Abstract
Bridge displacement measurements are important data for assessing the condition of a bridge. Measuring bridge displacement under moving vehicle loads is helpful for rating the load-carrying capacity and evaluating the structural health of a bridge. Displacements are conventionally measured using a linear variable differential transformer (LVDT), which needs stable reference points and thus prohibits the use of this method for measuring displacements for bridges crossing sea channels, large rivers, and highways. This paper proposes a reference-free indirect bridge displacement sensing system using a multichannel sensor board strain and accelerometer with a commercial wireless sensor platform (Xnode). The indirect displacement estimation method is then optimized for measuring the structural displacement. The performance of the developed system was experimentally evaluated on concrete- and steelbox girder bridges. In comparison with the reference LVDT data, the maximum displacement error for the proposed method was 2.17%. The proposed method was successfully applied to the displacement monitoring of a tall bridge (height = 20 m), which was very difficult to monitor using existing systems.
Highlights
linear variable differential transformer (LVDT) data, the maximum displacement error for the proposed method was 2.17%
The computer vision-based method has emerged as an alternative to the traditional method as it accurately measures the structure using a camera installed on a remote stationary reference instead of that on a bridge [4,5,6,7]
Acceleration-based displacement estimation for reference-free measurement can be performed through direct integration in the frequency domain using finite impulse response (FIR) filters
Summary
A multimetric sensing of acceleration and strain is required for multiple and highsensitivity vibration and strain sensing. The wireless sensor platform on which the developed multimetric sensor board is integrated should be carefully selected. Resolution accelerometer and strain sensor with power management; and (3) designi stable and low-noise printed circuit board (PCB) for physically integrating the acceler eter with the wireless sensor platform. To measure multiple accelerations and strains at high sampling rates Xnode consists three main boards:capability the processor, radio/power, and se base wirelessstandard sensor platform requiresof sufficient processing for implementing boards Dard Xnode consists of three main boards: the processor, radio/power, and sensor boards has numerous interfaces, including general purpose input/output (GPIO) pins and (Figure 1a). An integrated circuit for charging and regulation of power board employs a 24-bit analog to digital converter (ADC)
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