Wall Shear Stress Measurement Method Based on Event Camera and Micro-cylinder Sensor

Abstract

This invention relates to the field of stress measurement technology, specifically to a method for measuring wall shear stress based on an event camera and a micro-cylindrical sensor. This method is used to measure wall shear stress in a flow field and includes: setting the installation position of the micro-cylindrical sensor; setting the light threshold of the event camera; acquiring the pixel position of the bright spot at the top of the micro-cylindrical sensor and the position of the marker point on its substrate at the initial moment based on the event camera; acquiring the pixel position of the bright spot at the top of the micro-cylindrical sensor during operation; and obtaining the wall shear stress in the flow field based on the offset of the bright spot at the top of the micro-cylindrical sensor and the curve between the wall shear stress and the offset of the bright spot at the top of the micro-cylindrical sensor. This invention can significantly improve the detection efficiency of the micro-cylindrical sensor, avoid the problem of uneven LED lighting, and effectively avoid the post-processing difficulties caused by simultaneous illumination from the top and bottom of the micro-cylindrical sensor after lighting.

Description

Technical Field

[0001] This invention relates to the field of stress measurement technology, and specifically to a method for measuring wall shear stress based on an event camera and a micro-cylinder sensor. Background Technology

[0002] Wall shear stress is the viscous resistance generated by a fluid passing over the surface of an object. In fluid mechanics, the spatiotemporal distribution of wall shear stress is key information for the interaction between near-wall turbulent structures. In medicine, wall shear stress is an important parameter in hemodynamics, closely related to the occurrence of diseases such as atherosclerosis. Current methods for measuring wall shear stress include direct and indirect methods. The microcylinder sensor method, an indirect method, utilizes optics for measurement. A high-speed CCD camera is used to optically detect the deflection at the tip of the microcylinder sensor. By combining the linear relationship between the sensor tip deflection and the local wall shear stress, the two-dimensional spatiotemporal distribution of wall shear stress in the measurement area and the instantaneous wall shear stress value can be obtained.

[0003] However, current microcylindrical sensor methods still have some shortcomings: First, traditional microcylindrical sensor methods rely on high-speed CCD camera imaging, which is limited by the CCD camera, resulting in a large amount of acquired image data and time-consuming data reading and writing. Second, due to the massive amount of image data acquired, real-time transmission and processing of image data is very difficult. Third, in optical detection schemes using high-speed CCD cameras, researchers employ LED illumination methods. The image quality acquired by the high-speed CCD camera is greatly affected by the uniformity of ambient LED lighting, and manually adjusting the lighting angle is time-consuming and laborious. Researchers have also used methods such as laser excitation of top fluorescent markers or laser illumination of reflective particles at the top of the microcylindrical sensor. However, because microcylindrical sensors made of transparent elastomer materials have characteristics similar to optical fibers, the top and bottom of the microcylindrical sensor may emit light simultaneously, making it difficult to accurately identify the deflection at the top of the microcylindrical sensor through post-processing and manual identification. Therefore, the aforementioned microcylindrical sensors and measurement schemes are not suitable for event camera detection.

[0004] An event camera is a bionic camera that outputs only brightness changes exceeding a set threshold. It boasts advantages such as low latency (<1 microsecond), high dynamic range (140dB), small data size, and extremely low power consumption (1mW). The event camera asynchronously measures the brightness change of each pixel, and the event camera's light-sensitive threshold... When the brightness change exceeds the threshold At any given time, the event camera sends an event consisting of the X and Y position of a pixel, time T, and a changing polarity P (i.e., brightness increase ("+1") or decrease ("-1")). Event information is output only when the received light intensity changes, and a series of event data is output, making it ideal for recording displacement detection of microcylindrical sensors with a bright spot marked at the top. Because the event camera has a high dynamic range and is sensitive to brightness changes, it can effectively output data in both bright and dark scenes. Furthermore, recording only the event data related to brightness changes consumes very little bandwidth, enabling real-time processing capabilities.

[0005] In conclusion, deeply exploring the unique advantages of event cameras to empower optical measurements of microcylindrical sensors is not only a cutting-edge challenge, but also an urgent need and an important development direction for propelling the measurement capabilities of microcylindrical sensors to new heights. We urgently need to explore how to utilize event cameras to achieve real-time and accurate wall shear force measurement of microcylindrical sensors. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention provides a method for measuring wall shear stress based on an event camera and a micro-cylindrical sensor. This method employs a high-contrast micro-cylindrical sensor suitable for event cameras, which can significantly improve the detection efficiency of the micro-cylindrical sensor, avoid the problem of uneven LED lighting, and effectively solve the post-processing problem of simultaneous illumination from the top and bottom of the micro-cylindrical sensor in traditional methods that use laser to excite the top fluorescent marker or laser to illuminate the reflective particles at the top of the micro-cylindrical sensor.

[0007] The first objective of this invention is to provide a method for measuring wall shear stress based on an event camera and a micro-cylinder sensor, used for measuring wall shear stress in a flow field, comprising:

[0008] Set the installation position of the microcylindrical sensor, install it at the measurement position in the flow field, place the event camera face to face with the microcylindrical sensor, use a laser to excite the fluorescent marker point on the top of the microcylindrical sensor, and make the event camera focus on the fluorescent marker point on the top of the microcylindrical sensor.

