Development of signal converter of thermal sensors based on combination of thermal and capacity research methods

Authors

DOI:

https://doi.org/10.15587/1729-4061.2018.139763

Keywords:

temperature sensor, transistor structures, capacitive signal transducer, functional integration, converter

Abstract

The problem of functional integration of thermal and capacity research methods, which provides the possibility of realizing a new generation of analog front­end of the Internet of Things in the areas of materials science, biophysics and medicine, is solved. Functional integration means the possibility of the use of the same structure for its controlled heating and temperature measurement. For this purpose, instead of discrete resistive heaters and temperature sensors, transistor structures are proposed. This helps to minimize the sizes of measurement transducers, and so the spatial resolution of the transducers­based sensors of thermal analysis.

The concept of constructing the functionally integrated thermal sensors based on the transistor structures and capacitive signal transducers is developed. The novelty of the proposed sensors of thermal analysis, in addition to measurement of temperature and amount of thermo­energy emitted and absorbed in the object of research, is the possibility of measuring the electrical capacity. This possibility could be particularly assured by the measurement of temperature deformation of a research object or a console that is bent under the effect of the object.

The new solution of the control scheme of the transistor transformers that support the pulse managed heating and forming the informative signal of the temperature of transistor is proposed. The high precision Analog Devices AD7747 24­bit converter is taken as the basis of the capacitive signal transducer.

The developed transducer provides the managed heating of research objects and is characterized by the high values of temperature resolution (not worse than 0.01 oC) and electrical capacity (not worse than 10–16 aF) measurement.

Author Biographies

Oksana Boyko, Danylo Halytsky Lviv National Medical University Pekarska str., 69, Lviv, Ukraine, 79010

PhD, Associate Professor

Department of Medical Informatics

Grygoriy Barylo, Lviv Polytechnic National University Bandery str., 12, Lviv, Ukraine, 79013

PhD, Associate Professor

Department of Electronic Devices

Roman Holyaka, Lviv Polytechnic National University Bandery str., 12, Lviv, Ukraine, 79013

Doctor of Technical Sciences, Professor

Department of Electronics and Information Technology

Zenon Hotra, Lviv Polytechnic National University Bandery str., 12, Lviv, Ukraine, 79013

Doctor of Technical Sciences, Professor

Department of Electronic Devices

Kateryna Ilkanych, Danylo Halytsky Lviv National Medical University Pekarska str., 69, Lviv, Ukraine, 79010

