DeepAI AI Chat
Log In Sign Up

A generalised form for a homogeneous population of structures using an overlapping mixture of Gaussian processes

06/23/2022
by   Tina A Dardeno, et al.
The University of Sheffield
0

Reductions in natural frequency are often used as a damage indicator for structural health monitoring (SHM) purposes. However, fluctuations in operational and environmental conditions, changes in boundary conditions, and slight differences among nominally-identical structures can also affect stiffness, producing frequency changes that mimic or mask damage. This variability has limited the practical implementation and generalisation of SHM technologies. The aim of this work is to investigate the effects of normal variation, and to identify methods that account for the resulting uncertainty. This work considers vibration data collected from a set of four healthy full-scale composite helicopter blades. The blades were nominally-identical but distinct, and slight differences in material properties and geometry among the blades caused significant variability in the frequency response functions, which presented as four separate trajectories across the input space. In this paper, an overlapping mixture of Gaussian processes (OMGP), was used to generate labels and quantify the uncertainty of normal-condition frequency response data from the helicopter blades. Using a population-based approach, the OMGP model provided a generic representation, called a form, to characterise the normal condition of the blades. Additional simulated data were then compared against the form and evaluated for damage using a marginal-likelihood novelty index.

READ FULL TEXT

page 1

page 2

page 3

page 4

03/14/2022

Modelling variability in vibration-based PBSHM via a generalised population form

Structural health monitoring (SHM) has been an active research area for ...
01/25/2021

Damage detection in operational wind turbine blades using a new approach based on machine learning

The application of reliable structural health monitoring (SHM) technolog...
05/31/2007

Local Area Damage Detection in Composite Structures Using Piezoelectric Transducers

An integrated and automated smart structures approach for structural hea...
06/03/2022

Constraining Gaussian processes for physics-informed acoustic emission mapping

The automated localisation of damage in structures is a challenging but ...
11/27/2018

The synthesis of data from instrumented structures and physics-based models via Gaussian processes

A recent development which is poised to disrupt current structural engin...
10/05/2017

A Multi-Objective DIRECT Algorithm Towards Structural Damage Identification with Limited Dynamic Response Information

A major challenge in Structural Health Monitoring (SHM) is to accurately...
03/05/2021

Foundations of Population-Based SHM, Part IV: The Geometry of Spaces of Structures and their Feature Spaces

One of the requirements of the population-based approach to Structural H...