Article | Proceedings of the 9th International MODELICA Conference; September 3-5; 2012; Munich; Germany | Fault Detection of Power Electronic Circuit using Wavelet Analysis in Modelica

Title:
Fault Detection of Power Electronic Circuit using Wavelet Analysis in Modelica
Author:
Jianbo Gao: Technische Universität München, Munich, Germany Yang Ji: German Aerospace Center, Wessling, Germany Johann Bals: German Aerospace Center, Wessling, Germany Ralph Kennel: Technische Universität München, Munich, Germany
DOI:
10.3384/ecp12076513
Download:
Full text (pdf)
Year:
2012
Conference:
Proceedings of the 9th International MODELICA Conference; September 3-5; 2012; Munich; Germany
Issue:
076
Article no.:
052
Pages:
513-522
No. of pages:
10
Publication type:
Abstract and Fulltext
Published:
2012-11-19
ISBN:
978-91-7519-826-2
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press; Linköpings universitet


Export in BibTex, RIS or text

In more electric aircrafts (MEA) the electric power network is important for the reliability. To prevent severe faults it is the key issue to identify the faults in the early stage before a complete failure happens. In this paper an early stage fault detection method using wavelet multi-resolution analysis (MRA) for a regulated buck DC-DC converter is studied. Specifically; the electrolyte input capacitor is diagnosed. The study was carried out using simulation with Modelica / Dymola. The fault features that were extracted from different levels of MRA decomposition provided clear information for both fast and slow occurring faults. This method showed significant advantages compared with filter technique. It is concluded that wavelet transform is a suitable tool for early stage fault detection of the power electronics in MEA. In addition; the simulation language Modelica provides a convenient possibility for the quick design of fault detection strategy.

Keywords: power electronics; DC-DC converter; fault detection; wavelet; Modelica; Dymola

Proceedings of the 9th International MODELICA Conference; September 3-5; 2012; Munich; Germany

Author:
Jianbo Gao, Yang Ji, Johann Bals, Ralph Kennel
Title:
Fault Detection of Power Electronic Circuit using Wavelet Analysis in Modelica
DOI:
http://dx.doi.org/10.3384/ecp12076513
References:
[1] C. Schallert; A. Pfeiffer and J. Bals. Generator power optimisation for a more-electric aircraft by use of a virtual iron bird; 25th Internaltional Congress of the Aeronautical Sciences; 2006.
[2] M.R. Kuhn; Y. Ji; D. Schröder; Stability studies of critical DC power system comonent for More Electric Aircraft using µ sensitivity. Proc. of the 15th Mediterranean Conference on Contro & Automation; 2007.
[3] J. Gertler. Fault Detection and Diagnosis in Engineering Systems. Marcel Dekker; 1998.
[4] J. Chen and P.Patton. Robust Model-based Fault Diagnosis for Dynamic Systems. Kluwer Academic Publishers; 1999. doi: 10.1007/978-1-4615-5149-2.
[5] S. X. Ding. Model-based Fault Diagnosis Techniques: Design Schemes; Algorithms and Tools. Springer Berlin; 2008.
[6] K. Swarup and H. Chandrasekharaiah. Fault detection and diagnosis of power systems using artificial neural networks. 1st international forum on application of neural networks to power system; 1991.
[7] M. Aldeen and F. Crusca. Observer-based fault detection and identification scheme for power systems: Generation; Transmission and Distribution. lEE Proceedings; vol. 153; pp.71-79; 2006.
[8] Y. Ji and J. Bals. Multi-Model Based Fault Detection for the Power System of More Electric Aircraft. Proceedings of the 7th Asian Control Conference; Hong Kong; China; Aug. 27-29; 2009.
[9] Y. Ji; J. Bals; Application of model detection techniques to health monitoring for the electrical network of More Electric Aircraft; International Conference on Electrical Engineering and applications; 2009.
[10] S. Mallat (2009): A wavelet tour of signal processing - the sparse way. Amsterdam: Elsevier.
[11] H. T. Zhang; Q. An; et al. Fault Detection Wavelet Fractal Method of Circuit of Three-Phase Bridge Rectifier. International Conference on Intelligent System Design and Engineering Application (ISDEA); 2010; S. 725–729.
[12] V. Prasannamoorthy; N. Devarajan; et al. Wavelet and Fuzzy Classifier Based Fault Detection Methodology for Power Electronic Circuits. International Conference on Process Automation; Control and Computing (PACC); 2011; S. 1–6.
[13] T. Buente; A. Sahin; and N. Bajcinca; Naim. Inversion of Vehicle Steering Dynamics with Modelica/Dymola. Proceedings of the 4th International Modelica Conference 2005; S. 319–328.
[14] J. Bals; Y. Ji; M. R. Kuhn; C. Schallert; Model based design and integration of More Electric Aircraft systems using Modelica. Moet forum at European power electronics conference and exhibition; 2009.
[15] Y. Ji; J. Bals; A Modelica signal analysis tool towards design of More Electric Aircraft; ICIAE; 2010.
[16] E. Jacobsen and R. Lyons. The sliding DFT. Signal Processing Magazine; vol. 20; issue 2; pp. 74–80; March 2003.
[17] I. Daubechies. Ten Lectures on Wavelets. SIAM 1992. doi: 10.1137/1.9781611970104.

Proceedings of the 9th International MODELICA Conference; September 3-5; 2012; Munich; Germany

Author:
Jianbo Gao, Yang Ji, Johann Bals, Ralph Kennel
Title:
Fault Detection of Power Electronic Circuit using Wavelet Analysis in Modelica
DOI:
http://dx.doi.org/10.3384/ecp12076513
Note: the following are taken directly from CrossRef
Citations:
No citations available at the moment