Wavelet-based vibration data compression technique for natural frequencies identification of civil infrastructure

Abstract

Civil infrastructure is one of the fundamental items in the modern economy. For this reason, it is necessary the continuous assessment of its condition, as any deterioration might cause economic and, potentially, human losses. Modern structures incorporate sensing technology with the aim of obtaining data in real-life operation conditions. Hence, it is necessary the compressing of the acquired data in order to use as less storage space as possible. Bearing this in mind, this paper proposes the utilization of the discrete wavelet transform to perform the data compression by using the approximation coefficients, since its estimation already implies the compression of the in-test signal. To find out if the data have a closely resemblance with its uncompressed version, the box counting fractal, a tool from the non-linear theory is used to measure if the compressed signal has similar patterns, and thus the same frequency content, that the original version. The most common wavelet mother functions are studied. A real-life signal acquired from a 4-story 2 × 2 bay 3D frame structure is analyzed, where the frequencies contained in the signal are estimated. The obtained results show that the proposal can be considered as an effective tool for compressing vibration signals.