Abstract
The in-situ measurement of thermal stress in beams or continuous welded rails may prevent structural anomalies such as buckling. This study proposed a non-contact monitoring/inspection approach based on the use of a smartphone and a computer vision algorithm to estimate the vibrating characteristics of beams subjected to thermal stress. It is hypothesized that the vibration of a beam can be captured using a smartphone operating at frame rates higher than conventional 30 Hz, and the first few natural frequencies of the beam can be extracted using a computer vision algorithm. In this study, the first mode of vibration was considered and compared to the information obtained with a conventional accelerometer attached to the two structures investigated, namely a thin beam and a thick beam. The results show excellent agreement between the conventional contact method and the non-contact sensing approach proposed here. In the future, these findings may be used to develop a monitoring/inspection smartphone application to assess the axial stress of slender structures, to predict the neutral temperature of continuous welded rails, or to prevent thermal buckling.
| Original language | English |
|---|---|
| Article number | 1250 |
| Journal | Sensors |
| Volume | 18 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 18 Apr 2018 |
Bibliographical note
Publisher Copyright:© 2018 by the authors. Licensee MDPI, Basel, Switzerland.
Funding
Author Contributions: M.S.O. developed the idea of applying the multi-thresholded technique to the images recorded during the experiments; he also performed the experiments at the University of Pittsburgh, analyzed the data (mainly at the University of Pittsburgh), and wrote the paper. A.N. helped in the execution of the experiments, wrote the paper, and provided some data analysis. T.O. is the Ph.D. advisor of M.S.O., provided funding from the Scientific and Technological Research Council of Turkey to support M.S.O.’s 1-year visit at the University of Pittsburgh, provided some feedback on the application of the multi-thresholded technique, and reviewed and edited the final draft of the manuscript. D.M. and B.F. developed the original multi-threshold image processing algorithm in Matlab and wrote section 2 of the manuscript. P.R. conceived the idea of applying smartphone-based vibration monitoring to measure axial stress in rails and beams, designed the experiments, wrote the manuscript, and acted as the corresponding author. Acknowledgments: The first author was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) 2214/A International Doctoral Research Fellowship Programme (Grant #1059B141600085). Support for the second author came from the U.S. National Academy of Sciences Transit IDEA program, project T-86. The opinion expressed in this manuscript are solely of the authors and the U.S. National Academy of Sciences and the US Government do not necessarily concur with, endorse, or adopt the findings, conclusions and recommendations either inferred or expressly stated in the manuscript. The first author was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) 2214/A International Doctoral Research Fellowship Programme (Grant #1059B141600085). Support for the second author came from the U.S. National Academy of Sciences Transit IDEA program, project T-86. The opinion expressed in this manuscript are solely of the authors and the U.S. National Academy of Sciences and the US Government do not necessarily concur with, endorse, or adopt the findings, conclusions and recommendations either inferred or expressly stated in the manuscript.
| Funders | Funder number |
|---|---|
| TUBITAK | |
| U.S. National Academy of Sciences Transit IDEA program | |
| National Academy of Sciences | |
| University of Pittsburgh | |
| Türkiye Bilimsel ve Teknolojik Araştirma Kurumu | 1059B141600085 |
| National Council for Scientific Research |
Keywords
- Computer vision
- Neutral temperature
- Nondestructive testing
- Smartphone technology
- Structural health monitoring
- Thermal stress