利用中国气象科学研究院灾害天气国家重点实验室的车载C波段双线偏振多普勒雷达(C-band PolarimetricDoppler Radar on Wheel,CPDRW)的外场试验,在统计分析降水、地物回波差分传播相移φ_(DP)数据的差别与信噪比关系等基础上,提出了一...利用中国气象科学研究院灾害天气国家重点实验室的车载C波段双线偏振多普勒雷达(C-band PolarimetricDoppler Radar on Wheel,CPDRW)的外场试验,在统计分析降水、地物回波差分传播相移φ_(DP)数据的差别与信噪比关系等基础上,提出了一套数据分析和处理的方法。该方法通过φ_(DP)的异常波动并结合回波的强度Z_H和速度V_r信息将地物回波信号分离出来,在降水估测或衰减订正等定量应用时将其剔除。对于气象回波则根据信噪比及零滞后互相关系数ρ_(HV)(0)将φ_(DP)资料分为较好、较差和差3类。对于较好数据直接进行后续的预处理,对于较差数据先订正后处理,而对于差数据将其剔除以保证φ_(DP)资料的整体质量。经过大量资料的验证,该方法在最大程度上保留气象信息的同时也保证了φ_(DP)资料的质量,并能估算出质量较高的差分传播相移率K_(DP)资料。展开更多
The histories of differential pressure fluctuations and their Fast Fourier Transform spectrum have close relation with the flow regimes.Unfortunately,each type of flow regime is very difficult or impossible to be dist...The histories of differential pressure fluctuations and their Fast Fourier Transform spectrum have close relation with the flow regimes.Unfortunately,each type of flow regime is very difficult or impossible to be distinguished from the other on the basis of the fluctuations or the spectrum.The present paper provides a feasible solution, which the gas-liquid two-phase flow regimes can be recognized automatically and objectively on the basis of the combination of the Counter Propagation Network (CPN) and the FFT spectrum of the differential pressure fluctuations. The CPN takes advantages of simpler algorithm and fast training processes.Furthermore,it does not require a great deal of samples.The recognition possibility is determined by the clustering results of the Kohonen layer in the CPN.With the presented test cases,the possibility can be higher than 90 percent for different liquid phase velocity.展开更多
文摘利用中国气象科学研究院灾害天气国家重点实验室的车载C波段双线偏振多普勒雷达(C-band PolarimetricDoppler Radar on Wheel,CPDRW)的外场试验,在统计分析降水、地物回波差分传播相移φ_(DP)数据的差别与信噪比关系等基础上,提出了一套数据分析和处理的方法。该方法通过φ_(DP)的异常波动并结合回波的强度Z_H和速度V_r信息将地物回波信号分离出来,在降水估测或衰减订正等定量应用时将其剔除。对于气象回波则根据信噪比及零滞后互相关系数ρ_(HV)(0)将φ_(DP)资料分为较好、较差和差3类。对于较好数据直接进行后续的预处理,对于较差数据先订正后处理,而对于差数据将其剔除以保证φ_(DP)资料的整体质量。经过大量资料的验证,该方法在最大程度上保留气象信息的同时也保证了φ_(DP)资料的质量,并能估算出质量较高的差分传播相移率K_(DP)资料。
文摘The histories of differential pressure fluctuations and their Fast Fourier Transform spectrum have close relation with the flow regimes.Unfortunately,each type of flow regime is very difficult or impossible to be distinguished from the other on the basis of the fluctuations or the spectrum.The present paper provides a feasible solution, which the gas-liquid two-phase flow regimes can be recognized automatically and objectively on the basis of the combination of the Counter Propagation Network (CPN) and the FFT spectrum of the differential pressure fluctuations. The CPN takes advantages of simpler algorithm and fast training processes.Furthermore,it does not require a great deal of samples.The recognition possibility is determined by the clustering results of the Kohonen layer in the CPN.With the presented test cases,the possibility can be higher than 90 percent for different liquid phase velocity.