[0009] Set the event camera light threshold;

[0010] The curve between the wall shear stress and the offset of the bright spot at the top of the micro-cylinder sensor was obtained by calibrating the micro-cylinder sensor.

[0011] Based on the event camera, the pixel position of the bright spot at the top of the micro-cylindrical sensor and the position of the marker point on its substrate are acquired at the initial moment; and the pixel position of the bright spot at the top of the micro-cylindrical sensor is acquired during the working state.

[0012] Based on the pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment and the pixel position of the bright spot at the top of the micro-cylindrical sensor in the working state, the offset of the bright spot at the top of the micro-cylindrical sensor is obtained.

[0013] The wall shear stress in the flow field is obtained by using the offset of the bright spot at the top of the micro-cylindrical sensor and the curve between the wall shear stress and the offset of the bright spot at the top of the micro-cylindrical sensor.

[0014] Preferably, the event camera light threshold is set according to the following steps:

[0015] A stable inflow is applied to the flow field, the event camera is turned on, and then the laser is turned on to excite the fluorescent marker at the top of the micro-cylindrical sensor. After continuous excitation for 1 to 2 seconds, the laser is turned off. After waiting for 1 to 2 seconds, the event camera is turned off, the event data is exported, and the curve with the timestamp on the horizontal axis and the number of events corresponding to the timestamp on the vertical axis is obtained. The n repeated operations are recorded as n cycles.

[0016] Count the number of events before T0. These events represent background noise events. Adjust the camera light threshold based on the number of background noise events before T0. .

[0017] Preferably, the pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment is obtained according to the following steps:

[0018] During initial parameter acquisition, first activate the event camera, then activate the laser to excite the fluorescent marker at the top of the micro-cylindrical sensor. After excitation for 1 to 2 seconds, turn off the laser. Repeat this process n times while keeping the event camera active. These n repetitions constitute n acquisition cycles. Generally, [the sequence is not specified in the original text]. Wait 1 to 2 seconds and then turn off the event camera;

[0019] Export the event data collected by the event camera, plot the x-axis as timestamp and the y-axis as the number of events corresponding to the timestamp, and obtain a curve of the number of events corresponding to the timestamp;

[0020] Based on the curve of the number of events corresponding to the timestamps, and cropping the non-measurement area image according to the sensor's field of view, background noise is removed. The two-dimensional kernel density value of each event timestamp is calculated, and the threshold is adjusted to remove event stream information in the two-dimensional kernel density value region below the threshold, thus completing the removal of background noise events on timestamps T3 to T4. Then, events with polarity P=-1 between T3 and T4 are superimposed on the two-dimensional pixel space. The K-means clustering algorithm is used to classify the events. The number of clusters is set, the initial position of the cluster center is manually marked, and the Euclidean distance from each cluster object to the cluster center is calculated for division. For each cluster, its cluster center is recalculated. The new cluster center is the mean of all data points in the cluster. The calculation continues until the maximum number of iterations is reached. Otherwise, the calculation continues. The cluster centers of each class are the pixel positions of the bright spots at the top of the micro-cylindrical sensor at the initial moment.

[0021] Preferably, the number of clusters is the sum of the number of microcylindrical sensors in the field of view and the number of fluorescent markers on the substrate.

[0022] Preferably, the pixel position of the bright spot at the top of the micro-cylindrical sensor in the working state is obtained according to the following steps:

[0023] After the flow field is activated and the incoming flow velocity stabilizes, the event camera is activated to collect event data. After 1 to 2 seconds, the continuous laser is activated to excite the fluorescent marker point at the top of the micro-cylindrical sensor. The data collection time is t.

[0024] Export the event data and plot a curve showing the number of events corresponding to the timestamps;

[0025] Remove background noise from the exported event data.

[0026] Using the K-means clustering algorithm, positive and negative polarity events in the stable measurement timestamp intervals are processed separately to obtain the centroid positions of the positive and negative polarity event clusters, which are the pixel positions of the bright spots at the top of the micro-cylindrical sensor in the working state.

[0027] Preferably, the offset of the bright spot at the top of the micro-cylindrical sensor is obtained by subtracting the pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment from the pixel position of the bright spot at the top of the micro-cylindrical sensor in the working state.

[0028] Preferably, when the influence of environmental vibration is considered in the flow field, the offset of the bright spot at the top of the micro-cylindrical sensor is as follows:

[0029] The laser shutdown timestamp event should be entirely composed of negative polarity events in the environment. The negative polarity event positions of the substrate fluorescent markers are obtained through pixel location. These positions are then pushed forward by timestamp to obtain the negative polarity event positions of the substrate fluorescent markers at each timestamp. The negative polarity event positions of the substrate fluorescent markers at each timestamp are then... Subtract the position of the marker point on the base at the initial time ( )have to and Then, subtract the pixel position of the bright spot at the top of the microcylindrical sensor at the initial moment from the centroid position of the positive polarity event of the microcylindrical sensor at each timestamp. )have to and ,so and These are the lateral and longitudinal offsets of the top of the micro-cylindrical sensor after environmental factors affect it.

[0030] Preferably, the microcylindrical sensor is manufactured according to the following steps:

[0031] (1) Mix PDMS prepolymer and curing agent in a ratio of 10:1, mix carbon black powder into PDMS, stir thoroughly with a magnetic stirrer to form a carbon black PDMS gel mixture, and put it into a vacuum pump for degassing.

