Waterbath Temperature Control System with Fuzzy Logic

  • Annastadia Afifah Department of Medical Electronics Technology, Poltekkes Kemenkes Surabaya, Surabaya, Indonesia
  • Levana Forra Wakidi Department of Medical Electronics Engineering Technology, Poltekkes Kemenkes Surabaya https://orcid.org/0000-0002-4092-4019
  • Her Gumiwang Ariswati Department of Medical Electronics Technology, Poltekkes Kemenkes Surabaya, Surabaya, Indonesia https://orcid.org/0000-0002-8267-5057
  • Dyah Titisari Department of Medical Electronics Technology, Poltekkes Kemenkes Surabaya, Surabaya, Indonesia https://orcid.org/0000-0003-0125-2384
  • Shubhrojit Misra Department of Electronics and Telecommunication Engineering, Jadavpur University, India https://orcid.org/0000-0003-3835-3998
Keywords: Waterbath, Fuzzy, DS18B20

Abstract

Unstable temperature or being outside the control temperature of a sample will cause a change in the quality of the sample itself. The purpose of this study was to create a temperature control system on waterbath with fuzzy logic using 7 labels. Used the DS18B20 sensor as a temperature sensor, a processor in the form of an UNO arduino, a thermostat as part of safety control, and displayed on a 16x4 LCD. Temperature selection between 30°C-60C. Design research using pre-experimental methods with one type group of post-testing design research, by comparing modules with comparison tools in the form of digital thermometers. The results of the research in the manufacture of waterbath tools were conducted compared to the results of measurements in the room with a digital thermometer. Obtained the highest Error value of 0.91% at 35 °C and the lowest error of 0.049% at 60 °C. While the error value based on the setting temperature obtained the highest error value at the temperature setting of 30°C of 1.38% and the lowest error at the temperature setting of 60 °C of 0.05%. The average time required to reach the shortest setting temperature in the temperature range is 27°C-30°C for 193 seconds, and the longest time in the temperature range is 27°C-60°C for 2257 seconds. the results showed that the fuzzy method is better compared to conventional methods. The results of this study can be implemented for waterbath temperature control system to get more stable results in maintaining setting temperature.

Downloads

Download data is not yet available.

References

C. G. T. Mathias, D. M. Wilson, and H. I. Maibacj, “Transepidermal water loss as a function of skin surface temperature,” J. Invest. Dermatol., vol. 77, no. 2, pp. 219–220, 1981, doi: 10.1111/1523-1747.ep12479939.

S. Kolhatkar and A. K. Joshi, “Automatic temperature control technique for a clinical water bath,” Proc. - 2nd Int. Conf. Comput. Commun. Control Autom. ICCUBEA 2016, pp. 1–4, 2017, doi: 10.1109/ICCUBEA.2016.7860141.

M. Rofi’i, S. Syaifudin, D. Titisari, and B. Utomo, “Waterbath Calibrator with Nine Channels Sensor,” Indones. J. Electron. Electromed. Eng. Med. informatics, vol. 1, no. 1, pp. 1–6, 2019, doi: 10.35882/ijeeemi.v1i1.1.

M. E. Peterson, R. M. Daniel, M. J. Danson, and R. Eisenthal, “The dependence of enzyme activity on temperature: Determination and validation of parameters,” Biochem. J., vol. 402, no. 2, pp. 331–337, 2007, doi: 10.1042/BJ20061143.

K. Rezaei, F. Temelli, and E. Jenab, “Effects of pressure and temperature on enzymatic reactions in supercritical fluids,” Biotechnol. Adv., vol. 25, no. 3, pp. 272–280, 2007, doi: 10.1016/j.biotechadv.2006.12.002.

M. R. Hariri and A. S. D. Irsyam, “Jurnal Riset Biologi dan Aplikasinya,” J. Ris. Biol. dan Apl., vol. 1, no. 2, pp. 18–25, 2019.

M. Suutari and S. Laakso, “Unsaturated and branched chain-fatty acids in temperature adaptation of Bacillus subtilis and Bacillus megaterium,” Biochim. Biophys. Acta (BBA)/Lipids Lipid Metab., vol. 1126, no. 2, pp. 119–124, 1992, doi: 10.1016/0005-2760(92)90281-Y.

