scholarly journals Improved Defect Detection of Guided Wave Testing Using Split-Spectrum Processing

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4759
Author(s):  
Seyed Kamran Pedram ◽  
Tat-Hean Gan ◽  
Mahdieh Ghafourian
Keyword(s):  
Defect Detection ◽  
Background Noise ◽  
Structural Integrity ◽  
Traditional Approach ◽  
Signal To Noise Ratio ◽  
Guided Wave ◽  
Signal Quality ◽  
Ultrasonic Guided Wave ◽  
Split Spectrum ◽  
Dispersive Propagation

Ultrasonic guided wave (UGW) testing is widely applied in numerous industry areas for the examination of pipelines where structural integrity is of concern. Guided wave testing is capable of inspecting long lengths of pipes from a single tool location using some arrays of transducers positioned around the pipe. Due to dispersive propagation and the multimodal behavior of UGW, the received signal is usually degraded and noisy, that reduce the inspection range and sensitivity to small defects. Therefore, signal interpretation and identifying small defects is a challenging task in such systems, particularly for buried/coated pipes, in that the attenuation rates are considerably higher compared with a bare pipe. In this work, a novel solution is proposed to address this issue by employing an advanced signal processing approach called “split-spectrum processing” (SSP) to minimize the level of background noise and enhance the signal quality. The SSP technique has already shown promising results in a limited trial for a bar pipe and, in this work, the proposed technique has been experimentally compared with the traditional approach for coated pipes. The results illustrate that the proposed technique significantly increases the signal-to-noise ratio and enhances the sensitivity to small defects that are hidden below the background noise.

scholarly journals Enhancement of Ultrasonic Guided Wave Signals Using a Split-Spectrum Processing Method

2018 ◽  
Vol 8 (10) ◽  
pp. 1815 ◽  
Author(s):  
Seyed Kamran Pedram ◽  
Peter Mudge ◽  
Tat-Hean Gan
Keyword(s):  
Structural Integrity ◽  
Signal To Noise Ratio ◽  
Processing Technique ◽  
Guided Wave ◽  
Signal Processing Technique ◽  
Pipeline Inspection ◽  
Ultrasonic Guided Wave ◽  
Small Defect ◽  
Split Spectrum ◽  
Wave Modes

Ultrasonic guided wave (UGW) systems are broadly utilised in several industry sectors where the structural integrity is of concern, in particular, for pipeline inspection. In most cases, the received signal is very noisy due to the presence of unwanted wave modes, which are mainly dispersive. Hence, signal interpretation in this environment is often a challenging task, as it degrades the spatial resolution and gives a poor signal-to-noise ratio (SNR). The multi-modal and dispersive nature of such signals hampers the ability to detect defects in a given structure. Therefore, identifying a small defect within the noise level is a challenging task. In this work, an advanced signal processing technique called split-spectrum processing (SSP) is used firstly to address this issue by reducing/removing the effect of dispersive wave modes, and secondly to find the limitation of this technique. The method compared analytically and experimentally with the conventional approaches, and showed that the proposed method substantially improves SNR by an average of 30dB. The limitations of SSP in terms of sensitivity to small defects and distances are also investigated, and a threshold has been defined which was comparable for both synthesised and experimental data. The conclusions reached in this work paves the way to enhance the reliability of UGW inspection.

High Speed Non-Contact Ultrasonic Guided Wave Inspections of Rails

2014 ◽  
Author(s):  
Stefano Mariani ◽  
Thompson V. Nguyen ◽  
Francesco Lanza di Scalea ◽  
Mahmood Fateh
Keyword(s):  
Defect Detection ◽  
High Speed ◽  
Surface Characterization ◽  
Rail Steel ◽  
Signal To Noise Ratio ◽  
High Reliability ◽  
False Positive Rate ◽  
Roc Curves ◽  
Guided Wave ◽  
Ultrasonic Guided Wave

This paper describes a new system for high-speed and non-contact rail defect detection being developed at the University of California at San Diego (UCSD). A prototype using an ultrasonic air-coupled guided wave signal generation and air-coupled signal detection has been tested at the UCSD Rail Defect Farm. This solution presents an improvement over the previously considered laser/air-coupled hybrid system because it replaces the costly and hard-to-maintain laser with a much cheaper, faster, and easier-to-maintain air-coupled transmitter. In addition to a real-time statistical analysis algorithm, the prototype uses a specialized filtering approach to mitigate the inherently poor signal-to-noise ratio of the air-coupled ultrasonic measurements in rail steel. The laboratory results indicate that the prototype is able to detect internal rail defects with a high reliability. 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. Many of the system 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. Extensions of the system capability are planned to add rail surface characterization to the internal rail defect detection to optimize rail grinding operations.

