Modal identification of bridges under varying environmental conditions: Temperature and wind effects

Abstract

Numerous investigations have indicated that structural modal parameters are significantly impacted by varying environmental and operational conditions. This phenomenon will cause confusion when conducting modal-based damage detection and model updating. This paper investigates the dependency of modal frequencies, modal shapes and the associated damping ratios on temperature and wind velocity. The nonlinear principal component analysis (NLPCA) is first employed as a signal pre-processing tool to distinguish temperature and wind effects on structural modal parameters from other environmental factors. The pre-processed dataset by NLPCA implies the relationship between modal parameters and temperature as well as wind velocity. Consequently, the artificial neural network (ANN) technique is employed to model the relationship between the pre-processed modal parameters and environmental factors. Numerical results indicate that pre-processed modal parameters by NLPCA can retain the most features of original signals. Furthermore, the pre-processed modal frequency and damping ratios are dramatically affected by temperature and wind velocity. The ANN regression models have good capacities for mapping relationship of environmental factors and modal frequency, damping ratios. However, environmental effects on the entire modal shapes are insignificant. damping ratio are the accurate reflection of the structural properties such as stiffness and damage. However, the application vibration-based damage detection method for civil engineering structures is complicated, because modal parameters of a real structure are strongly affected by factors other than structural damages. These factors include (i) variations in material properties; (ii) environmental variability (such as temperature, wind velocity and humidity, etc.) and variability in operational conditions (such as traffic flow) during measurement; and (iii) errors associated with measured datasets and processing techniques. If the effect of these uncertainties on modal parameters is larger than or comparable to effect of structural damage on its modal parameters, the structural damage cannot be reliably identified. As a matter of fact, it has been observed from some field tests that the variation of modal parameters due to changes of environmental factors is very significant, and can be even larger than those due to rather severe structural damage. For example, Alampalli [3] presented that the relative modal frequency differences (df ) of a bridge due to freezing of the supports (df 5 40-50%) were an order of magnitude larger than changes due to damage (df 5 3-8%), which was in that case an artificial saw cut across the bottom flanges of both girders. Therefore, studying the environmental effects on modal parameters is important for reliable performance of damage detection algorithm. Considerable research efforts have been devoted to investigating the influence of environmental factors on dynamical characteristics via field measurements and dynamic tests, including Roberts and...

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