Wall surface shear stress measurement method based on event camera and micro-cylinder sensor

Abstract

The invention relates to the technical field of stress measurement, in particular to a wall surface shear stress measurement method based on an event camera and a micro-cylinder sensor, and the method is used for measuring wall surface shear stress in a flow field and comprises the following steps: setting a mounting position of the micro-cylinder sensor; setting an event camera light threshold; based on an event camera, acquiring a pixel position of a top bright spot of the micro-cylinder sensor at an initial moment and a mark point position on a substrate of the micro-cylinder sensor; the pixel position of a bright spot at the top end of the micro-cylinder sensor in the working state is collected; and obtaining the wall surface shear stress in the flow field according to the micro-cylinder sensor top end bright spot offset and a curve between the wall surface shear stress and the micro-cylinder sensor top end bright spot offset. According to the invention, the detection efficiency of the micro-cylinder sensor can be obviously improved, the problem of uneven lighting caused by using an LED is avoided, and the post-processing problem caused by simultaneous lighting of the top end and the bottom end of the micro-cylinder sensor after lighting is effectively avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of stress measurement, and in particular to a method for measuring wall shear stress based on an event camera and a micro-cylindrical sensor. Background Art

[0002] Wall shear stress is the viscous resistance generated by fluid passing through the surface of an object. In the field of fluid mechanics, the distribution of wall shear stress in time and space is the key information of the interaction between turbulent structures near the wall. In the medical field, wall shear stress is an important parameter of hemodynamics, which is closely related to the occurrence of diseases such as atherosclerosis. At present, the measurement methods of wall shear stress include direct measurement methods and indirect measurement methods. The micro-cylindrical sensor method in the indirect measurement method uses optics for measurement. The high-speed CCD camera is used to optically detect the deflection of the top of the micro-cylindrical sensor. Combined with the linear relationship between the sensor top deflection and the local wall shear stress, the two-dimensional distribution of the wall shear stress in time and space in the measurement area and the instantaneous wall shear stress value can be obtained.

[0003] However, the current micro-cylindrical sensor method still has some shortcomings: First, the traditional micro-cylindrical sensor method is based on high-speed CCD camera shooting. Due to the limitation of CCD camera, the amount of image data collected is large and the data reading and writing is time-consuming; second, due to the massive amount of image data collected, it is very difficult to realize real-time transmission and processing of image data; third, in the optical detection scheme using high-speed CCD camera, researchers use LED lighting method. The image quality collected by high-speed CCD camera is greatly affected by the uniformity of ambient LED lighting, and manual adjustment of lighting angle is time-consuming and laborious. Researchers also use the method of laser excitation of top fluorescent markers or laser illumination of reflective particles at the top of micro-cylindrical sensor. However, since the micro-cylindrical sensor made of transparent elastomer material has similar characteristics to optical fiber, the micro-cylindrical sensor has the situation that the top and bottom of the micro-cylindrical sensor emit light at the same time, and it is difficult to accurately identify the top deflection of the micro-cylindrical sensor through post-processing procedures and manual recognition methods. The above micro-cylindrical sensors and measurement schemes are not suitable for event camera detection.

[0004] An event camera is a bionic camera that only outputs changes in brightness that exceed a set threshold. It has the advantages of low latency (<1 microsecond), high dynamic range (140dB), small data volume, and extremely low power consumption (1mW). The event camera asynchronously measures the brightness changes of each pixel. The event camera light sensitivity threshold , when the brightness changes beyond the threshold When a pixel is detected, the event camera sends an event consisting of the X, Y position of the pixel, the time T, and the polarity P of the change (i.e., the brightness increases ("+1") or decreases ("-1")). Event information is output only when the received light intensity changes, and a series of event data is output, which is very suitable for recording the displacement detection of the top mark bright spot of the micro-cylindrical sensor. Because the event camera has a high dynamic range and is very sensitive to brightness changes, it can effectively output in brighter or darker scenes. Moreover, only recording the event data of the output brightness change occupies a small bandwidth, which can achieve real-time processing capabilities.

[0005] In summary, it is not only a cutting-edge challenge to deeply explore the unique advantages of event cameras and use them to enable the optical measurement of micro-cylindrical sensors, but also an urgent need and important development direction to push the measurement capabilities of micro-cylindrical sensors to a new level. We urgently need to explore how to use event cameras to achieve real-time and accurate wall shear force measurement of micro-cylindrical sensors. Summary of the invention

[0006] In order to solve the above technical problems, the present invention provides a wall shear stress measurement method based on an event camera and a micro-cylindrical sensor. The method adopts a high-contrast micro-cylindrical sensor suitable for an event camera, 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 light emission at the top and bottom of the micro-cylindrical sensor in the traditional method of using laser to excite the top fluorescent marking point or the method of laser illuminating the reflective particles at the top of the micro-cylindrical sensor.

