Study on the Measurement of Laser Drilling Depth by Combining Digital Image Relationship Measurement in Aluminum

Ho, Chao-Ching; Li, Guanhong

doi:10.3390/ma14030489

Cited by 3 publications

(1 citation statement)

References 24 publications

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“…Ho [16,17] used machine vision to detect glass surface profiles and defects during a laser-cutting process. The image pre-processing process and the use of deep learning techniques enhanced the detection process of defects in glass.…”

Section: Introductionmentioning

confidence: 99%

Hole Depth Prediction in a Femtosecond Laser Drilling Process Using Deep Learning

et al. 2023

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In high-aspect ratio laser drilling, many laser and optical parameters can be controlled, including the high-laser beam fluence and number of drilling process cycles. Measurement of the drilled hole depth is occasionally difficult or time consuming, especially during machining processes. This study aimed to estimate the drilled hole depth in high-aspect ratio laser drilling by using captured two-dimensional (2D) hole images. The measuring conditions included light brightness, light exposure time, and gamma value. In this study, a method for predicting the depth of a machined hole by using a deep learning methodology was devised. Adjusting the laser power and the number of processing cycles for blind hole generation and image analysis yielded optimal conditions. Furthermore, to forecast the form of the machined hole, we identified the best circumstances based on changes in the exposure duration and gamma value of the microscope, which is a 2D image measurement instrument. After extracting the data frame by detecting the contrast data of the hole by using an interferometer, the hole depth was predicted using a deep neural network with a precision of within 5 μm for a hole within 100 μm.

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Section: Introductionmentioning

confidence: 99%

Hole Depth Prediction in a Femtosecond Laser Drilling Process Using Deep Learning

et al. 2023

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Laser Beam Machining of Tungsten Alloy: Experimental and Numerical Analysis

Begić-Hajdarević

Bijelonja

2022

Metals

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Laser beam machining of various materials has found wide applications in the industry due to its advantages of high-speed machining, no tool wear and no vibration, precision and accuracy, low cost of machining, etc. Investigations into the laser beam machining of uncommon alloy are still limited and more research is needed in this field. In this paper, an analysis of the laser beam machining of tungsten alloy was performed, for cutting and drilling machining processes. First, an experimental analysis of microhardness and microstructure on the laser-cut samples was performed, and then the numerical simulation of the laser beam drilling process and its experimental validation was carried out. The experiments were carried out on a tungsten alloy plate of two different thicknesses, 0.5 and 1 mm. No significant changes in the microhardness, nor in the microstructure characteristics in the heat-affected zone (HAZ), were observed for the cutting conditions considered. A two-dimensional axisymmetric mathematical model for the simulation of the laser beam drilling process is solved by a finite volume method. The model was validated by comparing numerical and experimental results in terms of the size of HAZ and the size and shape of the drilled hole. Experimental and numerical results showed that HAZ is larger in the 0.5-mm-thick plate than in the 1-mm-thick plate under the same drilling conditions. Good agreement was observed between the experimental and numerical results. The developed model improves the understanding of the physical phenomena of laser beam machining and allows the optimization of laser and process parameters.

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Efficient Depth Measurement for Live Control of Laser Drilling Process with Optical Coherence Tomography

Zhao,

Zhang,

Ding

et al. 2024

Photonics

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Laser drilling is widely used for fabricating holes in the semiconductor industry due to high throughput and a small heat-affected zone. However, it produces varying depths owing to uncertain external conditions and requires live control at the rate of a few tens of kHz to handle the fast material removal rate. Optical coherent tomography is capable of in situ acquiring a raw interferogram at a high rate (>80 kHz), but the depth extraction is slow due to the involved heavy Fast Fourier Transform (FFT). To address this, an efficient depth-tracking algorithm is proposed to save the FFT. It searches the depth in the raw interferogram locally with a known last depth given the two truths that only one depth exists and the adjacent depths do not change significantly. The proposed algorithm was proven to expedite the measuring rate six times with sub-pixel tracking precision. To further secure the rate against the interrupting of the system, the tracking process is parallelly implemented in a field-programmable gate array. The closed-loop control tests were conducted on probe cards with depth variations introduced by offsetting laser focus. The proposed method maintained a uniform depth, with variations reduced by 80% compared to traditional methods.

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Study on the Measurement of Laser Drilling Depth by Combining Digital Image Relationship Measurement in Aluminum

Cited by 3 publications

References 24 publications

Hole Depth Prediction in a Femtosecond Laser Drilling Process Using Deep Learning

Hole Depth Prediction in a Femtosecond Laser Drilling Process Using Deep Learning

Laser Beam Machining of Tungsten Alloy: Experimental and Numerical Analysis

Efficient Depth Measurement for Live Control of Laser Drilling Process with Optical Coherence Tomography

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