1. bookVolume 19 (2019): Issue 4 (August 2019)
Journal Details
License
Format
Journal
eISSN
1335-8871
First Published
07 Mar 2008
Publication timeframe
6 times per year
Languages
English
access type Open Access

Information-measuring System to Study the Thermocouple with Controlled Temperature Field

Published Online: 24 Aug 2019
Volume & Issue: Volume 19 (2019) - Issue 4 (August 2019)
Page range: 161 - 169
Received: 26 Feb 2019
Accepted: 31 Jul 2019
Journal Details
License
Format
Journal
eISSN
1335-8871
First Published
07 Mar 2008
Publication timeframe
6 times per year
Languages
English
Abstract

Error due to inhomogeneity is the main problem of thermocouples (TCs), e.g., during the operation of a type K TC, this error can reach 11-30 °C. Thus, metrological reliability of TCs is threatened by this error because there is a high risk of exceeding the permissible error when the temperature distribution along the TC legs changes. Such a large error, in turn, can threaten a proper operation or even safety of a measured object. A TC with controlled temperature field was proposed to cope with this error. An information-measuring system to perform proper measurements, measurement data acquisition and collection to construct mathematical models is proposed. Its property is high diurnal stability of ±(0.0025+0,002(X/XMAX–1) %. The requirements for the information-measuring system and its structure are considered in this paper. In particular, one of the key problems of such a sensor is how stable is its own temperature field under the influence of the temperature field of a measured object. The experimental studies were carried out using the developed system. They showed that the coefficient of penetration of the temperature field of the measured object is about 0.04. This allows decreasing error due to inhomogeneity by about 10-20 times.

Keywords

[1] Webster, J.G. (1998). The Measurement, Instrumentation and Sensors Handbook. CRC Press.10.1201/9781003040019Search in Google Scholar

[2] Glowacz, A., Glowacz, W. (2018). Vibration-based fault diagnosis of commutator motor. Shock and Vibration, 2018, 7460419.10.1155/2018/7460419Search in Google Scholar

[3] Lee, G.W., Kim, H.K. (2018). Personalized HRTF modeling based on deep neural network using anthropometric measurements and images of the ear. Applied Sciences, 8 (11), 2180.10.3390/app8112180Search in Google Scholar

[4] Stadnyk, B., Khoma, Y. (2013). Improving the accuracy of the single chip impedance analyzer for sensor applications. Sensors & Transducers, 150 (3), 27-31.Search in Google Scholar

[5] Glowacz, A. (2018). Acoustic-based fault diagnosis of commutator motor. Electronics, 7 (11), 299.10.3390/electronics7110299Search in Google Scholar

[6] Glowacz, A. (2019). Fault diagnosis of single-phase induction motor based on acoustic signals. Mechanical Systems and Signal Processing, 117, 65-80.10.1016/j.ymssp.2018.07.044Search in Google Scholar

[7] Przystupa, K. (2017). An attempt to use FMEA method for an approximate reliability assessment of machinery. ITM Web of Conferences, 15, 05001.10.1051/itmconf/20171505001Search in Google Scholar

[8] Birch, J.A. (2003). Benefit of legal metrology for the economy and society: A study for the International Committee of Legal Metrology. http://www.oiml.org/publications/E/birch/E002-e03.pdf.Search in Google Scholar

[9] Pohrebennyk, V., Mitryasova, O., Dzhumelia, E., Kochanek, A. (2017). Evaluation of surface water quality in mining and chemical industry. In Proceedings of the 17th International Multidisciplinary Scientific GeoConference (SGEM 2017). SGEM, Vol. 17 (51), 425-432.10.5593/sgem2017/51/S20.056Search in Google Scholar

[10] Zhang, Y., Chen, B., Pan, G., Zhao, Y. (2019). A novel hybrid model based on VMD-WT and PCA-BPRBF neural network for short-term wind speed forecasting. Energy Conversion and Management, 195, 180-197.10.1016/j.enconman.2019.05.005Search in Google Scholar

[11] Perzel, V., Flimel, M., Krolczyk, J., et al. (2017). Measurement of thermal emission during cutting of materials using abrasive water jet. Thermal Science, 21 (5), 2197-2203.10.2298/TSCI150212046PSearch in Google Scholar

[12] Józwik, J., Ostrowski, D., Milczarczyk, R., Krolczyk, G.M. (2018). Analysis of relation between the 3D printer laser beam power and the surface morphology properties in ti-6Al-4V titanium alloy parts. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 40 (4), 215.10.1007/s40430-018-1144-2Search in Google Scholar

[13] Zhang, Y., Wang, P., Zhang, C., Lei, S. (2017). Wind energy prediction with LS-SVM based on Lorenz perturbation. The Journal of Engineering, 2017 (13), 1724-1727.10.1049/joe.2017.0626Search in Google Scholar

[14] Jun, S., Kochan, O., Kochan, V., Wang, C. (2016). Development and investigation of the method for compensating thermoelectric inhomogeneity error. International Journal of Thermophysics, 37 (1), 1-14.10.1007/s10765-015-2025-xSearch in Google Scholar

[15] Zhang, Y., Wang, P., Ni, T., Cheng, P., Lei, S. (2017). Wind power prediction based on LS-SVM model with error correction. Advances in Electrical and Computer Engineering, 17 (1), 3-9.10.4316/AECE.2017.01001Search in Google Scholar