M. Sohail, R. Siddiqi, A. Ahmad, and S. A. Khan, “Cellulase production from Aspergillus niger MS82: effect of temperature and pH,” N. Biotechnol., vol. 25, no. 6, pp. 437–441, 2009, doi: 10.1016/j.nbt.2009.02.002.

J. McKearnan, “The Effect of Temperature on the Growth of Three Species of Bacteria.” p. Laboratory exercises in microbiology, 4th ed. 1–3, 2007.

Y. Mulge, “International Journal of Computer Science and Mobile Computing Remote Temperature Monitoring Using LM35 sensor and Intimate Android user via C2DM Service,” Ijcsmc, vol. 2, no. 6, pp. 32–36, 2013, [Online]. Available: www.ijcsmc.com

M. Fezari and A. Al Dahoud, “Exploring One-wire Temperature sensor ‘DS18B20’ with Microcontrollers,” Univ. Al-Zaytoonah Fac. IT, no. February, pp. 1–9, 2019, [Online]. Available: https://www.researchgate.net/profile/Mohamed-Fezari-2/publication/330854061_Exploring_One-wire_Temperature_sensor_DS18B20_with_Microcontrollers/links/5c58388d92851c22a3a832d2/Exploring-One-wire-Temperature-sensor-DS18B20-with-Microcontrollers.pdf

Febri Indiani, Dyah Titisari, and Lamidi, “Waterbath Design equipped With Temperature Distribution Monitor,” J. Electron. Electromed. Eng. Med. Informatics, vol. 1, no. 1, pp. 11–15, 2019, doi: 10.35882/jeeemi.v1i1.3.

V. Vijayalakshmi, “Design of superheated steam temperature control using fuzzy logic controller,” ICONSTEM 2017 - Proc. 3rd IEEE Int. Conf. Sci. Technol. Eng. Manag., vol. 2018-Janua, pp. 1076–1084, 2017, doi: 10.1109/ICONSTEM.2017.8261365.

V. Pattanshett and P. M. V. Kuma, “International Journal of Advance Research in Engineering , Science & Technology Performance Evaluation of Fuzzy based Water bath System with Variation in Number of Linguistic Variables and Membership Function Range All Rights Reserved , @ IJAREST-2016 All,” vol. 3, no. 5, pp. 684–692, 2016.

Q. Hidayati, N. Yanti, N. Jamal, and M. Adisaputra, “Portable Baby Incubator Based On Fuzzy Logic,” J. Telemat. Informatics, vol. 8, no. 1, 2020.

C. F. Juang and J. S. Chen, “Water bath temperature control by a recurrent fuzzy controller and its FPGA implementation,” IEEE Trans. Ind. Electron., vol. 53, no. 3, pp. 941–949, 2006, doi: 10.1109/TIE.2006.874260.

B. Dai, R. Chen, and R. C. Chen, “Temperature control with fuzzy neural network,” Proc. - 2017 IEEE 8th Int. Conf. Aware. Sci. Technol. iCAST 2017, vol. 2018-Janua, no. iCAST, pp. 452–455, 2017, doi: 10.1109/ICAwST.2017.8256499.

M. Coban and M. Fidan, “Fuzzy Logic Based Temperature Control,” 3rd Int. Symp. Multidiscip. Stud. Innov. Technol. ISMSIT 2019 - Proc., pp. 1–4, 2019, doi: 10.1109/ISMSIT.2019.8932906.

J. C. Mugisha, B. Munyazikwiye, and H. R. Karimi, “Design of temperature control system using conventional PID and Intelligent Fuzzy Logic controller,” iFUZZY 2015 - 2015 Int. Conf. Fuzzy Theory Its Appl. Conf. Dig., pp. 50–55, 2016, doi: 10.1109/iFUZZY.2015.7391893.

Published
2023-05-30
How to Cite
[1]
A. Afifah, L. F. Wakidi, H. G. Ariswati, D. Titisari, and S. Misra, “Waterbath Temperature Control System with Fuzzy Logic”, Indones.J.electronic.electromed.med.inf, vol. 5, no. 2, pp. 92-100, May 2023.
Section
Research Article

Most read articles by the same author(s)