[0007] The first object of the present invention is to provide a method for measuring wall shear stress based on an event camera and a micro-cylindrical sensor, which is used for measuring wall shear stress in a flow field, comprising: 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 the laser to excite the fluorescent mark point on the top of the micro-cylindrical sensor, and focus the event camera to the bright spot of the fluorescent mark on the top of the micro-cylindrical sensor; Set event camera light threshold; The micro-cylindrical sensor is calibrated to obtain a curve between the wall shear stress and the offset of the bright spot at the top of the micro-cylindrical sensor; Based on the event camera, the pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment and the position of the marking point on the substrate are collected; and the pixel position of the bright spot at the top of the micro-cylindrical sensor in the working state is collected; According to 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; The wall shear stress in the flow field is obtained according to 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.

[0008] Preferably, the event camera light threshold is set according to the following steps: Apply a stable incoming flow in the flow field, turn on the event camera, then turn on the laser to excite the fluorescent mark point on the top of the micro-cylindrical sensor, continue to excite for 1 to 2 seconds and then turn off the laser, wait for 1 to 2 seconds and then turn off the event camera, export the event data, draw a curve with the horizontal axis as the timestamp and the vertical axis as the number of events corresponding to the timestamp, and obtain the curve of the number of events corresponding to the timestamp; record n ​​repeated operations as n cycles; Count the number of events before T0, which represents the background noise events. Adjust the event camera light threshold according to the number of background noise events before T0. .

[0009] 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: When collecting initial parameters, first open the event camera to collect, then turn on the laser to excite the fluorescent mark on the top of the micro-cylindrical sensor, continue to excite for 1 to 2 seconds and then turn off the laser. While keeping the event camera working, repeat the above steps n times. The n repeated operations are recorded as n collection cycles. Generally, , wait 1 to 2 seconds and then close the event camera; Export the event data collected by the event camera, plot the timestamp as the horizontal axis and the number of events corresponding to the timestamp as the vertical axis, and obtain a curve of the number of events corresponding to the timestamp; According to the curve of the number of events corresponding to the timestamp, the image of the non-measurement area is cropped according to the sensor field of view, and then the background noise is removed. The two-dimensional kernel density value on each event timestamp is calculated, and the threshold is adjusted to remove the event flow information of the two-dimensional kernel density value area below the threshold, that is, the background noise event removal on the T3 to T4 timestamp is completed. Then, the events with polarity P=-1 between T3 and T4 are superimposed on the two-dimensional pixel space, and the K-means clustering algorithm is used to classify the events, set the number of clusters, manually mark the initial position of the cluster center, and calculate the Euclidean distance from each cluster object to the cluster center for division. For each cluster, its cluster center is recalculated. The new cluster center is the mean of all data points in the cluster until the maximum number of iterations is reached, then stop, otherwise, continue the calculation, and the cluster center of each type is the pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment.

[0010] Preferably, 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 marking points.

[0011] 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: The flow field is turned on. After the incoming flow velocity is stable, 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 marking point on the top of the micro-cylindrical sensor. The collection time is t; Export event data and plot the curve of timestamps versus number of events; For exported event data, background noise is removed.

[0012] The K-means clustering algorithm is used to process the positive and negative polarity events in the time stamp interval of stable measurement respectively, and the centroid position of the positive and negative polarity event clusters is obtained, which is the pixel position of the bright spot at the top of the micro-cylindrical sensor in the working state.

[0013] 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.

[0014] 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: For events with laser off timestamps, all events in the environment should be negative polarity events. Obtain the negative polarity event positions of the base fluorescent markers through the pixel positions. Push forward by the timestamps to obtain the negative polarity event positions of the base fluorescent markers for each timestamp. ) minus the initial position of the marker point on the base ( )have to and , then subtract the pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment from the centroid position of the micro-cylindrical sensor positive polarity event at each timestamp ( )have to and ,so and They are the lateral and longitudinal offsets of the top of the micro-cylindrical sensor after the environmental factors affect the micro-cylindrical sensor.

