Cracking assessment in concrete structures by distributed optical fiber

In this paper, a method to obtain crack initiation, location and width in concrete structures subjected to bending and instrumented with an optical backscattered reflectometer (OBR) system is proposed. Continuous strain data with high spatial resolution and accuracy are the main advantages of the OBR system. These characteristics make this structural health monitoring technique a useful tool in early damage detection in important structural problems. In the specific case of reinforced concrete structures, which exhibit cracks even in-service loading, the possibility to obtain strain data with high spatial resolution is a main issue. In this way, this information is of paramount importance concerning the durability and long performance and management of concrete structures. The proposed method is based on the results of a test up to failure carried out on a reinforced concrete slab. Using test data and different crack modeling criteria in concrete structures, simple nonlinear finite element models were elaborated to validate its use in the localization and appraisal of the crack width in the testing slab.Peer ReviewedPostprint (author’s final draft

Benchmarking Image Processing Algorithms for Unmanned Aerial System-Assisted Crack Detection in Concrete Structures

This paper summarizes the results of traditional image processing algorithms for detection of defects in concrete using images taken by Unmanned Aerial Systems (UASs). Such algorithms are useful for improving the accuracy of crack detection during autonomous inspection of bridges and other structures, and they have yet to be compared and evaluated on a dataset of concrete images taken by UAS. The authors created a generic image processing algorithm for crack detection, which included the major steps of filter design, edge detection, image enhancement, and segmentation, designed to uniformly compare dierent edge detectors. Edge detection was carried out by six filters in the spatial (Roberts, Prewitt, Sobel, and Laplacian of Gaussian) and frequency (Butterworth and Gaussian) domains. These algorithms were applied to fifty images each of defected and sound concrete. Performances of the six filters were compared in terms of accuracy, precision, minimum detectable crack width, computational time, and noise-to-signal ratio. In general, frequency domain techniques were slower than spatial domain methods because of the computational intensity of the Fourier and inverse Fourier transformations used to move between spatial and frequency domains. Frequency domain methods also produced noisier images than spatial domain methods. Crack detection in the spatial domain using the Laplacian of Gaussian filter proved to be the fastest, most accurate, and most precise method, and it resulted in the finest detectable crack width. The Laplacian of Gaussian filter in spatial domain is recommended for future applications of real-time crack detection using UAS