[0032] (2) Pour the carbon black PDMS gel mixture obtained in step (1) into a pre-processed demolding mold, and then heat it in a heating furnace at 30 degrees Celsius for 24 hours;

[0033] (3) After the carbon black PDMS gel mixture has cured, the demolding mold is peeled off to obtain the black micro cylindrical sensor and its substrate;

[0034] (4) Dip the micro cylindrical sensor in a mixture of PDMS and fluorescent microspheres to form a match head-shaped mark on the top of the micro cylindrical sensor, and then place it in a heating furnace at 30°C for 24 hours.

[0035] (5) Use a microneedle to dip into the mixture of PDMS and fluorescent microspheres on the downstream side of the micro cylindrical sensor array and mark it on the substrate surface of the micro cylindrical sensor. Then cure at room temperature in the dark for 72 hours.

[0036] The second objective of this invention is to provide a wall shear stress measurement system based on an event camera and a micro-cylinder sensor, comprising:

[0037] The position marking module is used to set the installation position of the micro-cylindrical sensor, install it at the measurement position in the flow field, place the event camera and the micro-cylindrical sensor face to face, use a laser to excite the fluorescent marker point on the top of the micro-cylindrical sensor, and make the event camera focus on the fluorescent marker point on the top of the micro-cylindrical sensor; and set the light threshold of the event camera.

[0038] The offset curve module is used to calibrate the micro-cylindrical sensor and obtain the curve between the wall shear stress and the offset of the bright spot at the top of the micro-cylindrical sensor.

[0039] The offset acquisition module is used to acquire the pixel position of the bright spot at the top of the micro-cylindrical sensor and the position of the marker point on its substrate at the initial moment based on the event camera; and to acquire the pixel position of the bright spot at the top of the micro-cylindrical sensor in the working state; and to acquire the offset of the bright spot at the top of the micro-cylindrical sensor based on the pixel position of the bright spot at the initial moment and the pixel position of the bright spot at the top of the micro-cylindrical sensor in the working state.

[0040] The stress acquisition module is used to acquire the wall shear stress in the flow field based on the offset of the bright spot at the top of the micro-cylindrical sensor and the curve between the wall shear stress and the offset of the bright spot at the top of the micro-cylindrical sensor.

[0041] A third objective of this invention is to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, performs the steps of the method described above.

[0042] The present invention has at least the following beneficial effects:

[0043] This invention provides a method for measuring wall shear stress based on an event camera and a microcylindrical sensor. This method fully utilizes the advantages of the event camera—low latency (<1 microsecond), high dynamic range (140dB), small data volume, and extremely low power consumption (1mW)—to achieve real-time, high-precision measurement using the microcylindrical sensor. The high-contrast microcylindrical sensor employed in this invention significantly improves the detection efficiency of the microcylindrical sensor, avoids the problem of uneven LED lighting, and effectively avoids the post-processing difficulties caused by simultaneous illumination from the top and bottom of the microcylindrical sensor after illumination. Attached Figure Description

[0044] Figure 1 This invention provides a curve showing the number of events corresponding to a timestamp T.

[0045] Figure 2 is a schematic diagram of events on the event camera timestamp in this invention. Detailed Implementation

[0046] To illustrate the technical means and effects adopted by the present invention in order to achieve the intended purpose, the following detailed description is provided in conjunction with embodiments.

[0047] The purpose of this invention is to provide a method for measuring wall shear stress based on an event camera and a micro-cylindrical sensor. The high-contrast micro-cylindrical sensor using an event camera can significantly improve the detection efficiency of the micro-cylindrical sensor, avoid the problem of uneven LED lighting, and effectively solve the post-processing problem of simultaneous illumination at the top and bottom of the micro-cylindrical sensor in previous methods that used laser excitation of top fluorescent markers or laser illumination of reflective particles at the top of the micro-cylindrical sensor.

[0048] To achieve the above objectives, a method for measuring wall shear stress based on an event camera and a micro-cylinder sensor is provided for measuring wall shear stress in a flow field, comprising:

[0049] S1. Set the installation position of the micro-cylindrical sensor, install it at the measurement position in the flow field, place the event camera face to face with the micro-cylindrical sensor, use a laser to excite the fluorescent marker point on the top of the micro-cylindrical sensor, and make the event camera focus on the fluorescent marker point on the top of the micro-cylindrical sensor.

[0050] The microcylindrical sensor is fabricated according to the following steps:

[0051] (1) Mix PDMS prepolymer and curing agent in a ratio of 10:1, mix carbon black powder into PDMS, stir thoroughly with a magnetic stirrer to form a carbon black PDMS gel mixture, and put it into a vacuum pump for degassing.

[0052] (2) Pour the carbon black PDMS gel mixture obtained in step (1) into a pre-processed demolding mold, and then heat it in a heating furnace at 30 degrees Celsius for 24 hours;

[0053] (3) After the carbon black PDMS gel mixture has cured, the demolding mold is peeled off to obtain the black micro cylindrical sensor and its substrate;

[0054] (4) Dip the micro cylindrical sensor in a mixture of PDMS and fluorescent microspheres to form a match head-shaped mark on the top of the micro cylindrical sensor, and then place it in a heating furnace at 30°C for 24 hours.

