在极端自然灾害频发、城市系统高度耦合及运行压力持续增长的背景下，提升城市基础设施的安全韧性水平成为保障国家安全和推动可持续发展的关键举措。然而，当前基础设施韧性技术的发展水平与建设韧性城市的实际需求之间仍存在显著差距，亟需对相关技术体系和研究进展进行系统梳理与总结。本文从自然灾害预测与预警、基础设施脆弱性与风险评估、基础设施功能损失与韧性评估、基础设施韧性提升与设计、基础设施灾害应急响应与优化决策等5个方面，深入分析了当前技术研究现状与未来发展趋势。研究认为，尽管“韧性防灾”推动了基础设施防灾从单纯关注抗灾安全转变为更加注重灾后系统级的功能与恢复，“智能防灾”提高了灾害感知、预测预警以及应急响应决策的效率与精确性，但仍然存在缺乏统一的韧性技术标准和规范、多灾种联合建模不足、跨系统协同机制缺失、智能模型泛化能力弱以及可解释性差等问题。未来，构建统一的基础设施安全韧性理论体系和标准规范，基于“数据赋能+语言驱动+认知推理”形成多源数据融合、跨模态知识迁移、跨灾种联合评估、跨系统协同、可解释性强的智能技术体系是重要发展趋势。本文进一步从制度保障、智慧赋能与资源支撑、技术标准体系建设等维度提出发展建议，以期为推动我国城市基础设施安全韧性能力的系统性跃升提供理论支撑与技术参考。

Amid increasingly frequent extreme natural disasters, highly interconnected urban systems, and mounting operational pressures, enhancing the safety and resilience of urban infrastructure has become a vital strategy for safeguarding national security and advancing sustainable development. However, a significant gap persists between the current state of resilience-related technologies and the practical demands of building resilient cities, highlighting the urgent need for a systematic review of relevant technical systems and recent research progress. This study analyzes the current state and future development trends of urban infrastructure resilience technologies across five key domains: natural disaster forecasting and early warning, infrastructure vulnerability and risk assessment, functionality degradation and resilience evaluation, resilience enhancement and design, and emergency response and decision-making optimization. The study finds that while resilience-based disaster prevention has shifted the focus of infrastructure safety from structural robustness to system-level functionality and post-disaster recovery, and intelligent disaster prevention has greatly enhanced the efficiency and accuracy of disaster sensing, forecasting, and emergency response, several major challenges persist. These challenges include the absence of unified standards for resilience technologies, insufficient multi-hazard joint modeling, weak cross-system coordination, poor generalization and interpretability of intelligent models, and limited transparency in decision-making processes. Looking ahead, a key development trend will involve building a unified theoretical framework and standardized system for infrastructure safety and resilience. This should be supported by an intelligent technology system characterized by data empowerment, language-driven interaction, and cognitive reasoning, facilitating multi-source data fusion, cross-modal knowledge transfer, multi-hazard joint assessment, system-level coordination, and high interpretability with transparent mechanisms. Furthermore, the study offers development recommendations from the aspects of institutional support, intelligent enablement and resource allocation, as well as technical standardization, aiming to provide theoretical foundations and practical guidance for systematically enhancing urban infrastructure resilience in China.