A method for obtaining high-speed flow velocity based on stripe imaging

Abstract

A method for acquiring high-speed flow velocity based on fringe imaging belongs to the field of aerodynamic testing technology. To address the problem of improving the accuracy of high-speed flow velocity measurement, this invention constructs a measurement system including a femtosecond laser, a multi-pass compressor, mirror I, mirror II, mirror III, a plano-concave lens, a plano-convex lens, a high-speed camera, an image intensifier, a telephoto lens, a fixing device, a computer device, and a synchronization signal generator. A timing control and multi-delay gating acquisition method is developed; scale conversion parameters are calculated; and using the timing control and multi-delay gating acquisition method, images are acquired based on the measurement system, and image processing is performed based on the correspondence between image pixel coordinates and actual physical dimensions to calculate the high-speed flow velocity based on fringe imaging. This invention features a clear process, high system integration, and is suitable for velocity measurement under transient high-speed flow conditions, exhibiting good engineering applicability and measurement reliability.

Description

Technical Field

[0001] This invention belongs to the field of aerodynamic testing technology, specifically relating to a method for obtaining high-speed flow velocity based on stripe imaging. Background Technology

[0002] The measurement of high-speed flow velocities is a fundamental technology in aerodynamics research, high-speed aircraft design, and ground-based wind tunnel testing. Especially under transient high-enthalpy flow conditions, the flow process is characterized by short duration, rapid changes, and small spatial scale, placing higher demands on measurement methods in terms of temporal resolution, spatial resolution, and measurement stability. How to achieve accurate measurement of high-speed flow velocities without interfering with the physical properties of the flow field itself has always been a key focus in the field of experimental fluid mechanics.

[0003] Currently, high-speed flow field velocity measurement methods mainly include contact measurement methods and non-contact optical measurement methods. Contact measurement methods, such as Pitot tube velocimetry, have a simple structure but are prone to disturbing the flow field and are difficult to apply to high-temperature, high-enthalpy, or strongly pulsating flow environments. Among non-contact optical velocimetry methods, particle image velocimetry (PIV) technology introduces tracer particles into the flow field and performs image analysis on their motion to invert the velocity distribution of the flow field. However, under high-speed or high-enthalpy flow conditions, the introduction of tracer particles may cause some contamination to the flow field, affecting the accuracy of the flow. At the same time, the survivability and following ability of particles in high-temperature environments can also adversely affect the measurement accuracy.

[0004] Furthermore, optical velocimetry methods based on laser-induced fluorescence and other techniques reduce direct interference with the flow field to some extent, but their measurement performance is still limited by laser pulse energy, imaging system time response capability, and synchronization control accuracy. In experimental environments such as combined pulsed high-enthalpy wind tunnels, the flow field duration is typically on the order of microseconds to milliseconds, making it difficult for traditional continuous exposure or low temporal resolution imaging methods to effectively capture the flow process. Simultaneously, existing velocimetry methods still have shortcomings in multi-frame synchronous acquisition, imaging stability, and consistency of subsequent data processing, limiting further improvements in the accuracy and repeatability of high-speed flow velocity measurements. Summary of the Invention

[0005] The problem this invention aims to solve is to improve the accuracy of high-speed flow velocity measurement, and proposes a method for obtaining high-speed flow velocity based on stripe imaging.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for obtaining high-speed flow velocity based on stripe imaging includes the following steps:

[0008] S1. Establish a measurement system;

[0009] S2. Construct a timing control and multi-delay gating acquisition method, setting the image intensifier to be gated sequentially under different delay conditions, and synchronously acquiring laser stripe images corresponding to each delay time;

[0010] S3. Calculate the scale conversion parameters. Under imaging conditions consistent with actual measurements, acquire a calibration image containing a calibration target with known geometric dimensions. This image is used to establish the correspondence between image pixel coordinates and actual physical dimensions.

[0011] S4. Using the timing control and multi-delay gating acquisition method in step S2, images are acquired based on the measurement system, and image processing is performed based on the correspondence between the image pixel coordinates and the actual physical size obtained in step S3 to calculate the high-speed flow velocity based on stripe imaging.

[0012] Furthermore, in step S1, the laser emitted by the femtosecond laser is reflected by mirrors I and II and then enters the multi-pass compressor. The laser emitted again is reflected by mirror III, and then passes through a plano-concave lens and a plano-convex lens before entering the target area in the vacuum chamber. The femtosecond laser is connected to a synchronization signal generator, which triggers a high-speed camera and an image intensifier. The high-speed camera is connected to the image intensifier, which is connected to a telephoto lens. The high-speed camera is connected to a computer device.