[0055] (5) Use a microneedle to dip into the mixture of PDMS and fluorescent microspheres on the downstream side of the micro cylindrical sensor array and mark it on the substrate surface of the micro cylindrical sensor. Then cure at room temperature in the dark for 72 hours.

[0056] In one embodiment, a method for manufacturing a high-contrast microcylindrical sensor suitable for event cameras includes the following steps:

[0057] (1) Mix PDMS prepolymer and curing agent in a ratio of 10:1, mix carbon black powder into PDMS, stir thoroughly with a magnetic stirrer to form a carbon black PDMS gel mixture, and put it into a vacuum pump for degassing.

[0058] (2) Pour the carbon black PDMS gel mixture obtained in step (1) into a pre-processed demolding mold, and then heat it in a heating furnace at 30 degrees Celsius for 24 hours.

[0059] (3) After the carbon black PDMS gel mixture has solidified, the demolding mold is peeled off to obtain a black micro cylindrical sensor and its substrate.

[0060] (4) Dip the micro cylindrical sensor in a mixture of PDMS and fluorescent microspheres to form a match head-shaped mark on the top of the micro cylindrical sensor, and then heat it in a heating furnace at 30 degrees Celsius for 24 hours.

[0061] (5) Use a microneedle (tip diameter 20um) to dip into the mixture of PDMS and fluorescent microspheres on the downstream (relative to the incoming flow) side of the micro cylindrical sensor array, mark it on the substrate surface of the micro cylindrical sensor, and then cure it at room temperature in the dark for 72h.

[0062] S2, Set the event camera light threshold;

[0063] The event camera light threshold is set according to the following steps:

[0064] A stable inflow is applied to the flow field, the event camera is turned on, and then the laser is turned on to excite the fluorescent marker at the top of the micro-cylindrical sensor. After continuous excitation for 1 to 2 seconds, the laser is turned off. After waiting for 1 to 2 seconds, the event camera is turned off, the event data is exported, and the curve with the timestamp on the horizontal axis and the number of events corresponding to the timestamp on the vertical axis is obtained. The n repeated operations are recorded as n cycles.

[0065] Count the number of events before T0. These events represent background noise events. Adjust the camera light threshold based on the number of background noise events before T0. .

[0066] S3. Calibrate the micro-cylindrical sensor to obtain the curve between the wall shear stress and the offset of the bright spot at the top of the micro-cylindrical sensor;

[0067] Based on the event camera, the pixel position of the bright spot at the top of the micro-cylindrical sensor and the position of the marker point on its substrate are acquired at the initial moment; and the pixel position of the bright spot at the top of the micro-cylindrical sensor is acquired during the working state.

[0068] The pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment is obtained according to the following steps:

[0069] During initial parameter acquisition, first activate the event camera, then activate the laser to excite the fluorescent marker at the top of the micro-cylindrical sensor. After excitation for 1 to 2 seconds, turn off the laser. Repeat this process n times while keeping the event camera active. These n repetitions constitute n acquisition cycles. Generally, [the sequence is not specified in the original text]. Wait 1 to 2 seconds and then turn off the event camera;

[0070] Export the event data collected by the event camera, plot the x-axis as timestamp and the y-axis as the number of events corresponding to the timestamp, and obtain a curve of the number of events corresponding to the timestamp;

[0071] Based on the curve showing the number of events corresponding to timestamps, and cropping the non-measurement area image according to the sensor's field of view, background noise is removed. The two-dimensional kernel density value for each event timestamp is calculated, and a threshold is adjusted to remove event stream information from regions with kernel density values ​​below the threshold. This completes the removal of background noise events at timestamps T3 to T4. Then, events with polarity P=-1 between T3 and T4 are superimposed on the two-dimensional pixel space. K-means clustering is used to classify the events, setting the number of clusters, manually marking the initial positions of the cluster centers, and calculating the Euclidean distance from each cluster object to its center. For each cluster, its cluster center is recalculated; the new cluster center is the mean of all data points within that cluster. This process continues until the maximum number of iterations is reached, at which point the calculation stops; otherwise, it continues. The resulting cluster centers represent the pixel positions of the bright spots at the top of the micro-cylindrical sensors at the initial moment. The number of clusters is the sum of the number of micro-cylindrical sensors in the field of view and the number of substrate fluorescent markers.

[0072] The pixel position of the bright spot at the top of the micro-cylindrical sensor in the working state is obtained according to the following steps:

[0073] After the flow field is activated and the incoming flow velocity stabilizes, the event camera is activated to collect event data. After 1 to 2 seconds, the continuous laser is activated to excite the fluorescent marker point at the top of the micro-cylindrical sensor. The data collection time is t.

[0074] Export the event data and plot a curve showing the number of events corresponding to the timestamps;

[0075] Remove background noise from the exported event data.

[0076] Using the K-means clustering algorithm, positive and negative polarity events in the stable measurement timestamp intervals are processed separately to obtain the centroid positions of the positive and negative polarity event clusters, which are the pixel positions of the bright spots at the top of the micro-cylindrical sensor in the working state.

[0077] S4. Based on the pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment and the pixel position of the bright spot at the top of the micro-cylindrical sensor in the working state, obtain the offset of the bright spot at the top of the micro-cylindrical sensor.

[0078] The offset of the bright spot at the top of the micro-cylindrical sensor is obtained by subtracting the pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment from the pixel position of the bright spot at the top of the micro-cylindrical sensor in the working state.

