Harbin Engineering University

About: Harbin Engineering University is a education organization based out in Harbin, Heilongjiang, China. It is known for research contribution in the topics: Control theory & Computer science. The organization has 31149 authors who have published 27940 publications receiving 276787 citations. The organization is also known as: HEU.

Patterning of YVO4:Eu3+ Luminescent Films by Soft Lithography

Abstract: Ordered arrays of luminescent YVO4:Eu3+ films with square (side length 19.17 ± 2.05 μm) and dot (diameter 11.20 ± 1.82 μm) patterns were fabricated by two kinds of soft lithography processes, namely, microtransfer molding (μTM) and microcontact printing (μCP), respectively. Both soft-lithography processes utilize a PDMS elastomeric mold as the stamp combined with a Pechini-type sol-gel process to produce luminescent patterns on quartz plates, in which a YVO4:Eu3+ precursor solution was employed as ink. The ordered luminescent YVO4:Eu3+ patterns are revealed by optical micro­scopy and their microstructure, consisting of nanometer-scale particles, is unveiled by scanning electronic microscopy (SEM) observations. Additionally, photoluminescence (PL) and cathodoluminescence (CL) were carried out to characterize the patterned YVO4:Eu3+ samples. A strong red emission as a result of 5D0–7F2 transition of Eu3+ was observed under UV-light or electron-beam excitation, which implies that combining soft lithography with a Pechini-type sol-gel route has potential for fabricating rare-earth luminescent pixels for next-generation field-emission display devices.

A vision-based system for post-welding quality measurement and defect detection

Abstract: The measurement of the welding bead and the followed evaluation of the weld quality is an important part in the industrial welding. However, the main difficulty in using visual inspection to evaluate the weld quality is the time taken and labor wasted. In order to solve these problems, an automated vision-based system is presented for non-destructive and online post-welding quality inspection. The trouble with respect to vision-based system is the robustness of image processing algorithms. This paper presents a novel image processing method that can automatically extract the weld joint profile and feature points, measure the weld bead size, and detect defects. At the same time, the three-dimensional (3D) profile of the weld surface can be reconstructed with the aim of monitoring the weld quality online. The proposed algorithm is validated through experiment in industrial environment.