中文摘要：

为揭示非平稳随机脉动风的时频特性，基于小波变换原理推导了时变功率谱的时间、频率和幅值与小波变换系数的关系，建立了非平稳随机脉动风时变功率谱估计的小波函数加权和法，并采用模拟非平稳脉动风和实测台风过程对理论推导结果进行了验证。研究结果表明：非平稳随机过程在某一时刻的不同尺度小波变换系数是一个以此非平稳随机过程的调制函数与小波函数的乘积为调制函数的非平稳随机过程的傅里叶变换，非平稳随机过程的时变功率谱等于不同尺度和不同时移的小波函数模平方的加权和，小波函数加权和法计算的非平稳随机脉动风的时变功率谱与理论结果具有良好的一致性。小波函数加权和法可有效地估计非平稳随机脉动风的时变功率谱，估计的时变功率谱可为进一步理解强（台）风的随机脉动特性奠定基础。

英文摘要：

To further understand the time-frequency characteristics of non-stationary fluctuating wind, the relationship between time, frequency and amplitude of the evolutionary power spectrum （EPS） and wavelet transform coefficients are analyzed based on the principle of wavelet transform. The weighted wavelet function method （WWFM） is proposed to estimate the EPS of non-stationary fluctuating wind. The theoretical results are demonstrated by a series of simulated non-stationary fluctuating wind and field measurement typhoon process. The study results show that the wavelet transformation coefficients under different scales of a certain non-stationary stochastic process at a certain time are the Fourier transform of a new non-stationary stochastic process and the modulating function of the new non-stationary stochastic process is the product of the modulating function of this certain non-stationary stochastic processes and the wavelet function. The EPS of non-stationary stochastic processes can be calculated by the sum of weighted square modulus of wavelet functions at different scales and different time parameters, and the weighted coefficients are defined by the wavelet transformation results. The EPS of simulated non-stationary stochastic wind estimated by the WWFM is accordant well to theanalytical results. The WWFM can estimate the EPS of non-stationary fluctuating wind effectively and the computed EPS can aid to understand the randomness of fluctuate wind further more.