A supervised learning computer-based algorithm to derive the amplitude of oscillations of structures using noisy GPS and Robotic Theodolites (RTS) records

A computer-based algorithm computing the mean amplitude of small-scale, high frequency oscillations of civil engineering structures using GPS and Robotic Theodolites (RTS) is presented. This algorithm is based on a peak-picking filter derived from supervised learning through independent experiments. This filter is a function of the oscillation frequency, computed even from noisy, apparent displacement records. The algorithm minimizes the noise of high-frequency GPS and RTS recordings and calculates the mean amplitude of the oscillations with millimeter accuracy.The application of this method to the Structural Health Monitoring is demonstrated in the case of measurement of displacements of two short-span bridges.

► Developing an algorithm for the estimation of the noisy GPS/RTS data amplitude.
► Focus on the limitation of the GPS/RTS noise effect to the amplitude estimation.
► Use of a filter derived from supervised learning through oscillation experiments.
► The noise of GPS/RTS data proved to be affected by the oscillation frequency.
► The filter was adjusted to the noise characteristics of GPS/RTS data.