Work

Computer Vision-Based Adhesion Quality Inspection Model for Exterior Insulation and Finishing System

Year: 2024

Type: article

Abstract: The adhesion quality is one of the critical factors affecting EIFS quality. The traditional visual inspection method is time-consuming and labor-intensive work because limited inspectors have to check all insulation units when they are installed. Thus, this study proposes a CV-based automatic adhesion quality-inspection model for EIFS that can quickly and quantitatively inspect the shape and amount of adhesive. In the case study, the proposed models accurately determined the adhesion quality with measurement accuracies of 90.58%, 95.28%, and 93.58% in ribbon width, dab diameter, and adhesive area, respectively, and a root mean-square error of 6.9 mm in dab distance. The results of this study can achieve automation of inspection for EIFS.

Source: Applied Sciences

DOI: 10.3390/app15010125

Authors: Mingyun Kang, Sebeen Yoon, Taehoon Kim

Institution: Seoul National University of Science and Technology

Language: English

Topic: Industrial Vision Systems and Defect Detection

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,728