In-situ heat losses measurements of parabolic trough receiver tubes based on infrared camera and artificial intelligence
•Importance of non-contact thermography inspection.•Analysis of the parameters impacting remote inspection.•Benchmarking image processing methods.•Validation of the solution by comparing it with manual inspection.•Embedding of the solution in the vehicle and description of the transmission and monit...
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Published in: | Environmental challenges (Amsterdam, Netherlands) Vol. 10; p. 100679 |
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Abstract | •Importance of non-contact thermography inspection.•Analysis of the parameters impacting remote inspection.•Benchmarking image processing methods.•Validation of the solution by comparing it with manual inspection.•Embedding of the solution in the vehicle and description of the transmission and monitoring system.
Thermal problems occurring in glass cover, getters, vacuum, expansion bellows, and HTF lead to significant thermal losses due to convection-conduction, which accelerates the absorber degradation and implies replacing immediately these tubes. The replacement of the absorbers tubes is very expensive and interrupts the normal production of concentrated solar power plants. Therefore, the maintenance of the absorber tubes is one of the most critical challenges. In this paper, the Heat Loss Out System (Heat LOS) is proposed for regular evaluation and monitoring of absorbers tubes to maintain their efficiency and reduce operation and maintenance costs through immediate intervention. The proposed system is based on the intelligent processing of photos and videos in real time taken by a robust infrared camera with exact GPS coordinates and implemented on a vehicle. The Heat LOS evaluates in real-time, precisely, and rapidly, the temperature distribution of the absorbers tubes without contacting the surface or interrupting the normal production. First, an analytical study is performed to determine the appropriate speed of the vehicle, which can reach up to and the distance between the camera and the absorber tube that meet a high accuracy of measurement and do not disturb it which should not exceed 5 m. In addition, several absorbers tubes installed in the Green Energy Park (GEP, Morocco) research center are tested and evaluated using the Heat Loss Out system. The results obtained show a promising performance of the proposed system up to an accuracy of 93% based on deep learning with the CNN method, which will be valid when compared to manual analysis. This solution was assembled on a vehicle to rapidly evaluate several tubes and goes through many loops. |
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AbstractList | Thermal problems occurring in glass cover, getters, vacuum, expansion bellows, and HTF lead to significant thermal losses due to convection-conduction, which accelerates the absorber degradation and implies replacing immediately these tubes. The replacement of the absorbers tubes is very expensive and interrupts the normal production of concentrated solar power plants. Therefore, the maintenance of the absorber tubes is one of the most critical challenges. In this paper, the Heat Loss Out System (Heat LOS) is proposed for regular evaluation and monitoring of absorbers tubes to maintain their efficiency and reduce operation and maintenance costs through immediate intervention. The proposed system is based on the intelligent processing of photos and videos in real time taken by a robust infrared camera with exact GPS coordinates and implemented on a vehicle. The Heat LOS evaluates in real-time, precisely, and rapidly, the temperature distribution of the absorbers tubes without contacting the surface or interrupting the normal production. First, an analytical study is performed to determine the appropriate speed of the vehicle, which can reach up to and the distance between the camera and the absorber tube that meet a high accuracy of measurement and do not disturb it which should not exceed 5 m. In addition, several absorbers tubes installed in the Green Energy Park (GEP, Morocco) research center are tested and evaluated using the Heat Loss Out system. The results obtained show a promising performance of the proposed system up to an accuracy of 93% based on deep learning with the CNN method, which will be valid when compared to manual analysis. This solution was assembled on a vehicle to rapidly evaluate several tubes and goes through many loops. •Importance of non-contact thermography inspection.•Analysis of the parameters impacting remote inspection.•Benchmarking image processing methods.•Validation of the solution by comparing it with manual inspection.