Correlation analysis of factors affecting bridge health under the background of big data

Once the bridge is put into use, in addition to its own material aging, it will also receive damage from human factors such as vehicles, wind, earthquakes, fatigue, and overload. This damage has more or less reduced the service life of the bridge or even destroyed the safety performance of the bridge, causing huge losses to people's lives and property. This requires us to pay attention to the safety, reliability and durability of the bridge at all times during the construction of the bridge and in the later maintenance process. The traditional bridge monitoring work and operation and maintenance have a low degree of automation, bridge condition assessment, and bridge real-time monitoring and comprehensive information management is difficult. This requires real-time monitoring of this information in the context of big data to ensure the healthy use of the bridge. In this paper, a finite element analysis model is established to monitor the sensor network of the bridge and the data detected by the sensor in the context of big data. The optimization analysis results in an optimized layout plan of the identifiable static sensors, taking into account both the economic and structural operating conditions of the bridge.