Frequency Response Analysis Techniques and Their Applications in Electrical Power System: A Review
Downloads
Over the years, a number of methods have been developed to diagnose and monitor electrical and mechanical integrity of the power system equipment. Frequency response analysis (FRA) is one of the popular methods used for evaluating electrical as well as mechanical condition of power system components, especially for Power Transformers. This review presents a comprehensive and chronological overview of FRA applications in power systems. The evolution of methodologies from early offline methods to advance online approaches discussed in this article. This review aims to clarify current state of the FRA applications in power system.
G. S. Chawda et al., “Comprehensive Review on Detection and Classification of Power Quality Disturbances in Utility Grid With Renewable Energy Penetration,” IEEE Access, vol. 8, p. 146807, Jan. 2020, doi: 10.1109/access.2020.3014732.
Y. Venkatachalam and S. Thangavel, “Intelligent fault diagnosis in power systems: A comparative analysis of machine learning-based algorithms,” Expert Systems with Applications, p. 125945, Dec. 2024,
doi: 10.1016/j.eswa.2024.125945.
Y. Park, S. S. Fan, and C.-Y. Hsu, “A Review on Fault Detection and Process Diagnostics in Industrial Processes,” Processes, vol. 8, no. 9. Multidisciplinary Digital Publishing Institute, p. 1123, Sep. 09, 2020.
doi: 10.3390/pr8091123.
S. Govindarajan, A. Morales, J. A. Ardila‐Rey, and N. Purushothaman, “A review on partial discharge diagnosis in cables: Theory, techniques, and trends,” Measurement, vol. 216. Elsevier BV, p. 112882, Apr. 27, 2023. doi: 10.1016/j.measurement.2023.112882.
G. Singaram, K. Sathiyasekar, S. Padmanaban, and C. Bharatiraja, “Insulation condition assessment of high‐voltage rotating machines using hybrid techniques,” IET Generation Transmission & Distribution, vol. 13, no. 2, p. 171, Sep. 2018, doi: 10.1049/iet-gtd.2018.6500.
I. Fofana and Y. Hadjadj, “Electrical-Based Diagnostic Techniques for Assessing Insulation Condition in Aged Transformers,” Energies, vol. 9, no. 9, p. 679, Aug. 2016, doi: 10.3390/en9090679.
R. Krishnan, “A Review of the Monitoring Diagnostic Methods of Oil Immersed Transformers,” International Journal of Engineering Research and, no. 3. International Research Publication House, Mar. 26, 2018. doi: 10.17577/ijertv7is030156.
S. M. Al-Ameri, M. S. Kamarudin, M. F. M. Yousof, A. A. Salem, A. Abu‐Siada, and M. I. Mosaad, “Interpretation of Frequency Response Analysis for Fault Detection in Power Transformers,” Applied Sciences, vol. 11, no. 7, p. 2923, Mar. 2021,
doi: 10.3390/app11072923.
Q. Yang, P. Su, and Y. Chen, “Comparison of Impulse Wave and Sweep Frequency Response Analysis Methods for Diagnosis of Transformer Winding Faults,” Energies, vol. 10, no. 4, p. 431, Mar. 2017,
doi: 10.3390/en10040431.
Z. Zhao, C. Yao, X. Zhao, N. Hashemnia, and S. Islam, “Impact of capacitive coupling circuit on online impulse frequency response of a power transformer,” IEEE Transactions on Dielectrics and Electrical Insulation, vol. 23, no. 3, p. 1285, Jun. 2016,
doi: 10.1109/tdei.2015.005518.
Z. Zhao et al., “Improved Method to Obtain the Online Impulse Frequency Response Signature of a Power Transformer by Multi Scale Complex CWT,” IEEE Access, vol. 6, p. 48934, Jan. 2018,
doi: 10.1109/access.2018.2868058.
M. X. Cohen, “A better way to define and describe Morlet wavelets for time-frequency analysis,” NeuroImage, vol. 199, p. 81, May 2019,
doi: 10.1016/j.neuroimage.2019.05.048.
Z. Yan, A. Miyamoto, and Z. Jiang, “Frequency slice wavelet transform for transient vibration response analysis,” Mechanical Systems and Signal Processing, vol. 23, no. 5, p. 1474, Jan. 2009,
doi: 10.1016/j.ymssp.2009.01.008.
J. Secue and E. E. Mombello, “Sweep frequency response analysis (SFRA) for the assessment of winding displacements and deformation in power transformers,” Electric Power Systems Research, vol. 78, no. 6, p. 1119, Oct. 2007, doi: 10.1016/j.epsr.2007.08.005.