•Embedding of the solution in the vehicle and description of the transmission and monitoring system. Thermal problems occurring in glass cover, getters, vacuum, expansion bellows, and HTF lead to significant thermal losses due to convection-conduction, which accelerates the absorber degradation and implies replacing immediately these tubes. The replacement of the absorbers tubes is very expensive and interrupts the normal production of concentrated solar power plants. Therefore, the maintenance of the absorber tubes is one of the most critical challenges. In this paper, the Heat Loss Out System (Heat LOS) is proposed for regular evaluation and monitoring of absorbers tubes to maintain their efficiency and reduce operation and maintenance costs through immediate intervention. The proposed system is based on the intelligent processing of photos and videos in real time taken by a robust infrared camera with exact GPS coordinates and implemented on a vehicle. The Heat LOS evaluates in real-time, precisely, and rapidly, the temperature distribution of the absorbers tubes without contacting the surface or interrupting the normal production. First, an analytical study is performed to determine the appropriate speed of the vehicle, which can reach up to and the distance between the camera and the absorber tube that meet a high accuracy of measurement and do not disturb it which should not exceed 5 m. In addition, several absorbers tubes installed in the Green Energy Park (GEP, Morocco) research center are tested and evaluated using the Heat Loss Out system. The results obtained show a promising performance of the proposed system up to an accuracy of 93% based on deep learning with the CNN method, which will be valid when compared to manual analysis. This solution was assembled on a vehicle to rapidly evaluate several tubes and goes through many loops. |
ArticleNumber | 100679 |
Author | Abdi, Farid Ydrissi, Massaab El Hassani, Aicha Alami Ghennioui, Abdelattif Ghennioui, Hicham Oufadel, Ayoub Amri, Abderrahmane El Ghali bennouna, El |
Author_xml | – sequence: 1 givenname: Ayoub surname: Oufadel fullname: Oufadel, Ayoub email: Ayoub.Oufadel@usmba.ac.ma organization: Laboratory of Signals, Systems, and Components, University Sidi Mohamed Ben Abdellah, Fez, Morocco – sequence: 2 givenname: Massaab El orcidid: 0000-0003-3980-8085 surname: Ydrissi fullname: Ydrissi, Massaab El organization: Laboratory of Signals, Systems, and Components, University Sidi Mohamed Ben Abdellah, Fez, Morocco – sequence: 3 givenname: Aicha Alami surname: Hassani fullname: Hassani, Aicha Alami organization: Laboratory of Signals, Systems, and Components, University Sidi Mohamed Ben Abdellah, Fez, Morocco – sequence: 4 givenname: Hicham surname: Ghennioui fullname: Ghennioui, Hicham organization: Laboratory of Signals, Systems, and Components, University Sidi Mohamed Ben Abdellah, Fez, Morocco – sequence: 5 givenname: Abdelattif surname: Ghennioui fullname: Ghennioui, Abdelattif organization: Green Energy Park Research Platform, BenGuérir, Morocco – sequence: 6 givenname: El surname: Ghali bennouna fullname: Ghali bennouna, El organization: Green Energy Park Research Platform, BenGuérir, Morocco – sequence: 7 givenname: Abderrahmane El surname: Amri fullname: Amri, Abderrahmane El organization: Laboratory of Signals, Systems, and Components, University Sidi Mohamed Ben Abdellah, Fez, Morocco – sequence: 8 givenname: Farid surname: Abdi fullname: Abdi, Farid organization: Laboratory of Signals, Systems, and Components, University Sidi Mohamed Ben Abdellah, Fez, Morocco |
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Cites_doi | 10.1007/BF00344251 10.1016/j.patcog.2017.10.013 10.1016/j.renene.2015.07.090 10.1016/j.solener.2014.09.020 10.1515/gps-2020-0059 10.1016/j.egypro.2015.03.168 10.1016/j.energy.2021.120565 10.1016/S0031-3203(01)00178-9 10.1016/j.apenergy.2019.113893 10.1016/j.energy.2022.125650 10.1016/j.rser.2019.109438 10.1016/j.ifacol.2021.10.468 10.1016/j.desal.2007.04.062 10.1016/j.rser.2018.04.097 10.1016/j.renene.2016.09.036 10.1016/j.heliyon.2018.e00938 10.1177/1475921717734501 |
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Keywords | Concentrated solar power Solar collectors Thermal efficiency Artificial intelligence Solar receiver tubes |
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Snippet | •Importance of non-contact thermography inspection.•Analysis of the parameters impacting remote inspection.•Benchmarking image processing methods.•Validation... Thermal problems occurring in glass cover, getters, vacuum, expansion bellows, and HTF lead to significant thermal losses due to convection-conduction, which... |
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SubjectTerms | Artificial intelligence Concentrated solar power Solar collectors Solar receiver tubes Thermal efficiency |
Title | In-situ heat losses measurements of parabolic trough receiver tubes based on infrared camera and artificial intelligence |
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