Advancing NDE Education for Future Engineers – A South African Perspective

Non-Destructive Evaluation has gained vast popularity in industry due to its effectiveness in the inspection of engineering structures. To date, a lot of advances to train NDE technicians have been achieved, with the objective to instill the understanding of basic principles of NDE methods and the practical application of such methods. The testing of structures is classically performed according to design codes such as American Society of Mechanical Engineers –V (ASME-V), American Society for Testing and Materials (ASTM), British Standard 3923 (BS 3923) and others. For performing in-service inspection, there is no existing design code. This calls for a need to highly advance NDE engineering education. There is also a need to design NDT systems. To develop reliable systems, technical justifications will be required, and can be achieved through modelling capabilities. It is therefore significant to develop a thorough understanding of the NDE system and qualifications based on correct inputs from allied sciences, and also develop modelling capabilities at engineering level for an integrated approach to NDE. The use of university education at undergraduate and postgraduate levels to help facilitate NDE education should be promoted

Optimal Design of a Piezoelectric Transducer for Exciting Guided Wave Ultrasound in Rails

An existing Ultrasonic Broken Rail Detection System [1] installed in South Africa on a heavy duty railway line is currently being upgraded to include defect detection and location. To accomplish this, an ultrasonic piezoelectric transducer to strongly excite a guided wave mode with energy concentrated in the web (web mode) of a rail is required. A previous study [2] demonstrated that the recently developed SAFE-3D (Semi-Analytical Finite Element – 3 Dimensional) method can effectively predict the guided waves excited by a resonant piezoelectric transducer. In this study, the SAFE-3D model is used in the design optimization of a rail web transducer. A bound-constrained optimization problem was formulated to maximize the energy transmitted by the transducer in the web mode when driven by a pre-defined excitation signal. Dimensions of the transducer components were selected as the three design variables. A Latin hypercube sampled design of experiments that required a total of 500 SAFE- 3D analyses in the design space was employed in a response surface-based optimization approach. The Nelder-Mead optimization algorithm was then used to find an optimal transducer design on the constructed response surface. The radial basis function response surface was first verified by comparing a number of predicted responses against the computed SAFE-3D responses. The performance of the optimal transducer predicted by the optimization algorithm on the response surface was also verified to be sufficiently accurate using SAFE-3D. The computational advantages of SAFE-3D in transducer design is noteworthy given we needed to conduct more than 500 analyses. The optimal design was then manufactured and experimental measurements were used to validate the predicted performance. The adopted design method has demonstrated the capability to automate the design of transducers for a particular rail cross- section and frequency range

Digital twin hybrid modeling for enhancing guided wave ultrasound inspection signals in welded rails

Guided wave ultrasound (GWU) systems have been widely used for monitoring structures such as rails, pipelines, and plates. In railway tracks, the monitoring process involves the complicated propagation of waves over several hundred meters. The propagating waves are multi-modal and interact with discontinuities differently, increasing complexity and leading to different response signals. When the researcher wants to gain insight into the behavior of guided waves, predicting response signals for different combinations of modes becomes necessary. However, the task can become computationally costly when physics-based models are used. Digital twins can enable a practitioner to deal systematically with the complexities of guided wave monitoring in practical or user-specified settings. This paper investigates the use of a hybrid digital model of an operational rail track to predict response signals for varying user-specified settings, specifically, the prediction of response signals for various combinations of modes of propagation in the rail. The digital twin hybrid model employs a physics-based model and a data-driven model. The physics-based model simulates the wave propagation response using techniques developed from the traditional 3D finite element method and the 2D semi-analytical finite element method (FEM). The physics-based model is used to generate virtual experimental signals containing different combinations of modes of propagation. These response signals are used to train the data-driven model based on a variational auto-encoder (VAE). Given an input baseline signal containing only the most dominant mode excited by a transducer, the VAE is trained to predict an inspection signal with increased complexity according to the specified combination of modes. The results show that, once the VAE has been trained, it can be used to predict inspection signals for different combinations of propagating modes, thus replacing the physics-based model, which is computationally costly. In the future, the VAE architecture will be adapted to predict response signals for varying environmental and operational conditions.http://www.mdpi.com/journal/mcaMechanical and Aeronautical EngineeringSDG-09: Industry, innovation and infrastructureSDG-11:Sustainable cities and communitie

A data-driven hybrid approach to generate synthetic data for unavailable damage scenarios in welded rails for ultrasonic guided wave monitoring

eveloping reliable ultrasonic-guided wave monitoring systems requires a significant amount of inspection data for each application scenario. Experimental investigations are fundamental but require a long period and are costly, especially for real-life testing. This is exacerbated by a lack of experimental data that includes damage. In some guided wave applications, such as pipelines, it is possible to introduce artificial damage and perform lab experiments on the test structure. However, in rail track applications, laboratory experiments are either not possible or meaningful. The generation of synthetic data using modelling capabilities thus becomes increasingly important. This paper presents a variational autoencoder (VAE)-based deep learning approach for generating synthetic ultrasonic inspection data for welded railway tracks. The primary aim is to use a VAE model to generate synthetic data containing damage signatures at specified positions along the length of a rail track. The VAE is trained to encode an input damage-free baseline signal and decode to reconstruct an inspection signal with damage by adding a damage signature on either side of the transducer by specifying the distance to the damage signature as an additional variable in the latent space. The training data was produced from a physics-based model that computes virtual experimental response signals using the semi-analytical finite element and the traditional finite element procedures. The VAE reconstructed response signals containing damage signatures were almost identical to the original target signals simulated using the physics-based model. The VAE was able to capture the complex features in the signals resulting from the interaction of multiple propagating modes in a multi-discontinuous waveguide. The VAE model successfully generated synthetic inspection data by fusing reflections from welds with the reflection from a crack model at specified distances from the transducer on either the right or left side. In some cases, the VAE did not exactly reconstruct the peak amplitude of the reflections. This study demonstrated the potential and highlighted the benefit of using a VAE to generate synthetic data with damage signatures as opposed to using superposition to fuse the damage-free responses containing reflections from welds with a damage signature. The results show that it is possible to generate realistic inspection data for unavailable damage scenarios.https://journals.sagepub.com/home/shmhj2024Mechanical and Aeronautical EngineeringSDG-09: Industry, innovation and infrastructur

