You can view the full text of this article for free using the link below.

Title: Uncertainty quantification of thermal image-based concrete diagnosis

Authors: Yanqing Bao; Sankaran Mahadevan

Addresses: Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, TN, 37235, USA ' Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, TN, 37235, USA

Abstract: This paper investigates uncertainty quantification in internal damage diagnosis in concrete based on thermal imaging. Thermal imaging can be used for detection, localisation, as well as quantification of the damage. The proposed methodology for uncertainty quantification aggregates various sources of uncertainty introduced at each step of image processing. Further, global sensitivity analysis is applied to identify the dominant contributors to diagnosis uncertainty. Based on the results of uncertainty quantification and global sensitivity analysis, a Bayesian technique is formulated to identify the optimal values of parameters to be selected at each step of the image processing, in order to minimise the uncertainty in diagnosis. An illustrative example of damage diagnosis of a concrete slab is used to examine the effectiveness of the proposed uncertainty quantification and parameter selection methods.

Keywords: image processing; concrete slabs; damage diagnosis; uncertainty quantification; parameter selection; Bayesian statistics; thermography; thermal imaging; internal damage.

DOI: 10.1504/IJSMSS.2015.078362

International Journal of Sustainable Materials and Structural Systems, 2015 Vol.2 No.1/2, pp.77 - 95

Available online: 15 Aug 2016 *

Full-text access for editors Access for subscribers Free access Comment on this article