[0013] Furthermore, in step S1, the high-speed camera and image intensifier are mounted on a fixed device; the telephoto lens is aimed at the target area in the vacuum chamber.

[0014] Furthermore, the fixing device in step S1 includes an image intensifier mounting plate and a camera mounting platform. The image intensifier mounting plate is a rectangular plate, and the camera mounting platform is installed on the right half of the image intensifier mounting plate. Both the image intensifier mounting plate and the camera mounting platform are provided with multiple hollowed-out grooves extending parallel to the long side of the fixing device.

[0015] Furthermore, in step S2, within each exposure cycle, the image intensifier is gated according to different time delay strategies; the first gated opening of the image intensifier occurs simultaneously with the triggering of the femtosecond laser, followed by gated opening at fixed time intervals. The gating is opened sequentially, with the gating time for each gating action of the enhancer being [time to be specified]. Set up to acquire n frames of images, the nth frame... The secondary gate opening time is , =1,2, .

[0016] Furthermore, step S3 obtains the correspondence between image pixel coordinates and actual physical dimensions as scale conversion parameters. This is used for converting subsequent measurement results from pixel scale to physical scale.

[0017] Furthermore, the specific implementation method of step S4 includes the following steps:

[0018] S4.1. Following the timing control in step S2, acquire L images, let I... For any one of these images, x represents the pixel coordinates in the horizontal direction and y represents the pixel coordinates in the vertical direction.

[0019] S4.2. For I Background correction and noise reduction smoothing are performed to obtain the corrected image. The expression is:

[0020] =I -

[0021] in, Images acquired under laser-free conditions;

[0022] Then to After smoothing, the following is obtained:

[0023]

[0024] in, The image after smoothing. This represents the convolution operation. It is a two-dimensional smoothing kernel function;

[0025] S4.3. For the smoothed image, coordinate transformation or image rotation is used to make the overall extension direction of the laser stripes consistent with the horizontal direction of the image. Then, the normalized cross-correlation function is calculated using the brightness sequence and template function. The translation amount corresponding to the maximum value of the normalized cross-correlation function is taken as the coarse localization result of the laser stripe center. The coarse localization of the laser stripe center is performed to obtain a set of coarse localization points of the laser stripe center at multiple locations.

[0026] S4.4. At each sampling location The corresponding coarse positioning result obtained in step S4.3 is used at this location. Centered on the laser stripe, a local search area is selected along the direction perpendicular to the laser stripe extension. ,in, The preset search half-width;

[0027] Within the local search range, extract local brightness data. ;

[0028] Within the local search interval, a Gaussian model is used to model the brightness distribution of the laser stripes in the vertical direction. The expression is:

[0029]

[0030] in, This refers to the amplitude parameter of the stripe brightness. The sub-pixel coordinates are the center position of the laser stripe. The lateral width parameter of the laser stripe. Background biased items;

[0031] Using the least squares criterion, local brightness data With Gaussian model Perform fitting and solve for the model parameters. ;

[0032] After fitting, take As sampling location Precise positioning results of the center of the laser stripe ,Right now For all sampling locations Performing the above steps separately yields a set of sub-pixel-level positioning points for the laser stripe: M is the total number of sampling locations;

[0033] S4.5. Perform overall construction and smoothing on the discrete center positioning points in the sub-pixel-level positioning point set of the laser stripe to construct the laser stripe center point sequence. A consistency check is performed on the laser stripe center point sequence to remove outliers that significantly deviate from the local trend.

[0034] Then, a polynomial function was used to fit the sequence of laser stripe center points after the consistency check: ,in, This represents the vertical coordinate value of the center line of the laser stripe in the image. Let be the order of the polynomial. These are the fitting coefficients. Let x be the j-th power of the abscissa x. Based on the fitting results, the expression for the center line of the laser stripe is: The center line of the laser stripe is used as the final stripe extraction result;

[0035] S4.6. For the L acquired images, process them according to the methods in steps S4.2-S4.5 to obtain the continuous representation of the laser stripe center in the image coordinate system at different times.

[0036] For the center line of the laser stripe in the t-th frame image 1 t , Let be the vertical coordinate value of the center line of the laser stripe in the t-th frame of the image;

[0037] The feature positions used to characterize the overall position in the center line area are determined by statistically analyzing the coordinates of the center line in the direction of stripe extension.

