Advancing Fault Diagnosis in BLDC Motors: Surge Test-Based Diagnostic Equipment for Phase to Ground Faults
DOI:
https://doi.org/10.35335/p5j7yp39Keywords:
BLDC Motors, Diagnostic Equipment, Fault Diagnosis, Phase to Ground Faults, Surge TestsAbstract
This research introduces a groundbreaking approach to fault diagnosis in Brushless DC (BLDC) motors through the design and validation of specialized diagnostic equipment utilizing surge tests for phase to ground faults. The study focuses on identifying, localizing, and classifying various fault types, including insulation breakdowns, erosion, penetration, and partial grounding within BLDC motors. The research methodology encompasses theoretical frameworks, experimental validations, and comparative analyses with existing diagnostic methods. Surge tests conducted on BLDC motors with induced faults revealed distinct fault signatures, providing precise fault localization and aiding in the establishment of diagnostic criteria and thresholds. The findings showcased the developed equipment's precision, reliability, and automated fault classification capabilities, surpassing the limitations of traditional diagnostic methods. Comparisons with conventional techniques highlighted the advantages of the developed approach, emphasizing its heightened sensitivity, objectivity, and potential for predictive maintenance strategies. The equipment's ability to offer quantifiable fault parameters and establish diagnostic thresholds presents a transformative potential for proactive maintenance, minimizing downtime, and enhancing operational efficiency in BLDC motor-driven systems. The research findings underline the significance of surge tests and specialized diagnostic equipment in revolutionizing fault diagnosis practices for BLDC motors. The implications extend to industry-wide adoption, offering a pathway for enhanced reliability, safety, and operational continuity in various industrial applications.
References
Asfani, D. A., Negara, I. M. Y., Hernanda, I. G. N. S., Mulyadana, D. T., Wijanarko, V. R., & Muljadi, E. (2020). Design of BLDC Motor Diagnostic Device Based on Surge Test for Phase to Ground Fault. 2020 International Seminar on Intelligent Technology and Its Applications (ISITIA), 398–404.
Barnish, T. J., Muller, M. R., & Kasten, D. J. (1997). Motor maintenance: a survey of techniques and results. Proceedings of the 1997 ACEEE Summer Study on Energy Efficiency in Industry. American Council for an Energy-Efficient Economy, Washington, DC.
Brown, R. E. (2017). Electric power distribution reliability (Vol. 1). CRC press.
Chamia, M., & Liberman, S. (1978). Ultra high speed relay for EHV/UHV transmission lines--Development, design and application. IEEE Transactions on Power Apparatus and Systems, 6, 2104–2116.
Dai, X., & Gao, Z. (2013). From model, signal to knowledge: A data-driven perspective of fault detection and diagnosis. IEEE Transactions on Industrial Informatics, 9(4), 2226–2238.
Ferreira, F. J. T. E., Baoming, G., & de Almeida, A. T. (2015). Reliability and operation of high-efficiency induction motors. 2015 IEEE/IAS 51st Industrial & Commercial Power Systems Technical Conference (I&CPS), 1–13.
Fico, V. M., Rodríguez Vázquez, A. L., Martín Prats, M. Á., & Bernelli-Zazzera, F. (2019). Failure Detection by signal similarity measurement of Brushless DC motors. Energies, 12(7), 1364.
Gangsar, P., & Tiwari, R. (2020). Signal based condition monitoring techniques for fault detection and diagnosis of induction motors: A state-of-the-art review. Mechanical Systems and Signal Processing, 144, 106908.
Ghosh, E. (2018). Machine Learning based Early Fault Diagnosis of Induction Motor for Electric Vehicle Application. University of Windsor (Canada).
Kim, S.-H. (2017). Electric motor control: DC, AC, and BLDC motors. Elsevier.
Kirianaki, N. V, Yurish, S. Y., Shpak, N. O., & Deynega, V. P. (2002). Data acquisition and signal processing for smart sensors. Wiley New York.
Li, X. (2015). Model-Based Design of Brushless DC Motor Control and Motion Control Modelling for RoboCup SSL Robots.
Mobley, R. K. (2002). An introduction to predictive maintenance. Elsevier.
Schein, R. H. (1997). The place of landscape: A conceptual framework for interpreting an American scene. Annals of the Association of American Geographers, 87(4), 660–680.
Shifat, T. A., & Hur, J. W. (2020). An effective stator fault diagnosis framework of BLDC motor based on vibration and current signals. IEEE Access, 8, 106968–106981.
Siddique, A., Yadava, G. S., & Singh, B. (2005). A review of stator fault monitoring techniques of induction motors. IEEE Transactions on Energy Conversion, 20(1), 106–114.
Skibinski, G., Liu, Z. T., Van Lieshout, R., Lukaszewski, R., & Tuchalski, M. (2008). Part I: Application guidelines for high resistance grounding of low voltage common AC Bus and common DC BUS PWM drive systems. Conference Record of 2008 54th Annual Pulp and Paper Industry Technical Conference, 27–34.
Smyth, R. (2004). Exploring the usefulness of a conceptual framework as a research tool: a researcher’s reflections. Issues in Educational Research, 14(2), 167–180.
Srivastava, P., & Hopwood, N. (2009). A practical iterative framework for qualitative data analysis. International Journal of Qualitative Methods, 8(1), 76–84.
Sumega, M., Zoššák, Š., Varecha, P., & Rafajdus, P. (2019). Sources of torque ripple and their influence in BLDC motor drives. Transportation Research Procedia, 40, 519–526.
Treetrong, J. (2009). The Use of Parameter Identification Methods for the Condition Monitoring of Electric Motor Drives. The University of Manchester (United Kingdom).
Vanchinathan, K., & Valluvan, K. R. (2016). A study of sensorless BLDC motor drives and future trends. Asian Journal of Research in Social Sciences and Humanities, 6(9), 1863–1887.
Victora, C. G., Huttly, S. R., Fuchs, S. C., & Olinto, M. T. (1997). The role of conceptual frameworks in epidemiological analysis: a hierarchical approach. International Journal of Epidemiology, 26(1), 224–227.
Villani, M., Tursini, M., Fabri, G., & Castellini, L. (2011). High reliability permanent magnet brushless motor drive for aircraft application. IEEE Transactions on Industrial Electronics, 59(5), 2073–2081.
Watson, S. K., Rudge, J. W., & Coker, R. (2013). Health systems’“surge capacity”: state of the art and priorities for future research. The Milbank Quarterly, 91(1), 78–122.
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