Automated crack pattern recognition from images for condition assessment of concrete structures

2021 ◽  
Vol 128 ◽  
pp. 103765
Author(s):  
Yiqing Liu ◽  
Justin K.W. Yeoh
2020 ◽  
pp. 147592172096544
Author(s):  
Aravinda S Rao ◽  
Tuan Nguyen ◽  
Marimuthu Palaniswami ◽  
Tuan Ngo

With the growing number of aging infrastructure across the world, there is a high demand for a more effective inspection method to assess its conditions. Routine assessment of structural conditions is a necessity to ensure the safety and operation of critical infrastructure. However, the current practice to detect structural damages, such as cracks, depends on human visual observation methods, which are prone to efficiency, cost, and safety concerns. In this article, we present an automated detection method, which is based on convolutional neural network models and a non-overlapping window-based approach, to detect crack/non-crack conditions of concrete structures from images. To this end, we construct a data set of crack/non-crack concrete structures, comprising 32,704 training patches, 2074 validation patches, and 6032 test patches. We evaluate the performance of our approach using 15 state-of-the-art convolutional neural network models in terms of number of parameters required to train the models, area under the curve, and inference time. Our approach provides over 95% accuracy and over 87% precision in detecting the cracks for most of the convolutional neural network models. We also show that our approach outperforms existing models in literature in terms of accuracy and inference time. The best performance in terms of area under the curve was achieved by visual geometry group-16 model (area under the curve = 0.9805) and best inference time was provided by AlexNet (0.32 s per image in size of 256 × 256 × 3). Our evaluation shows that deeper convolutional neural network models have higher detection accuracies; however, they also require more parameters and have higher inference time. We believe that this study would act as a benchmark for real-time, automated crack detection for condition assessment of infrastructure.


Author(s):  
R. Ceravolo

<p>Great architects and structural engineers such as Berg (1870-1947), Maillart (1872-1940), Freyssinet (1879- 1962), Torroja (1899 -1961), Nervi (1891-1979), Candela (1910-1997), Isler (1926-2009) and many others have designed recognized works of art in their discipline. They conceived extraordinary concrete spatial structures, that are located mostly in Europe and represent a unique legacy. It is important to raise awareness of this heritage, define the criteria for preserving it and begin the process of its renovation and rehabilitation. <p> While concrete has become a 20th century emblem, much of the world’s heritage from this period is unrecognized or undervalued, and therefore it is at risk and in need of analysis and protection. Innovative technologies and solutions are needed that contribute to the successful reuse of modern concrete built heritage. Indeed, such structures are plagued by significant deterioration and most of them are in urgent need of retrofitting and/or radical refurbishment. In other words, there is a need to bring some of these buildings back to life, while respecting the spirit of their original characters, through new technologies for long-term conservation that can maintain an adequate level of structural performance. Achieving this goal would produce substantial economic impacts through activities such as restoration, maintenance, and cultural industry. <p> The keynote lecture, more specifically, focuses on the condition assessment, monitoring and preservation of 20th century architectural heritage characterized by a complex spatial structural design. The service life of civil and cultural heritage concrete spatial structures is typically thought to range from 10 to 200 years, but in practice the service environment plays a pivotal role in sustained durability. Indeed, the collapse of Polcevera Viaduct in Genoa has raised strong concerns on the durability of concrete structures conceived at that time. The scientific community has once again underlined the important role played by maintenance and continuous structural health monitoring in avoiding these disastrous events. In order to demonstrate a correct approach to condition monitoring of concrete spatial buildings and bridges, some important experiences are described that were recently obtained at the Polytechnic of Turin on the structural analysis, seismic vulnerability and condition assessment for iconic 20th century heritage buildings.


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