Physics-based modelling and simulation of reverberating reflections in ultrasonic guided wave inspections applied to welded rail tracks

The development of ultrasonic guided wave monitoring systems has become increasingly important as they have demonstrated the ability to detect damage in structures. An example of such a system is the Ultrasonic Broken Rail Detection system which uses pitch-catch piezoelectric transducers permanently attached to the rail to excite and receive ultrasonic guided wave signals. Changes in signals can provide a reliable indication of damage growth in the rail and ultimately reduce broken rails and derailments. However, the challenge during system development is obtaining monitoring data containing damage signatures as damaged sections of rail are immediately replaced when detected. Laboratory damage experiments are also not plausible due to end reflections from short rail sections dominating the response. Modelling and simulation thus become increasingly important to enable the simulation of unavailable damage scenarios for the upgradation of existing (or development of new reliable) guided wave-based monitoring systems. Two numerical procedures to model and simulate guided wave inspections encompassing the excitation, propagation and scattering from discontinuities in 1D waveguides are presented and applied to the inspection of the web of a welded rail. The major contribution highlighted by these procedures is the ability to simulate complex back and forth reverberating reflections. These reflections occur between various reflectors such as welds and other discontinuities such as damage. The two methods are different but complementary. The first one, which is based on a simple manual simulation of finite reverberating reflections, is useful for interpreting the results to understand how different reflections interact, especially where they overlap. The second method accounts for the scattering by all defects or discontinuities arbitrarily positioned in the waveguide. It offers a more accurate approximation of the simulated inspection since it accounts for infinite reflections. The simulation results obtained from the two modelling procedures are validated using a field experiment from a damage-free rail containing welds and holes as discontinuities. The results show that it would be possible to simulate inspections for unavailable damage scenarios. The paper is concluded with a thorough analysis of the inspection measurement using the first method.http://www.elsevier.com/locate/jsvihj2022Mechanical and Aeronautical Engineerin

Digital Twin Hybrid Modeling for Enhancing Guided Wave Ultrasound Inspection Signals in Welded Rails

Guided wave ultrasound (GWU) systems have been widely used for monitoring structures such as rails, pipelines, and plates. In railway tracks, the monitoring process involves the complicated propagation of waves over several hundred meters. The propagating waves are multi-modal and interact with discontinuities differently, increasing complexity and leading to different response signals. When the researcher wants to gain insight into the behavior of guided waves, predicting response signals for different combinations of modes becomes necessary. However, the task can become computationally costly when physics-based models are used. Digital twins can enable a practitioner to deal systematically with the complexities of guided wave monitoring in practical or user-specified settings. This paper investigates the use of a hybrid digital model of an operational rail track to predict response signals for varying user-specified settings, specifically, the prediction of response signals for various combinations of modes of propagation in the rail. The digital twin hybrid model employs a physics-based model and a data-driven model. The physics-based model simulates the wave propagation response using techniques developed from the traditional 3D finite element method and the 2D semi-analytical finite element method (FEM). The physics-based model is used to generate virtual experimental signals containing different combinations of modes of propagation. These response signals are used to train the data-driven model based on a variational auto-encoder (VAE). Given an input baseline signal containing only the most dominant mode excited by a transducer, the VAE is trained to predict an inspection signal with increased complexity according to the specified combination of modes. The results show that, once the VAE has been trained, it can be used to predict inspection signals for different combinations of propagating modes, thus replacing the physics-based model, which is computationally costly. In the future, the VAE architecture will be adapted to predict response signals for varying environmental and operational conditions

A modelling framework for simulation of ultrasonic guided wave-based inspection of welded rail tracks

A modelling framework for ultrasonic inspection of waveguides with arbitrary discontinuities, excited using piezoelectric transducers, is developed. The framework accounts for multi-modal, dispersive and damped one dimensional propagation over long distances. The proposed model is applied to simulate a realistic guided wave-based inspection of a welded rail. The framework models the excitation, propagation and scattering of guided waves from welds by respectively employing a hybrid model that couples a 3D FEM model of a piezoelectric transducer with a 2D SAFE model of the rail; a 2D SAFE model of the rail; and another hybrid method which couples a 3D FEM model of the arbitrary discontinuity (weld) with two SAFE models of the rail to represent the semi-infinite incoming and outgoing waveguides. Optimal damping parameters for hysteretic and viscous damping, respectively, are determined using a model updating procedure to approximate attenuation in the rail. Good agreement between the experimental measurement and simulation is demonstrated, even for weld reflections originating over 640 m from the transducer location. The proposed physics-based framework can be used to efficiently perform multiple analyses considering different numbers and locations of welds, different excitation signals or to investigate the effects of changes in parameters such as transducer geometry, or material property variations caused by temperature fluctuations. The framework could therefore be used in future to set up a digital twin of a section of rail track, or in the development of a rail monitoring system by predicting reflections from defects which cannot readily be measured, but which can be simulated.https://www.elsevier.com/locate/ultras2022-07-26hj2021Mechanical and Aeronautical Engineerin