Comparative analysis of hardware and software of the monitoring method of fun ctioning electromechanical DC converters
https://doi.org/10.30724/1998-9903-2020-22-5-142-154
Abstract
THE PURPOSE. The task of analysis and monitoring of the functioning of electromechanical converters in transient and static modes is relevant at the design and operation stages. Software products for recording and processing measurement information, as well as for performing the necessary technical calculations, such as LabView, MatLab Simulink and others, offer great opportunities for solving the task and allow obtaining reliable results. METHODS. The study of electromechanical DC converters with built-in tachogenerators carried out, the measurement and fixing of the output coordinates of which is provided by experimental sets of various configuration with subsequent processing of the results of functional monitoring using application programs. RESULTS. The developed experimental sets differ in the composition and cost of hardware, the need to use one or another software support, the form of presenting the results of monitoring the functioning of research objects and the accuracy of the results. CONCLUSION. The present study aimed at a comparative analysis of two experimental sets. These sets allow obtaining mathematical models of electromechanical DC converters necessary for the implementation of the monitoring method of the function ing. The analysis performed from the point of view of material costs for hardware and software, the processing time of the experimental results and the correspondence of the obtained results to the required accuracy of the formation of mathematical models.
Keywords
About the Authors
N. A. Malev
Kazan State Power Engineering University
Russian Federation
Russian Federation
Nikolai A. Malev
Kazan
A. I. Mukhametshin
Kazan State Power Engineering University
Russian Federation
Russian Federation
Azat I. Mukhametshin
Kazan
O. V. Pogoditsky
Kazan State Power Engineering University
Russian Federation
Russian Federation
Oleg V. Pogoditsky
Kazan
P. V. Chichkov
JSC «Kazan Giproniiaviaprom»
Russian Federation
Russian Federation
Pavel V. Chichkov
Kazan
References
1. Malev NA, Mukhametshin AI, Pogoditsky OV, et al. Experimental-analytical identification of a mathematical model of a dc motor using the least squares method. Power engineering: research, equipment, technology. 2019;21(4):113-122.
2. Malev NA, Pogoditsky OV, Lyubarchuk FN. Analysis of changes in the parameters of an asynchronous motor by a linear integral criterion using a reference model . Bulletin of KSPEU. 2019;1:60-67.
3. Malev NA, Mukhametshin AI, Pogoditsky OV, et al. Method of analysis and monitoring of the electromechanical converters parameters based on a linear integral criterion using sensitivity models. International Scientific and Technical Conference Smart Energy Systems 2019 (SES-2019). V. 124.
4. Saushev AV, Shirokov NV. Diagnosis of the state of electrical systems in the space of parameters of their elements. Bulletin of the SUSRF after admiral S.O. Makarov. 2016;2 (36):143-156.
5. Frisk E, Krysander M and. Jung D. A toolbox for analysis and design of model based diagnosis systems for large scale model. IFAC-PapersOnLine. 2017;50(1):3287–3293.
6. Delgado-Arredondo PA, Morinigo-Sotelo D, Osornio-Rios RA. J. G. Methodology for fault detection in induction motors via sound and vibration signals. Mechanical Systems and Signal Processing 2017;83:568–589.
7. Jardine AK, Lin D, and Banjevic D.A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical systems and signal processing. 2006;20,(7):14831510.
8. Dmitriev BF, Cherevko AI, Gavrilov DA. Universal MatLab-Simulink model of a generalized electrical machine. Russian Electrical Engineering. 2005;76(7):1-8.
9. Lankin AM, Lankin MV, Kucherov VA, et al. Application of the algorithm nature-model tests for the diagnosis of electrical systems. Modern problems of science and education. 2015;1-2:98.
10. Study of the parameters of the mathematical model for calculating the additional losses in a DC motor with pulsed power / Sedova I.Yu., Yudina O.I .; Sev. -Kavk. state tech. un-t – Stavropol, 2007.
11. Shmarin YaA, Kodkin VL. Experimental study of synchronous motors with permanent magnets. BULLETIN of the CIGRE Russian National Committee. Issue N.7. Materials of the Youth Section of the RNC CIGRE: a collection of competitive reports “Energy-2015” in the field of electricity and electrical engineering in the areas of CIGRE research. Ivanovo, 2015. 118 p.
12. Matveeva OL, Seliverov D.I. Modern electric motors for switch drives. Actual problems of technical sciences: materials of the 2th Intern. scientific conf. (Perm, February 2013). Perm: Mercury, 2013 . pp. 102–104.
13. Smedley Trevor J. Cox Philip T. Visual Languages for the Design and Development of Structured Objects. Journal of Visual Languages and Computing.VLC. 1997;8(1):57–84.
14. Meurice L. Nagy C. Cleve A. Static analysis of dynamic database usage in Java systems. CAiSE 2016. LNCS. 2016;9694:491-506. Springer, Cham.
15. Borisko SN, Kislov OV, Kobzar AA, et al. Results analysis of informative signals with a modulation frequency close to the Nyquist frequency processing Dual Technologies. CJSC Advanced Special Technologies and Materials. 2019;1:53–56.
16. Bilfeld N.V. Programming application of Excel functions. New University. Series: Engineering. 2013;3:3–7.
17. Kreindelin VB, Grigoryeva E.D. Development of the bilinear conversion method for the synthesis of digital filters. Materials of ISTC “INTERMATIC-2017” Fundamental Problems of Radioelectronic Instrument Making. November 20–24, 2017 Moscow. In the collection: Information Technologies and Telecommunications. pp. 1183-1185.
18. Kwaha BJ. Kolawole EA., Batu A.M. The design and implementation of a digital infinite impulse response (IIR) lowpass Butterworth filter. A comparison of Matlab and Bilinear transformation methods Indian Journal of Science and Technology. 2011; 4(4):451–455.
19. Ziatdinov SI, Agranovsky AV, Osipov LA. Synthesis of a complex filter with specified transfer function. Instrumentation. 2016;59(7):542–546.
20. Omelchenko EYa, Tanich VO, Maklakov AS, et al. A brief overview and prospects for the use of the Arduino microprocessor platform. Magnitogorsk: "Magnitogorsk State Technical University" Electrotechnical systems and complexes. 2017. pp. 28–33.
21. Milan Matijevic, and VladamirCvjetkovic. Overview of architectures with Arduino boards as building blocks for data acquisition and control systems. Remote Engineering and Virtual Instrumentation (REV), International Conference on, 2016. pp. 56-63.
Review
For citations:
Malev N.A., Mukhametshin A.I., Pogoditsky O.V., Chichkov P.V. Comparative analysis of hardware and software of the monitoring method of fun ctioning electromechanical DC converters. Power engineering: research, equipment, technology. 2020;22(5):142-154. (In Russ.) https://doi.org/10.30724/1998-9903-2020-22-5-142-154
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