桥梁健康监测系统利用通讯传感设备远程记录运营中的结构持续响应，通过对信号数据的处理分析实现桥梁结构的实时预警与安全评估，从而达到保护结构正常运营、延长结构使用寿命、指导桥梁结构管养与维护决策的目的。桥梁健康监测技术作为桥梁工程领域新兴的分支，已逐渐成为一个热门研究方向。为了促进该领域研究进一步发展，指导健康监测系统在桥梁工程中更高效的应用，对桥梁健康监测系统的信号降噪、信号预警、模态参数识别、有限元模型修正、损伤识别、状态预测与评估等关键技术方法的研究现状进行了详细介绍，并对2020年度内相关研究进展及应用进行了总结与评述，最终发现机器学习方法正越来越广泛地应用到桥梁健康监测各项关键技术的现阶段研究中。

The bridge health monitoring system (BHMS) continuously measures and records the structural responses by using a variety of sensors and communication devices in the bridge operation process. The automatic analysis of signal data can be done effectively in the BHMS to fulfill the timely danger warning and safety assessment. The BHMS leads to the better transportation operation of bridges, the longer service life of bridges, and the more reasonable determination of the bridge management and maintenance for engineers. For the sake of the more efficient application of health monitoring system in bridge engineering, this paper summarizes the current states of several representative BHMS techniques: signal denoising, signal warning, modal parameter identification, finite element model updating, damage identification, condition prediction and assessment. Then, the related researches and applications of these key techniques during 2020 are summarized and discussed. Consequently, it is found that the machine learning methods have been more and more widely used in the current research of key technologies of the bridge health monitoring.

国家自然科学基金(51978577、51678489)；国家重点研发计划(2016YFC0802202)；国家重点基础研究发展计划(2013CB0363)；中电建路桥集团资助科研项目(SCMQ-201728-ZB)