Dynamic identification of a cable-stayed footbridge using a low-cost data acquisition system

Identificação dinâmica de uma passarela estaiada utilizando um sistema de aquisição de dados de baixo custo

Abstract

This study describes the dynamic identification of a cable-stayed footbridge using an alternative data acquisition system and output-only modal identification methods. Data were collected during dynamic tests performed using an acquisition system based on the Arduino platform, consisting of low-cost devices with on-board Micro-Electro-Mechanical System (MEMS) accelerometers. The Peak-Picking (PP) method was used for the stay cables. The Frequency Domain Decomposition (FDD) and Stochastic Subspace Identification - Unweighted Principal Components (SSI-UPC) methods were used for the complete structure. The proposed data acquisition system efficiently recorded the time series required for Operational Modal Analysis and the acceleration acquisition process provided stable results. At least four mode shapes were identified in all tests. A minimum of four high energy peaks in the 0 - 24 Hz frequency range of the spectrum were obtained by the acquisition system in all of the cable tests and selected by the method. In the complete structure tests, the low-cost data acquisition system and the identification methods provided the first four flexural mode shapes, within the 0 - 9 Hz frequency range. Results for the frequency domain method showed a maximum difference of 2.37% in the first experimental frequency when compared to a 3D finite element numerical model, while in the other frequencies the difference was between 1 and 2%. For the time domain method, the maximum difference was 1.74% in the fourth frequency, with differences of between 0.1 and 0.7% in the other frequencies. The mode shapes were evaluated using the Modal Assurance Criterion (MAC) index, and the results varied between 0.8513 and 0.9990.

Keywords:
cable-stayed footbridge; data acquisition system; modal identification; dynamic tests; low-cost devices