[0079] When the influence of environmental vibration is considered in the flow field, the offset of the bright spot at the top of the micro-cylindrical sensor is as follows:

[0080] The laser shutdown timestamp event should be entirely composed of negative polarity events in the environment. The negative polarity event positions of the substrate fluorescent markers are obtained through pixel location. These positions are then pushed forward by timestamp to obtain the negative polarity event positions of the substrate fluorescent markers at each timestamp. The negative polarity event positions of the substrate fluorescent markers at each timestamp are then... Subtract the position of the marker point on the base at the initial time ( )have to and Then, subtract the pixel position of the bright spot at the top of the microcylindrical sensor at the initial moment from the centroid position of the positive polarity event of the microcylindrical sensor at each timestamp. )have to and ,so and These are the lateral and longitudinal offsets of the top of the micro-cylindrical sensor after environmental factors affect it.

[0081] S5. Based on the offset of the bright spot at the top of the micro-cylindrical sensor and the curve between the wall shear stress and the offset of the bright spot at the top of the micro-cylindrical sensor, obtain the wall shear stress in the flow field.

[0082] To illustrate the wall shear stress measurement method based on an event camera and a micro-cylinder sensor provided by the present invention, further explanation is provided in conjunction with the accompanying drawings.

[0083] A method for measuring wall shear stress based on an event camera and a micro-cylinder sensor, comprising:

[0084] Step 1: Set up the experimental environment. Using the high-contrast microcylindrical sensor manufactured according to technical solution one, suitable for the event camera, install it at the measurement location in a wind tunnel or water tunnel. Place the event camera and the microcylindrical sensor face-to-face, and attach a filter to the front of the event camera lens. Use a 540nm long-pass filter (allowing only light with wavelengths >540nm to pass through). Cover the area outside the camera's light path with a black light-blocking cloth, and turn off the ambient light source. Use a laser (a high-frequency laser with a wavelength of 532nm and a frequency >15000Hz) to excite the fluorescent marker at the top of the microcylindrical sensor and the marker on its substrate. Focus the event camera on the fluorescent marker at the top of the microcylindrical sensor, and then calibrate the event camera using a dynamic calibration board.

[0085] Step 2: Initial Parameter Acquisition. Acquire the pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment. ) and the location of the marker points on its base ( ), where i and j represent the row and column numbers in the micro-cylindrical sensor array, and 0 represents the initial time.

[0086] Before starting initial parameter acquisition, it is necessary to set the focus and the light threshold of the event camera. A laser is used to excite the fluorescent marker at the top of the microcylindrical sensor, causing the event camera to automatically focus on the stationary bright spot at the top of the microcylindrical sensor.

[0087] The steps for setting the light threshold of the event camera are as follows: Apply a stable incoming flow in the water tunnel or wind tunnel experimental environment, turn on the event camera to acquire data, then turn on the laser to excite the fluorescent marker at the top of the micro-cylindrical sensor, continue excitation for 1 to 2 seconds, then turn off the laser, wait 1 to 2 seconds, and then turn off the event camera. Export the event data (X, Y, T, P), and plot the x-axis as timestamp T and the y-axis as the number of events corresponding to timestamp T. A typical curve of the number of events corresponding to timestamp T is shown below. Figure 1 As shown, let n repeated operations be denoted as n cycles. Figure 1 The example uses idealized statistical data for one period. First, the number of events before T0 is counted; this represents background noise events. The event camera light threshold C is then adjusted based on the number of background noise events before T0. .

[0088] During initial parameter acquisition, first activate the event camera, then activate the laser to excite the fluorescent marker at the top of the micro-cylindrical sensor. After excitation for 1 to 2 seconds, turn off the laser. Repeat this process n times while keeping the event camera active. These n repetitions constitute n acquisition cycles. Generally, [the sequence is not specified in the original text]. Wait 1 to 2 seconds and then close the event camera. Export the event data (X, Y, T, P) collected by the event camera, and plot the graph with the horizontal axis representing the timestamp T and the vertical axis representing the number of events corresponding to timestamp T. A typical curve showing the number of events corresponding to timestamp T over one acquisition period is shown below. Figure 1 As shown. Based on the approximate range of the sensor's field of view, the image of the non-measurement area is cropped, then background noise is removed. The two-dimensional kernel density value of each event timestamp is calculated, and the threshold is adjusted appropriately to remove event stream information in the region with a two-dimensional kernel density value below the threshold, thus completing the removal of background noise events at timestamps T3 to T4. Then, events with polarity P=-1 between T3 and T4 are superimposed on the two-dimensional pixel space. The K-means clustering algorithm is used to classify the events. The number of clusters K is set as the number of micro-cylindrical sensors in the field of view + the number of substrate fluorescent markers. The initial position of the cluster center is manually marked, and the Euclidean distance from each cluster object to the cluster center is calculated for division. For each cluster, its cluster center is recalculated. The new cluster center is the mean of all data points in the cluster. The calculation continues until the maximum number of iterations is reached. The cluster center of each class is the pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment. ).

