Title
Features of Cross-Correlation Analysis in a Data-Driven Approach for Structural Damage Assessment.
Abstract
This work discusses the advantage of using cross-correlation analysis in a data-driven approach based on principal component analysis (PCA) and piezodiagnostics to obtain successful diagnosis of events in structural health monitoring (SHM). In this sense, the identification of noisy data and outliers, as well as the management of data cleansing stages can be facilitated through the implementation of a preprocessing stage based on cross-correlation functions. Additionally, this work evidences an improvement in damage detection when the cross-correlation is included as part of the whole damage assessment approach. The proposed methodology is validated by processing data measurements from piezoelectric devices (PZT), which are used in a piezodiagnostics approach based on PCA and baseline modeling. Thus, the influence of cross-correlation analysis used in the preprocessing stage is evaluated for damage detection by means of statistical plots and self-organizing maps. Three laboratory specimens were used as test structures in order to demonstrate the validity of the methodology: (i) a carbon steel pipe section with leak and mass damage types, (ii) an aircraft wing specimen, and (iii) a blade of a commercial aircraft turbine, where damages are specified as mass-added. As the main concluding remark, the suitability of cross-correlation features combined with a PCA-based piezodiagnostic approach in order to achieve a more robust damage assessment algorithm is verified for SHM tasks.
Year
DOI
Venue
2018
10.3390/s18051571
SENSORS
Keywords
Field
DocType
piezodiagnostics,Baseline Models,Damage Statistical Analysis,principal component analysis,structural damage detection
Data mining,Cross correlation analysis,Data cleansing,Data-driven,Structural health monitoring,Outlier,Electronic engineering,Preprocessor,Turbine,Engineering,Principal component analysis
Journal
Volume
Issue
Citations 
18
5.0
0
PageRank 
References 
Authors
0.34
4
5
Name
Order
Citations
PageRank
Jhonatan Camacho-Navarro100.34
Magda Ruiz252.34
Rodolfo Villamizar300.34
L. E. Mujica462.70
Jabid Quiroga500.34