Quantification of Damage Using Indirect Structural Health Monitoring

01/24/2023
by   Achyuth Madabhushi, et al.
0

Structural health monitoring is important to make sure bridges do not fail. Since direct monitoring can be complicated and expensive, indirect methods have been a focus on research. Indirect monitoring can be much cheaper and easier to conduct, however there are challenges with getting accurate results. This work focuses on damage quantification by using accelerometers. Tests were conducted on a model bridge and car with four accelerometers attached to to the vehicle. Different weights were placed on the bridge to simulate different levels of damage, and 31 tests were run for 20 different damage levels. The acceleration data collected was normalized and a Fast-Fourier Transform (FFT) was performed on that data. Both the normalized acceleration data and the normalized FFT data were inputted into a Non-Linear Principal Component Analysis (separately) and three principal components were extracted for each data set. Support Vector Regression (SVR) and Gaussian Process Regression (GPR) were used as the supervised machine learning methods to develop models. Multiple models were created so that the best one could be selected, and the models were compared by looking at their Mean Squared Errors (MSE). This methodology should be applied in the field to measure how effective it can be in real world applications.

READ FULL TEXT

page 2

page 4

page 5

research
02/06/2020

Damage-sensitive and domain-invariant feature extraction for vehicle-vibration-based bridge health monitoring

We introduce a physics-guided signal processing approach to extract a da...
research
05/13/2023

Neural operator for structural simulation and bridge health monitoring

Infusing deep learning with structural engineering has received widespre...
research
06/05/2020

Knowledge transfer between bridges for drive-by monitoring using adversarial and multi-task learning

Monitoring bridge health using the vibrations of drive-by vehicles has v...
research
07/23/2021

HierMUD: Hierarchical Multi-task Unsupervised Domain Adaptation between Bridges for Drive-by Damage Diagnosis

Monitoring bridge health using vibrations of drive-by vehicles has vario...
research
06/30/2020

On the Potenital of Dynamic Substructuring Methods for Model Updating

While purely data-driven assessment is feasible for the first levels of ...
research
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 ...

Please sign up or login with your details

Forgot password? Click here to reset