[0038]

[0039] in, Let be the sub-pixel ordinate of the i-th center point in the t-th frame of the image. The feature location of the t-th frame image;

[0040] By performing difference calculations on the feature locations obtained from two consecutive image frames, the displacement of the stripes in the pixel coordinate system can be obtained. :

[0041]

[0042] Then calculate the actual speed. for:

[0043]

[0044] in, The time interval between two adjacent frames;

[0045] For any two consecutive frames of images, calculate the velocity according to step S4.6, and average all velocities to obtain the final high-speed flow velocity based on stripe imaging.

[0046] The beneficial effects of this invention are:

[0047] This invention discloses a high-speed flow velocity acquisition method based on stripe imaging. By introducing a laser excitation structure combining a femtosecond laser with a multi-pass compressor, it effectively enhances the peak power of ultrashort pulse lasers while ensuring laser energy transmission efficiency, thus providing stable and high-contrast laser illumination conditions for high-speed flow stripe imaging. The multi-pass compressor extends the equivalent propagation path of nonlinear effects, achieving pulse compression while reducing the intensity of single nonlinear effects. This improves system stability and reduces the risk of optical damage, providing a reliable laser source foundation for transient imaging of high-speed flow fields. Furthermore, this invention combines multi-delay gated imaging with precise synchronous timing control to achieve multi-frame independent acquisition of laser stripes during high-speed flow. By constructing a complete laser stripe center extraction and evolution analysis process, it achieves sub-pixel-level precise positioning of the stripe center position. By constructing the stripe centerline as a whole and converting it into the feature quantity required for velocity calculation, stable inversion of high-speed flow velocity is achieved. This invention has a clear process, high system integration, and is suitable for velocity measurement under transient high-speed flow conditions, exhibiting good engineering applicability and measurement reliability. Attached Figure Description

[0048] Figure 1 This is a flowchart of a high-speed flow velocity acquisition method based on stripe imaging according to the present invention;

[0049] Figure 2 This is a schematic diagram of the measurement system of the present invention;

[0050] Figure 3 This is a schematic diagram of the fixing device of the present invention. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only for explaining the invention and are not intended to limit the invention; that is, the described specific embodiments are merely a part of the embodiments of the invention, and not all of them. The components of the specific embodiments of the invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations, and the invention may also have other embodiments.

[0052] Therefore, the following detailed description of specific embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected specific embodiments of the invention. All other specific embodiments obtained by those skilled in the art based on these specific embodiments without inventive effort are within the scope of protection of this invention.

[0053] To further understand the invention's content, features, and effects, the following specific embodiments are provided, along with accompanying drawings. Figure 1 - Appendix Figure 3 Detailed explanation is as follows:

[0054] Example 1:

[0055] A method for obtaining high-speed flow velocity based on stripe imaging includes the following steps:

[0056] S1. Construct a measurement system, including a femtosecond laser 1, a multi-pass compressor 2, a mirror I 3, a mirror II 4, a mirror III 5, a plano-concave lens 6, a plano-convex lens 7, a high-speed camera 8, an image intensifier 9, a telephoto lens 10, a fixed connection device 11, a computer device 12, and a synchronization signal generator 13.

[0057] Furthermore, in step S1, the laser emitted by the femtosecond laser 1 is reflected by mirror I3 and mirror II4 and then enters the multi-pass compressor 2. The laser emitted again is reflected by mirror III5, and then enters the target area in the vacuum chamber after passing through the plano-concave lens 6 and plano-convex lens 7. The femtosecond laser 1 is connected to the synchronization signal generator 13. The synchronization signal generator 13 triggers the high-speed camera 8 and the image intensifier 9. The high-speed camera 8 is connected to the image intensifier 9. The image intensifier 9 is connected to the telephoto lens 10. The high-speed camera 8 is connected to the computer device 12.

[0058] Furthermore, in step S1, the high-speed camera 8 and image intensifier 9 are mounted on the fixed device 11; the telephoto lens 10 is aimed at the target area in the vacuum chamber.

[0059] Furthermore, the fixing device 11 in step S1 includes an image intensifier mounting plate 14 and a camera mounting platform 15. The image intensifier mounting plate 14 is a rectangular plate, and the camera mounting platform 15 is installed on the right half of the image intensifier mounting plate 14. Both the image intensifier mounting plate 14 and the camera mounting platform 15 are provided with a plurality of hollowed-out grooves extending in a direction parallel to the long side of the fixing device 11.