[0015] Preferably, the micro-cylindrical sensor is prepared according to the following steps: (1) PDMS prepolymer and curing agent are mixed in a ratio of 10:1, carbon black powder is mixed into PDMS, and a magnetic stirrer is used to fully stir to form a carbon black PDMS colloidal mixture, and then placed in a vacuum pump for degassing; (2) pouring the carbon black PDMS colloidal mixture obtained in step (1) into a pre-processed demoulding mold, and then placing it in a heating furnace and heating it at 30 degrees Celsius for 24 hours; (3) After the carbon black PDMS colloid mixture is solidified, the demoulding mold is peeled off to obtain a black micro-cylindrical sensor and its substrate; (4) Dip the micro-cylindrical sensor into the 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 and heat it at 30°C for 24 hours; (5) Using a microneedle, dip a mixture of PDMS and fluorescent microspheres on the downstream side of the micro-cylindrical sensor array relative to the incoming flow, mark the surface of the substrate of the micro-cylindrical sensor, and then cure it at room temperature in the dark for 72 hours.

[0016] The second object of the present invention is to provide a wall shear stress measurement system based on an event camera and a micro-cylindrical sensor, comprising: 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 the laser to excite the fluorescent marking point on the top of the micro-cylindrical sensor, and make the event camera focus on the fluorescent marking bright spot on the top of the micro-cylindrical sensor; set the light threshold of the event camera; An offset curve module is used to calibrate the micro-cylindrical sensor to obtain a curve between the wall shear stress and the offset of the bright spot at the top of the micro-cylindrical sensor; The offset acquisition module is used to collect the pixel position of the bright spot at the top of the micro-cylindrical sensor and the position of the marking point on the substrate at the initial moment based on the event camera; and collect the pixel position of the bright spot at the top of the micro-cylindrical sensor in the working state; according to 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; The stress acquisition module is used to obtain the wall shear stress in the flow field according to the bright spot offset at the top of the micro-cylindrical sensor and the curve between the wall shear stress and the bright spot offset at the top of the micro-cylindrical sensor.

[0017] The third object of the present invention is to provide an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the steps of the above method when executed by the processor.

[0018] The present invention has at least the following beneficial effects: The present invention provides a wall shear stress measurement method based on an event camera and a micro-cylindrical sensor, which can fully utilize the advantages of the event camera's low latency (<1 microsecond), high dynamic range (140dB), small data volume, and extremely low power consumption (1mW) to achieve real-time, high-precision measurement of the micro-cylindrical sensor. The high-contrast micro-cylindrical sensor of the event camera used in the present 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 problem caused by the simultaneous light emission of the top and bottom of the micro-cylindrical sensor after lighting. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A curve of the number of events corresponding to a timestamp T according to the present invention; FIG. 2 is a schematic diagram of events on the event camera timestamp in the present invention. DETAILED DESCRIPTION

[0020] In order to illustrate the technical means and effects adopted by the present invention to achieve the predetermined purpose of the invention, the following is a detailed description in conjunction with embodiments.

[0021] The purpose of the present invention is to provide a wall shear stress measurement method based on an event camera and a micro-cylindrical sensor. The high-contrast micro-cylindrical sensor of the event camera is used to 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 light emission at the top and bottom of the micro-cylindrical sensor in the previous method of using laser to excite the top fluorescent marking point or laser to illuminate the reflective particles at the top of the micro-cylindrical sensor.

[0022] In order to achieve the above purpose, a wall shear stress measurement method based on an event camera and a micro-cylindrical sensor is used to measure the wall shear stress in a flow field, comprising: S1. 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 mark point on the top of the micro-cylindrical sensor, and focus the event camera to the fluorescent mark bright spot on the top of the micro-cylindrical sensor; The micro-cylindrical sensor is prepared according to the following steps: (1) PDMS prepolymer and curing agent are mixed in a ratio of 10:1, carbon black powder is mixed into PDMS, and a magnetic stirrer is used to fully stir to form a carbon black PDMS colloidal mixture, and then placed in a vacuum pump for degassing; (2) pouring the carbon black PDMS colloidal mixture obtained in step (1) into a pre-processed demoulding mold, and then placing it in a heating furnace and heating it at 30 degrees Celsius for 24 hours; (3) After the carbon black PDMS colloid mixture is solidified, the demoulding mold is peeled off to obtain a black micro-cylindrical sensor and its substrate; (4) Dip the micro-cylindrical sensor into the 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 and heat it at 30°C for 24 hours; (5) Using a microneedle, dip a mixture of PDMS and fluorescent microspheres on the downstream side of the micro-cylindrical sensor array relative to the incoming flow, mark the surface of the substrate of the micro-cylindrical sensor, and then cure it at room temperature in the dark for 72 hours.