scholarly journals Rail Diagnostics Based on Ultrasonic Guided Waves: An Overview

2021 ◽  
Vol 11 (3) ◽  
pp. 1071
Author(s):  
Davide Bombarda ◽  
Giorgio Matteo Vitetta ◽  
Giovanni Ferrante
Keyword(s):  
Guided Waves ◽  
Structural Integrity ◽  
Diagnostic Procedures ◽  
Guided Wave ◽  
Rolling Stock ◽  
Technical Literature ◽  
Track Maintenance ◽  
Rail Network ◽  
Ultrasonic Guided Wave ◽  
Maintenance And Inspection

Rail tracks undergo massive stresses that can affect their structural integrity and produce rail breakage. The last phenomenon represents a serious concern for railway management authorities, since it may cause derailments and, consequently, losses of rolling stock material and lives. Therefore, the activities of track maintenance and inspection are of paramount importance. In recent years, the use of various technologies for monitoring rails and the detection of their defects has been investigated; however, despite the important progresses in this field, substantial research efforts are still required to achieve higher scanning speeds and improve the reliability of diagnostic procedures. It is expected that, in the near future, an important role in track maintenance and inspection will be played by the ultrasonic guided wave technology. In this manuscript, its use in rail track monitoring is investigated in detail; moreover, both of the main strategies investigated in the technical literature are taken into consideration. The first strategy consists of the installation of the monitoring instrumentation on board a moving test vehicle that scans the track below while running. The second strategy, instead, is based on distributing the instrumentation throughout the entire rail network, so that continuous monitoring in quasi-real-time can be obtained. In our analysis of the proposed solutions, the prototypes and the employed methods are described.

Defect detection performance of the UCSD non-contact air-coupled ultrasonic guided wave inspection of rails prototype

2016 ◽  
Author(s):  
Stefano Mariani ◽  
Thompson V. Nguyen ◽  
Simone Sternini ◽  
Francesco Lanza di Scalea ◽  
Mahmood Fateh ◽  
...  
Keyword(s):  
Defect Detection ◽  
Detection Performance ◽  
Guided Wave ◽  
Ultrasonic Guided Wave

Defect detection in pipes using Van der Pol systems based on ultrasonic guided wave

2021 ◽  
pp. 104577
Author(s):  
Jing Wu ◽  
Fei Yang ◽  
Lin Jing ◽  
Zhongming Liu ◽  
Yizhou Lin ◽  
...  
Keyword(s):  
Defect Detection ◽  
Guided Wave ◽  
Van Der Pol ◽  
Ultrasonic Guided Wave

scholarly journals Research on ultrasonic guided wave dispersion compensation for steel strand defect detection

2020 ◽  
Vol 740 ◽  
pp. 012101
Author(s):  
Molin Zhao ◽  
Haisheng Wang ◽  
Bin Xue ◽  
Yonggang Yue ◽  
Pengfei Zhang ◽  
...  
Keyword(s):  
Defect Detection ◽  
Dispersion Compensation ◽  
Wave Dispersion ◽  
Guided Wave ◽  
Ultrasonic Guided Wave ◽  
Steel Strand

scholarly journals An Empirical Study on Transmission Beamforming for Ultrasonic Guided-Wave Based Structural Health Monitoring

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1445 ◽  
Author(s):  
Sergio Cantero-Chinchilla ◽  
Gerardo Aranguren ◽  
Muhammad Khalid Malik ◽  
Josu Etxaniz ◽  
Federico Martín de la Escalera
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Guided Waves ◽  
Signal To Noise Ratio ◽  
Guided Wave ◽  
High Signal ◽  
Efficient Operation ◽  
Structural Health ◽  
Thin Walled Structures ◽  
Ultrasonic Guided Wave

The development of reliable structural health monitoring techniques is enabling a healthy transition from preventive to condition-based maintenance, hence leading to safer and more efficient operation of different industries. Ultrasonic guided-wave based beamforming is one of the most promising techniques, which supports the monitoring of large thin-walled structures. However, beamforming has been typically applied to the post-processing stage (also known as virtual or receiver beamforming) because transmission or physical beamforming requires complex hardware configurations. This paper introduces an electronic structural health monitoring system that carries out transmission beamforming experiments by simultaneously emitting and receiving ultrasonic guided-waves using several transducers. An empirical characterization of the transmission beamforming technique for monitoring an aluminum plate is provided in this work. The high signal-to-noise ratio and accurate angular precision of the physical signal obtained in the experiments suggest that transmission beamforming can increase the reliability and robustnessof this monitoring technique for large structures and in real-world noisy environments.

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