Real-time safety assessment (RTSA) of dynamic systems is a critical task that has significant implications for various fields such as industrial and transportation applications, especially in non-stationary environments. However, the absence of a comprehensive review of real-time safety assessment methods in non-stationary environments impedes the progress and refinement of related methods. In this paper, a review of methods and techniques for RTSA tasks in non-stationary environments is provided. Specifically, the background and significance of RTSA approaches in non-stationary environments are firstly highlighted. We then present a problem description that covers the definition, classification, and main challenges. We review recent developments in related technologies such as online active learning, online semi-supervised learning, online transfer learning, and online anomaly detection. Finally, we discuss future outlooks and potential directions for further research. Our review aims to provide a comprehensive and up-to-date overview of real-time safety assessment methods in non-stationary environments, which can serve as a valuable resource for researchers and practitioners in this field.

翻译：动态系统的实时安全评估是一项关键任务，在工业与交通等应用领域具有重要影响，尤其是在非平稳环境中。然而，目前尚缺乏对非平稳环境下实时安全评估方法的系统性综述，这阻碍了相关方法的进展与完善。本文对非平稳环境下实时安全评估任务的方法与技术进行了综述。具体而言，首先强调了非平稳环境下实时安全评估方法的背景与重要性，随后给出了涵盖定义、分类及主要挑战的问题描述。我们综述了在线主动学习、在线半监督学习、在线迁移学习及在线异常检测等技术的近期发展。最后，探讨了未来研究方向与潜在发展路径。本综述旨在为非平稳环境下的实时安全评估方法提供全面且最新的概述，可作为该领域研究人员与实践者的重要参考资料。