Comparative analysis of infrared thermography processing techniques for roadways’ sub-pavement voids detection

Kulkarni, Nitin Nagesh; Dabetwar, Shweta; Benoit, Jason; Yu, Tzuyang; Sabato, Alessandro

doi:10.1016/j.ndteint.2022.102652

Cited by 20 publications

(3 citation statements)

References 39 publications

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“…The advantage of using IT sensors in civil engineering is that they can provide real-time data that can be used in difficult-to-access locations and in harsh environments. They also can detect hidden defects, which can help identify potential problems before they lead to equipment failure or structural damage [109,110].…”

Section: Infrared Thermographymentioning

confidence: 99%

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Exploring the Potential of Promising Sensor Technologies for Concrete Structural Health Monitoring

Shilar,

Ganachari,

Patil

et al. 2024

Materials

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Structural health monitoring (SHM) is crucial for maintaining concrete infrastructure. The data collected by these sensors are processed and analyzed using various analysis tools under different loadings and exposure to external conditions. Sensor-based investigation on concrete has been carried out for technologies used for designing structural health monitoring sensors. A Sensor-Infused Structural Analysis such as interfacial bond-slip model, corroded steel bar, fiber-optic sensors, carbon black and polypropylene fiber, concrete cracks, concrete carbonation, strain transfer model, and vibrational-based monitor. The compressive strength (CS) and split tensile strength (STS) values of the analyzed material fall within a range from 26 to 36 MPa and from 2 to 3 MPa, respectively. The material being studied has a range of flexural strength (FS) and density values that fall between 4.5 and 7 MPa and between 2250 and 2550 kg/m3. The average squared difference between the predicted and actual compressive strength values was found to be 4.405. With cement ratios of 0.3, 0.4, and 0.5, the shear strength value ranged from 4.4 to 5.6 MPa. The maximum shear strength was observed for a water–cement ratio of 0.4, with 5.5 MPa, followed by a water–cement ratio of 0.3, with 5 MPa. Optimizing the water–cement ratio achieves robust concrete (at 0.50), while a lower ratio may hinder strength (at 0.30). PZT sensors and stress-wave measurements aid in the precise structural monitoring, enhanced by steel fibers and carbon black, for improved sensitivity and mechanical properties. These findings incorporate a wide range of applications, including crack detection; strain and deformation analysis; and monitoring of temperature, moisture, and corrosion. This review pioneers sensor technology for concrete monitoring (Goal 9), urban safety (Goal 11), climate resilience (Goal 13), coastal preservation (Goal 14), and habitat protection (Goal 15) of the United Nations’ Sustainable Development Goals.

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Section: Infrared Thermographymentioning

confidence: 99%

“…As ML algorithms become more complex, there is a growing emphasis on developing explainable AI techniques that provide insights into how models make decisions. Interpretable models enhance trust and understanding, especially in safety-critical applications like SHM [109].…”

Section: Vibrational-based Monitor In Concrete Structurementioning

confidence: 99%

Exploring the Potential of Promising Sensor Technologies for Concrete Structural Health Monitoring

Shilar,

Ganachari,

Patil

et al. 2024

Materials

View full text Add to dashboard Cite

show abstract

“…The temporal evolution of the surface temperature is recorded using an infrared (IR) camera [12]. The thermal contrast between defective and sound regions is normally weak and degraded by the non-uniform distribution of the applied heat stimulant, lateral thermal diffusion (especially for composites), and various noise sources [13,14]. Many processing algorithms, including principal component thermography (PCT) [15], thermal signal reconstruction (TSR) [16] and pulsed phase thermography (PPT) [12], have been developed to improve defect detectability in thermographic data.…”

Section: Introductionmentioning

confidence: 99%