[0089] Step 3: Collect the pixel position of the bright spot at the top of the micro-cylindrical sensor in working condition. The superscript 1 indicates the working state. Under the action of fluid force, the top of the micro-cylindrical sensor shifts, and ideally, the image is formed in the field of view of the event camera as shown in the diagram. Figure 2 As shown, white dots represent positive events, and black dots represent negative events. Therefore, the white dots in the left image are timestamps. Positive events at a given moment; the green dots in the right-hand image represent timestamps. Negative events at a given moment; the white dots in the right image represent timestamps. A positive polarity event at a given moment.

[0090] like Figure 2 As shown, the images were captured by the event camera; the left image is... Moment events ( , , P =+1), the right figure is Moment events ( , , P =+1 (white), -1 (green)); Figure 2 In the middle, timestamp The pixel position of a negative polarity event represents the timestamp of the previous event. The position of the fluorescent marker at the top of the micro-cylindrical sensor, and the timestamp. The pixel position of a positive polarity event represents the current event timestamp. The new position of the fluorescent marker at the top of the micro-cylindrical sensor under the action of fluid force. This is under conditions of no environmental vibration or where environmental vibration is not considered. Positive polarity events at any moment The positions of negative events at any given time should be consistent. Through comprehensive analysis, the pixel positions of the fluorescent markers at the top of the micro-cylindrical sensor are obtained. The method is as follows:

[0091] Experiment: After the water tunnel or wind tunnel is turned on and the free flow velocity stabilizes, the event camera is turned on to collect event data. After 1 to 2 seconds, the continuous laser is turned on to excite the fluorescent marker at the top of the micro-cylindrical sensor. The collection time is t. After completing a set of collections, the continuous laser, the event camera, and the water tunnel or wind tunnel are turned off in sequence.

[0092] Export the event data (X, Y, T, P), and plot the graph with timestamp T on the x-axis and the number of events corresponding to timestamp T on the y-axis. A typical curve showing the number of events corresponding to timestamp T is shown below. Figure 1 As shown.

[0093] Background noise removal: For event cameras that only output (X,Y,T,P), background noise is removed using the classic spatiotemporal correlation filter method described in step two.

[0094] Cluster analysis: such as Figure 1 At timestamp T2, two scenarios exist in actual measurements: 1) The deflection at the top of the micro-cylindrical sensor is small, resulting in an orange area where positive and negative polarity events overlap; 2) The deflection at the top of the micro-cylindrical sensor is large, and no overlap area exists. For the first scenario, the event polarity in the orange overlap area is approximately randomly distributed. Therefore, the processing method is essentially the same as for the second scenario: using the K-means clustering algorithm to process the stable measurement timestamp intervals separately, for example... Figure 2 For events of positive and negative polarity in the T3 to T4 timestamp interval, the centroid position of the positive and negative polarity event cluster is obtained.

[0095] When the vibration of the measurement environment is negligible, the algorithm for the offset of the top of a single micro-cylinder sensor at each time stamp is as follows: In step four, cluster analysis obtains the centroid positions of positive and negative polarity events at the same time stamp. The centroid position of the positive polarity event minus the centroid position of the negative polarity event is the offset of the top of a single micro-cylinder sensor.

[0096] Considering the influence of environmental vibration, the algorithm for the offset of the top of a single micro-cylinder sensor at each time stamp is as follows: For the laser-off time stamp event, the environment should consist entirely of negative events. The negative event positions of the substrate fluorescent markers are obtained by approximate pixel location regions. By pushing forward according to the time stamp, the negative event positions of the substrate fluorescent markers at each time stamp are obtained. The negative event positions of the substrate fluorescent markers at each time stamp are then... Subtract the position of the marker point on the base at the initial time ( )have to and Then, subtract the pixel position of the bright spot at the top of the microcylindrical sensor at the initial moment from the centroid position of the positive polarity event of the microcylindrical sensor at each timestamp. )have to and ,so and These are the lateral and longitudinal offsets of the top of the micro-cylindrical sensor after removing the influence of environmental factors on the micro-cylindrical sensor, with a total offset of... .

[0097] Missing value imputation: For missing events of a single micro-cylindrical sensor on a timestamp, search backwards according to the timestamp until a timestamp event corresponding to the position of the single micro-cylindrical sensor is found. It can be assumed that no brightness change occurred during this period, that is, the micro-cylindrical sensor did not shift its top during this timestamp interval. Therefore, the event on this timestamp is taken as the missing value imputation.

[0098] Step 4: Perform static calibration and measurements on the microcylindrical sensors using the method described in Step 3. Arrange the microcylindrical sensors in a laminar flow field with known wall shear. Use an event camera to capture the position of the top of the microcylindrical sensors. Calculate the time-averaged offset of the top of each microcylindrical sensor under different flow field velocities using the method described in Step 3. Since the wall shear stress and the time-averaged offset of the top of the microcylindrical sensor are linearly related, the following can be obtained: curve, in which Given the wall shear stress with a known flow field, k This is the proportionality coefficient. The proportionality coefficient for each microcylindrical sensor can be calculated.

[0099] The microcylindrical sensors are deployed in a turbulent region for measurement, and the top position of the microcylindrical sensors is captured using an event camera. For the average wall shear stress: the time-averaged offset of the top of each microcylindrical sensor under different flow velocities is calculated using the method described in step three, and then divided by the scaling factor for each microcylindrical sensor. k The time-averaged wall shear stress of each microcylindrical sensor is obtained. The time-averaged wall shear stress of all microcylindrical sensors in the field of view is summed and averaged to obtain the average wall shear stress of the flow in the field of view. For instantaneous wall shear stress, the sensor top offset at the timestamp of each event is obtained using the method described in step three, and then divided by the scaling factor of each microcylindrical sensor. k The instantaneous wall shear stress of each micro-cylindrical sensor is obtained, and the instantaneous changes in the flow field can be analyzed by drawing cloud maps and other means.

