Monitoring of Varying Joint Gap Width During Laser Beam Welding by a Dual Vision and Spectroscopic Sensing System

Nilsen, Morgan; Sikström, Fredrik; Christiansson, Anna-Karin; Ancona, Antonio

doi:10.1016/j.phpro.2017.08.014

Cited by 8 publications

(7 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Optical sensors have been significantly improved during the past years from simple sensors like photodiodes to advanced digital cameras [10], [11], [12]. So far, the most successful optical sensors are the ones that measure spatially integrated optical intensities such as spectrometers, which are capable to measure spectral ranges from gamma rays to microwaves [13], [14]. Spectral analysis is one of the most reliable methods in detecting spectrum from a plasma plume, which occurs due to high intensity power in laser processing [15].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Monitoring and Control of Ultra-Fast Laser Engraving Process Utilizing Spectrometer

et al. 2022

View full text Add to dashboard Cite

The objective of this study was to develop a novel real-time monitoring and control method for ultra-fast laser scribing processes utilizing spectrometer. Adjustment of laser process parameters such as laser power with high precision in real-time is critical in the laser engraving process due to the premium quality and speed requirements of the process. An online monitoring system was established using the Ocean Optics spectrometer, IPG ytterbium pulsed laser, and PXIe-8880 industrial computer. An algorithm for realtime control of the laser scribing process was developed based on the monitoring outcomes using LabVIEW® software. Experimental methods were performed to evaluate the reliability of the developed monitoring system and control algorithm. The sensitivity of the spectrometer was assessed by changing laser power, pulse length, and focal point position. A workpiece consisting of two different metals, including stainless steel SS304L and steel S355, was used to evaluate the performance of the developed algorithm when scribing moved from one material to another. Instant accurate setting of the laser power based on the variations in intensities of metals from 750 AU to 1400 AU validated the reliability of the algorithm.

show abstract

Section: Introductionmentioning

confidence: 99%

Real-Time Monitoring and Control of Ultra-Fast Laser Engraving Process Utilizing Spectrometer

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Spectrometers are considered in the classification of spectrally resolved techniques and are one the most successful optical sensors used for monitoring various laser processes by analyzing the radiation intensity of material [19], [24], [25]. They can measure a wide spectral range from gamma rays to microwaves; however, the monitored range generally encloses ultraviolet and visible wavelengths for laser material processing [16], [26], [27]. Characteristics such as sensitivity, ability to resolve lines, and path configurations distinguish spectrometers from each other.…”

Section: ) Spectrometermentioning

confidence: 99%

Design and Development of a Multisensory Real-Time Monitoring Platform for Ultrafast Laser Engraving Process

et al. 2022

View full text Add to dashboard Cite

Process online monitoring is a vital and integral part of high-speed laser scribing process in which speed and quality are paramount. In this study, a multi-sensory platform for real-time monitoring of the ultrafast pulsed laser engraving process has been developed. Four different sensors have been examined from various perspectives and the results have been analyzed and compared. The real-time monitoring system developed for this study consisted of IPG ytterbium pulsed fiber laser, scan head, illumination system, and four monitoring sensors, including a spectrometer, pyrometer, infrared (IR) camera, and high-speed camera. Various experiments were performed to evaluate the performance of the designed platform by applying each sensor to monitor a high-speed laser scribing process in real-time. The output of each sensor was analyzed by changing different laser and process parameters, such as laser power, focal position, beam speed, and pulse length. Strengths, weaknesses, and challenges of using each monitoring tool for the laser engraving process were discussed based on the obtained results.INDEX TERMS Laser scribing, Real-time monitoring, Spectrometer, High-speed camera, Infrared camera, Pyrometer.

show abstract

“…However, a combination of photo-diodes is necessary to cover the whole relevant spectral range. In a study conducted by Nilsen et al [ 24 ], a dual vision and spectroscopic sensing system was employed to monitor a varying joint gap during LBW. Image processing techniques followed by Kalman filter were used to estimate the gap width, using the data captured by a CMOS camera.…”

Section: Introductionmentioning

confidence: 99%

Beam Offset Detection in Laser Stake Welding of Tee Joints Using Machine Learning and Spectrometer Measurements

Jadidi

Sikström

et al. 2022

Sensors

Self Cite

View full text Add to dashboard Cite

Laser beam welding offers high productivity and relatively low heat input and is one key enabler for efficient manufacturing of sandwich constructions. However, the process is sensitive to how the laser beam is positioned with regards to the joint, and even a small deviation of the laser beam from the correct joint position (beam offset) can cause severe defects in the produced part. With tee joints, the joint is not visible from top side, therefore traditional seam tracking methods are not applicable since they rely on visual information of the joint. Hence, there is a need for a monitoring system that can give early detection of beam offsets and stop the process to avoid defects and reduce scrap. In this paper, a monitoring system using a spectrometer is suggested and the aim is to find correlations between the spectral emissions from the process and beam offsets. The spectrometer produces high dimensional data and it is not obvious how this is related to the beam offsets. A machine learning approach is therefore suggested to find these correlations. A multi-layer perceptron neural network (MLPNN), support vector machine (SVM), learning vector quantization (LVQ), logistic regression (LR), decision tree (DT) and random forest (RF) were evaluated as classifiers. Feature selection by using random forest and non-dominated sorting genetic algorithm II (NSGAII) was applied before feeding the data to the classifiers and the obtained results of the classifiers are compared subsequently. After testing different offsets, an accuracy of 94% was achieved for real-time detection of the laser beam deviations greater than 0.9 mm from the joint center-line.

show abstract

Monitoring of Varying Joint Gap Width During Laser Beam Welding by a Dual Vision and Spectroscopic Sensing System

Cited by 8 publications

References 14 publications

Real-Time Monitoring and Control of Ultra-Fast Laser Engraving Process Utilizing Spectrometer

Real-Time Monitoring and Control of Ultra-Fast Laser Engraving Process Utilizing Spectrometer

Design and Development of a Multisensory Real-Time Monitoring Platform for Ultrafast Laser Engraving Process

Beam Offset Detection in Laser Stake Welding of Tee Joints Using Machine Learning and Spectrometer Measurements

Contact Info

Product

Resources

About