Abstract

Strain is a direct indicator of structural safety. Therefore, strain sensors have been used in most structural health monitoring systems for bridges. However, until now, the investigation of strain response has been insufficient. This paper conducts a comprehensive study of the strain features of the U ribs and transverse diaphragm on an orthotropic steel deck and proposes a statistical paradigm for crack detection based on the features of vehicle-induced strain response by using the densely distributed optic fibre Bragg grating (FBG) strain sensors. The local feature of strain under vehicle load is highlighted, which enables the use of measurement data to determine the vehicle loading event and to make a decision regarding the health status of a girder near the strain sensors via technical elimination of the load information. Time–frequency analysis shows that the strain contains three features: the long-term trend item, the short-term trend item, and the instantaneous vehicle-induced item (IVII). The IVII is the wheel-induced strain with a remarkable local feature, and the measured wheel-induced strain is only influenced by the vehicle near the FBG sensor, while other vehicles slightly farther away have no effect on the wheel-induced strain. This causes the local strain series, among the FBG strain sensors in the same transverse locations of different cross-sections, to present similarities in shape to some extent and presents a time delay in successive order along the driving direction. Therefore, the strain series induced by an identical vehicle can be easily tracked and compared by extracting the amplitude and calculating the mutual ratio to eliminate vehicle loading information, leaving the girder information alone. The statistical paradigm for crack detection is finally proposed, and the detection accuracy is then validated by using dense FBG strain sensors on a long-span suspension bridge in China.

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