Abstract
References
- 1. Ahıska R, Dişlitaş S. Computer controlled test system for measuring the parameters of the real thermoelectric module. Energy Conversion and Management 2011; 52: 27-36.
- 2. Harman TC. Special techniques for measurement of thermoelectric properties. J. Appl. Phys. 1958; 29:1373-1379.
- 3. Rowe DM, Marlow R, Burke E. CRC handbooks of thermoelectrics. Boca Raton; 1995.
- 4. Riffat SB, Ma X. Thermoelectrics: a review of present and potential applications. Appl. Thermal Eng. 2003; 23:913-935.
- 5. Dişlitaş S, Ahıska R. Üç ayrık ölçüme dayalı parabol algoritması ile termoelektrik modülün Imax, Vmax ve Emax parametrelerinin belirlenmesi. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 2016; 31(4):1063-1072.
- 6. Dişlitaş S, Ömer G, Ahıska R. Microcontroller-based test system for determining the P-N type and Seebeck coefficient of the thermoelectric Semiconductors. Measurement 2019; 139:361-369.
- 7. Tiwari M, Singhai R. A Review of Detection and Tracking of Object from Image and Video Sequences. International Journal of Computational Intelligence Research 2017; 13(5):745-765.
- 8. Fan L, Wang Z, Cail B, Tao C. A Survey on Multiple Object Tracking Algorithm. Proceedings of the IEEE International Conference on Information and Automation 2016; 1855-1862.
- 9. Minichino J, Howse J. Learning OpenCV 3 Computer Vision with Python (Second Edition), Packt Publishing, Birmingham-Mumbai; 2015.
- 10. Rowe D (Ed.). Thermoelectrics Handbook: Macro to Nano (third ed.), CRC Press; 2006.
- 11. Laird Thermal Systems. Thermoelectric Modules. (https://lairdthermal.com/products/thermoelectric- cooler-modules. Last Retrieved March 12, 2023).
- 12. Pollock DD. Thermoelectric Phenomena, Editor: D.M. Rowe, CRC handbook of thermoelectrics, FL, USA: CRC Press; 1995:21-31.
- 13. OpenCV Reference Guide. (https://docs.opencv.org/4.7.0/, Last Retrieved: Feb 15, 2023).
- 14. Salhi A, Jammoussi AY. Object tracking system using Camshift, Meanshift and Kalman Filter. World Academy of Science, Engineering and Technology 2012; 6 (4):1-6.
- 15. Hema D, Kannan S. Interactive Color Image Segmentation using HSV Color Space. Science and Technology Journal 2019;7(1):37-41.
- 16. Manipriya S, Mala C, Mathew S. Performance Analysis of Spatial Color Information for Object Detection Using Background Subtraction. IERI Procedia 2014; 10:63-69.
- 17. Chena Y, Xiaoa X, Liub H, Fenga P. Dynamic color image resolution compensation under low light. Optik 2015;126:603-608.
Design of Image Processing-based System for Detection of Heat Transfer Direction in Thermoelectric Modules
Abstract
It is extremely important for the performance and success of the system to know the cooling or heating surfaces of the thermoelectric modules (TEMs) as cooler or generator, according to the heat transfer direction, and to carry out their installation correctly, taking this into account. In TEMs, the direction of heat transfer between surfaces changes depending on the applied DC direction, and while one surface of the module cools, the other heats up. In this respect, the state of the positive and negative poles in the design and production of TEMs directly affects the heat transfer direction between the module surfaces. On the other hand, the contact direction of the surfaces of the TEMs used in a designed thermoelectric system (TES) is of great importance in order to perform the heat transfer correctly without loss of performance. In this study, a system is designed to detect the heat transfer direction of TEMs using image processing techniques. The basic principle of the system is to determine the positive and negative poles of the TEMs together with the ceramic plate, using the color-based image processing method, and to determine the heat transfer direction by utilizing their relative positions. With the designed system, the heat transfer direction of TEMs at different illuminance levels is tried to be determined and successful results were obtained. As a result, it is thought that the developed system will contribute to the automatic error control for the production and assembly of TEMs.
Keywords
Thermoelectric Module Peltier Effect Seebeck Effect Heat Transfer Image Processing Software
References
- 1. Ahıska R, Dişlitaş S. Computer controlled test system for measuring the parameters of the real thermoelectric module. Energy Conversion and Management 2011; 52: 27-36.
- 2. Harman TC. Special techniques for measurement of thermoelectric properties. J. Appl. Phys. 1958; 29:1373-1379.
- 3. Rowe DM, Marlow R, Burke E. CRC handbooks of thermoelectrics. Boca Raton; 1995.
- 4. Riffat SB, Ma X. Thermoelectrics: a review of present and potential applications. Appl. Thermal Eng. 2003; 23:913-935.
- 5. Dişlitaş S, Ahıska R. Üç ayrık ölçüme dayalı parabol algoritması ile termoelektrik modülün Imax, Vmax ve Emax parametrelerinin belirlenmesi. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 2016; 31(4):1063-1072.
- 6. Dişlitaş S, Ömer G, Ahıska R. Microcontroller-based test system for determining the P-N type and Seebeck coefficient of the thermoelectric Semiconductors. Measurement 2019; 139:361-369.
- 7. Tiwari M, Singhai R. A Review of Detection and Tracking of Object from Image and Video Sequences. International Journal of Computational Intelligence Research 2017; 13(5):745-765.
- 8. Fan L, Wang Z, Cail B, Tao C. A Survey on Multiple Object Tracking Algorithm. Proceedings of the IEEE International Conference on Information and Automation 2016; 1855-1862.
- 9. Minichino J, Howse J. Learning OpenCV 3 Computer Vision with Python (Second Edition), Packt Publishing, Birmingham-Mumbai; 2015.
- 10. Rowe D (Ed.). Thermoelectrics Handbook: Macro to Nano (third ed.), CRC Press; 2006.
- 11. Laird Thermal Systems. Thermoelectric Modules. (https://lairdthermal.com/products/thermoelectric- cooler-modules. Last Retrieved March 12, 2023).
- 12. Pollock DD. Thermoelectric Phenomena, Editor: D.M. Rowe, CRC handbook of thermoelectrics, FL, USA: CRC Press; 1995:21-31.
- 13. OpenCV Reference Guide. (https://docs.opencv.org/4.7.0/, Last Retrieved: Feb 15, 2023).
- 14. Salhi A, Jammoussi AY. Object tracking system using Camshift, Meanshift and Kalman Filter. World Academy of Science, Engineering and Technology 2012; 6 (4):1-6.
- 15. Hema D, Kannan S. Interactive Color Image Segmentation using HSV Color Space. Science and Technology Journal 2019;7(1):37-41.
- 16. Manipriya S, Mala C, Mathew S. Performance Analysis of Spatial Color Information for Object Detection Using Background Subtraction. IERI Procedia 2014; 10:63-69.
- 17. Chena Y, Xiaoa X, Liub H, Fenga P. Dynamic color image resolution compensation under low light. Optik 2015;126:603-608.
Details
| Primary Language | English |
|---|---|
| Subjects | Image Processing |
| Journal Section | Research Articles |
| Authors | |
| Publication Date | June 30, 2024 |
| Submission Date | September 8, 2023 |
| Published in Issue | Year 2024 Volume: 11 Issue: 2 |
Hittite Journal of Science and Engineering is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY NC).