S. Rai and N. Gupta, “SFRA, Detect Of Winding Deformation in Power Transformer,” IOSR Journal of Electrical and Electronics Engineering, vol. 9, no. 6, p. 53, Jan. 2014, doi: 10.9790/1676-09645357.
S. Ma and H. Ren, “Method for detecting system on power transformer winding deformation,” p. 1, Nov. 2009, doi: 10.1109/icems.2009.5382646.
C. X. Li, T. Y. Zhu, Q. Xia, C. Yao, and Z. Y. Zhao, “Study on factors of repetitive impulse influencing online IFRA test,” IEEE Transactions on Dielectrics and Electrical Insulation, vol. 24, no. 4, p. 2189, Jan. 2017, doi: 10.1109/tdei.2017.006366.
J. Wu, J. J. Huang, T. Qian, and W. Tang, “Study on Nanosecond Impulse Frequency Response for Detecting Transformer Winding Deformation Based on Morlet Wavelet Transform,” vol. 35, p. 3479, Nov. 2018,
doi: 10.1109/powercon.2018.8602322.
N. Shanmugam, S. Gopal, B. Madanmohan, S. Balaji, and R. Rajamani, “Diagnosis of Inter-Turn Shorts of Loaded Transformer Under Various Load Currents and Power Factors; Impulse Voltage-Based Frequency Response Approach,” IEEE Access, vol. 9, p. 40811, Jan. 2021, doi: 10.1109/access.2021.3064347.
N. Shanmugam, B. Madanmohan, and R. Rajamani, “Influence of the Load on the Impulse Frequency Response Approach Based Diagnosis of Transformer’s Inter-Turn Short-Circuit,” IEEE Access, vol. 8, p. 39454, Jan. 2020, doi: 10.1109/access.2020.2976157.
B. Mohseni, N. Hashemnia, S. Islam, and Z. Zhao, “Application of online impulse technique to diagnose inter-turn short circuit in transformer windings,” p. 1, Sep. 2016, doi: 10.1109/aupec.2016.7749309.
B. Mohseni, N. Hashemnia, and S. Islam, “Online detection of partial discharge inside power transformer winding through IFRA,” 2017, p. 1.
doi: 10.1109/PESGM.2017.8273725.
K. Arunachalam, B. Madanmohan, and R. Rajamani, “Extended Application for the Impulse-Based Frequency Response Analysis: Preliminary Diagnosis of Partial Discharges in Transformer,” IEEE Access, vol. 8, p. 226897, Jan. 2020, doi: 10.1109/access.2020.3045525.
M. Mayer and F. Oettl, “Reliable Inter Turn Fault Detection on Low Voltage Motors Using SFRA Measurements and Comparison to Surge Testing,” p. 409, Jun. 2021, doi: 10.1109/eic49891.2021.9612246.
Y. Yu, Z. Zhao, Y. Chen, H. Wu, C. Tang, and W. Gu, “Evaluation of the Applicability of IFRA for Short Circuit Fault Detection of Stator Windings in Synchronous Machines,” IEEE Transactions on Instrumentation and Measurement, vol. 71, p. 1, Jan. 2022, doi: 10.1109/tim.2022.3201561.
Y. Chen, Z. Zhao, Y. Yu, W. Wang, and C. Tang, “Understanding IFRA for Detecting Synchronous Machine Winding Short Circuit Faults Based on Image Classification and Smooth Grad-CAM++,” IEEE Sensors Journal, vol. 23, no. 3, p. 2422, Dec. 2022, doi: 10.1109/jsen.2022.3225210.
Y. Chen, Z. Zhao, Y. Yu, Y. Guo, and C. Tang, “Improved Interpretation of Impulse Frequency Response Analysis for Synchronous Machine Using Life long Learning Based on iCaRL,” IEEE Transactions on Instrumentation and Measurement, vol. 72, p. 1, Jan. 2023, doi: 10.1109/tim.2023.3315356.
M. Zamani, F. Haghjoo, M. R. Haseli, and S. M. A. Cruz, “IFRA Technique to Detect Stator Winding High Impedance Earth Faults During Startup in Salient-Pole Synchronous Generators,” IEEE Transactions on Industrial Electronics, vol. 72, no. 7, p. 7605, Dec. 2024, doi: 10.1109/tie.2024.3519635.
K. Ludwikowski, K. Siodła, and W. Ziomek, “Investigation of transformer model winding deformation using sweep frequency response analysis,” IEEE Transactions on Dielectrics and Electrical Insulation, vol. 19, no. 6, p. 1957, Dec. 2012,
doi: 10.1109/tdei.2012.6396953.
