Crack depth measurement in rail steel by Rayleigh waves aided by photoelastic visualization

Hall, Kevin G

doi:10.1016/0029-1021(76)90240-1

Cited by 25 publications

(5 citation statements)

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“…For reflection from edges and grooves see also [1186,1187,1606,1607,50,229,544,394], for picture displays see [597], for computer simulations see Sato [1321] and Harumi [617, 9, 618, 619, S 65]. Angles other than 90 0 are less interesting, but if the angle of incidence of a longitudinal wave (Fig.…”

Section: Reflection At a Right-angled Edge And In A Comermentioning

confidence: 97%

Ultrasonic Testing of Materials

Krautkrämer¹,

Krautkrämer²

1990

756

452

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Section: Reflection At a Right-angled Edge And In A Comermentioning

confidence: 97%

Ultrasonic Testing of Materials

Krautkrämer¹,

Krautkrämer²

1990

756

452

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“…In 1967, Viktorov proposed measuring the change in period of oscillation in the frequency domain to determine the defect depth [16]. This approach was enhanced further by Domarkas et al and Hall et al, whose research facilitated the determination of defect length via pulse time measurement [17,18]. In the research conducted by Papaelias et al, it was concluded that defect detection is optimised when transmitting ultrasound waves at incident angles of 0 • , 37 • , 45 • and 70 • [19].…”

Section: State Of the Artmentioning

confidence: 99%

Integration of an Ultrasonic Sensor within a Robotic End Effector for Application within Railway Track Flaw Detection

Cilia,

Griffiths,

Rees

et al. 2024

Applied Sciences

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The rail industry is constantly facing challenges related to safety with regard to the detection of surface cracks and internal defects within rail tracks. Significant focus has been placed on developing sensor technologies that would facilitate the detection of flaws that compromise rail safety. In parallel, robot automation has demonstrated significant advancements in the integration of sensor technologies within end effectors. This study investigates the novel integration of an ultrasonic sensor within a robotic platform specifically for the application of detecting surface cracks and internal defects within rail tracks. The performance of the robotic sensor system was assessed on a rail track specimen containing sacrificial surface cracks and internal defects and then compared against a manual detection system. The investigation concludes that the robotic sensor system successfully identified internal defects in the web region of the rail track when utilising a 60° and 70° wedged probe, with a frequency range between 4 MHz and 5 MHz. However, the surface crack investigation proved that the transducer was insensitive to the detection of cracks, possibly due to the inadequate angle of the wedged probe. The overall outcome of the study highlights the potential that robotic sensor systems have in the detection of internal defects and characterises the limitations of surface crack identification to assist in enhancing rail safety.

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“…Once the wave encounters the crack, interaction with the latter occurs. There exists a vast literature (for example [105,106,107]) about the interaction phenomena between Rayleigh waves and cracks in solids. Part of the wave is transmitted through the crack location; part is reflected back in opposite direction (clearly visible in Figure 4.100d-f); part propagates along the edges of the crack (visible in Figure 4.99c); finally, mode conversions will occur, and bulk waves are generated from the tips of the crack which act as secondary sources (visible in Figure 4.99c and Figure 4.100d).…”

Section: Air Modelingmentioning

confidence: 99%

Non-Contact Ultrasonic Guided Wave Inspection of Rails: Next Generation Approach

Mariani

Nguyen

Zhu

et al. 2016

2016 Joint Rail Conference

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The University of California at San Diego (UCSD), under a Federal Railroad Administration (FRA) Office of Research and Development (R&D) grant, is developing a system for high-speed and non-contact rail defect detection. A prototype using an ultrasonic air-coupled guided wave signal generation and air-coupled signal detection, paired with a real-time statistical analysis algorithm, has been realized. This system requires a specialized filtering approach based on electrical impedance matching due to the inherently poor signal-to-noise ratio of air-coupled ultrasonic measurements in rail steel. Various aspects of the prototype have been designed with the aid of numerical analyses. In particular, simulations of ultrasonic guided wave propagation in rails have been performed using a Local Interaction Simulation Approach (LISA) algorithm. The system’s operating parameters were selected based on Receiver Operating Characteristic (ROC) curves, which provide a quantitative manner to evaluate different detection performances based on the trade-off between detection rate and false positive rate. The prototype based on this technology was tested in October 2014 at the Transportation Technology Center (TTC) in Pueblo, Colorado, and again in November 2015 after incorporating changes based on lessons learned.

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Crack depth measurement in rail steel by Rayleigh waves aided by photoelastic visualization

Cited by 25 publications

References 0 publications

Ultrasonic Testing of Materials

Ultrasonic Testing of Materials

Integration of an Ultrasonic Sensor within a Robotic End Effector for Application within Railway Track Flaw Detection

Non-Contact Ultrasonic Guided Wave Inspection of Rails: Next Generation Approach

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