PhD

Department of Medical Informatics

References

  1. Baccelli, E., Gundogan, C., Hahm, O., Kietzmann, P., Lenders, M. S., Petersen, H. et. al. (2018). RIOT: an Open Source Operating System for Low-end Embedded Devices in the IoT. IEEE Internet of Things Journal, 1. doi: https://doi.org/10.1109/jiot.2018.2815038
  2. Kim, J., Yun, J., Choi, S.-C., Seed, D. N., Lu, G., Bauer, M. et. al. (2016). Standard-based IoT platforms interworking: implementation, experiences, and lessons learned. IEEE Communications Magazine, 54 (7), 48–54.doi: https://doi.org/10.1109/mcom.2016.7514163
  3. Huang, P.-C., Rabaey, J. M. (2017). A Bio-Inspired Analog Gas Sensing Front End. IEEE Transactions on Circuits and Systems I: Regular Papers, 64 (9), 2611–2623. doi: https://doi.org/10.1109/tcsi.2017.2697945
  4. Rahimi, A. A., Hu, H., Gupta, S. (2017). A compressive sensing information aware analog front end for IoT sensors using adaptive clocking techniques. 2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS). doi: https://doi.org/10.1109/mwscas.2017.8052926
  5. Vistak, M. V., Dmytrakh, V. Y., Diskovskyu, I. S., Kobylinska, L. I., Mikityuk, Z. M., Petryshak, V. S. (2017). The optoelectronic sensor creatinine and urea. Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2017. doi: https://doi.org/10.1117/12.2280990
  6. Barylo, G., Holyaka, R., Prudyus, I., Fabirovskyy, S. (2017). Parametric analysis of galvanostatic type impedance measuring front-end. 2017 4th International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T). doi: https://doi.org/10.1109/infocommst.2017.8246407
  7. Mohammad, K., Thomson, D. J. (2017). Differential Ring Oscillator Based Capacitance Sensor for Microfluidic Applications. IEEE Transactions on Biomedical Circuits and Systems, 11 (2), 392–399. doi: https://doi.org/10.1109/tbcas.2016.2616346
  8. Hotra, Z., Holyaka, R., Marusenkov, T., Potencki, J. (2010). Signal transducers of capacitive microelectronic sensors, 8, 129–132.
  9. Scarlett, J. (2014). Using CDCs to Control Motion for Sample. Application Note AN-1301. Analog Devices, 6. Available at: http://www.analog.com/media/en/technical-documentation/application-notes/AN-1301.pdf
  10. Holyaka, R., Kostiv, N. (2011). Energy-efficient signal converter of thermocouple, temperature sensors. Informatyka, Automatyka, Pomiary, 4, 26–28.
  11. Hotra, O., Boyko, O., Zyska, T. (2014). Improvement of the operation rate of medical temperature measuring devices. 13th International Scientific Conference on Optical Sensors and Electronic Sensors. doi: https://doi.org/10.1117/12.2070167
  12. Cassel, B., Packer, R., Shelton, C. T. Modulated Temperature DSC and the DSC 8500: A Step Up in Performance. PerkinElmer, Inc. Available at: http://labsense.fi/uploads/7/1/9/5/71957143/modulated_temperature_dsc_and_dsc_8500__a_step_up_in_performance_009122b_01_tch.pdf
  13. Barreneche, C., Solé, A., Miró, L., Martorell, I., Fernández, A. I., Cabeza, L. F. (2012). New methodology developed for the differential scanning calorimetry analysis of polymeric matrixes incorporating phase change materials. Measurement Science and Technology, 23 (8), 085606. doi: https://doi.org/10.1088/0957-0233/23/8/085606
  14. Elhissi, A. M. A., O’Neill, M., Ahmed, W., Taylor, K. M. G. (2011). High-sensitivity differential scanning calorimetry for measurement of steroid entrapment in nebulised liposomes generated from proliposomes. Micro & Nano Letters, 6 (8), 694. doi: https://doi.org/10.1049/mnl.2011.0086
  15. Jiang, Y., Wang, D., Chen, J., Zhang, Q., Xuan, T. (2018). Electromagnetic-Thermal-Fluidic Analysis of Permanent Magnet Synchronous Machine by Bidirectional Method. IEEE Transactions on Magnetics, 54 (3), 1–5. doi: https://doi.org/10.1109/tmag.2017.2760928
  16. Alberti, L., Bianchi, N. (2008). A Coupled Thermal–Electromagnetic Analysis for a Rapid and Accurate Prediction of IM Performance. IEEE Transactions on Industrial Electronics, 55 (10), 3575–3582. doi: https://doi.org/10.1109/tie.2008.2003197
  17. Boyko, O., Holyaka, R., Hotra, Z. (2018). Functionally integrated sensors on magnetic and thermal methods combination basis. 2018 14th International Conference on Advanced Trends in Radioelecrtronics, Telecommunications and Computer Engineering (TCSET). doi: https://doi.org/10.1109/tcset.2018.8336296
  18. Karpaty, D. (2013). Modeling Amplifiers as Analog Filters Increases SPICE Simulation Speed. Analog Dialogue, 47 (1), 18–22.
  19. MICRO-CAP. Electronic Circuit Analysis Program. Spectrum Software (2014). Available at: http://www.spectrum-soft.com

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Published

2018-07-27

How to Cite

Boyko, O., Barylo, G., Holyaka, R., Hotra, Z., & Ilkanych, K. (2018). Development of signal converter of thermal sensors based on combination of thermal and capacity research methods. Eastern-European Journal of Enterprise Technologies, 4(9 (94), 36–42. https://doi.org/10.15587/1729-4061.2018.139763

Issue

Section

Information and controlling system