Abstract

Serving as one of the most common measurements in the instrumented Structural Health Monitoring system of bridges, strain response measurement, especially longterm measurement on a continuous basis can provide ongoing information of bridge structures on its structural behavior and health condition under external load. However, the study on strain response is far from adequate. Based on the Fiber Bragg Grating (FBG) strain sensors, this paper conduct a study on the strain response feature of steel box girder on the important elements and critical locations, and develop a statistical paradigm for crack detection. The local response property of strain response under vehicle load is highlighted, since it enables the measurement data to tell the vehicle load events that occur to the area nearby the sensors and to tell the health condition of this area. Features of strain response subject to vehicle load is first studied, its timefrequency domain feature is used to detect vehicle load events and break the strain measurement series into segments that corresponded to the detected vehicle load events. Based on the matching technique of segments of strain series from successive sections along the traffic direction, strain response segments of different sections under the identical vehicle load is obtained. Extracting the amplitude of their changes in the value subject to the identical vehicle load and evaluating their mutual ratio (the indicator) to mitigate eliminate different affects due to vehicle weight for each passing heavy vehicle (sample), the paradigm finally collects a dataset of the condition of different sections, by analysing the statistical property of this indicator, it detects the crack on the nearby region of the sensor location and infer the condition of this region.

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