access icon free DGALab: an extensible software implementation for DGA

The development of a new dissolved gas analysis (DGA) method often requires a comparative study to assess the accuracy of the proposed technique. This is faced with the following challenges: (i) the time and effort required to implement and validate the implementation of existing DGA methods, adds to the comparative study cost; (ii) the output states of different DGA methods are not similar, which makes it difficult to put methods side by side in a comparative study; and (iii) the availability of test data is limited. In this study, a user-friendly graphical user interface software package, DGALab, is developed to overcome these challenges. DGALab implements a unified DGA diagnosis framework to map the output states of DGA methods to uniform specifications. DGALab includes a library implementing most common DGA techniques, and includes a repository for input datasets available in the literature and collected directly from laboratories. DGALab simplifies the addition of new DGA techniques written in virtually any programming language. As a result, the process of developing a new DGA technique is greatly simplified using DGALab. To evaluate the software package results, the datasets and methods implemented therein were used to regenerate the results published in earlier research papers.

Inspec keywords: software packages; power engineering computing; fault diagnosis; power transformer insulation; graphical user interfaces

Other keywords: user-friendly graphical user interface software package; unified DGA diagnosis framework; output states; DGALab; dissolved gas analysis method; software package results; extensible software implementation

Subjects: Graphical user interfaces; Transformers and reactors; Power engineering computing

