Optical Cutting Interruption Sensor for Fiber Lasers

Adelmann, Benedikt; Schleier, Max; Neumeier, B.; Wilmann, Eugen; Hellmann, Ralf

doi:10.3390/app5030544

Cited by 8 publications

(3 citation statements)

References 14 publications

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“…Also for cut interruption detection, most approaches are based on photodiode signals or camera images. Photodiode-based methods for cut interruption detection are signal threshold-based [ 10 ], done by the comparison of different photodiodes [ 11 ] or based on cross-correlations [ 12 ]. However, all those methods have the disadvantage of requiring thresholds that vary with the sheet thickness or laser parameters.…”

Section: Introductionmentioning

confidence: 99%

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

Adelmann

Hellmann

2021

Sensors

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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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Section: Introductionmentioning

confidence: 99%

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

Adelmann

Hellmann

2021

Sensors

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“…Less work was reported in cut interruptions or quality detection by photodiodes or visual monitoring. Authors developed algorithms based on single or dual photodiodes for laser cutting monitoring, detecting successfully cut interruptions in cuts of stainless steel, mild steel, and aluminum [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Influence of Process Parameters in Laser Piercing

Garcia¹,

Ramos²,

Lamíkiz

et al. 2019

Applied Sciences

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This work addresses the analysis of the influence of process parameters in laser piercing for mild steel, stainless steel, and aluminum thick sheets, carried out by the monitorization of the signal with a photodiode installed coaxially in the cutting head. The sensor captures the infrared or visible signal emitted during the piercing. The relationship between the intensity of the signal and the parameter values was analyzed, distinguishing between soft and fast piercings. The results permit the optimization of the piercing strategy with a reduction of 25% in time and the possibility of establishing a threshold to control the piercing process. This study reveals the importance of knowing parameter dependencies with the process results and highlights the potential of monitorization systems in laser cutting to improve the piercing duration and avoid wasting time during production.

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“…New powerful brilliant laser sources allow very high cutting velocities and process monitoring devices face new challenges due to the process dynamics and the large number of parameters involved during laser material processing [1]. Different approaches in monitoring the quality of laser cuts have been evaluated by various groups [2], [3], [4]. A promising approach is the measurement of the emitted thermal radiation out of the cut kerf, with the opportunity to observe the laser cut coaxially to the optical path of the processing laser beam.…”

Section: Introductionmentioning

confidence: 99%

Polarisation Measurement of the Emitted Thermal Radiation During Laser Material Processing

Humenberger¹,

Liedl²,

Bammer³

et al. 2018

Proceedings of the 29th International DAAAM Symposium 2018

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We present a new approach for quality control in laser material processing. By means of an active optical element (SCPEM -Single Crystal PhotoElastic Modulator) the emitted thermal radiation from the interaction zone of the focused laser radiation with the material surface is to be detected in order to determine a correlation to the process parameters from the polarisation state of the radiation. Due to the dependence of polarised radiation on the emission angle, the inclination of the interaction zone in the observed area can be deduced. For this purpose, an optomechanical setup for measuring two orthogonal polarisation directions of the emitted thermal radiation has been developed and a data acquisition system has been implemented. The amplitudes of two orthogonal polarisation directions could be determined from the signal modulated by the SCPEM during tests on different experimental setups. From the ratio of these polarisation components, emission angles can be derived using the Fresnel equations.

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Optical Cutting Interruption Sensor for Fiber Lasers

Cited by 8 publications

References 14 publications

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

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

Influence of Process Parameters in Laser Piercing

Polarisation Measurement of the Emitted Thermal Radiation During Laser Material Processing

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