High Speed Non-Contact Ultrasonic Guided Wave Inspections of Rails

Author(s):  
Stefano Mariani ◽  
Thompson V. Nguyen ◽  
Francesco Lanza di Scalea ◽  
Mahmood Fateh

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.

Author(s):  
Thompson V. Nguyen ◽  
Stefano Mariani ◽  
Robert R. Phillips ◽  
Piotr Kijanka ◽  
Francesco Lanza di Scalea ◽  
...  

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 integrity evaluation. A prototype using an ultrasonic air-coupled guided wave signal generation and air-coupled signal detection, in pair with a real-time statistical analysis algorithm, is being developed. 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. This system requires a specialized filtering approach due to the inherently poor signal-to-noise ratio of the 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. 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. Experimental tests have been carried out at the UCSD Rail Defect Farm. The laboratory results indicate that the prototype is able to detect internal rail defects with a high reliability. A field test will be planned later in the year to further validate these results. Extensions of the system are planned to add rail surface characterization to the internal rail defect detection.


Author(s):  
Stefano Mariani ◽  
Thompson V. Nguyen ◽  
Xuan Zhu ◽  
Simone Sternini ◽  
Francesco Lanza di Scalea ◽  
...  

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.


Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4759
Author(s):  
Seyed Kamran Pedram ◽  
Tat-Hean Gan ◽  
Mahdieh Ghafourian

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.


2016 ◽  
Author(s):  
Stefano Mariani ◽  
Thompson V. Nguyen ◽  
Simone Sternini ◽  
Francesco Lanza di Scalea ◽  
Mahmood Fateh ◽  
...  

Author(s):  
Jing Wu ◽  
Fei Yang ◽  
Lin Jing ◽  
Zhongming Liu ◽  
Yizhou Lin ◽  
...  

Author(s):  
Molin Zhao ◽  
Haisheng Wang ◽  
Bin Xue ◽  
Yonggang Yue ◽  
Pengfei Zhang ◽  
...  

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1445 ◽  
Author(s):  
Sergio Cantero-Chinchilla ◽  
Gerardo Aranguren ◽  
Muhammad Khalid Malik ◽  
Josu Etxaniz ◽  
Federico Martín de la Escalera

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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