[0100] This invention provides a wall shear stress measurement system based on an event camera and a micro-cylinder sensor, comprising:

[0101] The position marking module is used to set the installation position of the micro-cylindrical sensor, install it at the measurement position in the flow field, place the event camera and the micro-cylindrical sensor face to face, use a laser to excite the fluorescent marker point on the top of the micro-cylindrical sensor, and make the event camera focus on the fluorescent marker point on the top of the micro-cylindrical sensor; and set the light threshold of the event camera.

[0102] The offset curve module is used to calibrate the micro-cylindrical sensor and obtain the curve between the wall shear stress and the offset of the bright spot at the top of the micro-cylindrical sensor.

[0103] The offset acquisition module is used to acquire the pixel position of the bright spot at the top of the micro-cylindrical sensor and the position of the marker point on its substrate at the initial moment based on the event camera; and to acquire the pixel position of the bright spot at the top of the micro-cylindrical sensor in the working state; and to acquire the offset of the bright spot at the top of the micro-cylindrical sensor based on the pixel position of the bright spot at the initial moment and the pixel position of the bright spot at the top of the micro-cylindrical sensor in the working state.

[0104] The stress acquisition module is used to acquire the wall shear stress in the flow field based on the offset of the bright spot at the top of the micro-cylindrical sensor and the curve between the wall shear stress and the offset of the bright spot at the top of the micro-cylindrical sensor.

[0105] The present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the above-described method.

[0106] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for measuring wall shear stress based on an event camera and a micro-cylinder sensor, characterized in that, Measurement of wall shear stress in a flow field includes: Set the installation position of the microcylindrical sensor and install it at the measurement position in the flow field. Place the event camera face to face with the microcylindrical sensor, use a laser to excite the fluorescent mark bright spot on the top of the microcylindrical sensor, and make the event camera focus on the fluorescent mark bright spot on the top of the microcylindrical sensor. Set the event camera light threshold; The curve between the wall shear stress and the offset of the fluorescent marker spot at the top of the microcylinder sensor was obtained by calibrating the microcylinder sensor. Based on the event camera, the pixel position of the fluorescent marker spot on the top of the micro-cylindrical sensor and the position of the marker point on the substrate are acquired at the initial moment; and the pixel position of the fluorescent marker spot on the top of the micro-cylindrical sensor is acquired during the working state. Based on the pixel position of the fluorescent marker at the top of the micro-cylindrical sensor at the initial moment and the pixel position of the fluorescent marker at the top of the micro-cylindrical sensor in the working state, the offset of the fluorescent marker at the top of the micro-cylindrical sensor is obtained. The wall shear stress in the flow field is obtained based on the offset of the fluorescent marker spot at the top of the micro-cylinder sensor and the curve between the wall shear stress and the offset of the fluorescent marker spot at the top of the micro-cylinder sensor. The pixel position of the fluorescent marker bright spot at the top of the micro-cylindrical sensor at the initial moment is obtained according to the following steps: During initial parameter acquisition, the event camera is first activated, followed by the laser excitation of the fluorescent marker at the top of the micro-cylindrical sensor. Excitation is maintained for 1-2 seconds, then the laser is turned off while the event camera remains operational. This process is repeated n times, and the n repetitions are defined as n acquisition cycles. Typically, a time interval of n is used. Wait 1 to 2 seconds and then turn off the event camera; Export the event data collected by the event camera, plot the x-axis as timestamp and the y-axis as the number of events corresponding to the timestamp, and obtain a curve of the number of events corresponding to the timestamp; Based on the curve of the number of events corresponding to the timestamp, and cropping the non-measurement area image according to the field of view of the micro-cylindrical sensor, background noise events are removed. The two-dimensional kernel density value of each event timestamp is calculated, and the light threshold is adjusted to remove the event flow information in the two-dimensional kernel density value region below the light threshold. This completes the removal of background noise events on timestamps T3 to T4. Then, events with polarity P=-1 between T3 and T4 are superimposed on the two-dimensional pixel space. The K-means clustering algorithm is used to classify the events. The number of clusters is set, the initial position of the cluster center is manually marked, and the Euclidean distance from each cluster object to the cluster center is calculated for division. For each cluster, its cluster center is recalculated. The new cluster center is the mean of all data points in the cluster. The calculation continues until the maximum number of iterations is reached. Otherwise, the calculation continues. The cluster center of each class is the pixel position of the fluorescent marker bright spot at the top of the micro-cylindrical sensor at the initial moment. The pixel position of the fluorescent marker bright spot at the top of the micro-cylindrical sensor in the working state is obtained according to the following steps: After the flow field is activated and the inflow velocity stabilizes, the event camera is activated to collect event data. After 1 to 2 seconds, the laser is activated to excite the fluorescent marker spot on the top of the micro-cylindrical sensor. The data collection time is t. Export the event data and plot a curve showing the number of events corresponding to the timestamps; Remove background noise events from the exported event data; The K-means clustering algorithm is used to process the positive and negative polarity events in the stable measurement timestamp intervals to obtain the cluster centers of the positive and negative polarity events, which are the pixel positions of the fluorescent marker bright spots on the top of the micro cylindrical sensor in the working state.