[0060] Furthermore, the femtosecond laser 1 is used to generate femtosecond pulsed laser signals. It excites air molecules by outputting ultrashort pulsed lasers with high peak power, thereby forming molecular fluorescence radiation signals. The femtosecond laser is a ytterbium-doped gain medium. The ytterbium-doped ions have a quasi-two-level structure, with direct transitions between the ground and excited states, no redundant energy levels, and can effectively suppress parasitic oscillations. Its pump wavelength is close to the laser wavelength, resulting in low quantum defects and small thermal effects, which is beneficial for high-stability output. Simultaneously, the ytterbium-doped gain medium has a wide gain bandwidth, supporting femtosecond pulse generation. Ytterbium-doped laser crystals are typically grown using the Czochralski method, i.e.,... After being mixed and melted with the matrix raw material in a certain proportion, Yb³⁺ doped single crystals with high uniformity and low defects are obtained by seed crystal directional pulling and slow cooling.

[0061] The multi-pass compressor 2 is mainly used to compress the time of the high-energy femtosecond laser emitted by the femtosecond laser 1. It achieves effective shortening of pulse width by combining multiple controlled nonlinear actions with dispersion compensation, thereby obtaining femtosecond laser output with high peak power and taking into account high energy transmission efficiency.

[0062] After entering the multi-pass compressor, the femtosecond laser pulse passes through a nonlinear medium multiple times in a preset propagation path composed of reflective optical elements. During propagation, a nonlinear phase modulation effect gradually accumulates, effectively broadening the spectral range of the laser pulse. By extending the equivalent nonlinear interaction length, the intensity of a single nonlinear interaction is reduced, thereby ensuring good stability and controllability in the spectral broadening process, minimizing the risk of optical damage and maintaining beam quality. After spectral broadening is complete, the broadened femtosecond laser pulse enters the dispersion compensation module. Through precise adjustment of the propagation time of different frequency components, the spectral components are resynchronized in time, thus achieving compressed pulse output.

[0063] The reflectors I3 and II4 are used to adjust the propagation optical path of the femtosecond pulse laser to guide the femtosecond pulse laser and input it into the multi-pass compressor 2.

[0064] The reflector III5 is used to reflect the femtosecond laser compressed by the multi-pass compressor 2 and transmit it to the beam shaping module so that the compressed laser beam can be further diverged, expanded and shaped.

[0065] The beam shaping module includes a plano-concave lens 6 and a plano-convex lens 7. The plano-concave lens 6 is used to diverge the femtosecond laser beam, increasing the divergence angle of the laser beam and thus providing beam conditions for subsequent convergence control. The plano-convex lens 7 is used to converge the diverged laser beam, and by changing the convergence position and degree of convergence, the shape and spot size of the laser beam can be controlled.

[0066] Through the coordinated operation of the plano-concave lens 6 and the plano-convex lens 7, the divergence angle, convergence position, and beam diameter of the femtosecond laser beam can be flexibly adjusted, thereby meeting the requirements for the propagation characteristics and spatial distribution of the laser beam under different experimental conditions, and ensuring the stable transmission and effective positioning of the laser beam in the subsequent propagation process.

[0067] The high-speed camera 8, image intensifier 9, telephoto lens 10, and mounting device 11 between the image intensifier and the high-speed camera are capable of capturing laser stripe images with high precision. The high-speed camera 8 has an extremely high frame rate, enabling it to capture rapidly changing laser signals. The high-speed camera has an image resolution of 14 bits or higher, allowing for the subdivision of gray levels (signal intensity) into more levels, improving image accuracy and detail. The image intensifier enhances signal brightness, preventing the loss of weak laser signals during imaging. The telephoto lens 10 is used to precisely align with the target area in the vacuum chamber, ensuring a clear and accurate image.

[0068] The fastening device, such as Figure 3 As shown, the whole includes an image intensifier mounting plate 14 and a camera mounting platform 15, which are arranged sequentially along the optical axis to achieve stable installation and precise alignment of the image intensifier and the camera.

[0069] Both the image intensifier mounting plate 14 and the camera mounting platform 15 are provided with multiple groove structures extending in the horizontal direction. The grooves are used to cooperate with fasteners to make the installation position adjustable, thereby facilitating fine adjustment of the relative position of the image intensifier and the camera in the horizontal direction. At the same time, each installation area is provided with screw fastening space to meet the fixing requirements of different specifications of mounting parts and ensure the installation stability of the overall structure.

[0070] The bottom of the image intensifier mounting plate 14 adopts a hollow structure design, which reduces the overall weight of the fixing device while ensuring structural strength and installation reliability, thereby reducing the load on the imaging system support structure.