References

    1. 1)
      • 3. Duval, M.: ‘A review of faults detectable by gas-in-oil analysis in transformers’, IEEE Electr. Insul. Mag., 2002, 18, (3), pp. 817.
    2. 2)
      • 14. Ghoneim, S.S.M., Taha, I.B.M.: ‘A new approach of DGA interpretation technique for transformer fault diagnosis’, Int. J. Electr. Power Energy Syst., 2016, 81, pp. 265274.
    3. 3)
      • 23. Singh, S., Joshi, D., Bandyopadhyay, M.N.: ‘Software implementation of Duval triangle technique for DGA in power transformers’, Int. J. Electr. Eng., 2011, 4, (5), pp. 529540.
    4. 4)
      • 19. Qualitrol ‘Serveron’ commercial software package. Available at http://www.qualitrolcorp.com/products/dissolved-gas-analyzers/multi-gas-analyzers/serveron-tm8-multi-gas-on-line-dissolved-gas-monitor/, accessed March 2017.
    5. 5)
      • 16. Morais, D.R., Rolim, J.G.: ‘A hybrid tool for detection of incipient faults in transformers based on the dissolved gas analysis of insulating oil’, IEEE Trans. Power Deliv., 2006, 21, (2), pp. 673680.
    6. 6)
      • 4. Duval, M.: ‘Interpretation of gas-in-oil analysis using new IEC publication 60599 and IEC TC 10 databases’, IEEE Electr. Insul. Mag., 2001, 17, (2), pp. 3141.
    7. 7)
      • 27. Ghoneim, S.S.M.: ‘Intelligent prediction of transformer faults and severities based on dissolved gas analysis integrated with thermodynamics theory’, IET Sci. Meas. Technol., 2018, 12, (3), pp. 388394.
    8. 8)
      • 2. IEEE Guide for the Interpretation of Gases Generated in Oil-Immersed Transformers, IEEE Standard C57.104-2008, February 2009.
    9. 9)
      • 12. Bacha, K., Souahlia, S., Gossa, M.: ‘Power transformer fault diagnosis based on dissolved gas analysis by support vector machine’, Electr. Power Syst. Res., 2012, 83, (1), pp. 7379.
    10. 10)
      • 22. GE Perception Fleet. Available at http://www.gae.co.id/detail/ge-perception-fleet-284, accessed May 2018.
    11. 11)
      • 29. Ibrahim, S., Taha, I.B.M., Ghoneim, S.M.: ‘DGA tool GitHub repository’. https://github.com/Saleh860/DGA, accessed August 2017.
    12. 12)
      • 15. Taha, I.B.M., Mansour, D.A., Ghoneim, S.S.M., et al: ‘Conditional probability-based interpretation of dissolved gas analysis for transformer incipient faults’, IET Gener. Transm. Distrib., 2016, 11, (4), pp. 943951.
    13. 13)
      • 9. Huang, Y.-C., Sun, H.-C.: ‘Dissolved gas analysis of mineral oil for power transformer fault diagnosis using fuzzy logic’, IEEE Trans. Dielectr. Electr. Insul., 2013, 20, (3), pp. 974981.
    14. 14)
      • 18. M. Schaffer ‘Inside View’ commercial software package. Available at https://www.morganschaffer.com/page-inside_view.html, accessed March 2017.
    15. 15)
      • 13. Wei, C., Tang, W., Wu, Q.: ‘Dissolved gas analysis method based on novel feature prioritisation and support vector machine’, IET Electr. Power Appl., 2014, 8, (8), pp. 320328.
    16. 16)
      • 26. Taha, I.B.M., Ghoneim, S.M., Duaywah, A.S.A.: ‘Refining DGA methods of IEC code and Rogers four ratios for transformer fault diagnosis’. 2016 IEEE PES General Meeting, Boston, USA, 17–21 July 2016.
    17. 17)
      • 10. Hooshmand, R., Banejad, M.: ‘Application of fuzzy logic in fault diagnosis in transformers using dissolved gas based on different standards’, World Acad. Sci. Eng. Technol., 2006, 17, pp. 157161.
    18. 18)
      • 11. Taha, I.B.M., Ghoneim, S.S.M., Zaini, H.G.: ‘A fuzzy diagnostic system for incipient transformer faults based on DGA of the insulating transformer oils’, Int. Rev. Electr. Eng. (I.R.E.E.), 2016, 11, (3), pp. 305313.
    19. 19)
      • 7. Guardado, J.L., Nared, J.L., Moreno, P., et al: ‘A comparative study of neural network efficiency in power transformers diagnosis using dissolved gas analysis’, IEEE Trans. Power Deliv., 2001, 16, (4), pp. 643647.
    20. 20)
      • 25. Suleiman, A.A., Muhamad, N.A., Bashir, N., et al: ‘Introducing the hybrid-DGA interpretation software as an effective power transformer management tool’. Fourth Int. Conf. Power Engineering, Energy and Electrical Drives, Istanbul, Turkey, 13–17 May 2013, pp. 14101414.
    21. 21)
      • 20. DGA Expert Systems Software version 3 By Northern Technology & Testing. Available at http://www.nttworldwide.com/dgasoftware.htm, accessed May 2018.
    22. 22)
      • 1. IEC 60599: ‘Mineral oil-filled electrical equipment in service - Guidance on the interpretation of dissolved and free gases analysis’, (IEC, Geneva, Switzerland), Edition 2.1, 2007-05.
    23. 23)
      • 5. Mansour, D.A.: ‘Development of a new graphical technique for dissolved gas analysis in power transformers based on the five combustible gases’, IEEE Trans. Dielectr. Electr. Insul., 2015, 22, (5), pp. 25072512.
    24. 24)
      • 6. Ghoneim, S.S.M., Taha, I.B.M., Elkalashy, N.I.: ‘Integrated ANN-based proactive fault diagnostic scheme for power transformers using dissolved gas analysis’, IEEE Trans. Dielectr. Electr. Insul., 2016, 23, (3), pp. 18381845.
    25. 25)
      • 21. Smart DGA Monitoring Solutions. Available at https://www.lumasenseinc.com/uploads/Products/Gas_Sensing/SmartDGA_for_Transformers/SmartDGA_Products/pdf/EN-SmartDGA-Monitoring-Solutions_Brochure.pdf, accessed May 2018.
    26. 26)
      • 24. Victor, P., Marungsri, B.: ‘Implementation of computer based software for oil immersed power transformer condition monitoring via dissolved gas-in-oil results’. IEEE PES Thailand Joint Symp. Advanced Technology in Power Systems, Chulalongkorn, Indonesia, 11 March 2016, pp. 2935.
    27. 27)
      • 8. Miranda, V., Garez Castro, A.R., Lima, S.: ‘Diagnosing faults in power transformers with autoassociative neural networks and mean shift’, IEEE Trans. Power Deliv., 2012, 27, (3), pp. 13501357.
    28. 28)
      • 28. Rogers, R.R.: ‘IEEE and IEC codes to interpret incipient faults in transformers, using gas-in-oil analysis’, IEEE Trans. Electr. Insul., 1978, EI-13, (5), pp. 349354.
    29. 29)
      • 17. Abu-Siada, A., Islam, S.: ‘A New approach to identify power transformer criticality and asset management decision based on dissolved gas-in-oil analysis’, IEEE Trans. Dielectr. Electr. Insul., 2012, 19, (3), pp. 10071012.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2018.5564
Loading

Related content

content/journals/10.1049/iet-gtd.2018.5564
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading