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.So as to protect the normal operation of the structure, prolong the service life of the structure, and guide the management and maintenance decision of the bridge structure.As a new branch of bridge engineering, bridge health monitoring technology has gradually become a hot research field. 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: the decision-making analysis for the BHMS implementation, sensor signal preprocessing, signal de-noising processing, modal parameter identification, finite element model updating, damage identification, condition prediction and assessment. Then, the related researches and applications of these key techniques during 2019 are summarized and discussed.Consequently, it is found that the pattern recognition technology and the machine learning method are more and more widely used in the current research of bridge health monitoring.