[0071] The camera mounting platform 15 is equipped with two inclined structures, one at the front and one at the rear. The front ramp is used to adjust the camera's mounting posture, ensuring that the camera's imaging surface forms a predetermined angle with the image intensifier's output surface. This optimizes the optical path matching and reduces the impact of optical axis deviation on image quality. The rear ramp provides space for the camera's power and signal cables to exit, preventing cable bending or stress concentration, thus improving the reliability of cable connections and the overall wiring rationality of the system. Through this structural design, the fixing device can reliably fix the image intensifier to the camera while also considering installation and adjustment flexibility, lightweight structure, and optical path alignment accuracy, which is beneficial to improving the overall stability and imaging consistency of the imaging system.

[0072] The synchronization signal generator 13 is used to provide a unified timing reference signal to the laser, high-speed camera and related experimental equipment to realize synchronous triggering and timing control among multiple devices; the computer device 12 is electrically connected to the high-speed camera and is used to store, process and analyze the acquired image data, and manage and output the imaging results according to the experimental requirements.

[0073] S2. Construct a timing control and multi-delay gating acquisition method, setting the image intensifier 9 to be gating open sequentially under different delay conditions, and synchronously acquiring laser stripe images corresponding to each delay time;

[0074] Furthermore, in step S2, within each exposure cycle, the image intensifier 9 is gated according to different time delay strategies; the first gated opening of the image intensifier 9 occurs simultaneously with the triggering of the femtosecond laser 1, followed by gated opening at fixed time intervals. The gate opening times are sequentially delayed, such as the time for each gate opening of Intensifier 9. Set up to acquire n frames of images, the nth frame... The secondary gate opening time is , =1,2, .

[0075] Furthermore, the image intensifier is sequentially triggered under different delay conditions, and laser stripe images corresponding to each delay time are acquired simultaneously. Specifically, the timing control module modulates the pulse emission process of the femtosecond laser and drives the imaging system to complete image acquisition within multiple independent exposure cycles. When a trigger signal is sent to the femtosecond laser, the femtosecond laser generates laser pulses, and the imaging system performs multiple exposure operations according to preset timing parameters. Each exposure corresponds to acquiring an independent frame of laser stripe image. Since each frame of exposure corresponds to only one laser pulse stripe imaging signal, each image contains only the laser stripe distribution information at a single moment. By performing time-progressive analysis on the sequence of multiple frames of laser stripe images, velocity can be measured.

[0076] S3. Calculate the scale conversion parameters. Under imaging conditions consistent with actual measurements, acquire a calibration image containing a calibration target with known geometric dimensions. This image is used to establish the correspondence between image pixel coordinates and actual physical dimensions.

[0077] Furthermore, step S3 obtains the correspondence between image pixel coordinates and actual physical dimensions as scale conversion parameters. This is used for converting subsequent measurement results from pixel scale to physical scale.

[0078] Furthermore, the calibration target forms multiple structural features distributed along a predetermined direction with fixed spacing in the image, used to establish the correspondence between the image pixel scale and the actual physical scale. In the calibration image, a region of interest containing the structural features is selected, and the position of each structural feature is detected based on the changes in brightness distribution or geometric structure of the structural features in the image, to obtain the initial position coordinates of the corresponding structural features in the image coordinate system. Local neighborhood analysis is performed on the initial position coordinates, and the positioning accuracy of the structural features is improved through smoothing and local fitting operations, thereby obtaining the precise position coordinates of each structural feature in the image coordinate system. Based on the precise position coordinates of adjacent structural features, their pixel spacing in the image is calculated, and the pixel spacing is matched with the corresponding actual size in the calibration target to obtain the scale conversion parameter between pixel distance and actual physical distance. This is used for converting subsequent measurement results from pixel scale to physical scale.

[0079] Furthermore, the calibration target is a linear scale structure with equally spaced scribe lines. The structural feature is characterized by multiple scribe lines extending in the same direction. In the calibration image, the image grayscale information is accumulated or averaged along the direction perpendicular to the scribe line extension to obtain a one-dimensional brightness distribution curve. The boundary positions of each scribe line are determined based on the brightness abrupt change locations in the brightness distribution curve, and the precise position coordinates of the scribe lines in the image are obtained by locally fitting the boundary neighborhood signals. The pixel spacing is calculated based on the precise position coordinates of adjacent scribe lines, and combined with the actual physical spacing between the scribe lines, a conversion parameter between the pixel scale and the actual physical scale is obtained.

[0080] Furthermore, the calibration target is a two-dimensional array structure, characterized by multiple feature points regularly distributed along the row and column directions. In the calibration image, based on the geometric characteristics of the two-dimensional array structure, the intersection or center positions of each feature point in the array are detected to obtain the initial position coordinates of the feature points in the image coordinate system; local neighborhood fitting processing is performed on the initial position coordinates to improve the positioning accuracy of the feature points. Based on the position coordinates of adjacent feature points in the row or column direction, the corresponding pixel spacing is calculated, and combined with the actual physical spacing between adjacent feature points in the two-dimensional array, the conversion parameters between the pixel scale and the actual physical scale are obtained.

