Work

A Metrologically Validated Cost-Effective Solution for Laboratory Measurement of Long-Term Deformations in Construction Materials

Year: 2026

Type: article

Abstract: Investigating the long-term performance of building materials, such as drying shrinkage, moisture expansion, creep, and others, usually requires long-lasting tests with a high number of specimens. Given the initial costs, required data acquisition systems, and the time allocated, conventional sensors like LVDTs become costly for such long-term experimental studies. This article proposes an innovative cost-effective solution combining optical microscopy imaging, 3D printed sliding rulers, and Python-based artificial vision to overcome these limitations. The 3D printed rulers establish a local physical reference frame, while the artificial vision system uses contour detection and point tracking of optical targets to quantify displacements. Unlike continuous monitoring systems, the proposed solution utilises a discontinuous point-tracking approach, allowing a single USB microscope to monitor an unlimited number of specimens while maintaining the possibility for moisture exchange between the material surface and the environment. The system was metrologically validated against a laser interferometer, achieving an expanded instrumental uncertainty of 0.0042 mm (4.2 µm), determined through strict calibration. These results demonstrate that the proposed solution delivers accuracy comparable to conventional sensors but with significantly higher scalability and lower cost, making it highly suitable for extensive long-term experimental programmes.

Source: Applied Sciences

DOI: 10.3390/app16041866

Authors: Ahmad Fathi, Luís Lages Martins, João M. Pereira, Graça Vasconcelos, Miguel Azenha

Institutions: University of Minho, National Laboratory for Civil Engineering

Language: English

Topic: Optical measurement and interference techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,896