Fiber laser performance in industrial applications

2013 ◽  
Author(s):  
S. McCulloch ◽  
A. Hassey ◽  
P. Harrison
Keyword(s):  
Fiber Laser ◽  
Industrial Applications ◽  
Laser Performance

Enhancing Q-Switched Fiber Laser Performance Based on Reverse Saturable and Saturable Absorption Properties of CuCrO2 Nanoparticle-Polyimide Films

2021 ◽  
Author(s):  
Yingtian Xu ◽  
Hanfei Hu ◽  
Hongda Wu ◽  
Chongyang Xu ◽  
He Zhang ◽  
...  
Keyword(s):  
Fiber Laser ◽  
Saturable Absorption ◽  
Polyimide Films ◽  
Absorption Properties ◽  
Laser Performance

100 kW CW fiber laser for industrial applications

2014 ◽  
Author(s):  
V. Fomin ◽  
V. Gapontsev ◽  
E. Shcherbakov ◽  
A. Abramov ◽  
A. Ferin ◽  
...  
Keyword(s):  
Fiber Laser ◽  
Industrial Applications

scholarly journals On multi-sensor monitoring of fiber laser fusion cutting

2021 ◽  
Vol 1135 (1) ◽  
pp. 012014
Author(s):  
Nikita Levichev ◽  
Joost R. Duflou
Keyword(s):  
Fiber Laser ◽  
Monitoring System ◽  
Laser Cutting ◽  
High Speed ◽  
Process Zone ◽  
Industrial Process ◽  
Industrial Applications ◽  
Laser Fusion ◽  
Thick Plates ◽  
Sensor Monitoring

Abstract Laser cutting is a well-established industrial process for sheet metal applications. However, cutting thick plates is still accompanied by problems because of the characteristic limited process parameter window. Since cutting by means of fiber lasers has become dominant, tailored solutions are required in such systems for industrial applications. The development of a robust real-time monitoring system, which adapts the process parameters according to a specific quality requirement, implies a significant step forward towards automated laser cutting and increases the process robustness and performance. In this work, a coaxial multi-sensor monitoring system is tested for fiber laser cutting of stainless steel thick plates. A high-speed camera and a photodiode sensor have been selected for this investigation. Experiments at different cutting speeds, representing primary cut quality cases, have been conducted and various features of the obtained process zone signals have been examined. Finally, the feasibility of industrial application of the developed setup for high-power fiber laser cutting is discussed, followed by several implementation recommendations.

Research on Fiber Laser Performance Working at Different Temperatures

2015 ◽  
Vol 42 (s1) ◽  
pp. s102004
Author(s):  
杜雪原 Du Xueyuan ◽  
粟荣涛 Su Rongtao ◽  
王小林 Wang Xiaolin ◽  
周朴 Zhou Pu
Keyword(s):  
Fiber Laser ◽  
Laser Performance ◽  
Different Temperatures

Comparison of Tm-doped fiber laser performance as diode pumped at 800 nm and 1620 nm

2018 ◽  
Author(s):  
G. Alex Newburgh ◽  
Jun Zhang ◽  
Mark Dubinskii
Keyword(s):  
Fiber Laser ◽  
Laser Performance ◽  
Diode Pumped

Spectroscopy And Laser Performance Of A Pulsed Tm:Germanate Fiber Laser

2006 ◽  
Author(s):  
Norman P. Barnes ◽  
Brian M. Walsh ◽  
Donald J. Reichle ◽  
Shibin Jiang
Keyword(s):  
Fiber Laser ◽  
Laser Performance

Compact reliable fiber laser systems for industrial applications

1998 ◽  
Author(s):  
A. Galvanauskas ◽  
D. J. Harter ◽  
M. E. Fermann ◽  
A. Hariharan
Keyword(s):  
Fiber Laser ◽  
Industrial Applications ◽  
Laser Systems

scholarly journals Effect of Erbium Doped Fiber location on double spacing multi-wavelength Brillouin-Erbium fiber laser performance

2012 ◽  
Author(s):  
B. A. Ahmad ◽  
Gh. Mamdoohi ◽  
A. F. Abas ◽  
M. Mokhtar ◽  
M. A. Mahdi
Keyword(s):  
Fiber Laser ◽  
Laser Performance ◽  
Erbium Doped ◽  
Multi Wavelength

scholarly journals Simultaneous Burr and Cut Interruption Detection during Laser Cutting with Neural Networks

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5831
Author(s):  
Benedikt Adelmann ◽  
Ralf Hellmann
Keyword(s):  
Neural Networks ◽  
Fiber Laser ◽  
Convolutional Neural Networks ◽  
Laser Cutting ◽  
Single Mode ◽  
Industrial Applications ◽  
Single Mode Fiber ◽  
Burr Formation ◽  
The Neural Network ◽  
Failure Classification

In this contribution, we compare basic neural networks with convolutional neural networks for cut failure classification during fiber laser cutting. The experiments are performed by cutting thin electrical sheets with a 500 W single-mode fiber laser while taking coaxial camera images for the classification. The quality is grouped in the categories good cut, cuts with burr formation and cut interruptions. Indeed, our results reveal that both cut failures can be detected with one system. Independent of the neural network design and size, a minimum classification accuracy of 92.8% is achieved, which could be increased with more complex networks to 95.8%. Thus, convolutional neural networks reveal a slight performance advantage over basic neural networks, which yet is accompanied by a higher calculation time, which nevertheless is still below 2 ms. In a separated examination, cut interruptions can be detected with much higher accuracy as compared to burr formation. Overall, the results reveal the possibility to detect burr formations and cut interruptions during laser cutting simultaneously with high accuracy, as being desirable for industrial applications.

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