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

Mariani, Stefano; Nguyen, Thompson V.; Zhu, Xuan; Sternini, Simone; Scalea, Francesco Lanza di; Fateh, Mahmood; Wilson, Robert L.

doi:10.1115/jrc2016-5771

Cited by 7 publications

(7 citation statements)

References 67 publications

(74 reference statements)

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“…In order to properly assess the performance of the tests, receiver operating characteristic (ROC) curves were computed [ 25 ]. These plots compare the probability of detection (POD) to the probability of false alarm (PFA) for different threshold levels applied to the DI traces.…”

Section: Receiver Operating Characteristic Curvesmentioning

confidence: 99%

Non-Destructive Inspection of Impact Damage in Composite Aircraft Panels by Ultrasonic Guided Waves and Statistical Processing

et al. 2017

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This paper discusses a non-destructive evaluation (NDE) technique for the detection of damage in composite aircraft structures following high energy wide area blunt impact (HEWABI) from ground service equipment (GSE), such as heavy cargo loaders and other heavy equipment. The test structures typically include skin, co-cured stringers, and C-frames that are bolt-connected onto the skin with shear ties. The inspection exploits the waveguide geometry of these structures by utilizing ultrasonic guided waves and a line scan approach. Both a contact prototype and a non-contact prototype were developed and tested on realistic test panels subjected to impact in the laboratory. The results are presented in terms of receiver operating characteristic curves that show excellent probability of detection with low false alarm rates for defects located in the panel skin and stringers.

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Section: Receiver Operating Characteristic Curvesmentioning

confidence: 99%

Non-Destructive Inspection of Impact Damage in Composite Aircraft Panels by Ultrasonic Guided Waves and Statistical Processing

et al. 2017

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“…A separate finite element analysis was carried out to determine the exact shape of the pressure field generated by the air-coupled transmitter at its focal distance. 26 Based on the results of this analysis, the transmitter was simulated by exciting nodes on an 25 × 25 mm area of the rail top surface using the time-history of Figure 2(a), and with a spatial amplitude distribution as shown in Figure 2(b) and (c).…”

Section: Lisa Simulation Of Ultrasonic Wave Propagation In Railmentioning

confidence: 99%

“…In general, good agreements were found after comparing the SNRs suggested by these results with the actual SNRs of the waveforms acquired by each of the four pairs of air-coupled receivers during the field tests. 26…”

Section: Lisa Simulation Of Ultrasonic Wave Propagation In Railmentioning

confidence: 99%

“…In order to preserve shapes and frequency contents, 6000 waveforms were recorded from an air-coupled receiver of the prototype while the amplifier feeding the transmitter was turned off. A preliminary study 26 was performed to determine the correct multiplying factor f N that had to be applied to the noise before adding it to the numerical signals in order to achieve comparable SNRs as the experimental measurements for each of the three relevant air-coupled receiver pairs. The numerical signals were corrupted each time by randomly picking one of the 6000 waveforms of noise pre-multiplied by the factor f N .…”

Section: Parametric Studies Of Sensitivity To Defectsmentioning

confidence: 99%

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Predictions of defect detection performance of air-coupled ultrasonic rail inspection system

Mariani

Scalea

2017

Structural Health Monitoring

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A rail inspection system based on ultrasonic guided waves and non-contact (air-coupled) ultrasound transduction is under development at the University of California at San Diego. The system targets defects in the rail head that are major causes of train accidents. Because of the high acoustic impedance mismatch between air and steel, the non-contact system poses severe challenges and questions on the defect detection performance. This article presents an extensive numerical study, conducted with a local interaction simulation approach, to model the ultrasound propagation and interaction with defects in the proposed system. This model was used to predict the expected detection performance of the system in the presence of various defects of different sizes and positions, and at varying levels of signal-to-noise ratios. When possible, operating variables for the model were chosen consistently with the field test of an experimental prototype that was conducted in 2014. The defect detection performance was evaluated through the computation of receiver operating characteristic curves in terms of probability of detection versus probability of false alarms. The study indicates that despite the challenges of non-contact probing of the rail, quite satisfactory inspection performance can be expected for a variety of defect types, sizes, and positions. Beyond the specific cases examined in this article, this numerical framework can also be used in the future to examine a larger variety of field test conditions.

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“…These methods include Ultrasonic (US) measurements, 6 Eddy Current (EC) testing, 7 Axle Box Acceleration (ABA) measurements, 8 Video Images (VI) 9 and guided-wave based monitoring. 10 An extensive review of the US, EC and VI method can be found in Refs. 11,12 along with the advantages and disadvantages of each method.…”

Section: Introductionmentioning

confidence: 99%

A hybrid predictive methodology for head checks in railway infrastructure

Meghoe

Jamshidi²,

Loendersloot

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part F:

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This paper presents a hybrid method to assess the rail health with the focus on a specific type of rail surface defect called head check. The proposed method uses physics-based and data-driven models in order to model defect initiation and defect evolution on a rail for a given rail traffic tonnage. Ultrasonic (US) and Eddy Current (EC) defect detection measurements are used to provide Infrastructure Managers (IMs) with insight in the current rail condition. The defect initiation results obtained from the first part of the hybrid method which consists of the physics-based model is successfully validated with the EC measurements. Furthermore, the US and EC measurements are utilized to derive a data-driven model for defect evolution. Finally, a set of robust and predictive Key Performance Indicators (KPIs) are proposed to quantify the future condition of the rail based on different characteristics of rail health resulting from the defect initiation and defect evolution analysis.

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

Cited by 7 publications

References 67 publications

Non-Destructive Inspection of Impact Damage in Composite Aircraft Panels by Ultrasonic Guided Waves and Statistical Processing

Non-Destructive Inspection of Impact Damage in Composite Aircraft Panels by Ultrasonic Guided Waves and Statistical Processing

Predictions of defect detection performance of air-coupled ultrasonic rail inspection system

A hybrid predictive methodology for head checks in railway infrastructure

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