基于数据压缩的皮尔逊互相关烟丝测速方法

Tobacco Velocity Measurement of Pearson Cross Correlation Method Based on Data Compression

由于烟丝颗粒模型的特点比传统气固两相流更加复杂多变,一般的两相流测量方法难以应用于烟丝测速,而且在线测量难以同时兼顾精确性和实时性,故采用皮尔逊互相关原理进行测速,实现不依赖对象模型的光学互相关测速方法.同时针对皮尔逊互相关法计算量大的问题,提出基于数据压缩的改进方法,先用均值滤波压缩数据量进行互相关计算获得参考值,再用不滤波的互相关计算获得高精度测量值,最后通过实验验证所提出方法的有效性.

Because tobacco particle model is more complicated than the traditional gas-solid two-phase flow,the general two-phase flow measurement method cannot be applied to tobacco velocity measurement,and it is difficult to balance between accuracy and real-time when measuring online.Pearson cross-correlation theory was used to measure speed,and the measurement method by optical cross-correlation method does not rely on parameters was implemented.To address the problem of large volumes of Pearson cross-correlation calculations,an improved method was proposed based on data compression,that is,using mean filter to compress data and calculate the cross-correlation coefficient reference value first,and then calculate cross-correlation coefficient for high accuracy measurements.Finally,the effectiveness of the proposed method was verified by the experimental results.