Diagnostic System for Asynchronous Motors and Synchronous Generators Operating in Autonomous Mode Developed through the Use of DAQ Devices and Labview Programming Environment

Valentin Nikolov Gyurov; Milen Duganov; Yuliyan Yordanov

doi:10.29114/ajtuv.vol6.iss1.264

Valentin Nikolov Gyurov Technical University of Varna http://orcid.org/0000-0002-2626-2864
Milen Duganov Technical university of Varna http://orcid.org/0000-0001-8415-1532
Yuliyan Yordanov Technical university of Varna http://orcid.org/0000-0003-3836-9105

DOI: https://doi.org/10.29114/ajtuv.vol6.iss1.264

Keywords: diagnosis of generators, diagnosis of motors, MSCA, MVSA, GSCA, GVSA

Abstract

The paper explores the possibilities for the use of DAQ devices in developing specialised diagnostic systems for monitoring and diagnostics of electrical equipment with asynchronous electric drives and autonomous synchronous generators. The primary focus is on the construction of a system responsive to different complementary diagnostic methods, such as the spectral current- voltage analysis, Park's method, instantaneous power theories, etc. Such a system might be applied locally (discretely) and/or conjointly in a centralized equipment monitoring system with the use of the LabView platform.

References

Benbouzid, M. E. H. (2000). A review of induction motors signature analysis as a medium for faults detection. IEEE transactions on industrial electronics, 47(5), 984-993.
Crossref

Saad, N., Irfan, M., & Ibrahim, R. (2018). Condition monitoring and faults diagnosis of induction motors: electrical signature analysis. CRC Press.
Crossref

Cruz, S. M., & Cardoso, A. M. (2001). Stator winding fault diagnosis in three-phase synchronous and asynchronous motors, by the extended Park's vector approach. IEEE Transactions on industry applications, 37(5), 1227-1233.
Crossref

Fayazi, M., & Haghjoo, F. (2015, January). Turn to turn fault detection and classification in stator winding of synchronous generators based on terminal voltage waveform components. In The 9th Power Systems Protection and Control Conference (PSPC2015) (pp. 36-41). IEEE.
Crossref

ISO 20958-2013 Condition monitoring and diagnostics of machine systems- Electrical signature analysis of three-phase induction motors
Crossref

Nadarajan, S., Panda, S. K., Bhangu, B., & Gupta, A. K. (2014). Hybrid model for wound-rotor synchronous generator to detect and diagnose turn-to-turn short-circuit fault in stator windings. IEEE Transactions on Industrial Electronics, 62(3), 1888-1900.
Crossref

Salomon, C. P., Ferreira, C., Sant’Ana, W. C., Lambert-Torres, G., Borges da Silva, L. E., Bonaldi, E. L., ... & Torres, B. S. (2019). A study of fault diagnosis based on electrical signature analysis for synchronous generators predictive maintenance in bulk electric systems. Energies, 12(8), 1506.
Crossref

Fenger, M., LLoyd, B. A., & Thomson, W. T. (2003, May). Development of a tool to detect faults in induction motors via current signature analysis. In Cement Industry Technical Conference, 2003. Conference Record. IEEE-IAS/PCA 2003 (pp. 37-46). IEEE.
Crossref

Thomson, W. T., & Fenger, M. (2001). Current signature analysis to detect induction motor faults. IEEE Industry Applications Magazine, 7(4), 26-34.
Crossref

Thomson, W. T., & Culbert, I. (2017). Current signature analysis for condition monitoring of cage induction motors: Industrial application and case histories. John Wiley & Sons.
Crossref

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