对比现有的几种紊流积分尺度算法,针对其在某些来流条件下存在的系统偏差,提出了基于泰勒假定修正的紊流积分尺度识别算法.采用谐波合成法数值化地再现多组基于Von-Karman谱的宽频紊流及窄带单频的风速时程序列,利用该算法对紊流积分尺度进行识别,并将识别结果与预期理论值进行比较,提出基于时间尺度修正系数项的实用紊流积分尺度识别算法并进行了验证,得出对于宽带紊流,时间尺度修正系数适合取为2/3,对于窄带紊流,时间尺度修正系数适合取为6.结果表明:本文方法大大提高了紊流积分尺度的计算精度,具有很好的工程应用价值.%Through the comparison of multiple algorithms of turbulence integral scale, the correctional recognition algorithm based on Taylor assumption was proposed. The harmonic synthesis method was used to generate several broadband time-series based on Von-Karman spectrum and several single-frequency time-series. Through the turbulence integral scale calculation of these signals using the correctional algorithm, the recognition results were compared with the expected theoretical values and the correctness of the algorithm was validated. The correction factor obtained for the broadband turbulence was 2/3, and for the narrowband turbulence was 6. The results show that this method greatly improves the calculation accuracy of the turbulence integral scale, which has a good value in engineering application.
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