## 1 Introduction  
The steel transmission tower is a significant component of the electrical systems for the power transmission and distribution network [1; 2]. The reliability and safety of steel transmission towers are crucial issues in both the design process and the operation periods [3]. The failure or damage of steel transmission towers can cause huge economic losses and even disasters for both industrial manufacturing and people's daily lives [4]. The surveillance sensors are useful to help monitor the real-time status of transmission towers [5]. By the data of surveillance sensors, it is not only possible to predict the safe service life, but it is also possible to avoid the collapse of transmission towers by the maintenance in advance. The application of surveillance sensors in the key location of the transmission towers to monitor the real-time status attracts great concerns of engineers and researchers. For example, the inclination sensors are effective at reflecting the stress of the large deformation, but the parameters corresponding to the load balance and the yield failure of the local rods are ignored [6]. In addition, the strain sensors by the resistance strain gauge are sensitive enough to identify the fluctuation of forces, but are very susceptible to electromagnetic interference and are not robust enough to avoid rusting in the measurement circuits [7]. Even though the grating fiber strain sensors have some level of improvement in the measurement accuracy and range, the limitation in the installation location and quantity is not completely overcome [8]. The modal identification sensors are one of the promising technologies and have been widely used in structural health monitoring, such as in the reinforced concrete bridges [9; 10] and wind turbine blades [11]. By the modal identification of the reinforced concrete bridges, the passing vehicles on the bridge pavement deck and fatigue damage of the bridge body are tracked and recorded. Moreover, the modal frequency sensors are effective in identifying the vibration of wind turbine blade and are sensitive to the structural changes related to damage or failures. Furthermore, the modal identification technology is also applied in the safety and reliability analysis of transmission towers [12]. The inevitable uncertainties and interference in the modal identification of transmission towers are originated from several aspects. First, the terrain environment often has uncontrollable factors, such as the ground displacement, foundation inclination and even cracking and subsidence of rocks. In addition, the natural climate and weather environment also provides unpredictable uncertainties [13]. For example, snow in the winter not only evidently increases the weight of the transmission towers, but also heavily influences the material properties of steel, which causes the reduction of structural stiffness and strength and makes transmission towers fragile to fracture and collapse. Besides, the random wind force is non-negligible to affect the modal identification of transmission towers [14; 15]. Under the strong winds [16], such as hurricanes, tornados or isolated thunderstorms, the nonlinear inelastic behaviors of transmission tower structures become dominated [17; 18]. The quasi-steady dynamic loads make the modal frequencies of transmission towers difficult to analyze. Therefore, it is necessary to develop the feasible analytical model to identify and reduce the interference in modal identification sensors of transmission towers. This paper proposes a Kriging surrogate model to effectively reduce the interference in settlement surveillance sensors of steel transmission towers. At first, the finite element model of the transmission tower structure is created based on the ANSYS Parameter Design Language (ANSYS, APDL, Version 14.5). Meanwhile, the first five order vibration modes and natural frequencies are computed and recorded.