(1. Key Laboratory for Power Machinery and Engineering (the Ministry of Education)， Shanghai Jiaotong University, Shanghai, 200240, China； 2. Trane’s AsiaPacific Research Center, Shanghai 200001, China)
Abstract： Based on the statistic detecting methods, a reasonable algorithm was put forward to reduce the sample size of turbulent experiment. Wavelet analysis method was adopted in the algorithm to get the characteristic parameters of turbulent flow in both time domain and frequency domain. Comparing with the former algorithms, the reduced data size by the algorithm is larger, but it includes the same information with the initial sample data statistically. An example was provided to prove the reliability and rationality of the algorithm, where the sample data is from the experiment on the mechanism of riblets drag reduction and the turbulent kinetic energy is selected as the statistic characteristic parameter.
张斌，王彤，谷传纲，戴正元. 基于小波分析的湍流采样数据量缩减算法[J]. 上海交通大学学报（自然版）, .
ZHANG Bin1,WANG Tong1,GU Chuan-gang1,DAI Zheng-yuan2. Algorithm of Reducing the Sample Size of Turbulent Experiment Based on Wavelet Analysis. J. Shanghai Jiaotong Univ.(Sci.) , 2008, 42(11): 1896-1899.
