A Study And Application On Real-time Adaptive Particle Image Velocimetry Measurement Technology For Time-variant Flow Field

The time-variant flow field usually presents unsteady characteristic on time scale,and the fluid velocity at the same measuring point has a wide range of time-variant characteristics.The accurate measurement of the time-variant flow field has important theoretical significance and application value for the analysis of the aerodynamic characteristics of the aircraft and the study of the vehicle dynamics.Particle Image Velocimetry(PIV)has been widely used in various flow field measurements due to its advantages of non-contact,non-interference,transient and full-field measurements.The traditional PIV measurement technology has fixed interval time between two adjacent frames,which cannot meet the real-time accurate measurement of the time-variant flow field.Aiming at the limitations of traditional PIV measurement technology,this paper proposes a real-time adaptive PIV measurement technology,and develops a set of RTA-PIV device based on this technology,the accuracy and feasibility of RTA-PIV measurement technology are verified through experiments.The specific research work of this paper is as follows:(1)In view of the fact that the time interval of visual devices in PIV measurement technology is fixed and the time-varying flow field cannot be accurately measured,this paper develops a nanosecond-level cross-frame ultra-high-speed framing vision imaging device based on bipartite light technology.The firmware design is used to control the timing relationship between the exposure of the two image sensors and the pulse laser,so that the time interval of the adjacent two frames can be adjusted,and the measurement accuracy and dynamic range of the time-varying flow field measurement can be improved.The framing vision imaging device has a resolution of up to 2048×2048,a frame rate of up to 100 fps,and a time interval adjustable from 10 ns to 5 ms.(2)Aiming at the problem that the image sensor's noise affects the image quality and affects the accuracy of the flow field velocity measurement,this paper analyzes the cause of sensor noise so that the image signal-to-noise ratio is enhanced to 19.61 by using digital domain correlation double sampling,dark reference frame and dark reference column subtraction,flat field correction and water cooling.Double-gain image fusion is realized by the dual gain channel of the image sensor,and the dynamic range of the image is extended to 85.5dB,and provide high-quality images for the velocity field calculation of the flow field.(3)Aiming at the problem of insufficient real-time image processing calculation in PIV measurement technology,a real-time ultra-high-speed image processing device based on FPGA+2DSP distributed processor architecture was developed,and firmware design was implemented to realize image preprocessing,flow field velocity estimation and the calculation of the optimal time interval,the device has a transmission bandwidth of up to 12.5 Gbps and an image processing frequency up to 50 Hz.(4)Aiming at the limitations of the traditional PIV algorithm,this paper proposes a real-time adaptive PIV measurement algorithm,which uses correlation filtering to estimate the velocity field of the flow field,and uses the Kalman predictor to predict the speed of the next frame image to select the optimal time interval.In the simulation experiment and the real flow field measurement,the relative error between the measured value and the theoretical value of the algorithm is less than 1%.