[0023] In one embodiment, a method for manufacturing a high-contrast micro-cylindrical sensor suitable for an event camera includes the following steps: (1) Mix PDMS prepolymer and curing agent in a ratio of 10:1, mix carbon black powder into PDMS, use a magnetic stirrer to stir thoroughly to form a carbon black PDMS colloidal mixture, and place it in a vacuum pump for degassing.

[0024] (2) Pour the carbon black PDMS colloidal mixture obtained in step (1) into a pre-processed demoulding mold, and then place it in a heating furnace and heat it at 30 degrees Celsius for 24 hours.

[0025] (3) After the carbon black PDMS colloidal mixture is cured, the demoulding mold is peeled off to obtain a black micro-cylindrical sensor and its substrate.

[0026] (4) Dip the micro-cylindrical sensor into the 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 and heat it at 30 degrees Celsius for 24 hours.

[0027] (5) Use a microneedle (tip diameter 20 μm) to dip into the mixture of PDMS and fluorescent microspheres on the downstream side (relative to the incoming flow) of the micro-cylindrical sensor array, mark the substrate surface of the micro-cylindrical sensor, and then cure it at room temperature in the dark for 72 h.

[0028] S2, set event camera light threshold; The event camera light threshold is set by following these steps: Apply a stable incoming flow in the flow field, turn on the event camera, then turn on the laser to excite the fluorescent mark point on the top of the micro-cylindrical sensor, continue to excite for 1 to 2 seconds and then turn off the laser, wait for 1 to 2 seconds and then turn off the event camera, export the event data, draw a curve with the horizontal axis as the timestamp and the vertical axis as the number of events corresponding to the timestamp, and obtain the curve of the number of events corresponding to the timestamp; record n ​​repeated operations as n cycles; Count the number of events before T0, which represents the background noise events. Adjust the event camera light threshold according to the number of background noise events before T0. .

[0029] S3, calibrating the micro-cylindrical sensor to obtain a curve between the wall shear stress and the offset of the bright spot at the top of the micro-cylindrical sensor; Based on the event camera, the pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment and the position of the marking point on the substrate are collected; and the pixel position of the bright spot at the top of the micro-cylindrical sensor in the working state is collected; 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: When collecting initial parameters, first open the event camera to collect, then turn on the laser to excite the fluorescent mark on the top of the micro-cylindrical sensor, continue to excite for 1 to 2 seconds and then turn off the laser. While keeping the event camera working, repeat the above steps n times. The n repeated operations are recorded as n collection cycles. Generally, , wait 1 to 2 seconds and then close the event camera; Export the event data collected by the event camera, plot the timestamp as the horizontal axis and the number of events corresponding to the timestamp as the vertical axis, and obtain a curve of the number of events corresponding to the timestamp; According to the curve of the number of events corresponding to the timestamp, the image of the non-measurement area is cropped according to the sensor field of view, and then the background noise is removed, the two-dimensional kernel density value at each event timestamp is calculated, and the threshold is adjusted to remove the event flow information of the two-dimensional kernel density value area below the threshold, that is, the background noise event removal at the T3 to T4 timestamp is completed, and then the events with polarity P=-1 between T3 and T4 are superimposed on the two-dimensional pixel space, and the events are classified using the K-means clustering algorithm, 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 to divide. For each cluster, its cluster center is recalculated, and the new cluster center is the mean of all data points in the cluster until the maximum number of iterations is reached, then stop, otherwise, continue the calculation, and the cluster center of each type is the pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment. Among them, 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.

[0030] 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: The flow field is turned on. After the incoming flow velocity is stable, 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 marking point on the top of the micro-cylindrical sensor. The collection time is t; Export event data and plot the curve of timestamps versus number of events; For exported event data, background noise is removed.

[0031] The K-means clustering algorithm is used to process the positive and negative polarity events in the time stamp interval of stable measurement respectively, and the centroid position of the positive and negative polarity event clusters is obtained, which is the pixel position of the bright spot at the top of the micro-cylindrical sensor in the working state.

[0032] S4, obtaining an offset of the bright spot at the top of the micro-cylindrical sensor according to 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 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.

