Penetration-depth control in a remote laser-welding system based on an optical triangulation loop

Kos, Matjaž; Arko, Erih; Kosler, Hubert; Jezeršek, Matija

doi:10.1016/j.optlaseng.2020.106464

Cited by 6 publications

(5 citation statements)

References 32 publications

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“… [ 83 ] 2021 Triangulation Laser power is controlled via triangulation camera in a remote laser welding system. [ 84 ] 2020 Triangulation A data acquisition system is assembled based on differential laser triangulation method. [ 85 ] 2017 Laser scanning The accuracy of monocular depth estimation is improved by introducing 2D plane observations from the remaining laser rangefinder without any additional cost.…”

Section: Depth Perception Methods Based On Computer Visionmentioning

confidence: 99%

“…Triangulation method—a distance measurement technique based on the principles of triangulation. Unlike other methods that require precise sensors, it has a lower overall cost [ 83 , 84 , 85 ]. At short distances, the triangulation method can provide high accuracy, making it widely used in consumer and commercial products such as robotic vacuum cleaners.…”

Section: Depth Perception Methods Based On Computer Visionmentioning

confidence: 99%

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Visual Sensing and Depth Perception for Welding Robots and Their Industrial Applications

Wang,

Li,

2023

Sensors

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With the rapid development of vision sensing, artificial intelligence, and robotics technology, one of the challenges we face is installing more advanced vision sensors on welding robots to achieve intelligent welding manufacturing and obtain high-quality welding components. Depth perception is one of the bottlenecks in the development of welding sensors. This review provides an assessment of active and passive sensing methods for depth perception and classifies and elaborates on the depth perception mechanisms based on monocular vision, binocular vision, and multi-view vision. It explores the principles and means of using deep learning for depth perception in robotic welding processes. Further, the application of welding robot visual perception in different industrial scenarios is summarized. Finally, the problems and countermeasures of welding robot visual perception technology are analyzed, and developments for the future are proposed. This review has analyzed a total of 2662 articles and cited 152 as references. The potential future research topics are suggested to include deep learning for object detection and recognition, transfer deep learning for welding robot adaptation, developing multi-modal sensor fusion, integrating models and hardware, and performing a comprehensive requirement analysis and system evaluation in collaboration with welding experts to design a multi-modal sensor fusion architecture.

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Section: Depth Perception Methods Based On Computer Visionmentioning

confidence: 99%

Section: Depth Perception Methods Based On Computer Visionmentioning

confidence: 99%

Visual Sensing and Depth Perception for Welding Robots and Their Industrial Applications

Wang,

Li,

2023

Sensors

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“…However, it was identified that the electron temperature is sensitive to the experimental setup and must be thoroughly calibrated before executing the experiment. Kos et al [22] correlated camera images of the interaction zone with the weld depth. Linear behavior of the weld depth was shown for a partially penetrating process during remote laser beam welding.…”

Section: Process Control In Deep Penetration Laser Beam Weldingmentioning

confidence: 99%

Inline Weld Depth Evaluation and Control Based on OCT Keyhole Depth Measurement and Fuzzy Control

et al. 2022

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In an industrial joining process, exemplified by deep penetration laser beam welding, ensuring a high quality of welds requires a great effort. The quality cannot be fully established by testing, but can only be produced. The fundamental requirements for a high weld seam quality in laser beam welding are therefore already laid in the process, which makes the use of control systems essential in fully automated production. With the aid of process monitoring systems that can supply data inline to a production process, the foundation is laid for the efficient and cycle-time-neutral control of welding processes. In particular, if novel, direct measurement methods, such as Optical Coherence Tomography, are used for the acquisition of direct geometric quantities, e.g., the weld penetration depth, a significant control potential can be exploited. In this work, an inline weld depth control system based on an OCT keyhole depth measurement is presented. The system is capable of automatically executing an inline control of the deep penetration welding process based only on a specified target weld depth. The performance of the control system was demonstrated on various aluminum alloys and for different penetration depths. In addition, the ability of the control to respond to unforeseen external disturbances was tested. Within the scope of this work, it was thus possible to provide an outlook on future developments in the field of laser welding technology, which could develop in the direction of an intuitive manufacturing process. This objective should be accomplished through the use of intelligent algorithms and innovative measurement technology—following the example of laser beam cutting, where the processing systems themselves have been provided with the ability to select suitable process parameters for several years now.

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“…Recent results show that monitoring and control of the laser power during the adaptive 3D beam positioning can achieve a stable welding process and improved weld quality. [3][4][5] Chianese et al 6 investigated the use of photodiodes for the detection of variations in the part-to-part gap and weld penetration depth during RLW of Cu-to-steel for battery tab connectors. Findings showed a strong correlation between the plasma signal and both part-to-part gap and weld penetration depth.…”

Section: Introductionmentioning

confidence: 99%

Fusing optical coherence tomography and photodiodes for diagnosis of weld features during remote laser welding of copper-to-aluminum

Brežan

Franciosa

Jezeršek

et al. 2023

Journal of Laser Applications

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This study has been designed to investigate whether variations in the features of laser weldments can be isolated and diagnosed by fusing photodiodes and optical coherence tomography (OCT). Two manufacturing scenarios (variation in laser power and focal offset) have been considered during remote laser welding of 0.2 mm thick Cu foils on 2 mm thick Al 1050 plates with an adjustable ring mode laser integrated with a 1D oscillation head. The process was monitored by measuring weld penetration depth with OCT and by process emissions (plasma and back-reflection) via photodiodes. The acquisition frequency of all signals was 40 kHz. Strong correlations (r > 0.75) were shown between plasma, back-reflection, and OCT signals and measured depth and width of the weld. Weak correlations (r < 0.5) between voids, cracks, and sensor signals were observed. Although plasma is the predominant signal that carries most of the information about the process, and the OCT allows direct measurement of the penetration depth, their integration reached 87% classification accuracy of the tested welding scenarios. The main misclassification was observed between “good weld” and “over weld,” defined by the measured weld depth. Sensor fusion strategies with manufacturing implications are discussed throughout the paper.

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Penetration-depth control in a remote laser-welding system based on an optical triangulation loop

Cited by 6 publications

References 32 publications

Visual Sensing and Depth Perception for Welding Robots and Their Industrial Applications

Visual Sensing and Depth Perception for Welding Robots and Their Industrial Applications

Inline Weld Depth Evaluation and Control Based on OCT Keyhole Depth Measurement and Fuzzy Control

Fusing optical coherence tomography and photodiodes for diagnosis of weld features during remote laser welding of copper-to-aluminum

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