Simulation of Laser Ultrasonics for Detection of Surface-Connected Rail Defects

Zhong, Yunjie; Gao, Xiaorong; Luo, Lin; Pan, Yongdong; Qiu, Chun-Rong

doi:10.1007/s10921-017-0451-3

Cited by 30 publications

(13 citation statements)

References 12 publications

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“…The results also show that the selected feature parameters in this paper are suitable for the SVM model to nondestructively detect surface crack depths and angles. (2) This paper shows that the SVM method is suitable for laser ultrasound to quantitatively detect oblique surface cracks, and its advantages are especially revealed when the amount of training set is small sample data. All of the training sets used in this paper satisfy the definition of a small sample.…”

Section: Discussionmentioning

confidence: 98%

“…First, regarding the time domain methods, Guan [1] adopted the finite element method (FEM) to analyze the interaction of laser-generated surface acoustic waves with surface cracks and found four distinct reflected components in the captured waveforms, and the arrival time of the fourth peak was positively related to crack depth. Zhong [2] proposed a new method, in which two staggered lasers excited ultrasonic waves at two sides of a rail. Because the receiving time is related to the crack position, by forming two detection images of the crack, this method improves the laser ultrasound's sensitivity to crack widths.…”

Section: Introductionmentioning

confidence: 99%

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Depth and Angle Evaluation of Oblique Surface Cracks Using a Support Vector Machine Based on Seven Parameters

Liu

Deng

et al. 2022

Applied Sciences

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To intelligently and quickly verify the depths and angles of oblique surface cracks using the laser ultrasound technique, a crack geometry information evaluation method using a support vector machine (SVM) is proposed. The relationships between several parameters—which are based on transmitted waves and reflected waves containing crack geometry information in the time domain, frequency domain and time–frequency domain, and crack size—are presented in detail. To decide which feature parameters are involved in the SVM model, two selection standards are proposed according to the correlations between feature parameters and crack size and between the feature parameters themselves. Finally, a seven-feature-parameter SVM model which has an excellent ability to classify oblique crack depths and angles is built. The results of simulations using the finite element method (FEM) and experimental data show that seven parameters based on the SVM model are available for the oblique surface crack depth and angle evaluation and can be used to nondestructively detect natural cracks.

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Section: Discussionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Depth and Angle Evaluation of Oblique Surface Cracks Using a Support Vector Machine Based on Seven Parameters

Liu

Deng

et al. 2022

Applied Sciences

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“… To detect defects in the railway fasteners, analysis was done using machine vision methods using a camera [26][27][28][29][30][31].…”

Section: Methodsmentioning

confidence: 99%

Thermal Analysis In Fixed, Flowed And Airless Environment For Cooling In Led Luminaires

Cengiz¹,

Yetkin

2020

L&E

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In this study, a simulation study was conducted for the loss of efficiency caused by the heat emitted by the LED chips. The temperature change of LED luminaire was analysed for three different scenarios using finite element method. Due to the increase in the internal temperature of the luminaire and due to the air effect inside the LED luminaires, failure of the LEDs has been tried to be prevented. For this purpose, a passive cooling method was proposed in the simulation environment. So, in high power LED luminaires, the high heat emitted by the LED chips is reduced to low heat by an air flow method. In this way, efficiency in LED outputs has been achieved.

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“…Similarly, the temporal distribution of the laser is also approximated as a Gaussian distribution function and is given by [ 15 ].

where t 0 is the rising time of the laser.…”

Section: Development Of Fem Simulation Dictionarymentioning

confidence: 99%

“…The laser ultrasonic technique (LUT) is one of the latest candidates for non-destructive testing. Several research groups have investigated LUT for the inspection of rail tracks [ 9 , 10 , 11 , 12 , 13 , 14 , 15 ]. However, in these works, for the non-contact detection of laser-generated ultrasonic waves, mostly EMAT [ 9 ] and air-coupled transducers [ 11 , 12 ] were used.…”

Section: Introductionmentioning

confidence: 99%

Non-Contact Inspection of Railhead via Laser-Generated Rayleigh Waves and an Enhanced Matching Pursuit to Assist Detection of Surface and Subsurface Defects

Ghafoor

Tse

Rostami

et al. 2021

Sensors

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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.

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Simulation of Laser Ultrasonics for Detection of Surface-Connected Rail Defects

Cited by 30 publications

References 12 publications

Depth and Angle Evaluation of Oblique Surface Cracks Using a Support Vector Machine Based on Seven Parameters

Depth and Angle Evaluation of Oblique Surface Cracks Using a Support Vector Machine Based on Seven Parameters

Thermal Analysis In Fixed, Flowed And Airless Environment For Cooling In Led Luminaires

Non-Contact Inspection of Railhead via Laser-Generated Rayleigh Waves and an Enhanced Matching Pursuit to Assist Detection of Surface and Subsurface Defects

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