[0033] 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: For events with laser off timestamps, all events in the environment should be negative polarity events. Obtain the negative polarity event positions of the base fluorescent markers through the pixel positions. Push forward by the timestamps to obtain the negative polarity event positions of the base fluorescent markers for each timestamp. ) minus the initial position of the marker point on the base ( )have to and , then subtract the pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment from the centroid position of the micro-cylindrical sensor positive polarity event at each timestamp ( )have to and ,so and They are the lateral and longitudinal offsets of the top of the micro-cylindrical sensor after the environmental factors affect the micro-cylindrical sensor.

[0034] S5. Obtain the wall shear stress in the flow field according to 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.

[0035] In order to illustrate a wall shear stress measurement method based on an event camera and a micro-cylindrical sensor provided by the present invention, it is further described in conjunction with the accompanying drawings.

[0036] A method for measuring wall shear stress based on an event camera and a micro-cylindrical sensor, comprising: Step 1: Set up the experimental environment. Use the high-contrast micro-cylindrical sensor suitable for event cameras manufactured using Technical Solution 1, install it at the measurement position in the wind tunnel or water tunnel, place the event camera and the micro-cylindrical sensor face to face, and install a filter in front of the event camera lens. Use a 540nm long-wave pass filter (only allows light with a wavelength > 540nm to pass through), cover the outer part of the camera's light path with a black shading cloth, and turn off the experimental environment light source. Use a laser (a high-frequency laser with a wavelength of 532nm, a frequency > 15000Hz) to excite the fluorescent marking point on the top of the micro-cylindrical sensor and the marking point on its base, and focus the event camera to the bright fluorescent mark on the top of the micro-cylindrical sensor, and then use the dynamic calibration plate to calibrate the event camera.

[0037] Step 2: Initial parameter acquisition. Collect the pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment ( ) and the locations of the marking points on its base ( ), where i, j represent the number of rows and columns in the micro-cylindrical sensor array, and 0 represents the initial moment.

[0038] Before starting the initial parameter acquisition, you need to complete the focus and event camera light threshold settings. Use a laser to excite the fluorescent marker on the top of the micro-cylindrical sensor, so that the event camera automatically focuses on the stationary micro-cylindrical sensor top bright spot; The steps to set the light threshold of the event camera are as follows: apply a stable flow in a water tunnel or wind tunnel experimental environment, turn on the event camera to collect, then turn on the laser to excite the fluorescent marker on the top of the micro-cylindrical sensor, continue to excite for 1 to 2 seconds, then turn off the laser, wait for 1 to 2 seconds, then turn off the event camera. Export the event data (X, Y, T, P), plot the horizontal axis as the timestamp T, and the vertical axis as the number of events corresponding to the timestamp T. A typical curve of the timestamp T corresponding to the number of events is as follows: Figure 1 As shown, n repeated operations are recorded as n cycles. Figure 1 The example is an idealized statistical data of 1 cycle. First, the number of events before T0 is counted. The number of events before T0 represents the events of background noise. According to the number of background noise events before T0, the event camera light threshold C is adjusted so that .

[0039] When collecting initial parameters, first open the event camera to collect, then turn on the laser to excite the fluorescent mark on the top of the micro-cylindrical sensor, continue to excite for 1 to 2 seconds and then turn off the laser. While keeping the event camera working, repeat the above steps n times. The n repeated operations are recorded as n collection cycles. Generally, , wait 1 to 2 seconds and then turn off the event camera. Export the event data (X, Y, T, P) collected by the event camera, plot the horizontal axis as the timestamp T, and the vertical axis as the number of events corresponding to the timestamp T. A typical curve of the timestamp T corresponding to the number of events in a collection cycle is as follows Figure 1 As shown. The image of the non-measurement area is cropped according to the approximate range of the sensor field of view, and then the background noise is removed. The two-dimensional kernel density value at each event timestamp is calculated, and the threshold is adjusted reasonably to remove the event flow information in the area with two-dimensional kernel density values ​​below the threshold, that is, the background noise event removal at the T3 to T4 timestamps is completed. Then, the events with polarity P=-1 between T3 and T4 are superimposed in the two-dimensional pixel space, and the K-means clustering algorithm is used to classify the events. The number of clusters K is set to be 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 to divide it. For each cluster, its cluster center is recalculated. The new cluster center is the mean of all data points in the cluster. The operation stops when the maximum number of iterations is reached. Otherwise, the operation continues. The cluster center of each category is the pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment ( ).

