摘要
粒子图像测速技术(PIV)作为一种全新的无扰、瞬态、全场速度测量方法,在流体力学及空气动力学研究领域具有极高的学术意义和实用价值.本文对PIV技术的原理、分类作了简要地介绍,详细归纳和评述了现有的各种速度信息的提取方法,并对拓扑图论、神经网络、遗传算法、模糊聚类等新技术在PIV中的应用以及三维PIV技术、两相流PIV测试技术进行了介绍.指出当前PIV技术除了向三维和多相流方向发展外,如何提高PIV的测量精度以及缩短计算时间仍然是目前研究的主要目标. PIV技术随着计算机技术、激光技术和CCD性能的发展。
As a new method for non-intrusive, instantaneous and whole-field velocity measurement, the particle image velocimetry (PIV) is important both in the theoretical studies and application of the fields of fluid mechanics and aerodynamics. This paper briefly introduced the principle and classification of PIV techniques. Emphases are put on the detailed summarization and evaluation on the various extraction methods of velocity information from PIV images. The applications of new techniques such as topology, artificial neural network, genetic algorithm, fuzzy clustering, etc. in PIV are also discussed. The developments of three dimensional PIV (3-D PIV) and multiphase flow PIV techniques are also discussed. It is pointed out that besides extension to 3-D multiphase flow field measurements, further improvement of the accuracy and reducing the computational time still remains a current PIV research goal. With the developments of computer science, laser techniques and the performance of CCD, the PIV techniques are bound to achieve a further development and make more breakthroughs.
出处
《力学进展》
EI
CSCD
北大核心
2003年第4期533-540,共8页
Advances in Mechanics
基金
国家自然科学基金资助项目(50079020)~~
