Exploiting spatial sparsity in vibration-based damage detection

Abstract

One of the main limitations traditionally encountered in vibration-based structural health monitoring (SHM) is detecting, localizing and quantifying localized damage using global response measurements. This paper presents an impulse response sensitivity approach enhanced with a LASSO regularization in order to detect spatially sparse (localized) damage. The analytical expression for impulse response sensitivity was derived using Vetter calculus. The proposed algorithm exploits the fact that when damage is sparse, an l1-norm regularization is more suitable than the more common least squares (l2-norm) minimization. The proposed methodology is successfully applied in the context of a simulated non-uniform shear cantilever beam with noise-contaminated input–output measurements.