[0081] S4. Using the timing control and multi-delay gating acquisition method in step S2, images are acquired based on the measurement system, and image processing is performed based on the correspondence between the image pixel coordinates and the actual physical size obtained in step S3 to calculate the high-speed flow velocity based on stripe imaging.

[0082] Furthermore, the specific implementation method of step S4 includes the following steps:

[0083] S4.1. Following the timing control in step S2, acquire L images, let I... For any one of these images, x represents the pixel coordinates in the horizontal direction and y represents the pixel coordinates in the vertical direction.

[0084] S4.2. For I Background correction and noise reduction smoothing are performed to obtain the corrected image. The expression is:

[0085] =I -

[0086] in, Images acquired under laser-free conditions;

[0087] Then to After smoothing, the following is obtained:

[0088]

[0089] in, The image after smoothing. This represents the convolution operation. It is a two-dimensional smoothing kernel function;

[0090] Furthermore, the two-dimensional smoothing kernel function Using a Gaussian kernel, its expression is:

[0091] =

[0092] in, For smoothing parameters;

[0093] S4.3. For the smoothed image, coordinate transformation or image rotation is used to make the overall extension direction of the laser stripes consistent with the horizontal direction of the image. Then, the normalized cross-correlation function is calculated using the brightness sequence and template function. The translation amount corresponding to the maximum value of the normalized cross-correlation function is taken as the coarse localization result of the laser stripe center. The coarse localization of the laser stripe center is performed to obtain a set of coarse localization points of the laser stripe center at multiple locations.

[0094] Furthermore, the laser stripes extend along a predetermined direction in the image. To facilitate center positioning, coordinate transformation or image rotation is used to ensure that the overall extension direction of the laser stripes aligns with the horizontal direction of the image. For the processed image... Several fixed positions are selected along the extension direction of the laser stripe: x= ,in Indicates the sampling position along the stripe direction. This represents the number of sampling locations. At each location... At this location, pixel grayscale values ​​are read along the direction perpendicular to the extension of the laser stripes, forming a one-dimensional brightness sequence:

[0095] , ,in This represents the pixel range containing the laser stripes. Here, k represents the pixel index in the vertical direction of the image. The pixel range containing the laser stripes can be obtained through binarized images and contour extraction.

[0096] Constructing a one-dimensional template function The template function is used for the typical brightness distribution of laser stripes perpendicular to their extension direction.

[0097] The template function Using a zero-mean unimodal function, its mathematical expression is:

[0098]

[0099] Where n is the discrete sampling index of the template function. Center position of the template; This is the template width parameter. This is a constant term used for the zero-mean template function. The constant... Determined by the following formula: = , where N is the number of sampling points of the template function.

[0100] For each brightness sequence With template functions Calculate the normalized cross-correlation function:

[0101]

[0102] This represents the amount of translation of the template in the pixel index direction; Brightness sequence In the interval The mean within; template function The mean value within the sampling interval. In the above normalized cross-correlation calculation process, With brightness sequence Matching is performed using the same discrete sampling interval. Discrete sampling index of the template function. Pixel index of image brightness sequence A one-to-one correspondence is adopted, that is, in the template translation amount Given the following conditions, the first element in the template function The sampling point and the first sampling point in the brightness sequence =n+ The corresponding calculations are performed for each pixel position.

[0103] At each sampling location At this point, the translation amount corresponding to the maximum value of the normalized cross-correlation function is taken as the coarse localization result of the laser stripe center: = This yields a set of coarse positioning points for the center of the laser stripe at multiple locations: The coarse positioning result is used to limit the search range of the laser stripe center in the subsequent fine positioning step.

[0104] S4.4. At each sampling location The corresponding coarse positioning result obtained in step S4.3 is used at this location. Centered on the laser stripe, a local search area is selected along the direction perpendicular to the laser stripe extension. ,in, The preset search half-width;

[0105] Within the local search range, extract local brightness data. ;

[0106] Within the local search interval, a Gaussian model is used to model the brightness distribution of the laser stripes in the vertical direction. The expression is:

[0107]

[0108] in, This refers to the amplitude parameter of the stripe brightness. The sub-pixel coordinates are the center position of the laser stripe. The lateral width parameter of the laser stripe. Background biased items;

[0109] Using the least squares criterion, local brightness data With Gaussian model Perform fitting and solve for the model parameters. ;

[0110] After fitting, take As sampling location Precise positioning results of the center of the laser stripe ,Right now For all sampling locations Performing the above steps separately yields a set of sub-pixel-level positioning points for the laser stripe: M is the total number of sampling locations;

[0111] S4.5. Perform overall construction and smoothing on the discrete center positioning points in the sub-pixel-level positioning point set of the laser stripe to construct the laser stripe center point sequence. A consistency check is performed on the laser stripe center point sequence to remove outliers that significantly deviate from the local trend.

