Hybrid laser-double-arc welding (HLDAW) is an efficient welding method with multi-heat sources comprised of two arcs and a laser beam, which is an intricate process with much randomness and uncertainty due to the mutual effect between multi-plasmas. Compared with double-arc welding (DAW), HLDAW can generally obtain a more stable welding process and deeper weld penetration, which is directly affected by the synergistic effect of multiple heat sources; however, the mechanism has not been systematically studied. In this study, the multi-information analysis method is adopted to study the distribution of electron temperatures, electron densities and electrical conductivity of double-arc welding (DAW) and HLDAW by utilizing synchronous radiation spectrum, high-speed photography and electrical signal sensing technology. The results indicated that the high concentration of charged particles provided a conductive channel for the two arcs to achieve a more stable welding process in HLDAW. The synergy between the laser and the arc changed the flow mode of the weld pool, which facilitated the molten metal flowing toward the bottom of the molten pool. Obtaining the same melting depth, the line energy input of HLDAW was 13% lower than that of DAW; the heat affected zone is narrower and the grain size is smaller. The weld penetration depth was improved in HLDAW, which was 1.8 times that of DAW and 1.5 times that of pure laser welding under the laser power of 1.5 kW. The weld penetration of HLDAW increased with laser power.
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http://dx.doi.org/10.3390/ma12244207 | DOI Listing |
Sensors (Basel)
November 2024
School of Automobile and Transportation Engineering, Guangdong Polytechnic Normal University, Guangzhou 510632, China.
It is difficult to detect and identify natural defects in welded components. To solve this problem, according to the Faraday magneto-optical (MO) effect, a nondestructive testing system for MO imaging, excited by an alternating magnetic field, is established. For the acquired MO images of crack, pit, lack of penetration, gas pore, and no defect, Gaussian filtering, bilateral filtering, and median filtering are applied for image preprocessing.
View Article and Find Full Text PDFSensors (Basel)
November 2024
School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510640, China.
K-TIG welding offers the advantages of single-sided welding and double-sided formation, making it widely used for medium/thick-plate welding. The welding quality of K-TIG is closely linked to its penetration state. However, the assembly gap in medium/thick-plate workpieces can easily result in an unstable penetration state.
View Article and Find Full Text PDFJ Neurosurg Case Lessons
December 2024
Department of Neurosurgery, Hendrick Medical Center, Abilene, Texas.
Background: Transorbital penetrating brain injury (PBI) accompanied by electrical injury is an extremely rare presentation. This type of traumatic injury has a unique set of diagnostic and therapeutic challenges due to the potential multiple organ system involvement and severe neurological complications.
Observations: A 50-year-old male experienced a high-impact injury from a welding spike that penetrated the orbit just above the eyeball with a concurrent electrical injury; the electricity exited through the great toe.
Small
January 2025
State Key Laboratory of Precision Welding & Joining of Materials and Structures, Institute for Advanced Ceramics, Key Laboratory of Advanced Structure-Function Integrated Materials and Green Manufacturing Technology, Harbin Institute of Technology, Harbin, 150080, China.
Most thermal barrier coating materials exhibit transparent/semi-transparent properties at higher temperatures, causing the surface heat flow to directly heat the substrate with infrared radiation, which significantly reduces the thermal barrier effectiveness. Herein, composite ceramic materials composed of GdFeO diffusely dispersed within the GdTaO are produced. Specifically, the 0.
View Article and Find Full Text PDFPLoS One
November 2024
School of Mechatronic Engineering and Automation, Foshan University, Foshan, Guangdong, China.
Arc sound signals are considered appropriate for detecting penetration states in cold metal transfer (CMT) welding because of their noninvasive nature and immunity to interference from splatter and arc light. Nevertheless, the stability of arc sound signals is suboptimal, the conventional feature extraction methods are inefficient, and the significance of arc sound attributes for determining penetration statuses is often overlooked. In this study, a compact convolutional neural network (CNN) model is proposed for the adaptive extraction of features from arc sound signals.
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