Analysis of spatters in laser welding with beam oscillation: A machine vision approach

Schweier, M.; Haubold, Martin; Zaeh, Michael F.

doi:10.1016/j.cirpj.2016.05.004

Cited by 29 publications

(7 citation statements)

References 16 publications

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“…There are different mechanical and geometrical parameters which are investigated by researchers. According to the results reported by Schweier et al [1] there are three mechanisms of spatter formation in the laser welding process. These spatter formations are caused by material ablation, by laser spot entry into the melting spot and by dynamics of melt spot.…”

Section: Introductionmentioning

confidence: 94%

“…ANFIS structureThe fuzzy IF-THEN rules of Takagi and Sugeno's class and two inputs for the first-order Sugeno are employed for the purposes of this study: if x is A and y is C then f 1 =p 1 x+q 1 y+r 1(1) The first layer is made up of input parameters MFs, and it provides input values to the following layer. Each node here is considered as an adaptive node having a node function O= AB (x) and O= CD (x) where  AB (x) and  CD (x) are membership functions.…”

mentioning

confidence: 99%

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Parameters Forecasting of Laser Welding by the Artificial Intelligence Techniques

Nikolić¹,

Milovančević²,

Petković³

et al. 2018

FU Mech Eng

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Laser welding process is used in many industrial sectors. One of the most important aspects of the laser welding quality refers to the geometrical and mechanical properties of welding joints. In order to develop optimal conditions for the laser welding process it is desirable to know in advance which machining parameters to select. Though there are manuals which recommend specific parameters combinations for the desired laser welding quality it is difficult to cover all possible combinations because of the process nonlinearity. Therefore, in this study the main aim is to establish an algorithm for optimal parameters forecasting of the laser welding process. The algorithm is based on an artificial intelligence approach. The main goal is to forecast the geometrical parameters of the welding joints like front width, front heights, back width and back heights of the welding joints. Experimental process was performed in order to acquire training and testing data of the laser welding process. The obtained results could be of practical importance for engineers in industry.

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Section: Introductionmentioning

confidence: 94%

mentioning

confidence: 99%

Parameters Forecasting of Laser Welding by the Artificial Intelligence Techniques

Nikolić¹,

Milovančević²,

Petković³

et al. 2018

FU Mech Eng

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show abstract

“…However, spatter formation is still an issue in welding. Schweier et al [30] developed a machine vision system for tracking spatter using highspeed cameras. In recent years, machine vision has also been applied for object detection and size measurement in grinding or harvesting robots [31,32].…”

Section: Guaranteeing Filling Rate Of Diamond Grits In Segmentmentioning

confidence: 99%

Blade Segment with a 3D Lattice of Diamond Grits Fabricated via an Additive Manufacturing Process

Chen

Huang

et al. 2020

Chin. J. Mech. Eng.

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Diamond tools with orderly arrangements of diamond grits have drawn considerable attention in the machining field owing to their outstanding advantages of high sharpness and long service life. This diamond super tool, as well as the manufacturing equipment, has been unavailable to Chinese enterprises for a long time due to patents. In this paper, a diamond blade segment with a 3D lattice of diamond grits was additively manufactured using a new type of cold pressing equipment (AME100). The equipment, designed with a rotary working platform and 16 molding stations, can be used to additively manufacture segments with diamond grits arranged in an orderly fashion, layer by layer; under this additive manufacturing process, at least 216000 pcs of diamond green segments with five orderly arranged grit layers can be produced per month. The microstructure of the segment was observed via SEM and the diamond blade fabricated using these segments was compared to other commercial cutting tools. The experimental results showed that the 3D lattice of diamond grits was formed in the green segment. The filling rate of diamond grits in the lattice could be guaranteed to be above 95%; this is much higher than the 90% filling rate of the automatic array system (ARIX). When used to cut stone, the cutting amount of the blade with segments made by AME100 is two times that of ordinary tools, with the same diamond concentration. When used to dry cut reinforced concrete, its cutting speed is 10% faster than that of ARIX. Under wet cutting conditions, its service life is twice that of ARIX. By applying the machine vision online inspection system and a special needle jig with a negative pressure system, this study developed a piece of additive manufacturing equipment for efficiently fabricating blade segments with a 3D lattice of diamond grits.

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“…However, a high-power galvanometer scanner was developed and widely used for laser beam oscillation due to its high frequency and high flexibility. Currently, laser welding with beam oscillation is applied widely in remote laser welding for its good weldability [19][20][21][22]. The primary cause of good weldability with an oscillating beam is the dilution degree of the melt pool.…”

Section: Introductionmentioning

confidence: 99%

Microstructure and Mechanical Properties of Fiber Laser Welding of Aluminum Alloy with Beam Oscillation

et al. 2019

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Laser welding with beam oscillation is applied to join aluminum alloy plates in butt configuration. The effects of beam oscillating patterns on the quality of welds are compared and analyzed. The results indicate that beam oscillation can improve the weld formation and microstructure of butt joints. The circular oscillating weld has the features of fine grain and uniformly dispersed dendrites in the strengthening phase, and the porosity inhibitory effect of circular oscillation is the most obvious. In addition, beam oscillation has few effects on the tensile strength of welds, but exerts an influence on the elongation of welds.

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Analysis of spatters in laser welding with beam oscillation: A machine vision approach

Cited by 29 publications

References 16 publications

Parameters Forecasting of Laser Welding by the Artificial Intelligence Techniques

Parameters Forecasting of Laser Welding by the Artificial Intelligence Techniques

Blade Segment with a 3D Lattice of Diamond Grits Fabricated via an Additive Manufacturing Process

Microstructure and Mechanical Properties of Fiber Laser Welding of Aluminum Alloy with Beam Oscillation

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