[0112] Furthermore, a judgment is made based on the change in position between adjacent center points, when the following conditions are met: When this happens, the corresponding center point is identified as an outlier and removed. This is a preset threshold.

[0113] Then, a polynomial function was used to fit the sequence of laser stripe center points after the consistency check: ,in, To represent the vertical coordinate of the laser stripe center line in the image, Let be the order of the polynomial. These are the fitting coefficients. Let x be the j-th power of the abscissa x; based on the fitting results, the expression for the center line of the laser stripe is: The center line of the laser stripe is used as the final stripe extraction result;

[0114] S4.6. For the L acquired images, process them according to the methods in steps S4.2-S4.5 to obtain the continuous representation of the laser stripe center in the image coordinate system at different times.

[0115] For the center line of the laser stripe in the t-th frame image 1 t , Let be the center line of the laser stripe for the t-th frame of the image. 1 t , Let be the vertical coordinate value of the center line of the laser stripe in the t-th frame of the image;

[0116] The feature positions used to characterize the overall position in the center line area are determined by statistically analyzing the coordinates of the center line in the direction of stripe extension.

[0117]

[0118] in, Let be the sub-pixel ordinate of the i-th center point in the t-th frame of the image. The feature location of the t-th frame image;

[0119] By performing difference calculations on the feature locations obtained from two consecutive image frames, the displacement of the stripes in the pixel coordinate system can be obtained. :

[0120]

[0121] Then calculate the actual speed. for:

[0122]

[0123] in, The time interval between two adjacent frames;

[0124] For any two consecutive frames of images, calculate the velocity according to step S4.6, and average all velocities to obtain the final high-speed flow velocity based on stripe imaging.

[0125] It should be noted that relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0126] Although this application has been described above with reference to specific embodiments, various modifications can be made and components can be replaced with equivalents without departing from the scope of this application. In particular, as long as there is no structural conflict, the features in the specific embodiments disclosed in this application can be combined with each other in any way. The lack of an exhaustive description of these combinations in this specification is merely for the sake of brevity and resource conservation. Therefore, this application is not limited to the specific embodiments disclosed herein.

Claims

1. A streak imaging based high speed flow velocity acquisition method, characterized in that, Includes the following steps: S1. Establish a measurement system; In step S1, the measurement system is as follows: the laser emitted by the femtosecond laser (1) is reflected by mirror I (3) and mirror II (4) and then enters the multi-pass compressor (2). The laser emitted again is reflected by mirror III (5), and then enters the target area in the vacuum chamber after passing through the plano-concave lens (6) and plano-convex lens (7). The femtosecond laser (1) is connected to the synchronization signal generator (13). The synchronization signal generator (13) triggers the high-speed camera (8) and the image intensifier (9). The high-speed camera (8) is connected to the image intensifier (9). The image intensifier (9) is connected to the telephoto lens (10). The high-speed camera (8) is connected to the computer device (12). S2. Construct a timing control and multi-delay gating acquisition method, set the image intensifier (9) to be gated and opened sequentially under different delay conditions, and synchronously acquire the laser stripe image corresponding to each delay time; S3. Calculate the scale conversion parameters. Under imaging conditions consistent with actual measurements, acquire a calibration image containing the calibration target with known geometric dimensions. This image is used to establish the correspondence between image pixel coordinates and actual physical dimensions. The resulting correspondence between image pixel coordinates and actual physical dimensions is the scale conversion parameter. ; S4. Using the timing control and multi-delay gating acquisition method in step S2, images are acquired based on the measurement system, and image processing is performed based on the correspondence between the image pixel coordinates and the actual physical size obtained in step S3 to calculate the high-speed flow velocity based on stripe imaging. The specific implementation method of step S4 includes the following steps: S4.

1. Following the timing control in step S2, acquire L images, let I... For any one of these images, x represents the pixel coordinates in the horizontal direction and y represents the pixel coordinates in the vertical direction. S4.

