Experimental characterisation of laser surface remelting via acoustic emission wavelet decomposition

Mojškerc, Bor; Ravnikar, Dunja; Šturm, Roman

doi:10.1016/j.jmrt.2021.10.010

Cited by 9 publications

(2 citation statements)

References 24 publications

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“…Keeping the above single-echo eigenvector parameters unchanged, setting the attenuation factor to 0.6 and the time interval = 4 μ , signal is shown in Figure 11. Based on [23], wavelet 5-layer decomposition is chosen to simulate the above five thresholding methods, and the simulation results are shown in Figure 12. The root mean square error (RMSE) and signal-to-noise ratio (SNR) are calculated, and the results are shown in Table 1.…”

Section: Wavelet Noise Reduction Methods For Ultrasound Echo Signalsmentioning

confidence: 99%

Ultrasonic Thickness Measurement Method and System Implementation Based on Sampling Reconstruction and Phase Feature Extraction

Gong,

Wang,

Yang

et al. 2023

Sensors

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The existing ultrasonic thickness measurement systems require high sampling frequencies for echo signal acquisition, leading to complex circuit designs and high costs. Moreover, extracting the characteristics of ultrasonic echo signals for accurate thickness measurement poses significant challenges. To address these issues, this paper proposes a method that utilizes conventional sampling frequencies to acquire high-frequency ultrasonic echo signals, overcoming the limitations of high-frequency data acquisition imposed by the Nyquist–Shannon sampling theorem. By employing an improved sampling reconstruction technique, the multi-cycle sampling signals are reconstructed and rearranged within a single cycle, effectively increasing the equivalent sampling frequency. Additionally, a combination of coarse estimation using fast Fourier transform (FFT) and precise phase extraction using the moving sine fitting algorithm is proposed for accurate thickness measurement, resolving the limitations of common thickness measurement methods such as peak detection, envelope detection, and Hilbert autocorrelation in terms of low measurement accuracy. Experimental results obtained from thickness measurements on 45 steel ultrasonic test blocks within the range of 3 mm to 20 mm indicate a measurement error of ±0.01 mm, while for thicknesses ranging from 1 mm to 50 mm, the measurement error is ±0.05 mm.

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Section: Wavelet Noise Reduction Methods For Ultrasound Echo Signalsmentioning

confidence: 99%

Ultrasonic Thickness Measurement Method and System Implementation Based on Sampling Reconstruction and Phase Feature Extraction

Gong,

Wang,

Yang

et al. 2023

Sensors

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show abstract

“…In other studies, AE has been used as a tool for predicting welding defects such as hanging slags [ 23 – 25 ]. When applied in additive manufacturing, the AE technique presents more advantages in terms of monitoring [ 26 – 28 ], such as indicating processing quality in laser powder bed fusion [ 29 ], identifying processing state, diagnosing defects in laser cladding [ 30 ], classifying defects in selective laser melting [ 31 , 32 ], and so on. Almost all of the studies mentioned above have worked on AE monitoring of continuous laser processing of metal materials, and very little work has focused on pulsed laser processing [ 33 , 34 ].…”

Section: Introductionmentioning

confidence: 99%

Revealing the interaction mechanism of pulsed laser processing with the application of acoustic emission

Liu

Rong

Yang

et al. 2023

Front. Optoelectron.

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The mechanisms of interaction between pulsed laser and materials are complex and indistinct, severely influencing the stability and quality of laser processing. This paper proposes an intelligent method based on the acoustic emission (AE) technique to monitor laser processing and explore the interaction mechanisms. The validation experiment is designed to perform nanosecond laser dotting on float glass. Processing parameters are set differently to generate various outcomes: ablated pits and irregular-shaped cracks. In the signal processing stage, we divide the AE signals into two bands, main and tail bands, according to the laser processing duration, to study the laser ablation and crack behavior, respectively. Characteristic parameters extracted by a method that combines framework and frame energy calculation of AE signals can effectively reveal the mechanisms of pulsed laser processing. The main band features evaluate the degree of laser ablation from the time and intensity scales, and the tail band characteristics demonstrate that the cracks occur after laser dotting. In addition, from the analysis of the parameters of the tail band very large cracks can be efficiently distinguished. The intelligent AE monitoring method was successfully applied in exploring the interaction mechanism of nanosecond laser dotting float glass and can be used in other pulsed laser processing fields. Graphical Abstract

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Aspects of Structure and Properties Formation in Steels During Laser-Acoustic Processing

Brover,

Shcherbakova

2023

Metallurgist

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Experimental characterisation of laser surface remelting via acoustic emission wavelet decomposition

Cited by 9 publications

References 24 publications

Ultrasonic Thickness Measurement Method and System Implementation Based on Sampling Reconstruction and Phase Feature Extraction

Ultrasonic Thickness Measurement Method and System Implementation Based on Sampling Reconstruction and Phase Feature Extraction

Revealing the interaction mechanism of pulsed laser processing with the application of acoustic emission

Aspects of Structure and Properties Formation in Steels During Laser-Acoustic Processing

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