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

2021 ◽  
Vol 1135 (1) ◽  
pp. 012014
Author(s):  
Nikita Levichev ◽  
Joost R. Duflou

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.

2014 ◽  
Vol 26 (4) ◽  
pp. 042004 ◽  
Author(s):  
Grigory V. Ermolaev ◽  
Petr V. Yudin ◽  
Francis Briand ◽  
Alexandr V. Zaitsev ◽  
Oleg B. Kovalev

2017 ◽  
Vol 94 ◽  
pp. 244-247 ◽  
Author(s):  
Jae Sung Shin ◽  
Seong Yong Oh ◽  
Hyunmin Park ◽  
Chin-Man Chung ◽  
Sangwoo Seon ◽  
...  

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5831
Author(s):  
Benedikt Adelmann ◽  
Ralf Hellmann

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.


2016 ◽  
Vol 854 ◽  
pp. 237-242
Author(s):  
Andreas Wetzig ◽  
Jan Hauptmann ◽  
Patrick Herwig ◽  
Eckhard Beyer ◽  
Wieland Bundschuh ◽  
...  

Laser cutting is introduced as an alternative technique to manufacture typical metallic punching and bending parts. Assets and drawbacks of high speed laser cutting technologies like Remote Laser Cutting and laser fusion cutting by means of a high dynamic form cutter are discussed. Finally, the concept of the world´s first industrial inline reel to reel laser cutting machine for metal strips is presented.


2021 ◽  
Vol 136 ◽  
pp. 106743
Author(s):  
Nikita Levichev ◽  
Gonçalo Costa Rodrigues ◽  
Vitalii Vorkov ◽  
Joost R. Duflou

2005 ◽  
Vol 6-8 ◽  
pp. 809-816 ◽  
Author(s):  
Johan De Keuster ◽  
Joost R. Duflou ◽  
Jean Pierre Kruth

Laser cutting is a well-established sheet metal processing method. Nowadays a trend towards the cutting of thick plates (> 15 mm) can be observed. However for these thick plates the process window in which good cutting results can be obtained is more narrow compared to that for thin sheets due to the very difficult balance to be found between the different process parameters. Even after determination of the process window, a good cutting quality cannot always be guaranteed. Therefore cutting of thick plates is still characterized by a large scrap percentage, which impedes a breakthrough to large scale industrial use. A solution to this problem is to incorporate a sensor system in the laser cutting machine that monitors the cut quality on-line. This monitoring system could then be integrated in a process control system, which adapts the process parameters in function of the observed cut quality in real time. In this way a good cut quality could always be guaranteed. In this study, the first step in this direction, the determination of an appropriate monitoring system, is dealt with. The applicability for monitoring purposes of two types of sensors is investigated: a microphone and a photodiode. For both types, correlation between the sensor output and the cut quality is investigated in a qualitative way. The scope of the reported research was not limited to contour cutting, also piercing is covered in the study.


Procedia CIRP ◽  
2020 ◽  
Vol 94 ◽  
pp. 499-504 ◽  
Author(s):  
Nikita Levichev ◽  
Gonçalo Costa Rodrigues ◽  
Joost R. Duflou

2000 ◽  
Vol 627 ◽  
Author(s):  
Gabriel Popescu ◽  
Aristide Dogariu

ABSTRACTIn many industrial applications involving granular media, knowledge about the structural transformations suffered during the industrial process is desirable. Optical techniques are noninvasive, fast, and versatile tools for monitoring such transformations. We have recently introduced optical path-length spectroscopy as a new technique for random media investigation. The principle of the method is to use a partially coherent source in a Michelson interferometer, where the fields from a reference mirror and the sample are combined to obtain an interference signal. When the system under investigation is a multiple-scattering medium, by tuning the optical length of the reference arm, the optical path-length probability density of light backscattered from the sample is obtained. This distribution carries information about the structural details of the medium. In the present paper, we apply the technique of optical path-length spectroscopy to investigate inhomogeneous distributions of particulate dielectrics such as ceramics and powders. The experiments are performed on suspensions of systems with different solid loads, as well as on powders and suspensions of particles with different sizes. We show that the methodology is highly sensitive to changes in volume concentration and particle size and, therefore, it can be successfully used for real-time monitoring. In addition, the technique is fiber optic-based and has all the advantages associated with the inherent versatility.


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