ABSTRACT
Laser ultrasonic technology can provide a non-contact, reliable and efficient inspection of train rails. However, the laser-generated signals measured at the railhead are usually contaminated with a high level of noise and unwanted wave components that complicate the identification of defect echoes in the signal. This study explores the possibility of combining laser ultrasonic technology (LUT) and an enhanced matching pursuit (MP) to achieve a fully non-contact inspection of the rail track. A completely non-contact laser-based inspection system was used to generate and sense Rayleigh waves to detect artificial surface horizontal, surface edge, subsurface horizontal and subsurface vertical defects created at railheads of different dimensions. MP was enhanced by developing two novel dictionaries, which include a finite element method (FEM) simulation dictionary and an experimental dictionary. The enhanced MP was used to analyze the experimentally obtained laser-generated Rayleigh wave signals. The results show that the enhanced MP is highly effective in detecting defects by suppressing noise, and, further, it could also overcome the deficiency in the low repeatability of the laser-generated signals. The comparative analysis of MP with both the FEM simulation and experimental dictionaries shows that the enhanced MP with the FEM simulation dictionary is highly efficient in both noise removal and defect detection from the experimental signals captured by a laser-generated ultrasonic inspection system. The major novelty contributed by this research work is the enhanced MP method with the developments of, first, an FEM simulation dictionary and, second, an experimental dictionary that is especially suited for Rayleigh wave signals. Third, the enhanced MP dictionaries are created to process the Rayleigh wave signals generated by laser excitation and received using a 3D laser scanner. Fourth, we introduce a pioneer application of such laser-generated Rayleigh waves for inspecting surface and subsurface detects occurring in train rails.
ABSTRACT
Multiple wire twisted steel strands are commonly used to hoist elevators, concrete structures, etc. Due to frequent and long-time usage, the steel strands are subjected to corrosion, overloads, and aging, making strands may fail unexpectedly. Hence, the health monitoring of steel strands becomes more important to avoid the sudden collapse of hoisting structures. Guided waves (GW) inspection methods have become favorable in recent years due to its long-distance transmission and stability of evaluation in the area of structural health monitoring (SHM) and Non-Destructive Testing (NDT). Many researchers have reported different GW methods to detect different types of defects that occurred in steel strands. However, researchers rarely carry out comparative studies to investigate the effectiveness of each method or system in monitoring the health state of steel strands. This article reports some vital observations revealed from conducting experiments by using contact and noncontact methods, which include three different popular types of GW sensors and methods during their applications in surface-type defect detection. The proper selection of sensors systems has been identified through the present study. The result of the present study is believed to be useful guidance for selecting appropriate GW methods and sensor systems to monitor the integrity of the steel strand and thereby ensure the safety of the hoisted structures.
ABSTRACT
The Letter presents a new design of Sagnac interferometer-based optical system (SIOS) that emits a line-arrayed pattern generating narrowband high-energy waves in a specimen. The SIOS is further used to excite Rayleigh waves in a pristine rail specimen to evaluate its intrinsic nonlinearity resulting from the lattice anharmonicity and dissolved impurities. Such a nonlinearity appears in the response in the form of a second harmonic that is sensed in this Letter using a scanning laser Doppler vibrometer. In addition to this noncontact measurement, a contact measurement of the nonlinearity of rail steel using wedge transducers is also carried out to compare the performance of the SIOS. Both experimentally evaluated nonlinearities are compared with those obtained using the nonlinear elasticity equations. The close agreement with the theoretically estimated nonlinearity and higher repeatability shows that the SIOS is effective in measuring the intrinsic nonlinearity of the rail steel and, thereby, predicting the health status of the rail specimens before fixing them on the track.
