| Hydrodynamic coupling is hydrodynamic element which is depend on thekinetic energy of work fluid to transfer and achieve the power transmission.Hydrodynamic couplings are widely employed as transmission elements in vehicletransmission, inertial equipment start-up and high-power speed drive. They havebroad application prospects in many fields of national economy. The internal flowfield of hydrodynamic coupling is extremely complex three-dimensional unsteadyflow. The external performance of hydrodynamic components is determined by theirinternal flow characteristics. Strengthening the internal flow characteristics researchon hydrodynamic coupling has great important meanings to improve its workperformance and ensure its operational safety and reliability. With the development ofmodern science and technology, a lot of important achievements have been made inthe study of the internal flow of fluid machines based on flow visualizationtechniques. The whole internal flow of hydrodynamic coupling and the characteristicsof flow velocity can be directly observed by the method of flow visualization. On thisbasis, the internal flow distribution of hydrodynamic coupling can be qualitativeanalyzed, the flow parameters of flow field can be identificated and quantitativeextracted. At the same time, the results of flow visualization and recognition of flowparameters can be provided to verify the theoretical numerical calculation of internalflow field in hydrodynamic coupling. In order to consummate the modern designmethod of hydrodynamic coupling step-by-step, as a powerful means, the study ofinternal flow law must be carried out by flow visualization. Particle ImageVelocimetry (PIV) is a new method of flow visualization. Its characteristics are non-invasive, transient and full field measurement with no interference. It can notonly show such as flow field and the physical form of the flow, but also providequantitative informations of the instantaneous flow field. Because there are manyadvantages to measure the flow field in fluid machines, PIV technology is becominga main flow visualization method in the study of internal flow in hydrodynamiccomponent.This paper associates with the special subject "Key Technological Research onHydrodynamic Variable Speed and Saving Energy of Large Pump and Fan" of theNational High-tech Research Development Plan (863Plan). This thesis is mainlyconcerned with the internal flow visualization method of hydrodynamiccoupling.Study on visualization of internal flow in hydrodynamic coupling andrecognition method of flow velocity are carried out based on Particle ImageVelocimetry technology. Velocity vector on two-dimensional crosssection ofhydrodynamic coupling is identified and extracted by digital image processingtechnology. Single image PTV algorithm and consecutive frames of PIVcross-correlation algorithm are study deeply. Visualization of internal flow field inhydrodynamic coupling and quantitative measurement of flow velocity ontwo-dimensional crosssection are achieved. This paper is mainly about the followingaspects:1. Internal flow visualization of hydrodynamic couplnigThe internal flow visualization of hydrodynamic couplnig is achieved based onParticle Image Velocimetry (PIV). Three typical working conditions ofhydrodynamic coupling are chosen as the measurement conditions. Whenhydrodynamic couplnig is working on rated condition (i=0.97), middle workingcondition (i=0.6) and braking condition (i=0), flow images with different particleconcentrations of hydrodynamic couplnig are recorded. Visualization of the internalflow field in hydrodynamic couplnig is achieved. The flow phenomena and flowcharacteristics on the flow area are observed directly. The quality of flow images areimproved and enhanced effectively through image preprocessing, tracer particles inflow field become much clearer and they are easily identified. All of these laid afoundation for recognition and extraction of flow velocity. 2. Recognition method of flow velocity in hydrodynamic coupling based onPTV technologyThe internal flow velocity of hydrodynamic coupling are identified and extractedbased on the study on Particle Tracking Velocimetry (PTV) method. When theconcentration of particles is low, flow images on two-dimensional crosssection ofpumb and turbine are recorded by PTV technology. Triple exposure technique onsingle frame is used to record three different length motion track of particles, they arecalled arrow head, arrow body and arrow tail. Motion trajectories of particles becomemuch clearer and easier to identify through dynamic image processing, includingimage enhancement, threshold segmentation and image sharpening. The flowdirections of hydrodynamic coupling are determined accurately and directly, flowvisualization becomes true. Hough transform straight line detection theory is studiedto identity flow velocity direction. Flow velocity directions of the whole flow fieldare identified automatically by this method. Particle motion trajectory is extracted byedge detection algorithm, double threshold method is used to detect single-pixel edgeof particle trajectories efficiently. The displacements of particles are extracteddirectly, then the internal flow velocimetry is acquired, quantitative measurement ofvelocity is achieved.The accuracy and precision of flow velocity recognition are depeond oncalibration. High-precision calibration plate is manufactured and it is attached to theouter wall surface of hydrodynamic coupling. Holes of2mm diameter are distributedevenly on the calibration plate. Images of holes are recorded by CCD camera, andthen pixel size of holes are detected after image processing, the sizes of them arecompared with the actual diameters of holes. Static image calibration coefficient isacquired. When hydrodynamic coupling is working on a certain rotating speed, themotion trajectories of holes on the calibration plate are record by CCD camera. Thelength of the trajectories are extracted through the corner detection, the values arecompared with the length of the trajectories by theoretical calculation. Dynamicimage calibration coefficient is acquired. The size of each pixel in the images isdetermined through static calibration and dynamic calibration, then the internal flowvelocity are extracted. 3. Recognition method of flow velocity in hydrodynamic coupling based onPIV correlation algorithmInternal flow field of hydrodynamic coupling is extracted based on ParticleImage Velocimetry. In order to study the complex unsteady flow characteristics inturbine of hydrodynamic coupling on braking condition (i=0), when the concentrationof particles is high, the flow images of internal flow field are recorded by PIVtechnology. Two-dimensional flow velocity distribution on radial section of turbine isextracted based on the principle of image matching and PIV cross-correlationalgorithm of two continuous images. Two points of image are chosen and the distancebetween them is calculated. Then the actual distance between the two pionts ofhydrodynamic coupling model is compared with the theoretical calculated value. Onthis basis, calibration coefficient is acquired, flow field velocity after calibration areobtained. Reasons of error velocity vector in the flow field are studied and analyzed.Spurious vectors are removed based on correction criteria of error vector. The resultsof the flow field are optimized. Visualization and quantitative measurement ofinternal flow field in hydrodynamic coupling are achieved. A high-precision flowvelocity distribution map is obtained. Flow structure and velocity distribution ofinternal flow field in turbine on the braking condition are analyzed in detail.4. Comparative analysis between experiment and simulationThree-dimensional model of hydrodynamic coupling is built by UG(Unigraphics NX). The internal flow channel model of hydrodynamic coupling isextracted for CFD analysis after simplifying the model. The extracted flow channelmodel is imported into ICEM-CFD. The regular hexahedral mesh of flow channelmodel is obtained with reflection method. The sliding mesh is chosen for simulationof relative movement between pump wheel and turbine wheel. The turbulent model isset as standard k-ε model in FLUENT, SIMPLE velocity-pressure coupling algorithm,the first order upwind scheme and standard wall function are chosen for thecalculation. Three-dimensional flow velocity distribution is calculated by CFDsimulation, radial cross-section and axial cross-section of pump wheel and turbinewheel are selected, the position of them are the same as the experiment's. Flowvelocity distribution of CFD simulation is compared with the results of PIVexperiment, it shows good agreement between them. The reliability of simulationmethod and the accuracy of calculated results are verified by PIV experimental results.The reasons of error in PIV experiment are analyzed in detail and some corresponding solutions are given.
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