[16] Kozieł, J., Przystupa, K. (2019). Using the FTA method to analyze the quality of an uninterruptible power supply unit reparation UPS. Przegląd Elektrotechniczny, 95 (1), 77-80.Search in Google Scholar

[17] Fluke Corporation. Data Acquisition Units. http://www.fluke.com.Search in Google Scholar

[18] Smalcerz, A., Przylucki, R. (2013). Impact of electromagnetic field upon temperature measurement of induction heated charges. International Journal of Thermophysics, 34 (4), 667-679.10.1007/s10765-013-1423-1Search in Google Scholar

[19] Sachenko, A., Kochan, V., Turchenko, V. (2003). Instrumentation for gathering data [DAQ systems]. IEEE Instrumentation & Measurement Magazine, 6 (3), 34-40.10.1109/MIM.2003.1238339Search in Google Scholar

[20] Jun, S., Kochan, O. (2015). The mechanism of the occurrence of acquired thermoelectric inhomogeneity of thermocouples and its effect on the result of temperature measurement. Measurement Techniques, 57 (10), 1160-1166.10.1007/s11018-015-0596-3Search in Google Scholar

[21] Körtvélyessy, L. (1981). Thermoelement Praxis. Vulkan-Verlag.Search in Google Scholar

[22] Heyer, D., Noatsch, U., Tegeler, E., et al. (2007). Intercomparison of the realization of the ITS-90 at the freezing points of Al and Ag among European NMIs. International Journal of Thermophysics, 28 (6), 1964-1975.10.1007/s10765-007-0283-ySearch in Google Scholar

[23] Southworth, D.J. (1999). Temperature Calibration with Isotech Block Baths: Handbook of Isothermal Corporation Limited. Isotech.Search in Google Scholar

[24] Sloneker, K.C. (2009). Thermocouple inhomogeneity. Ceramic Industry, 159 (4), 13-18.Search in Google Scholar

[25] Kim, Y.G., Song, C.H., Gam, K.S., Yang, I. (2009). Change in inhomogeneity with temperature between 180°C and 950°C in base-metal thermocouples. Measurement Science and Technology, 20 (7), 075102.10.1088/0957-0233/20/7/075102Search in Google Scholar

[26] White, W.P. (1906). The constancy of thermoelements. Physical Review, 23, 449–474.Search in Google Scholar

[27] Trisna, B.A., Hanifa, S.A., Wiriadinata, H., et al. (2018). Effect of electrical annealing to the inhomogeneity improvement of type-S thermocouples. Journal of Physics: Conference Series, 1065, 122001.Search in Google Scholar

[28] Jun, S., Kochan, O.V., Jotsov, V.S. (2015). Methods of reducing the effect of the acquired thermoelectric inhomogeneity of thermocouples on temperature measurement error. Measurement Techniques, 58 (3), 327-331.10.1007/s11018-015-0709-zSearch in Google Scholar

[29] Yang, Q., Kochan, R. (2013). Investigation of thermocouple’s drift speed influence on error of their heterogeneity correction. Sensors & Transducers, 160 (12), 514-520.Search in Google Scholar

[30] Jun, S., Kochan, O. (2014). Investigations of thermocouple drift irregularity impact on error of their inhomogeneity correction. Measurement Science Review, 14 (1), 29-34.10.2478/msr-2014-0005Search in Google Scholar

[31] Vasylkiv, N., Kochan, O., Kochan, R., Chyrka, M. (2009). The control system of the profile of temperature field. In 2009 IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications. IEEE, 201-206.10.1109/IDAACS.2009.5342994Search in Google Scholar

[32] Kochan, O., Sapojnyk, H., Kochan, R. (2013). Temperature field control method based on neural network. In 2013 IEEE 7th International Conference on Intelligent Data Acquisition and Advanced Computing Systems. IEEE, Vol. 1, 21-24.Search in Google Scholar

[33] Jun, S., Kochan, O., Chunzhi, W., Kochan, R. (2015). Theoretical and experimental research of error of method of thermocouple with controlled profile of temperature field. Measurement Science Review, 15 (6), 304-312.10.1515/msr-2015-0041Search in Google Scholar

[34] Analog Devices Inc. (2002). ADuC834: Details, datasheet, quote on part number. https://www.chipdig.com/datasheets/parts/datasheet/041/ADUC834.php.Search in Google Scholar

[35] Analog Devices Inc. (2002-2017). AD780, 2.5 V/3.0 V. High Precision Reference. https://www.analog.com/en/products/ad780.html.Search in Google Scholar

[36] iElekt.ru. Integral circuit 301HP5. http://ielekt.ru/datasheet/301nr5.pdf. (in Russian)Search in Google Scholar

[37] Kochan, R., Kochan, V., Sachenko, A., Maykiv, I., Stepanenko, A. (2005). Interface and reprogramming controller for dynamically reprogrammable Network Capable Application Processor (NCAP). In 2005 IEEE Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications. IEEE, 639-642.10.1109/IDAACS.2005.283063Search in Google Scholar

[38] Yeromenko, V., Kochan, O. (2013). The conditional least squares method for thermocouples error modeling. In 2013 IEEE 7th International Conference on Intelligent Data Acquisition and Advanced Computing Systems. IEEE, Vol. 1, 157-162.Search in Google Scholar

Recommended articles from Trend MD

Plan your remote conference with Sciendo