Cargando…
Research on the Road Performance of Asphalt Mixtures Based on Infrared Thermography
Temperature segregation during the paving of asphalt pavements is one of the causes of asphalt pavement distress. Therefore, controlling the paving temperature is crucial in the construction of asphalt pavements. To quickly evaluate the road performance of asphalt mixtures during paving, in this wor...
Autores principales: | , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9227256/ https://www.ncbi.nlm.nih.gov/pubmed/35744369 http://dx.doi.org/10.3390/ma15124309 |
_version_ | 1784734124713443328 |
---|---|
author | Chen, Wei Wei, Kesen Wei, Jincheng Han, Wenyang Zhang, Xiaomeng Hu, Guiling Wei, Shuaishuai Niu, Lei Chen, Kai Fu, Zhi Xu, Xizhong Xu, Baogui Cui, Ting |
author_facet | Chen, Wei Wei, Kesen Wei, Jincheng Han, Wenyang Zhang, Xiaomeng Hu, Guiling Wei, Shuaishuai Niu, Lei Chen, Kai Fu, Zhi Xu, Xizhong Xu, Baogui Cui, Ting |
author_sort | Chen, Wei |
collection | PubMed |
description | Temperature segregation during the paving of asphalt pavements is one of the causes of asphalt pavement distress. Therefore, controlling the paving temperature is crucial in the construction of asphalt pavements. To quickly evaluate the road performance of asphalt mixtures during paving, in this work, we used unmanned aerial vehicle infrared thermal imaging technology to monitor the construction work. By analyzing the temperature distribution at the paving site, and conducting laboratory tests, the relationship between the melt temperature, high-temperature stability, and water stability of the asphalt mix was assessed. The results showed that the optimal temperature measurement height for an unmanned aerial vehicle (UAV) with an infrared thermal imager was 7–8 m. By coring the representative temperature points on the construction site and then conducting a Hamburg wheel tracking (HWT) test, the test results were verified through the laboratory test results in order to establish a prediction model for the melt temperature and high-temperature stability of y = 10.73e(0.03x) + 1415.78, where the predictive model for the melt temperature and water was y = −19.18e(−0.02x) + 98.03. The results showed that using laboratory tests combined with UAV infrared thermography could quickly and accurately predict the road performance of asphalt mixtures during paving. We hope that more extensive evaluations of the roadworthiness of asphalt mixtures using paving temperatures will provide reference recommendations in the future. |
format | Online Article Text |
id | pubmed-9227256 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-92272562022-06-25 Research on the Road Performance of Asphalt Mixtures Based on Infrared Thermography Chen, Wei Wei, Kesen Wei, Jincheng Han, Wenyang Zhang, Xiaomeng Hu, Guiling Wei, Shuaishuai Niu, Lei Chen, Kai Fu, Zhi Xu, Xizhong Xu, Baogui Cui, Ting Materials (Basel) Article Temperature segregation during the paving of asphalt pavements is one of the causes of asphalt pavement distress. Therefore, controlling the paving temperature is crucial in the construction of asphalt pavements. To quickly evaluate the road performance of asphalt mixtures during paving, in this work, we used unmanned aerial vehicle infrared thermal imaging technology to monitor the construction work. By analyzing the temperature distribution at the paving site, and conducting laboratory tests, the relationship between the melt temperature, high-temperature stability, and water stability of the asphalt mix was assessed. The results showed that the optimal temperature measurement height for an unmanned aerial vehicle (UAV) with an infrared thermal imager was 7–8 m. By coring the representative temperature points on the construction site and then conducting a Hamburg wheel tracking (HWT) test, the test results were verified through the laboratory test results in order to establish a prediction model for the melt temperature and high-temperature stability of y = 10.73e(0.03x) + 1415.78, where the predictive model for the melt temperature and water was y = −19.18e(−0.02x) + 98.03. The results showed that using laboratory tests combined with UAV infrared thermography could quickly and accurately predict the road performance of asphalt mixtures during paving. We hope that more extensive evaluations of the roadworthiness of asphalt mixtures using paving temperatures will provide reference recommendations in the future. MDPI 2022-06-17 /pmc/articles/PMC9227256/ /pubmed/35744369 http://dx.doi.org/10.3390/ma15124309 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Chen, Wei Wei, Kesen Wei, Jincheng Han, Wenyang Zhang, Xiaomeng Hu, Guiling Wei, Shuaishuai Niu, Lei Chen, Kai Fu, Zhi Xu, Xizhong Xu, Baogui Cui, Ting Research on the Road Performance of Asphalt Mixtures Based on Infrared Thermography |
title | Research on the Road Performance of Asphalt Mixtures Based on Infrared Thermography |
title_full | Research on the Road Performance of Asphalt Mixtures Based on Infrared Thermography |
title_fullStr | Research on the Road Performance of Asphalt Mixtures Based on Infrared Thermography |
title_full_unstemmed | Research on the Road Performance of Asphalt Mixtures Based on Infrared Thermography |
title_short | Research on the Road Performance of Asphalt Mixtures Based on Infrared Thermography |
title_sort | research on the road performance of asphalt mixtures based on infrared thermography |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9227256/ https://www.ncbi.nlm.nih.gov/pubmed/35744369 http://dx.doi.org/10.3390/ma15124309 |
work_keys_str_mv | AT chenwei researchontheroadperformanceofasphaltmixturesbasedoninfraredthermography AT weikesen researchontheroadperformanceofasphaltmixturesbasedoninfraredthermography AT weijincheng researchontheroadperformanceofasphaltmixturesbasedoninfraredthermography AT hanwenyang researchontheroadperformanceofasphaltmixturesbasedoninfraredthermography AT zhangxiaomeng researchontheroadperformanceofasphaltmixturesbasedoninfraredthermography AT huguiling researchontheroadperformanceofasphaltmixturesbasedoninfraredthermography AT weishuaishuai researchontheroadperformanceofasphaltmixturesbasedoninfraredthermography AT niulei researchontheroadperformanceofasphaltmixturesbasedoninfraredthermography AT chenkai researchontheroadperformanceofasphaltmixturesbasedoninfraredthermography AT fuzhi researchontheroadperformanceofasphaltmixturesbasedoninfraredthermography AT xuxizhong researchontheroadperformanceofasphaltmixturesbasedoninfraredthermography AT xubaogui researchontheroadperformanceofasphaltmixturesbasedoninfraredthermography AT cuiting researchontheroadperformanceofasphaltmixturesbasedoninfraredthermography |