Wind speed and wind direction are two important factors to describe the wind properties. The statistical probability model of wind speed and wind direction is widely used to characterize the uncertainty of wind field around the structures. Considering the correlation between the wind speed and wind direction, they should be modeled simultaneously, which highlights the importance of using joint probability density function (JPDF) to describe the wind properties. An angular–linear (AL) model is employed to construct the JPDF of wind speed and wind direction based on long-term monitoring data. The finite mixture (FM) Gumbel distribution, which models the wind speed, and the FM von Mises distribution, which models the wind direction, are proposed to formulate the AL model. Expectation–maximization (EM) and genetic algorithm (GA) are adopted to estimate the AL model parameters. For the EM method, the analytical expressions for calculating the AL model parameters are derived. For the GA method, the analytical fitness functions are derived. These derived analytical expressions facilitate the implementation of the EM and GA methods. One-year wind monitoring data collected by structural health monitoring (SHM) system installed on Jiubao Bridge is employed to demonstrate the feasibility of the AL model-based method in evaluating the wind properties. The results show that the AL model formulated by the FM Gumbel distribution and FM Von Mises distribution is effective for establishing JPDF for joint modeling of the wind speed and wind direction. In the AL model, the EM method is more effective for estimating the parameters of the FM von Mises distribution, whereas the GA methods is more powerful for estimating the parameters of the FM Gumbel distribution.

风速和风向是描述风特性的两个重要因素。风速和风向的统计概率模型被广泛用于表征结构周围风场的不确定性。考虑到风速和风向之间的相关性，应该同时对它们进行建模，这突出了使用联合概率密度函数（JPDF）来描述风属性的重要性。基于长期监测数据，采用角线（AL）模型构造风速和风向的JPDF。提出了模拟风速的有限混合（FM）Gumbel分布和模拟风向的FM von Mises分布，以建立AL模型。期望最大化（EM）和遗传算法（GA）用于估计AL模型参数。对于EM方法，推导了用于计算AL模型参数的解析表达式。对于GA方法，推导了解析适应度函数。这些导出的分析表达式有助于实现EM和GA方法。通过安装在九堡大桥上的结构健康监测（SHM）系统收集的一年风监测数据，证明了基于AL模型的方法在评估风特性方面的可行性。结果表明，由FM Gumbel分布和FM Von Mises分布建立的AL模型对于建立JPDF进行风速和风向联合建模是有效的。在AL模型中