Research on the application of deep learning in bridge health monitoring data analysis and anomaly diagnosis
Bridge SHM systems generate large amounts of multi-sensor time-series data for structural condition assessment. However, sensor faults, transmission errors, missing data, noise, drift, and environmental disturbances often reduce the reliability of anomaly diagnosis and may lead to unnecessary maintenance alarms. This s...