[0040] Step 3: Collect the pixel position of the bright spot at the top of the micro-cylindrical sensor in working state ( ), the superscript 1 represents the working state. Under the action of fluid force, the top of the micro-cylindrical sensor is offset. Ideally, the imaging diagram in the field of view of the event camera is as follows Figure 2 As shown, white dots represent positive polarity events, and black dots represent negative polarity events. Therefore, the white dots on the left are timestamps. The positive polarity event at the moment, the green dot in the right figure is the time stamp Negative polarity event at the moment, the white dot in the right figure is the time stamp Positive event at the moment.

[0041] like Figure 2 As shown, the event camera takes images, the left image is Moment Events ( , , P =+1), the right picture is Moment Events ( , , P =+1(white),-1(green)); Figure 2 In, timestamp The pixel position of the negative polarity event at the moment represents the timestamp of the previous event The position of the fluorescent marker on the top of the micro-cylindrical sensor at the moment, timestamp The pixel position of the positive polarity event at the moment represents the current event timestamp The new position of the fluorescent mark on the top of the micro-cylindrical sensor under the action of fluid force. Positive polarity events at all times The positions of negative events at the same time should be consistent. Comprehensive analysis is performed to obtain the pixel position of the fluorescent marker at the top of the micro-cylindrical sensor ( ) method is as follows: Experiment: Open the water tunnel or wind tunnel. After the free flow velocity stabilizes, turn on the event camera to collect event data. After 1 to 2 seconds, turn on the continuous laser to excite the fluorescent marker on the top of the micro-cylindrical sensor. The collection time is t. After completing a set of collections, turn off the continuous laser, turn off the event camera, and close the water tunnel or wind tunnel in turn.

[0042] Export event data (X, Y, T, P), plot the horizontal axis as timestamp T, and the vertical axis as the number of events corresponding to timestamp T. A typical curve of timestamp T corresponding to the number of events is as follows: Figure 1 shown.

[0043] Remove background noise: For event cameras that only output (X, Y, T, P), remove background noise using the classic spatiotemporal correlation filter method introduced in step 2.

[0044] Cluster analysis: Figure 1 At timestamp T2, there are two situations in actual measurement: 1) the micro-cylindrical sensor tip has a small deflection, and there is an orange positive and negative polarity event superposition area; 2) the micro-cylindrical sensor tip has a large deflection, and there is no superposition area. For the former case, the event polarity of the orange superposition area is approximately randomly distributed, so the processing method is essentially the same as the latter case, that is, using the K-means clustering algorithm to process the stable measurement timestamp interval separately, such as Figure 2 The positive and negative polarity events in the time stamp interval from T3 to T4 are used to obtain the centroid position of the positive and negative polarity event clusters.

[0045] When the vibration of the measurement environment is negligible, the algorithm for calculating the top offset of a single micro-cylindrical sensor at each timestamp is as follows: In step 4, cluster analysis is performed to obtain the centroid positions of the positive and negative polarity events at the same timestamp respectively. The centroid position of the positive polarity event minus the centroid position of the negative polarity event is the top offset of a single micro-cylindrical sensor.

[0046] Considering the influence of environmental vibration, the algorithm for the top offset of a single micro-cylindrical sensor at each timestamp is as follows: for the events of the laser off timestamp, all the events in the environment should be negative polarity events. The negative polarity event positions of the base fluorescent marker points are obtained through the approximate area of ​​the pixel position. The negative polarity event positions of the base fluorescent marker points at each timestamp are obtained by pushing forward the timestamp. The negative polarity event positions of the base fluorescent marker points at each timestamp are converted into negative polarity event positions ( ) minus the initial position of the marker point on the base ( )have to and , then subtract the pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment from the centroid position of the micro-cylindrical sensor positive polarity event at each timestamp ( )have to and ,so and 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, and the total offset is .

[0047] Missing value filling: For the missing events of a single micro-cylindrical sensor at the timestamp, search forward according to the timestamp until the timestamp event at which the event occurs at the corresponding position of the single micro-cylindrical sensor is found. It can be considered that no brightness change occurs during this period, that is, the micro-cylindrical sensor does not have a top shift in the timestamp interval. Therefore, the event at the timestamp is taken as the missing value filling.

[0048] Step 4: Use the method described in step 3 to statically calibrate the micro-cylindrical sensor and measure it in the turbulent area of ​​interest. Place the micro-cylindrical sensor in a laminar flow field with known wall shear. Use an event camera to capture the position of the top of the micro-cylindrical sensor. Use the method described in step 3 to calculate the time-averaged offset of the top of each micro-cylindrical sensor under different flow field velocities. Since the wall shear stress is linearly related to the time-averaged offset of the top of the micro-cylindrical sensor, it can be obtained Curve, where is the wall shear stress known in the flow field, k is the proportional coefficient. The proportional coefficient of each micro-cylindrical sensor can be calculated.