A. Hołdyk, B. Gustavsen, I. Arana, and J. Holboell, “Wideband Modeling of Power Transformers Using Commercial sFRA Equipment,” IEEE Transactions on Power Delivery, vol. 29, no. 3, p. 1446, Feb. 2014,
doi: 10.1109/tpwrd.2014.2303174.
G. M. Kennedy, A. J. McGrail, and J. Lapworth, “Using Cross-Correlation Coefficients to Analyze Transformer Sweep Frequency Response Analysis (SFRA) Traces,” p. 1, Jul. 2007, doi: 10.1109/pesafr.2007.4498059.
S. Ryder, “Methods for comparing frequency response analysis measurements,” p. 187, Jun. 2003,
doi: 10.1109/elinsl.2002.995909.
K. Usha and S. Usa, “Inter disc fault location in transformer windings using SFRA,” IEEE Transactions on Dielectrics and Electrical Insulation, vol. 22, no. 6, p. 3567, Dec. 2015, doi: 10.1109/tdei.2015.005060.
M. Bagheri, B. T. Phung, and T. R. Blackburn, “Transformer frequency response analysis: mathematical and practical approach to interpret mid-frequency oscillations,” IEEE Transactions on Dielectrics and Electrical Insulation, vol. 20, no. 6, p. 1962, Dec. 2013, doi: 10.1109/tdei.2013.6678842.
A. Kumar, B. R. Bhalja, and G. B. Kumbhar, “Approach for Identification of Inter-Turn Fault Location in Transformer Windings Using Sweep Frequency Response Analysis,” IEEE Transactions on Power Delivery, vol. 37, no. 3, p. 1539, Jun. 2021,
doi: 10.1109/tpwrd.2021.3092397.
W. Sant’Ana et al., “Influence of rotor position on the repeatability of frequency response analysis measurements on rotating machines and a statistical approach for more meaningful diagnostics,” Electric Power Systems Research, vol. 133, p. 71, Apr. 2016,
doi: 10.1016/j.epsr.2015.11.044.
C. Platero, F. Blazquez, P. Frías Marín, and D. Ramirez, “Influence of rotor position in FRA response for detection of insulation failures in salient pole synchronous machines,” IEEE Transactions on Energy Conversion, vol. 26, p. 671, Jul. 2011,
doi: 10.1109/TEC.2011.2106214.
M. Fairouz Mohd Yousof, A. Allawy Alawady, S. Mgammal Al-Ameri, N. Azis, and H. Azil Illias, “FRA indicator limit for faulty winding assessment in rotating machine,” 2021, p. 346.
doi: 10.1109/ICPADM49635.2021.9493862.
T. G. Vilhekar, M. S. Ballal, and B. S. Umre, “Application of Sweep Frequency Response Analysis for the detection of winding faults in induction motor,” 2016, p. 1458. doi: 10.1109/IECON.2016.7793565.
M. Florkowski and J. Furgał, “Detection of winding faults in electrical machines using the frequency response analysis method,” Measurement Science and Technology, vol. 15, p. 2067, Aug. 2004,
doi: 10.1088/0957-0233/15/10/017.
G. Bucci, F. Ciancetta, and E. Fiorucci, “Apparatus for Online Continuous Diagnosis of Induction Motors Based on the SFRA Technique,” IEEE Transactions on Instrumentation and Measurement, vol. 69, no. 7, p. 4134, Sep. 2019, doi: 10.1109/tim.2019.2942172.
H. Mayora, A. Mugarra, J. M. Guerrero, and C. A. Platero, “Synchronous Salient Poles Fault Localization by SFRA and Fault Diagram Method,” IEEE Transactions on Energy Conversion, vol. 37, no. 4, p. 2669, Jun. 2022, doi: 10.1109/tec.2022.3182817.
M. S. Brandt, M. Gutten, T. N. Kołtunowicz, and P. Żukowski, “Analysis of winding fault in electric machines by frequency method,” 2018 ELEKTRO, p. 1, May 2018, doi: 10.1109/elektro.2018.8398298.
H. Mayora, R. E. Álvarez, G. R. Bossio, and E. Calo, “Condition Assessment of Rotating Electrical Machines using SFRA - A Survey,” p. 26, Jun. 2021,
doi: 10.1109/eic49891.2021.9612397. Available
M. S. Brandt, M. Gutten, and S. Kaščák, “Diagnostic of induction motor using SFRA method,” Sep. 2016,
doi: 10.1109/diagnostika.2016.7736474.
