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

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


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.


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.

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

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 applications37(5), 1227-1233.

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.

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

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 Electronics62(3), 1888-1900.

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. Energies12(8), 1506.

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.

Thomson, W. T., & Fenger, M. (2001). Current signature analysis to detect induction motor faults. IEEE Industry Applications Magazine7(4), 26-34.

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

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Gyurov, V., Duganov, M., & Yordanov, Y. (2022, July 25). Diagnostic System for Asynchronous Motors and Synchronous Generators Operating in Autonomous Mode Developed through the Use of DAQ Devices and Labview Programming Environment. ANNUAL JOURNAL OF TECHNICAL UNIVERSITY OF VARNA, BULGARIA, 6(1), 10-17. https://doi.org/10.29114/ajtuv.vol6.iss1.264
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