[0049] Place the micro-cylindrical sensor in the turbulent area for measurement, and use an event camera to capture the position of the micro-cylindrical sensor tip. For the average wall shear stress: use the method described in step 3 to calculate the average displacement of the tip of each micro-cylindrical sensor under different flow field velocities, and divide it by the proportional coefficient of each micro-cylindrical sensor. k , the time-averaged wall shear stress of each micro-cylindrical sensor is obtained, and the time-averaged wall shear stress of all micro-cylindrical sensors in the field of view is added and averaged to obtain the average wall shear stress of the flow in the field of view; for the instantaneous wall shear stress, the top offset of the sensor at the timestamp of each event is obtained using the method described in step 3, divided by the proportional coefficient of each micro-cylindrical sensor k , the instantaneous wall shear stress of each micro-cylindrical sensor is obtained, and the instantaneous changes of the flow field can be analyzed by drawing cloud maps and other means.

[0050] The present invention provides a wall shear stress measurement system based on an event camera and a micro-cylindrical sensor, comprising: 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 the laser to excite the fluorescent marking point on the top of the micro-cylindrical sensor, and make the event camera focus on the fluorescent marking bright spot on the top of the micro-cylindrical sensor; set the light threshold of the event camera; An offset curve module is used to calibrate the micro-cylindrical sensor to obtain a curve between the wall shear stress and the offset of the bright spot at the top of the micro-cylindrical sensor; The offset acquisition module is used to collect the pixel position of the bright spot at the top of the micro-cylindrical sensor and the position of the marking point on the substrate at the initial moment based on the event camera; and collect the pixel position of the bright spot at the top of the micro-cylindrical sensor in the working state; according to 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; The stress acquisition module is used to obtain the wall shear stress in the flow field according to the bright spot offset at the top of the micro-cylindrical sensor and the curve between the wall shear stress and the bright spot offset at the top of the micro-cylindrical sensor.

[0051] The present invention provides an electronic device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the steps of the above method are implemented when the computer program is executed by the processor.

[0052] 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 in the protection scope of the present invention.

Claims

1. A method for measuring wall shear stress based on an event camera and a micro-cylindrical sensor, characterized in that: Used to measure wall shear stress in flow fields, including: 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 the laser to excite the fluorescent mark point on the top of the micro-cylindrical sensor, and focus the event camera to the bright spot of the fluorescent mark on the top of the micro-cylindrical sensor; Set event camera light threshold; The micro-cylindrical sensor is calibrated to obtain a curve between the wall shear stress and the offset of the bright spot at the top of the micro-cylindrical sensor; Based on the event camera, the pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment and the position of the marking point on the substrate are collected; and the pixel position of the bright spot at the top of the micro-cylindrical sensor in the working state is collected; According to 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; The wall shear stress in the flow field is obtained according to 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.

2. The wall shear stress measurement method based on event camera and micro-cylindrical sensor according to claim 1 is characterized in that: The event camera light threshold is set by following these steps: Apply a stable incoming flow in the flow field, turn on the event camera, then turn on the laser to excite the fluorescent mark point on the top of the micro-cylindrical sensor, continue to excite for 1 to 2 seconds and then turn off the laser, wait for 1 to 2 seconds and then turn off the event camera, export the event data, draw a curve with the horizontal axis as the timestamp and the vertical axis as the number of events corresponding to the timestamp, and obtain the curve of the number of events corresponding to the timestamp; record n ​​repeated operations as n cycles; Count the number of events before T0, which represents the background noise events. Adjust the event camera light threshold according to the number of background noise events before T0. .

3. The wall shear stress measurement method based on event camera and micro-cylindrical sensor according to claim 1, characterized in that: 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: When collecting initial parameters, first open the event camera to collect, then turn on the laser to excite the fluorescent mark on the top of the micro-cylindrical sensor, continue to excite for 1 to 2 seconds and then turn off the laser. While keeping the event camera working, repeat the above steps n times. The n repeated operations are recorded as n collection cycles. Generally, , wait 1 to 2 seconds and then close the event camera; Export the event data collected by the event camera, plot the timestamp as the horizontal axis and the number of events corresponding to the timestamp as the vertical axis, and obtain a curve of the number of events corresponding to the timestamp; According to the curve of the number of events corresponding to the timestamp, the image of the non-measurement area is cropped according to the sensor field of view, and then the background noise is removed. The two-dimensional kernel density value at each event timestamp is calculated, and the threshold is adjusted to remove the event flow information of the two-dimensional kernel density value area below the threshold, that is, the background noise event removal at the T3 to T4 timestamp is completed. Then, the events with polarity P=-1 between T3 and T4 are superimposed on the two-dimensional pixel space, and the K-means clustering algorithm is used to classify the events, set the number of clusters, manually mark the initial position of the cluster center, and calculate the Euclidean distance from each cluster object to the cluster center for division. For each cluster, its cluster center is recalculated. The new cluster center is the mean of all data points in the cluster until the maximum number of iterations is reached, then stop, otherwise, continue the calculation, and the cluster center of each type is the pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment.