2. For I Background correction and noise reduction smoothing are performed to obtain the corrected image. The expression is: =I - ； in, Images acquired under laser-free conditions; Then to After smoothing, the following is obtained: ； in, The image after smoothing. This represents the convolution operation. It is a two-dimensional smoothing kernel function; S4.

3. For the smoothed image, coordinate transformation or image rotation is used to make the overall extension direction of the laser stripes consistent with the horizontal direction of the image. Then, the normalized cross-correlation function is calculated using the brightness sequence and template function. The translation amount corresponding to the maximum value of the normalized cross-correlation function is taken as the coarse localization result of the laser stripe center. The coarse localization of the laser stripe center is performed to obtain a set of coarse localization points of the laser stripe center at multiple locations. S4.

4. At each sampling location The corresponding coarse positioning result obtained in step S4.3 is used at this location. Centered on the laser stripe, a local search area is selected along the direction perpendicular to the laser stripe extension. ,in, The preset search half-width; Within the local search range, extract local brightness data. ; Within the local search interval, a Gaussian model is used to model the brightness distribution of the laser stripes in the vertical direction. The expression is: ； in, This refers to the amplitude parameter of the stripe brightness. The sub-pixel coordinates are the center position of the laser stripe. The lateral width parameter of the laser stripe. Background biased items; Using the least squares criterion, local brightness data With Gaussian model Perform fitting and solve for the model parameters. ; After fitting, take As sampling location Precise positioning results of the center of the laser stripe ,Right now For all sampling locations Performing the above steps respectively yields a set of sub-pixel-level positioning points for the laser stripe: M is the total number of sampling locations; S4.

5. Perform overall construction and smoothing on the discrete center positioning points in the sub-pixel-level positioning point set of the laser stripe to construct the laser stripe center point sequence. A consistency check is performed on the laser stripe center point sequence to remove outliers that significantly deviate from the local trend. Then, a polynomial function was used to fit the sequence of laser stripe center points after the consistency check: ,in, This represents the vertical coordinate value of the center line of the laser stripe in the image. Let be the order of the polynomial. These are the fitting coefficients. Let x be the j-th power of the abscissa x. Based on the fitting results, the expression for the center line of the laser stripe is: The center line of the laser stripe is used as the final stripe extraction result; S4.

6. For the L acquired images, process them according to the methods in steps S4.2-S4.5 to obtain the continuous representation of the laser stripe center in the image coordinate system at different times. For the center line of the laser stripe in the t-th frame image 1 t , Let be the vertical coordinate value of the center line of the laser stripe in the t-th frame of the image; The feature positions used to characterize the overall position in the center line area are determined by statistically analyzing the coordinates of the center line in the direction of stripe extension. ； in, Let be the sub-pixel ordinate of the i-th center point in the t-th frame of the image. The feature location of the t-th frame image; By performing difference calculations on the feature locations obtained from two consecutive image frames, the displacement of the stripes in the pixel coordinate system can be obtained. : ； Then calculate the actual speed. for: ； in, The time interval between two adjacent frames; For any two consecutive frames of images, calculate the velocity according to step S4.6, and average all velocities to obtain the final high-speed flow velocity based on stripe imaging.

2. The method for obtaining high-speed flow velocity based on stripe imaging according to claim 1, characterized in that, In step S1, the high-speed camera (8) and image intensifier (9) are mounted on the fixed device (11); the telephoto lens (10) is aimed at the target area in the vacuum chamber.

3. The method for obtaining high-speed flow velocity based on stripe imaging according to claim 2, characterized in that, The fixing device (11) in step S1 includes an image intensifier mounting plate (14) and a camera mounting platform (15). The image intensifier mounting plate (14) is a rectangular plate. The camera mounting platform (15) is installed on the right half of the image intensifier mounting plate (14). Both the image intensifier mounting plate (14) and the camera mounting platform (15) are provided with multiple hollowed-out grooves extending in a direction parallel to the long side of the fixing device (11).

4. The method for obtaining high-speed flow velocity based on stripe imaging according to claim 3, characterized in that, In step S2, within each exposure cycle, the image intensifier (9) is gated according to different time delay strategies; the first gate of the image intensifier (9) is performed simultaneously with the triggering of the femtosecond laser (1), followed by gated opening at fixed time intervals. The gating is opened sequentially and delayed, such as the gating time of the intensifier (9) is as follows: Set up to acquire n frames of images, the nth frame... The secondary gate opening time is , =1,2, .

5. The method for obtaining high-speed flow velocity based on stripe imaging according to claim 4, characterized in that, Step S3: Scale Conversion Parameters This is used for converting subsequent measurement results from pixel scale to physical scale.

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