and optical substrate include: A sapphire optical substrate (17) is disposed on the pool boiling experimental chamber (19); A conductive oxide film (16) is disposed on the sapphire optical substrate (17); Gold layer (15) is provided at both ends of the conductive oxide film (16).

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