Damage Detection of Bridges under Environmental Temperature Changes Using a Hybrid Method

Abstract

Principal component analysis (PCA)-based method is popular for detecting the damage of bridges under varying environmental temperatures. However, this method deletes some information when the damage features are projected in the direction of nonprincipal components; thus, the effectiveness of PCA-based methods will decrease if the deleted information is related to bridge damage. To address this issue, a hybrid method is proposed to detect the damage of bridges under environmental temperature changes. On one side, the PCA-based method is applied to deal with the nonprincipal components; on the other side, the Gaussian mixture method (GMM) is used to classify all the principal components into different clusters, and then the novel detection method is implemented to detect bridge damage for each cluster. In this way, all the damage feature information is saved and used to detect bridge damage. The numerical example and example of an actual bridge show that the proposed hybrid method is effective in detecting bridge damage under environmental temperature changes. The GMM is effective for classifying the natural monitoring frequency data of actual bridges, and the relationship between the natural frequencies of actual bridges and the environmental temperature is not always linear.

Challenges in Bridge Health Monitoring: A Review

“…Recent investigations are also exploiting statistical methods such as the PCA to recognize the individual influence of different types of loads such as thermal, wind, and traffic on the structural response of the bridges [ 42 , 43 , 44 ]. Huang et al [ 44 ] applied a temperature-strain correlation model to eliminate the thermal effects on the strain.…”

Combined Use of Cointegration Analysis and Robust Outlier Statistics to Improve Damage Detection in Real-World Structures

“…Within a SHM context, a potential issue is represented by the influence that environmental and operational variations (EOVs) have a structure features. This effect is particularly evident for civil infrastructures such as bridges, whose measured responses are constantly subjected to important variations induced by wind, humidity, traffic, human loading [ 8 ] and, above all, temperature [ 9 , 10 , 11 , 12 ]. Since changes due to these benign reasons typically manifest with the same order of magnitude of those due to structure degradations, they could appear as outliers in the data masking any potential indication of ongoing structural damage.…”

Influence of Temperature on the Natural Vibration Characteristics of Simply Supported Reinforced Concrete Beam

“…The natural vibration characteristics of bridges, including frequency, vibration mode, and damping, are affected by structural stiffness and the extent of damage, which can provide a reference basis for bridge design and comprehensive performance evaluation [ 1 , 2 , 3 , 4 ]. However, environmental factors, such as temperature, humidity, wind speed, and extremely harsh environments, can also cause significant changes in the natural vibration characteristics of the structure, which may even be greater than the changes in the natural vibration characteristics caused by actual damage, leading to difficulties in damage identification technologies for bridge monitoring [ 5 , 6 , 7 , 8 , 9 ].…”