Unsupervised identification of damage and load characteristics in time-varying systems

Abstract

Parameters identification of nonstationary systems is a very challenging topic that has only recently received critical attention from the research community. Aim of the paper is the structural health monitoring of bridge-like structures excited by a massive moving load, whose characteristics, such as the mass and speed, are unknown, in the presence of a localized damage along the structure. A novel method for the simultaneous identification of both the load characteristics and damage parameters from vibration measurements is proposed: the data processing relies on the ensemble empirical mode decomposition and the normalized Hilbert transform. Neither a priori information about the response of the undamaged structure nor the free decay of the damaged system is required, only a single-point measurement is needed. The empirical instantaneous frequency is firstly employed to estimate the load characteristics; secondly, the effect of the moving mass is filtered from the instantaneous frequency, and then, the damage position is identified. The performance of the technique are studied varying the load characteristics, damage locations, and crack depths. The effect of ambient noise is also taken into account. Numerical experiments show the identification is rather accurate, results are not very sensitive to the crack location and depth, while they are sensibly affected by the speed of the moving load.