Development and application of measurement system for surface flow field in large-scale river model test
-
摘要: 在河工模型试验中, 粒子图像表面流场测量方法得到了广泛应用。研制了一种新型分布式表面流场测量系统,该系统采用局域网组网与光纤传输相结合,通过POE千兆交换机与高清智能一体化工业摄像机相连,显著降低了布线复杂度,具有系统传输距离远、布设简单、集成度高、可扩展性强等优点。系统具备可视化全自动采集、可视化错误矢量剔除、导出多种数据格式,生成流场等值线图、流线等功能。在系统研制基础上,提出了一种对粒子图像表面流场测量系统进行精度检测的新方法,通过精确控制匀速旋转平台模拟水流运动,将表面流场测量系统实测数据与旋转平台上各点精确数据进行对比检测,检测结果表明,研制的表面流场测量系统测量误差小于5%,已在长江河口模型等多个大型河工模型中得到成功应用。Abstract: For river model tests, the particle image measurement methods for the surface flow field have been applied widely. A new type of distributed measurement system for the surface flow field was developed for large-scale river model tests. Million-pixel high-definition intelligent integrated industrial cameras were used in this system and connected with a computer with wireless network. There is a gigabit POE (Power Over Ethernet) interface in the camera. The image transmission and camera power supply can be completed at the same time by only a cable with a gigabit POE switch. The complexity of wiring can be significantly reduced so that the cameras can be easily added into the system. The system has functions such as visual and automatic acquisition, visual elimination for error vector, data export with a variety of data formats, generation of flow contours and streamlines; A new detection method for the measurement system of the particle image surface flow field is introduced in this study. Water flow can be simulated by the accurate control of the uniform rotation of the platform. The measured data from the flow field measurement system and the accurate data of the rotating platform are compared. The accuracy of the time of the image acquisition control, calibration of image distortion and flow extraction algorithm can be detected. The model test results show that the measurement errors of the measurement system for the surface flow field are less than 5%. The system has been successfully applied in the Yangtze River estuary model tests and other large river models tests.
-
Key words:
- model test /
- flow measurement /
- particle image /
- detection method
-
-
[1] 唐洪武. 复杂水流模拟问题及图像测速技术的研究[D]. 南京: 河海大学, 1996. TANG Hongwu. Research on complex flow simulation and image velocimetry[D]. Nanjing: Hohai University, 1996. (in Chinese) [2] 王兴奎, 庞东明, 王桂仙, 等.图像处理技术在河工模型试验流场量测中的应用[J].泥沙研究, 1996(4): 21-26. http://industry.wanfangdata.com.cn/dl/Detail/Patent?id=Patent... WANG Xingkui, PANG Dongming, WANG Guixian, et al. Application of image processing technics to velocity field measurement in physical model[J]. Journal of Sediment Research, 1996(4): 21-26. (in Chinese) http://industry.wanfangdata.com.cn/dl/Detail/Patent?id=Patent... [3] 田晓东, 陈嘉范, 李云生, 等. DPIV技术及其应用于潮汐流动表面流速的测量[J].清华大学学报(自然科学版), 1998, 38(1): 103-106. http://industry.wanfangdata.com.cn/dl/Detail/Periodical?id=... TIAN Xiaodong, CHEN Jiafan, LI Yunsheng, et al. DPIV technique and its application of velocity measuring tidal flow[J]. Journal of Tsinghua University (Sciences Technological), 1998, 38(1): 103-106. (in Chinese) http://industry.wanfangdata.com.cn/dl/Detail/Periodical?id=... [4] 唐洪武, 陈诚, 陈红, 等.实体模型表面流场、河势测量中图像技术应用研究进展[J].河海大学学报(自然科学版), 2007, 35(5): 567-572. http://d.wanfangdata.com.cn/Periodical_hhdxxb200705018.aspx TANG Hongwu, CHEN Cheng, CHEN Hong, et al. Review of image processing technique applied to measurement of surface flow field and river regime of physical model[J]. Journal of Hohai University(Natural Sciences), 2007, 35(5): 567-572. (in Chinese) http://d.wanfangdata.com.cn/Periodical_hhdxxb200705018.aspx [5] 吴龙华, 严忠民, 唐洪武. DPIV相关分析中相关窗口大小的确定[J].水科学进展, 2002, 13(5): 594-598. http://industry.wanfangdata.com.cn/dl/Detail/Periodical?id=... WU Longhua, YAN Zhongmin, TANG Hongwu. Determination of the correlation window sizes in correlation analysis of DPIV[J]. Advances in Water Sicence, 2002, 13(5): 594-598. (in Chinese) http://industry.wanfangdata.com.cn/dl/Detail/Periodical?id=... [6] SUTARTO T E. Application of large scale particle image velocimetry (LSPIV) to identify flow pattern in a channel[J]. Procedia Engineering, 2015, 125: 213-219. doi: 10.1016/j.proeng.2015.11.031 [7] KANTOUSH S A, SCHLEISS A J. Large-Scale PIV Surface Flow Measurements in Shallow Basins with Different Geometries[J]. Journal of Visualization, 2009, 12(4): 361-373. doi: 10.1007/BF03181879 [8] FOX J F, PATRICK A. Large-scale eddies measured with large scale particle image velocimetry[J]. Flow Measurement and Instrumentation, 2008, 19(5): 283-291. doi: 10.1016/j.flowmeasinst.2008.01.003 [9] FUJITA I, KUNITA Y. Application of aerial LSPIV to the 2002 flood of the Yodo River using a helicopter mounted high density video camera[J]. Journal of Hydro-Environment Research, 2011, 5(4): 323-331. doi: 10.1016/j.jher.2011.05.003 [10] SHI S, CHEN D. The development of an automated PIV image processing software—SmartPIV[J]. Flow Measurement and Instrumentation, 2011, 22(3): 181-189. doi: 10.1016/j.flowmeasinst.2011.01.007 [11] CHIN D, SANG J L. Evaluation of recursive PIV algorithm with correlation based correction method using various flow images[J]. KSME International Journal, 2003, 17(3): 409-421. doi: 10.1007/BF02984367 [12] TANG H W, CHEN C, CHEN H, et al. An improved PTV system for large-scale physical river model[J]. Journal of Hydraulics, 2008, 20(6): 669-678. [13] NEZU I, SANJOU M. PIV and PTV measurements in hydro-sciences with focus on turbulent open-channel flows[J]. Journal of Hydro-environment Research, 2011, 5(4): 215-230. doi: 10.1016/j.jher.2011.05.004 -