2. The method for measuring wall shear stress based on an event camera and a micro-cylinder sensor according to claim 1, characterized in that, The event camera light threshold is set according to the following steps: A stable inflow is applied to the flow field, the event camera is turned on, and then the laser is turned on to excite the fluorescent marker spot on the top of the micro-cylindrical sensor. After continuous excitation for 1 to 2 seconds, the laser is turned off. After waiting for 1 to 2 seconds, the event camera is turned off, the event data is exported, and the curve of the number of events corresponding to the timestamp is plotted with the horizontal axis as the timestamp and the vertical axis as the number of events corresponding to the timestamp. The n repeated operations are recorded as n cycles. Count the number of events before T0. These events represent background noise events. Adjust the event camera light threshold based on the number of background noise events before T0. .

3. The method for measuring wall shear stress based on an event camera and a micro-cylinder sensor according to claim 1, characterized in that, The number of clusters is the sum of the number of microcylindrical sensors in the field of view and the number of fluorescently labeled bright spots on the substrate.

4. The method for measuring wall shear stress based on an event camera and a micro-cylinder sensor according to claim 1, characterized in that, The offset of the fluorescent marker spot at the top of the micro-cylindrical sensor is obtained by subtracting the pixel position of the fluorescent marker spot at the top of the micro-cylindrical sensor at the initial moment from the pixel position of the fluorescent marker spot at the top of the micro-cylindrical sensor in the working state.

5. The method for measuring wall shear stress based on an event camera and a micro-cylinder sensor according to claim 1, characterized in that, When the influence of environmental vibration is considered in the flow field, the offset of the fluorescent marker spot at the top of the micro-cylindrical sensor is as follows: The laser shutdown timestamp event should be entirely composed of negative polarity events in the environment. The negative polarity event positions of the substrate fluorescent marker bright spots are obtained through pixel positions. By pushing forward according to the timestamp, the negative polarity event positions of the substrate fluorescent marker bright spots at each timestamp are obtained. The negative polarity event positions of the substrate fluorescent marker bright spots at each timestamp are then... Subtract the position of the marker point on the base at the initial time ( )have to and Then, subtract the pixel position of the fluorescent marker bright spot at the top of the microcylindrical sensor at the initial moment from the positive polarity event position of the microcylindrical sensor at each timestamp. )have to and ,so and These are the lateral and longitudinal offsets of the top of the micro-cylindrical sensor after environmental factors affect it.

6. The method for measuring wall shear stress based on an event camera and a micro-cylinder sensor according to claim 1, characterized in that, The microcylindrical sensor is fabricated according to the following steps: (1) Mix PDMS prepolymer and curing agent in a ratio of 10:1, mix carbon black powder into PDMS, stir thoroughly with a magnetic stirrer to form a carbon black PDMS gel mixture, and put it into a vacuum pump for degassing. (2) Pour the carbon black PDMS gel mixture obtained in step (1) into a pre-processed demolding mold, and then heat it in a heating furnace at 30 degrees Celsius for 24 hours; (3) After the carbon black PDMS gel mixture has cured, the demolding mold is peeled off to obtain the black micro cylindrical sensor and its substrate; (4) Dip the micro cylindrical sensor in a mixture of PDMS and fluorescent microspheres to form a match head-shaped fluorescent mark spot on the top of the micro cylindrical sensor, and then place it in a heating furnace at 30°C for 24 hours. (5) Use a microneedle to dip into the mixture of PDMS and fluorescent microspheres on the downstream side of the micro cylindrical sensor array and mark it on the substrate surface of the micro cylindrical sensor. Then cure at room temperature in the dark for 72 hours.

7. A wall shear stress measurement system based on an event camera and a micro-cylinder sensor, employing the wall shear stress measurement method as described in any one of claims 1 to 6, characterized in that, include: The position marking module is used to set the installation position of the micro-cylindrical sensor, install it at the measurement position in the flow field, place the event camera face to face with the micro-cylindrical sensor, use a laser to excite the fluorescent mark bright spot on the top of the micro-cylindrical sensor, and make the event camera focus on the fluorescent mark bright spot on the top of the micro-cylindrical sensor; and set the light threshold of the event camera. The offset curve module is used to calibrate the micro-cylindrical sensor and obtain the curve between the wall shear stress and the offset of the fluorescent mark spot at the top of the micro-cylindrical sensor. The offset acquisition module is used to acquire the pixel position of the fluorescent marker bright spot at the top of the micro-cylindrical sensor and the position of the marker point on the substrate at the initial moment based on the event camera; and to acquire the pixel position of the fluorescent marker bright spot at the top of the micro-cylindrical sensor in the working state; and to acquire the offset of the fluorescent marker bright spot at the top of the micro-cylindrical sensor based on the pixel position of the fluorescent marker bright spot at the initial moment and the pixel position of the fluorescent marker bright spot at the top of the micro-cylindrical sensor in the working state. The stress acquisition module is used to acquire the wall shear stress in the flow field based on the offset of the fluorescent marker spot at the top of the micro-cylindrical sensor and the curve between the wall shear stress and the offset of the fluorescent marker spot at the top of the micro-cylindrical sensor.

8. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the method as described in any one of claims 1-6.

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