针对粒子追踪技术中的粒子误对应问题与粒子相关法对粒子区域平均化处理所带来的误差问题,制定了用于粒子图像测速的细胞分裂准则,并提出了基于细胞分裂的粒子追踪匹配算法模型:将兴趣区域作为细胞体并以细胞体内单点匹配相关程度与粒子的近邻程度作为判断准则对分析窗口内的点进行分裂;分裂形成的子团之间进行竞争并将优胜团代表本分析区域参与其他区域优胜团的竞争;根据优胜团先后位置变化得到矢量位移场.最后,使用人工合成的粒子图进行了算法验证及误差分析.结果表明:所提算法在分析精度方面有了较大的提高.

False matching in particle tracking velocimetry(PTV)and low-pass feature of particle correlation velocimetry(PCV)can make the processing error improve.However,the two problems can be reduced by application of cell segmentation theory(CST)presented in this paper.Furthermore,the CST processing model is described as:Firstly,the interrogation fields are divided into different local spaces named as cells,and these cells continue to segment into sub-cells according to correlation degree and close degree.Secondly,these sub-cells compete against each other and the final victorious one attends competition in other fields.Thirdly,the velocity vector field is gotten according to the positional alteration of the victorious cell.At last,the standard particle images were tested and the errors were analyzed.The experimental results demonstrate the effectiveness and practicability of the proposed method.