## 1 Introduction  
In recent years, ultra-high voltage (UHV) transmission lines were rapidly developed in China. Transmission towers are important infrastructure for transmission lines and their safety is directly related to the operation of the line [1, 2, 3]. Due to prolonged exposure to the atmosphere, the steel members of transmission towers are prone to rust and corrosion under the effect of acid rain, leading to the degradation of tower performance. In this regard, it is of great engineering significance to conduct global time-varying reliability analysis of transmission towers to predict the service performance. The current global reliability analysis methods for transmission towers mainly include the Monte Carlo simulation (MCS) method [4], failure mode identification method [5, 6, 7], and performance function equivalent description method [8]. Although the MCS method is simple and easy to implement, it is not suitable for global reliability analysis of large and complex transmission towers due to its high computational cost. [PERSON]. [6, 7] combined the failure mode identification method with the Ditlevsen bounds method for the global reliability analysis of transmission towers. However, it is difficult to identify the failure mode due to the large number of members in transmission towers, and the correlation between any two failure modes was not reasonably considered. It is worth pointing out that the [PERSON]. [9] studied the global reliability of transmission towers by combining the equivalent description method of the performance function and high-order moment method. The equivalent description of the performance function reasonably considers the correlations of these failure modes. Nevertheless, existing research on the reliability of transmission towers still focuses on time-invariant global reliability analysis, and research on time-varying global reliability of in-service transmission towers in relation to performance degradation is rarely reported. Compared to research on time-invariant global reliability, research on time-varying global reliability is more challenging and computationally expensive. Over the past few decades, research on time-varying reliability received great attention and some novel methods were proposed, e.g., the time-discrete-integrated method [10], first transcendental reliability conversion method [11; 12; 13], time-invariant and time-varying reliability conversion method [14], probability density evolution method [15], and MCS [16]. However, these relevant studies mostly limit time-varying reliability analysis to the member level. Ref. [17] proposed a time-varying global reliability analysis method based on high-order moments, and the results indicate that this method can provide good precision for simple structural systems. However, the order of the required high-order moments is determined subjectively in this method, and the introduction of the dimension reduction method (DRM) cannot guarantee the required accuracy for complex engineering structures. In general, there is a lack of research on methods to analyze time-varying global reliability that can achieve a better tradeoff between accuracy, efficiency, and versatility for in-service transmission towers. The objective of this paper is to develop a time-varying global reliability analysis method for in-service transmission towers that can effectively evaluate their time-varying global reliability with a tradeoff between accuracy and efficiency. The remainder of this paper is organized as follows: In Section 2, the time-varying equivalent performance function for in-service transmission towers under the action of random wind loads is established. In Section 3, the high-order moments-based improved maximum entropy method (HM-IMEM) is proposed, and the time-varying global reliability analysis for in-service transmission towers is presented based on the HM-IMEM.