Contact Printing Based on Meniscus Vibration.

Utilizing the residual droplet produced from liquid bridge breakup for microdroplet deposition serves as an important supplementary method to conventional printing techniques. However, this approach typically relies on mechanical motion to form and break the liquid bridge between the liquid donor and acceptor surfaces, resulting in a relatively complex process and low printing efficiency (typically limited to several Hertz). Here, we propose a novel contact printing method based on the meniscus vibration (MVCP).

Humping Formation and Suppression in High-Speed Laser Welding.

Increasing welding speed can promote the productivity of laser welding. However, humping defects often occur, which limits the application of this strategy. The existing explanations for the humping formation remain vague, and mitigation and suppression methods are limited.

Multi-Output Monitoring of High-Speed Laser Welding State Based on Deep Learning.

In order to ensure the production quality of high-speed laser welding, it is necessary to simultaneously monitor multiple state properties. Monitoring methods combining vision sensing and deep learning models are popular but most models used can only make predictions on single welding state property. In this contribution, we propose a multi-output model based on a lightweight convolutional neural network (CNN) architecture and introduce the particle swarm optimization (PSO) technique to optimize the loss function of the model, to simultaneously monitor multiple state properties of high-speed laser welding of AISI 304 austenitic stainless steel.

Research on the Weld Position Detection Method for Sandwich Structures from Face-Panel Side Based on Backscattered X-ray.

Web-core sandwich panels are a typical lightweight structure utilized in a variety of fields, such as naval, aviation, aerospace, etc. Welding is considered as an effective process to join the face panel to the core panel from the face panel side. However, it is difficult to locate the joint position (i.

A Vision Based Detection Method for Narrow Butt Joints and a Robotic Seam Tracking System.

Automatic joint detection is of vital importance for the teaching of robots before welding and the seam tracking during welding. For narrow butt joints, the traditional structured light method may be ineffective, and many existing detection methods designed for narrow butt joints can only detect their 2D position. However, for butt joints with narrow gaps and 3D trajectories, their 3D position and orientation of the workpiece surface are required.

In-Process Monitoring of Lack of Fusion in Ultra-Thin Sheets Edge Welding Using Machine Vision.

Lack of fusion can often occur during ultra-thin sheets edge welding process, severely destroying joint quality and leading to seal failure. This paper presents a vision-based weld pool monitoring method for detecting a lack of fusion during micro plasma arc welding (MPAW) of ultra-thin sheets edge welds. A passive micro-vision sensor is developed to acquire clear images of the mesoscale weld pool under MPAW conditions, continuously and stably.