Abstract: This paper enriches the statistical moment-based damage detection method with approximate parametric solutions of the stationary second-order moments of nodal displacements and velocity, which are explicitly related to stiffness and modal damping parameters. Then, a weighted least-squares approach is employed to search for the stiffness and damping inversely when the objective function is minimized. The method is able to detect both stiffness reduction, simulating damage, and modal damping ratio of relevant modes, the latter being a decisive issue for damage detection. After the procedure to get an approximate explicit solution is recalled, the steps involved in the identification process are stated and an eventual modal truncation is proposed to allow the analysis of larger systems. Applications on a pinned beam and a two-dimensional panel are reported to check the consistency of the method and to investigate to effects of measurement noise on the identification procedure.
|Titolo:||Parametric Statistical Moment Method for Damage Detection and Health Monitoring|
|Data di pubblicazione:||2016|
|Citazione:||Parametric Statistical Moment Method for Damage Detection and Health Monitoring / Impollonia N; Failla I; Ricciardi G. - In: ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS. PART A, CIVIL ENGINEERING.. - ISSN 2376-7642. - 2:2(2016), pp. C4016001.1-C4016001.12.|
|Appare nelle tipologie:||1.1 Articolo in rivista|