Research on evaluating laser welding quality based on two-dimensional array ultrasonic probe

Zhou, Guanghao; Xu, Guangchen; Gu, Xiaopeng; Liu, Jing

doi:10.1007/s00170-015-8243-3

Cited by 11 publications

(4 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition to ordinary monitoring sensors, some special technologies can be used, such as on-line coherent imaging [60], X-ray diffractometer [61] and Hanover analyzer [62]. From the current research, the detection of laser welding process signal mainly focuses on sound, light, electricity and heat [63][64][65][66][67][68][69][70][71].…”

Section: Single Signal Monitoringmentioning

confidence: 99%

“…Zhou et al [67] studied the laser welding quality evaluation method based on twodimensional array ultrasonic probe, which is used to inspect the weld joint, analyzing the effect of fusion state on A-scan echo amplitude, and C-scan image of internal contact surface is established. Figure 1 shows schematic diagram of detection by two-dimensional array ultrasonic probe.…”

Section: Single Signal Monitoringmentioning

confidence: 99%

See 1 more Smart Citation

Innovations in Monitoring, Control and Design of Laser and Laser-Arc Hybrid Welding Processes

Cheng

Ning

et al. 2021

Metals

View full text Add to dashboard Cite

With the rapid development of high power laser, laser welding has been widely used in many fields including manufacturing, metallurgy, automobile, biomedicine, electronics, aerospace etc. Because of its outstanding advantages, such as high energy density, small weld size, easy automation. Combining the two heat sources of laser and arc for welding can achieve excellent results due to the synergistic effect. Laser welding is a complicated physical and chemical metallurgical process, involving the laser beam and molten pool, keyholes and materials melting, evaporation and multiple physical process. Process monitoring and quality control are important content of research and development in the field of laser welding, which is the premise to obtain fine weld with high quality. Numerical simulation technology can describe many complex physical phenomena in welding process, which is very important to predict weld forming and quality and clarify the underline mechanism. In this paper, the research progress of process monitoring, quality control and autonomous intelligent design of laser and laser-arc hybrid welding based on numerical simulation were reviewed, and the research hotspots and development trends of laser welding in the future are predicted.

show abstract

Section: Single Signal Monitoringmentioning

confidence: 99%

Section: Single Signal Monitoringmentioning

confidence: 99%

Innovations in Monitoring, Control and Design of Laser and Laser-Arc Hybrid Welding Processes

Cheng

Ning

et al. 2021

Metals

View full text Add to dashboard Cite

show abstract

“…Laser process: Seam tracking is a major issue in laser welding due to the small diameter of the laser beam. Typical signals to monitor a laser process are from sound, light, electricity and heat [217][218][219][220][221][222][223]. Lee and Na [220] developed a visual sensor without auxiliary light source and preview distance.…”

Section: Sensing and Controlmentioning

confidence: 99%

Advanced Welding Manufacturing: A Brief Analysis and Review of Challenges and Solutions

Zhang

Yang

Wei

et al. 2020

Journal of Manufacturing Science and Engineering

View full text Add to dashboard Cite

Welding is a major manufacturing process that joins two or more pieces of materials together through heating/mixing them followed by cooling/solidification. The goal of welding manufacturing is to join materials together to meet service requirements at lowest costs. Advanced welding manufacturing is to use scientific methods to realize this goal. This paper views advanced welding manufacturing as a three step approach: (1) pre-design that selects process and joint design based on available processes (properties, capabilities, and costs); (2) design that uses models to predict the result from a given set of welding parameters and minimizes a cost function for optimizing the welding parameters; (3) real-time sensing and control that overcome the deviations of welding conditions from their nominal ones used in optimizing the welding parameters by adjusting the welding parameters based on such real-time sensing and feedback control. The paper analyzes how these three steps depend on process properties/capabilities, process innovations, predictive models, numerical models for fluid dynamics, numerical models for structures, real-time sensing, and dynamic control. The paper also identifies the challenges in obtaining ideal solutions and reviews/analyzes the existing efforts toward better solutions. Special attention and analysis have been given to (1) gas tungsten arc welding (GTAW) and gas metal arc welding (GMAW) as benchmark processes for penetration and materials filling; (2) keyhole plasma arc welding (PAW), keyhole-tungsten inert gas (K-TIG), and keyhole laser welding as improved/capable penetrative processes; (3) friction stir welding (FSW) ......

show abstract

“…The post-process inspection methods include eddy current, ultrasonic, visual, or radiographic testing techniques [1][2][3][4][5][6][7]. But vision-based technique, including a 3D vision-based measuring approach under structured lighting, may be best suited to on-line inspection for welding joints than other methods, such as two-dimensional array ultrasonic detection [8] and X-ray testing [9] because they are expensive. These presented vision-based techniques can not be adopted directly to deal with the quality assessment for the Li- Based on many types of features extracted from multi-color solder joint images under tier lighting, classifier-based methods, such as support vector machine (SVM) by Wu [10], feature-based method, such as shape digital logistic(SDL) by Wu and Zhang [11], statistical modeling-based method, such as an improved visual background extraction (ViBe) by Cai [12], and deep learning-based method, were presented for IC solder joint inspection.…”

Section: Introductionmentioning

confidence: 99%

Non-destructive Inspection System Development for Secondary Battery Welding Part

Chun

2022

IJEEI

View full text Add to dashboard Cite

In this paper, we develop a non-destructive inspection system for secondary battery welding. In a secondary battery, when the insulation or separator of each electrode is damaged by an impact from the outside depending on the degree of welding, an internal short circuit occurs during charging and fires even if it does not ignite at that time. To detect this, a non-destructive AOI (Automatic Optical Inspection) system is developed that compares the inspection target with the reference image to determine whether there is a proper indentation in the welding part. The system consists of a precision alignment stage on the lower part and imaging equipment that performs AOI, a non-destructive inspection on the upper part. And the appropriate exposure, i.e., the aperture setting of the used camera, was confirmed through the experiment according to the position of the pole.

show abstract

Research on evaluating laser welding quality based on two-dimensional array ultrasonic probe

Cited by 11 publications

References 12 publications

Innovations in Monitoring, Control and Design of Laser and Laser-Arc Hybrid Welding Processes

Innovations in Monitoring, Control and Design of Laser and Laser-Arc Hybrid Welding Processes

Advanced Welding Manufacturing: A Brief Analysis and Review of Challenges and Solutions

Non-destructive Inspection System Development for Secondary Battery Welding Part

Contact Info

Product

Resources

About