液力偶合器内部流动可视化与流速识别方法研究
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摘要
液力偶合器是主要依靠工作液体的动能来传递和实现能量变换的液力元件。液力偶合器作为传动元件广泛应用在车辆传动、大惯性设备的启动和大功率调速驱动方面。在国民经济众多领域中液力偶合器具有广泛的应用前景。液力偶合器内部的流动是一种极其复杂的非定常三维流动，其内部流动特性决定了液力偶合器的外部性能。加强液力偶合器内部流场的特性研究对于提高液力偶合器的工作性能，保证其运行安全性和可靠性具有极其重要的意义。随着现代科学技术的发展，流动可视化技术在研究流体机械内部流动方面取得了巨大的进展。通过流动可视化方法能够直观地观察液力偶合器内部流动全貌和流速特征，能够定性地分析液力偶合器内部流场分布并对流动参数进行识别与定量提取。同时，流动可视化与流动参数识别结果能够为液力偶合器内部流场的理论数值计算提供检验依据。为了逐步完善液力偶合器现代设计方法，必须通过流动可视化这一有力手段开展液力偶合器内部流动规律的研究，对其内部流速进行识别，进而深入研究液力偶合器的流场状态变化。粒子图像测速技术（Particle Image Velocimetry，简称PIV）是一种全新的无扰、瞬态、全流场速度测量的流动可视化方法。它不仅能够显示流体流场、流动的物理形态，而且能够提供瞬时全场流动的定量信息。由于PIV在流体机械流场测量方面具有很多优点，所以在液力元件内部流动可视化研究中，PIV成为主要的一种研究方法，并得到广泛的应用。
本文结合国家高技术研究发展计划（863计划）专题课题“大型泵与风机液力调速节能关键技术研究”（2007AA05Z256），论文围绕液力偶合器内部流动可视化方法，基于粒子图像测速技术开展液力偶合器内部流动可视化和流速识别方法研究，通过数字图像处理技术，并结合单帧图像PTV算法和连续帧图像的PIV互相关算法，识别并提取了液力偶合器二维切面流场上的流动速度矢量，实现了液力偶合器内部二维切面流场可视化与流速的量化。本文的研究内容主要有以下几个方面：
1.液力偶合器内部流动可视化
基于粒子图像测速技术实现液力偶合器内部流动可视化。在设计工况（i=0.97）、中间工况（i=0.6）和制动工况（i=0）下，采集在不同粒子浓度下液力偶合器内部流动图像，可视化液力偶合器内部流场，直接观察到所要研究流动区域上的流动现象和流动特征。通过对采集图像进行图像预处理，有效改善并提高了图像质量，使流场中示踪粒子清晰易于识别，为后续流速识别与提取的研究工作奠定了基础。
2.基于PTV技术的液力偶合器内部流速识别方法
研究粒子跟踪测速方法识别并提取液力偶合器内部流速。在低粒子浓度下，基于PTV技术采集泵轮和涡轮内部二维切面流场图像，采用单帧三次曝光的方法记录单个示踪粒子在流场中三段不同长度的运动轨迹——箭头、箭身和箭尾。通过图像增强、阈值分割和图像锐化进行动态图像处理，有效识别并准确判断了液力偶合器内部流速方向，实现了流场可视化。研究了基于霍夫变换直线检测理论在识别流速方向上的具体应用，实现了全流场流速方向的自动识别。运用Canny边缘检测算法，并引入双阈值法有效地检测出粒子运动轨迹的单像素边缘，提取了粒子运动位移的大小，进而获得液力偶合器内部流速，实现了流速的量化。
流速识别的准确性和精度取决于标定。制造高精度标定盘贴附在液力偶合器外壁表面，标定盘上均匀分布有直径2mm的圆孔。通过CCD相机采集圆孔图像，经过图像处理检测图像上圆孔直径大小，将该值与圆孔的实际直径大小进行比较，获得静态图像标定系数。当液力偶合器以一定转速旋转工作时，CCD相机采集标定盘上圆孔的运动轨迹，通过角点检测算法提取图像上圆孔运动轨迹长度大小，将该值与理论计算下圆孔的运动轨迹长度进行比较，获得动态图像标定系数。通过静态标定和动态标定，确定流动图像上每个像素的大小，进而计算获得液力偶合器内部流场的速度大小。
3.基于PIV相关算法的液力偶合器内部流速识别方法
研究粒子图像测速方法提取液力偶合器内部速度场。为了研究制动工况（i=0）下液力偶合器涡轮内部复杂流场，在高粒子浓度下，通过PIV技术采集其内部二维切面流场图像。通过研究图像连续帧的PIV互相关算法，基于图像匹配的原则，计算了涡轮径向切面二维流场速度的分布。通过比较图像上两点之间的距离大小与实际对应的距离大小，确定标定系数，获得标定后流场速度。研究并分析了流场中错误速度矢量产生的原因，基于流场误矢量的修正准则，剔除了错误速度矢量，优化了PIV互相关计算后的速度场结果，实现了液力偶合器流场可视化与流速的量化，获得流速分布图谱，并在此基础上详细分析了涡轮内部流场结构特征与分布规律。
4.试验测试与仿真计算对比分析
对试验测试结果与基于CFD仿真计算的结果进行对比分析。利用UG建立液力偶合器三维计算模型，对模型进行一定的简化，抽取液力偶合器周期流道模型以进行内部流场分析。将流道模型导入到ICEM-CFD软件中，利用映射法对泵轮和涡轮流道模型进行规则的四面体网格划分。设置湍流模型为标准k-ε模型，速度-压力耦合算法为SIMPLE算法，离散格式为一阶迎风格式，使用标准的壁面函数。通过滑移网格技术来模拟泵轮和涡轮之间的相对运动，计算了液力偶合器三维流场速度分布，截取泵轮和涡轮径向、轴向剖面，剖面的位置与试验测试中激光片光的位置保持一致。通过PIV试验测试结果与CFD仿真计算结果进行对比分析，结果表明速度场分布保持一致，流速值大小相对接近，理论与试验结果达到较好的统一。详细分析了PIV试验测试过程中误差产生的原因，并给出了相应的解决方案。
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 couplnig
The 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 technology
The 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 algorithm
Internal 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 simulation
Three-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.
