Abstract
Model-based approach along with few signal processing techniques like EMD is used for diagnosing synchronous generators. Maintenance is essential for machines, and many industries started to rely more on condition-based and preventive maintenance rather than scheduled and risk-based as it reduces cost and also ensures safety. To reduce the complexity and cost, experimental test rig requirement can be eliminated using Maxwell software. DEKF is used as it has two cascaded EK filters; it can estimate both state and parameters. Residual and IMF3 together will work as a reliable fault signature which helps in differentiating the stator inter-turn fault and a pseudo stator fault.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Abbreviations
- \(\sum \) :
-
Covariance
- \(\theta \) :
-
Parameter of the system
- \(e_{k}\) :
-
Gaussian output or sensor white noise of modeled parameter
- L :
-
Kalman gain
- \(r_{k}\) :
-
Gaussian input or process white noise of modeled parameter
- \(T_\mathrm{s}\) :
-
Sampling period
- \(u_{k}\) :
-
Input
- \(v_{k}\) :
-
Gaussian output or sensor white noise
- \(w_{k}\) :
-
Gaussian input or process white noise
- x :
-
State of the system
- \(z_{k}\) :
-
True or measured output
- 0:
-
Initial
- d :
-
Discrete domain
- k :
-
Present moment in time
- \(k-1\) :
-
Previous moment in time
- \(+\) :
-
Estimated state or parameter
- −:
-
Predicted state or parameter
- \(\sim \) :
-
Error quantity which can be either true value–estimated value or true value–predicted value
- \(\wedge \) :
-
Either prediction or estimate of true state or parameter
- T :
-
Transpose of a matrix
References
Gao Z, Cecati C, Ding SX (2015) A survey of fault diagnosis and fault-tolerant techniques-part i: Fault diagnosis with model-based and signal-based approaches. IEEE Trans Ind Electron 62(6):3757–3767. https://doi.org/10.1109/TIE.2015.2417501
Chen Z, Qi R, Lin H (2007) Inter-turn short circuit fault diagnosis for PMSM based on complex gauss wavelet. In: 2007 International conference on wavelet analysis and pattern recognition, vol 4, pp 1915–1920. https://doi.org/10.1109/ICWAPR.2007.4421769
Cruz S, Cardoso A (2005) Multiple reference frames theory: a new method for the diagnosis of stator faults in three-phase induction motors. IEEE Trans Energy Convers 20(3):611–619. https://doi.org/10.1109/TEC.2005.847975
Gogulaanand R, Balasubramaniyavijayan T, Arunsivaram R, Aishwarya S, Nag PS, Kumar CS (2019) Intelligent monitoring of synchronous generators in smart grids using deep neural network. In: 2019 3rd International conference on trends in electronics and informatics (ICOEI), pp 1376–1379 (2019). https://doi.org/10.1109/ICOEI.2019.8862573
Ravikumar A, Mohan N, Soman K (2018) Performance enhancement of a series active power filter using kalman filter based neural network control strategy. In: 2018 International conference on advances in computing, communications and informatics (ICACCI), pp 1702–1706 1https://doi.org/10.1109/ICACCI.2018.8554889
Awadallah M, Morcos M, Gopalakrishnan S, Nehl T (2005) A neuro-fuzzy approach to automatic diagnosis and location of stator inter-turn faults in CSI-fed PM brushless dc motors. IEEE Trans Energy Conv 20(2):253–259. https://doi.org/10.1109/TEC.2005.847976
Nag PS, Kumar CS, Thampatty KS, Isha T (2018) A modified approach for application of augmented extended Kalman filter for stator interturn fault diagnosis of a synchronous generator. In: 2018 4th International conference on electrical energy systems (ICEES), pp 465–469. https://doi.org/10.1109/ICEES.2018.8442354
Nadarajan S, Panda SK, Bhangu B, Gupta AK (2016) Online model-based condition monitoring for brushless wound-field synchronous generator to detect and diagnose stator windings turn-to-turn shorts using extended Kalman filter. IEEE Trans Ind Electron 63(5):3228–3241. https://doi.org/10.1109/TIE.2016.2535959
Nadarajan S, Panda SK, Bhangu B, Gupta AK (2015) Hybrid model for wound-rotor synchronous generator to detect and diagnose turn-to-turn short-circuit fault in stator windings. IEEE Trans Ind Electron 62(3):1888–1900. https://doi.org/10.1109/TIE.2014.2370931
Sawhney A (1990) Electrical machine design. 1987. Dhanfat Rai & Sons. Gonen, Turan, New Delhi. Electric Power Distribution system engineering. Singapore
Prasob K, Kumar NP, Isha TB (2017) Inter-turn short circuit fault analysis of PWM inverter fed three-phase induction motor using finite element method. In: 2017 International conference on circuit, power and computing technologies (ICCPCT), pp 1–6. https://doi.org/10.1109/ICCPCT.2017.8074384
Chen Y, Wang L, Wang Z, Rehman AU, Cheng Y, Zhao Y, Tanaka T (2015) FEM simulation and analysis on stator winding inter-turn fault in DFIG. In: 2015 IEEE 11th international conference on the properties and applications of dielectric materials (ICPADM), pp 244–247. https://doi.org/10.1109/ICPADM.2015.7295254
Plett GL (2004) Extended Kalman filtering for battery management systems of lipb-based hev battery packs: Part 3. state and parameter estimation. J Power Sources 134(2):277–292. https://doi.org/10.1016/j.jpowsour.2004.02.033
Wang C, Liu X, Chen Z (2014) Incipient stator insulation fault detection of permanent magnet synchronous wind generators based on Hilbert-Huang transformation. IEEE Trans Magn 50(11):1–4. https://doi.org/10.1109/TMAG.2014.2318207
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Diwakar, B., Siddhartha, T.V.S., Manoj Kumar Reddy, B., Jagadeesh, C., Sunilnag, P.V., Santhosh Kumar, C. (2022). Model-Based Fault Diagnosis of Synchronous Generator Using Dual Extended Kalman Filter and Empirical Mode Decomposition. In: Kumar, J., Tripathy, M., Jena, P. (eds) Control Applications in Modern Power Systems. Lecture Notes in Electrical Engineering, vol 870. Springer, Singapore. https://doi.org/10.1007/978-981-19-0193-5_37
Download citation
DOI: https://doi.org/10.1007/978-981-19-0193-5_37
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-0192-8
Online ISBN: 978-981-19-0193-5
eBook Packages: EnergyEnergy (R0)