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On-line estimation of laser-drilled hole depth using a machine vision method.

Ho CC, He JJ, Liao TY - Sensors (Basel) (2012)

Bottom Line: Therefore, a low cost on-line inspection system is developed to increase productivity.A correlation between the cumulative size of the laser-induced plasma region and the depth of the hole is presented.The result indicates that the estimated depths of the laser-drilled holes were a linear function of the cumulative plasma size, with a high degree of confidence.

View Article: PubMed Central - PubMed

Affiliation: Department of Mechanical Engineering, National Yunlin University of Science and Technology, Douliou, Yunlin 64002, Taiwan. HoChao@yuntech.edu.tw

ABSTRACT
The paper presents a novel method for monitoring and estimating the depth of a laser-drilled hole using machine vision. Through on-line image acquisition and analysis in laser machining processes, we could simultaneously obtain correlations between the machining processes and analyzed images. Based on the machine vision method, the depths of laser-machined holes could be estimated in real time. Therefore, a low cost on-line inspection system is developed to increase productivity. All of the processing work was performed in air under standard atmospheric conditions and gas assist was used. A correlation between the cumulative size of the laser-induced plasma region and the depth of the hole is presented. The result indicates that the estimated depths of the laser-drilled holes were a linear function of the cumulative plasma size, with a high degree of confidence. This research provides a novel machine vision-based method for estimating the depths of laser-drilled holes in real time.

No MeSH data available.


Related in: MedlinePlus

Relationship between pixels and depth, along with process time.
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f12-sensors-12-10148: Relationship between pixels and depth, along with process time.

Mentions: The results reveal that the cumulative plasma size has high coefficient of determination (R2) of 0.984 (aluminum, 145 mJ), 0.95 (aluminum, 175 mJ), 0.983 (aluminum, 200 mJ), 0.892 (stainless steel, 145 mJ), 0.975 (stainless steel, 175 mJ), and 0.978 (stainless steel, 200 mJ) with the machining depth, respectively. The hole depth is directly proportional to the machining pulses and the sum of the pixels of all the frames of the plasma region. Based on the proportional relation, we could use the total cumulative pixel values to estimate and detect the laser-drilled hole depth. Also, higher laser energy could induce both a larger region and additional pixels of plasma. Considering the fact that the radiation energy of the laser machining also affects the machining depth, a higher energy could generate deeper holes for the same process time, as shown in Figure 12. We also found that when the laser beam struck the material surface, the higher energy induced a larger plasma region. In this study of image processing based on machine vision, we determined that the size of the laser-induced plasma region at the surface of the workpiece could be transformed into the value of the pixels. The laser energy conditions determined both the laser-drilled hole depth and size of the plasma region, along with the process time. Thus, we could analyze and obtain the total pixels of the plasma region in on-line during processing, and we achieved a on-line detection and estimation of the depth of a laser-drilled hole. However, as shown in the Figure 12, the variations in the cumulative plasma size and the drilling depth with the time were observed.


On-line estimation of laser-drilled hole depth using a machine vision method.

Ho CC, He JJ, Liao TY - Sensors (Basel) (2012)

Relationship between pixels and depth, along with process time.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3472821&req=5

f12-sensors-12-10148: Relationship between pixels and depth, along with process time.
Mentions: The results reveal that the cumulative plasma size has high coefficient of determination (R2) of 0.984 (aluminum, 145 mJ), 0.95 (aluminum, 175 mJ), 0.983 (aluminum, 200 mJ), 0.892 (stainless steel, 145 mJ), 0.975 (stainless steel, 175 mJ), and 0.978 (stainless steel, 200 mJ) with the machining depth, respectively. The hole depth is directly proportional to the machining pulses and the sum of the pixels of all the frames of the plasma region. Based on the proportional relation, we could use the total cumulative pixel values to estimate and detect the laser-drilled hole depth. Also, higher laser energy could induce both a larger region and additional pixels of plasma. Considering the fact that the radiation energy of the laser machining also affects the machining depth, a higher energy could generate deeper holes for the same process time, as shown in Figure 12. We also found that when the laser beam struck the material surface, the higher energy induced a larger plasma region. In this study of image processing based on machine vision, we determined that the size of the laser-induced plasma region at the surface of the workpiece could be transformed into the value of the pixels. The laser energy conditions determined both the laser-drilled hole depth and size of the plasma region, along with the process time. Thus, we could analyze and obtain the total pixels of the plasma region in on-line during processing, and we achieved a on-line detection and estimation of the depth of a laser-drilled hole. However, as shown in the Figure 12, the variations in the cumulative plasma size and the drilling depth with the time were observed.

Bottom Line: Therefore, a low cost on-line inspection system is developed to increase productivity.A correlation between the cumulative size of the laser-induced plasma region and the depth of the hole is presented.The result indicates that the estimated depths of the laser-drilled holes were a linear function of the cumulative plasma size, with a high degree of confidence.

View Article: PubMed Central - PubMed

Affiliation: Department of Mechanical Engineering, National Yunlin University of Science and Technology, Douliou, Yunlin 64002, Taiwan. HoChao@yuntech.edu.tw

ABSTRACT
The paper presents a novel method for monitoring and estimating the depth of a laser-drilled hole using machine vision. Through on-line image acquisition and analysis in laser machining processes, we could simultaneously obtain correlations between the machining processes and analyzed images. Based on the machine vision method, the depths of laser-machined holes could be estimated in real time. Therefore, a low cost on-line inspection system is developed to increase productivity. All of the processing work was performed in air under standard atmospheric conditions and gas assist was used. A correlation between the cumulative size of the laser-induced plasma region and the depth of the hole is presented. The result indicates that the estimated depths of the laser-drilled holes were a linear function of the cumulative plasma size, with a high degree of confidence. This research provides a novel machine vision-based method for estimating the depths of laser-drilled holes in real time.

No MeSH data available.


Related in: MedlinePlus