Damage imaging of reinforced concrete structures using electromagnetic migration algorithm

Nojavan, Saeed; Fang, Yuan

doi:10.1016/j.ijsolstr.2005.08.017

Cited by 14 publications

(7 citation statements)

References 41 publications

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“…In summary, the ultrasonic CT based damage detection method may not be suitable for SHM of concrete structures. The migration algorithm was introduced to the areas of concrete damage detection [28][29][30]. Nevertheless, like ultrasonic CT, migration based damage detection method confronts likewise severe limitations which need complex equipment, huge volume test data, acoustic couplant, and bulky and expensive ultrasonic transducers.…”

Section: Introductionmentioning

confidence: 99%

Smart concrete slabs with embedded tubular PZT transducers for damage detection

Gao

Huo

et al. 2018

Smart Mater. Struct.

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The objective of this study is to develop a new concept and methodology of smart concrete slab (SCS) with embedded tubular lead zirconate titanate transducer array for image based damage detection. Stress waves, as the detecting signals, are generated by the embedded tubular piezoceramic transducers in the SCS. Tubular piezoceramic transducers are used due to their capacity of generating radially uniform stress waves in a two-dimensional concrete slab (such as bridge decks and walls), increasing the monitoring range. A circular type delay-and-sum (DAS) imaging algorithm is developed to image the active acoustic sources based on the direct response received by each sensor. After the scattering signals from the damage are obtained by subtracting the baseline response of the concrete structures from those of the defective ones, the elliptical type DAS imaging algorithm is employed to process the scattering signals and reconstruct the image of the damage. Finally, two experiments, including active acoustic source monitoring and damage imaging for concrete structures, are carried out to illustrate and demonstrate the effectiveness of the proposed method.

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Section: Introductionmentioning

confidence: 99%

Smart concrete slabs with embedded tubular PZT transducers for damage detection

Gao

Huo

et al. 2018

Smart Mater. Struct.

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“…e key point of its algorithm is the transformation reconstruction, where the learning parameters c, β are ss shown in equation (1).…”

Section: Batch Normalization Layermentioning

confidence: 99%

“…In China, the road networks have a very large number of bridges built, and since the 1990s, the construction of highway bridges has vigorously developed. According to the Ministry of Transport, by 2020, there will be 832,500 bridges in service nationwide [1], an increase of 27,200 bridges over the same period last year, including more than 4,600 very large bridges. By now, China has more than 1 million highway and railroad bridges of all types, the largest number in the world.…”

Section: Introductionmentioning

confidence: 99%

Migration Learning-Based Bridge Structure Damage Detection Algorithm

Chen

2021

Scientific Programming

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Most of the bridge structures in the world are built of reinforced concrete. With the growth of service life and the increase of urban traffic and other factors, most bridges put into service have more or less damage. Traditional bridge damage detection methods include the manual inspection method and bridge inspection vehicle method, which have many shortcomings. Moreover, the detection of cracks in bridges is critical to the safety of transportation due to the extremely large number of bridges built in the road networks across the world. To this end, this paper uses the most widely used CNN in deep learning to identify and classify crack images and proposes a migration learning technique to solve the problem of the large amount of training data required for training CNN. The data augmentation and sliding window techniques are introduced to divide the collected crack data into training establish and test set. The experiments show that the method in this paper can classify the crack images better, extract and locate the cracks of bridge crack units, and finally extract the crack coordinates of boxing. Compared with the customary image recognition methods, the method used in this paper is easier to operate in practical engineering, and the accuracy of the obtained results is higher.

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“…Damage detection and failure analysis of concrete structures have been studied for many years (Otani and Sozen 1972, Abrams and Sozen 1979, Saiidi and Sozen 1981, Kreger and Sozen 1983, Park et al 1985, Hassan and Sozen 1997, Wang and Wen 2000, Nojavan and Yuan 2006. Various sensors and methods have been developed for damage detection and health monitoring.…”

Section: Literature Reviewmentioning

confidence: 99%

Smart aggregate based damage detection of circular RC columns under cyclic combined loading

Moslehy¹,

Gu²,

Belarbi³

et al. 2010

Smart Mater. Struct.

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Structural health monitoring is an important issue for the maintenance of large-scale civil infrastructures, especially for bridge columns. In this paper, an innovative piezoceramic-based approach is developed for the structural health monitoring of reinforced concrete columns. An innovative piezoceramic-based device, the smart aggregate, is utilized as a transducer for the purpose of health monitoring. To investigate the seismic behavior of reinforced concrete (RC) bridge columns, structural health monitoring tests were performed on two bridge columns under combined reversed cyclic loading at the Missouri University of Science and Technology. The proposed smart aggregate based approach successfully evaluated the health status of concrete columns during the loading procedure. Sensor energy plots and 3D normalized sensor energy plots demonstrated that the damage inside attenuated the transmitted energy. The wavelet packet based damage index and sensor history damage index evaluate the damage development in concrete columns under cyclic loading.

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Damage imaging of reinforced concrete structures using electromagnetic migration algorithm

Cited by 14 publications

References 41 publications

Smart concrete slabs with embedded tubular PZT transducers for damage detection

Smart concrete slabs with embedded tubular PZT transducers for damage detection

Migration Learning-Based Bridge Structure Damage Detection Algorithm

Smart aggregate based damage detection of circular RC columns under cyclic combined loading

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