4. The wall shear stress measurement method based on event camera and micro-cylindrical sensor according to claim 3 is characterized in that: 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.

5. The wall shear stress measurement method based on event camera and micro-cylindrical sensor according to claim 1, characterized in that: 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: The flow field is turned on. After the incoming flow velocity is stable, 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 marking point on the top of the micro-cylindrical sensor. The collection time is t; Export event data and plot the curve of timestamps versus number of events; For exported event data, background noise is removed. The K-means clustering algorithm is used to process the positive and negative polarity events in the time stamp interval of stable measurement respectively, and the centroid position of the positive and negative polarity event clusters is obtained, which is the pixel position of the bright spot at the top of the micro-cylindrical sensor in the working state.

6. The wall shear stress measurement method based on event camera and micro-cylindrical sensor according to claim 5, characterized in that: 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.

7. The wall shear stress measurement method based on event camera and micro-cylindrical sensor according to claim 1, characterized in that: 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: For events with laser off timestamps, all events in the environment should be negative polarity events. Obtain the negative polarity event positions of the base fluorescent markers through the pixel positions. Push forward by the timestamps to obtain the negative polarity event positions of the base fluorescent markers for each timestamp. ) minus the initial position of the marker point on the base ( )have to and , then subtract the pixel position of the bright spot at the top of the micro-cylindrical sensor at the initial moment from the centroid position of the micro-cylindrical sensor positive polarity event at each timestamp ( )have to and ,so and They are the lateral and longitudinal offsets of the top of the micro-cylindrical sensor after the environmental factors affect the micro-cylindrical sensor.

8. The wall shear stress measurement method based on event camera and micro-cylindrical sensor according to claim 1, characterized in that: The micro-cylindrical sensor is prepared according to the following steps: (1) PDMS prepolymer and curing agent are mixed in a ratio of 10:1, carbon black powder is mixed into PDMS, and a magnetic stirrer is used to fully stir to form a carbon black PDMS colloidal mixture, and then placed in a vacuum pump for degassing; (2) pouring the carbon black PDMS colloidal mixture obtained in step (1) into a pre-processed demoulding mold, and then placing it in a heating furnace and heating it at 30 degrees Celsius for 24 hours; (3) After the carbon black PDMS colloid mixture is solidified, the demoulding mold is peeled off to obtain a black micro-cylindrical sensor and its substrate; (4) Dip the micro-cylindrical sensor into the 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 and heat it at 30°C for 24 hours; (5) Using a microneedle, dip a mixture of PDMS and fluorescent microspheres on the downstream side of the micro-cylindrical sensor array relative to the incoming flow, mark the surface of the substrate of the micro-cylindrical sensor, and then cure it at room temperature in the dark for 72 hours.

9. A wall shear stress measurement system based on an event camera and a micro-cylindrical sensor, 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 and the micro-cylindrical sensor face to face, use the laser to excite the fluorescent marking point on the top of the micro-cylindrical sensor, and make the event camera focus on the fluorescent marking bright spot on the top of the micro-cylindrical sensor; set the light threshold of the event camera; An offset curve module is used to calibrate the micro-cylindrical sensor to obtain a curve between the wall shear stress and the offset of the bright spot at the top of the micro-cylindrical sensor; The offset acquisition module is used to collect the pixel position of the bright spot at the top of the micro-cylindrical sensor and the position of the marking point on the substrate at the initial moment based on the event camera; and collect the pixel position of the bright spot at the top of the micro-cylindrical sensor in the working state; according to 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; The stress acquisition module is used to obtain the wall shear stress in the flow field according to the bright spot offset at the top of the micro-cylindrical sensor and the curve between the wall shear stress and the bright spot offset at the top of the micro-cylindrical sensor.

10. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the computer program implements the steps of the method according to any one of claims 1 to 7 when executed by the processor.

Images