IoT sensors play a crucial core role in smart bridge management and control, acting like the “nervous system” of the bridge. They continuously perceive, collect, and transmit various state information of the bridge, which is fundamental for achieving intelligent management throughout the bridge’s lifecycle, ensuring safety, extending lifespan, and optimizing maintenance.
1.Structural Health Monitoring
(1)Real-time perception of key parameters
Sensors (such as strain gauges, accelerometers, inclinometers, displacement meters, GPS/Beidou receivers, fiber optic sensors, etc.) are deployed at critical locations of the bridge (main beams, piers, bearings, towers, cables, hangers, etc.) to monitor the bridge’s:
Strain/Stress: Reflects the structural loading state, detecting overload or localized damage.
Vibration/Acceleration: Monitors the dynamic characteristics of the bridge (frequency, mode shapes, damping ratio); abnormal vibrations may indicate damage or resonance risks.
Displacement/Deformation: Monitors the linear changes of the bridge under load, temperature, and wind effects, as well as bearing displacements, pier settlements, or tilts, to assess overall stability and geometric conditions.
Cracks: Utilizes crack gauges or image recognition sensors to monitor the width development of critical cracks.
(2)Assessing Structural Condition
By continuously collecting data and comparing it with design models, historical data, or thresholds, the overall structural performance and health of the bridge can be evaluated.
(3)Early Damage Identification
By analyzing trends and patterns in data changes, potential damages (such as micro-crack propagation, loose connections, material degradation, etc.) can be identified before they become visible or cause serious consequences.
2.Environmental Load Monitoring
(1)Meteorological Monitoring
By deploying wind speed and direction instruments, temperature and humidity sensors, rain gauges, and other equipment on the bridge, environmental conditions can be monitored to assess the impact of wind loads, thermal stresses, freeze-thaw cycles, and acid rain corrosion on the bridge. This is particularly important during strong winds, extreme temperatures, and icy weather.
(2)Hydrological Monitoring
Utilizes water level gauges and flow meters to monitor river water levels and flow rates at the bridge site, preventing the impact of floods and scouring on pier foundations.
(3)Seismic Monitoring
Records the seismic response of the bridge during seismic events using strong motion sensors, assessing post-earthquake damage to provide a basis for emergency response and repairs.
3.Traffic Load Monitoring and Assessment
(1)Dynamic Weighing
Utilizes sensors embedded in the road surface or vibration-based analysis to monitor the weight, axle load, speed, and vehicle type of passing vehicles. This is key for assessing the actual load capacity of the bridge, identifying overloaded vehicles, and conducting load spectrum analysis.
(2)Traffic Flow Statistics
By monitoring traffic volume and lane occupancy, data is provided for traffic management and congestion analysis.
(3)Load Effect Analysis
Combines traffic load data with structural response data (strain, vibration) to analyze the real effects of traffic on the bridge structure, verifying design assumptions or identifying potential issues.
4.Material Condition and Durability Monitoring
(1)Corrosion Monitoring
Reinforcement corrosion sensors, concrete resistivity/chloride ion content sensors, etc., monitor the corrosion status of reinforced concrete structures, assessing the rate of durability degradation.
(2)Fatigue Monitoring
Specifically for steel bridges or critical welded joints, high-frequency strain data collection is used to assess fatigue damage accumulation under cyclic loads.
5.Operational Safety Monitoring
(1)Video Monitoring
Combined with AI analysis, it monitors traffic conditions on the bridge (accidents, congestion, debris), illegal intrusions (under-bridge space), and navigation safety for vessels (cross-channel bridges).
(2)Falling Objects/Impact Monitoring
By deploying specific sensors (such as vibration, acoustic) or video analysis, falling objects on the bridge deck or impacts on piers/upper structures from vessels or vehicles can be detected, triggering alarms.
6.Supporting Intelligent Decision-Making and Control
(1)Data Aggregation and Analysis Platform
All sensor data is transmitted through IoT gateways to cloud or edge computing platforms for centralized storage, processing, and analysis.
(2)Early Warning and Alarms
When monitoring data exceeds preset safety thresholds or detects abnormal patterns, the system automatically triggers graded alarms (such as SMS, email, platform pop-ups), notifying management personnel for timely intervention.
(3)Status Assessment and Predictive Maintenance
Based on big data analysis and machine learning/AI models, a comprehensive assessment of the bridge’s health status is conducted, predicting future performance degradation trends and potential risk points, providing decision support for formulating scientific and economical preventive maintenance or reinforcement plans, transitioning from “scheduled maintenance” to “on-demand maintenance”.
(4)Digital Twin
Real-time data from sensors drives the digital twin model of the bridge, enabling visual monitoring, simulation analysis, and scenario deduction, enhancing management efficiency and decision-making levels.
(5)Optimizing Resource Allocation
Based on the actual condition of the bridge rather than fixed cycles for inspections and maintenance, significantly improves the utilization efficiency of maintenance resources and reduces overall costs.
(6)Emergency Response Support
After disasters (earthquakes, floods, typhoons, impacts), quickly obtaining actual status data of the bridge to assess safety and traffic capacity, guiding repairs and traffic control.
IoT sensor technology is the cornerstone of smart bridges,transforming the traditional passive, discrete, experience-driven bridge management model into a proactive, continuous, data-driven intelligent control model, which is the core embodiment of digital transformation in the field of bridge engineering.