本文结合国家高技术研究发展计划（863计划）专题课题“大型泵与风机液力调速节能关键技术研究”（2007AA05Z256），论文围绕液力偶合器内部流动可视化方法，基于粒子图像测速技术开展液力偶合器内部流动可视化和流速识别方法研究，通过数字图像处理技术，并结合单帧图像PTV算法和连续帧图像的PIV互相关算法，识别并提取了液力偶合器二维切面流场上的流动速度矢量，实现了液力偶合器内部二维切面流场可视化与流速的量化。本文的研究内容主要有以下几个方面：
1.液力偶合器内部流动可视化
基于粒子图像测速技术实现液力偶合器内部流动可视化。在设计工况（i=0.97）、中间工况（i=0.6）和制动工况（i=0）下，采集在不同粒子浓度下液力偶合器内部流动图像，可视化液力偶合器内部流场，直接观察到所要研究流动区域上的流动现象和流动特征。通过对采集图像进行图像预处理，有效改善并提高了图像质量，使流场中示踪粒子清晰易于识别，为后续流速识别与提取的研究工作奠定了基础。
2.基于PTV技术的液力偶合器内部流速识别方法
研究粒子跟踪测速方法识别并提取液力偶合器内部流速。在低粒子浓度下，基于PTV技术采集泵轮和涡轮内部二维切面流场图像，采用单帧三次曝光的方法记录单个示踪粒子在流场中三段不同长度的运动轨迹——箭头、箭身和箭尾。通过图像增强、阈值分割和图像锐化进行动态图像处理，有效识别并准确判断了液力偶合器内部流速方向，实现了流场可视化。研究了基于霍夫变换直线检测理论在识别流速方向上的具体应用，实现了全流场流速方向的自动识别。运用Canny边缘检测算法，并引入双阈值法有效地检测出粒子运动轨迹的单像素边缘，提取了粒子运动位移的大小，进而获得液力偶合器内部流速，实现了流速的量化。
流速识别的准确性和精度取决于标定。制造高精度标定盘贴附在液力偶合器外壁表面，标定盘上均匀分布有直径2mm的圆孔。通过CCD相机采集圆孔图像，经过图像处理检测图像上圆孔直径大小，将该值与圆孔的实际直径大小进行比较，获得静态图像标定系数。当液力偶合器以一定转速旋转工作时，CCD相机采集标定盘上圆孔的运动轨迹，通过角点检测算法提取图像上圆孔运动轨迹长度大小，将该值与理论计算下圆孔的运动轨迹长度进行比较，获得动态图像标定系数。通过静态标定和动态标定，确定流动图像上每个像素的大小，进而计算获得液力偶合器内部流场的速度大小。
3.基于PIV相关算法的液力偶合器内部流速识别方法
研究粒子图像测速方法提取液力偶合器内部速度场。为了研究制动工况（i=0）下液力偶合器涡轮内部复杂流场，在高粒子浓度下，通过PIV技术采集其内部二维切面流场图像。通过研究图像连续帧的PIV互相关算法，基于图像匹配的原则，计算了涡轮径向切面二维流场速度的分布。通过比较图像上两点之间的距离大小与实际对应的距离大小，确定标定系数，获得标定后流场速度。研究并分析了流场中错误速度矢量产生的原因，基于流场误矢量的修正准则，剔除了错误速度矢量，优化了PIV互相关计算后的速度场结果，实现了液力偶合器流场可视化与流速的量化，获得流速分布图谱，并在此基础上详细分析了涡轮内部流场结构特征与分布规律。
4.试验测试与仿真计算对比分析
对试验测试结果与基于CFD仿真计算的结果进行对比分析。利用UG建立液力偶合器三维计算模型，对模型进行一定的简化，抽取液力偶合器周期流道模型以进行内部流场分析。将流道模型导入到ICEM-CFD软件中，利用映射法对泵轮和涡轮流道模型进行规则的四面体网格划分。设置湍流模型为标准k-ε模型，速度-压力耦合算法为SIMPLE算法，离散格式为一阶迎风格式，使用标准的壁面函数。通过滑移网格技术来模拟泵轮和涡轮之间的相对运动，计算了液力偶合器三维流场速度分布，截取泵轮和涡轮径向、轴向剖面，剖面的位置与试验测试中激光片光的位置保持一致。通过PIV试验测试结果与CFD仿真计算结果进行对比分析，结果表明速度场分布保持一致，流速值大小相对接近，理论与试验结果达到较好的统一。详细分析了PIV试验测试过程中误差产生的原因，并给出了相应的解决方案。
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 couplnig
The 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 technology
The 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 algorithm
Internal 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 simulation
Three-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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