Intelligent fault diagnosis for on-line condition monitoring in smart distribution networks

Murtaza Hashmi, M. Lehtonen, Seppo Hänninen

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    2 Citations (Scopus)

    Abstract

    Partial discharge (PD) measurements can be regarded as an effective and reliable tool for on-line condition monitoring and asset management of high voltage (HV) apparatus. Recently, a novel application is observed in the monitoring of falling trees on covered-conductor (CC) overhead distribution lines. In this paper, Rogowski and Pearson coils are used as sensors to detect PDs for this specific application. These sensors are non-intrusive and superior to the conventional PD detecting methods. In the next stage of future developments, the wired sensor will be converted into a wireless one. The challenges faced while implementing future wireless technology are also described here. In future, the wireless sensors will be integrated into distribution management system (DMS) to detect and localize the falling trees. The proposed intelligent fault diagnosis system will improve the safety of CC lines and make them more attractive to utilities due to reduced maintenance costs and visual inspection work. In addition, the reliability of the distribution system will improve which is one of the significant characteristics of the future smart distribution networks.
    Original languageEnglish
    Title of host publicationProceedings
    Subtitle of host publicationIEEE International Conference on Condition Monitoring and Diagnosis, CMD 2012
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Pages946-949
    ISBN (Electronic)978-1-4673-1020-8
    ISBN (Print)978-1-4673-1019-2
    DOIs
    Publication statusPublished - 2012
    MoE publication typeNot Eligible
    EventIEEE International Conference on Condition Monitoring and Diagnosis, CMD 2012 - Bali, Indonesia
    Duration: 23 Sep 201227 Sep 2012

    Conference

    ConferenceIEEE International Conference on Condition Monitoring and Diagnosis, CMD 2012
    Abbreviated titleCMD 2012
    CountryIndonesia
    CityBali
    Period23/09/1227/09/12

    Fingerprint

    Condition monitoring
    Electric power distribution
    Failure analysis
    Partial discharges
    Sensors
    Asset management
    Inspection
    Monitoring
    Electric potential
    Costs

    Keywords

    • asset management
    • condition monitoring
    • covered-conductor
    • distribution management system
    • fault diagnosis
    • partial discharge
    • smart distribution networks
    • wireless sensors

    Cite this

    Hashmi, M., Lehtonen, M., & Hänninen, S. (2012). Intelligent fault diagnosis for on-line condition monitoring in smart distribution networks. In Proceedings: IEEE International Conference on Condition Monitoring and Diagnosis, CMD 2012 (pp. 946-949). IEEE Institute of Electrical and Electronic Engineers . https://doi.org/10.1109/CMD.2012.6416309
    Hashmi, Murtaza ; Lehtonen, M. ; Hänninen, Seppo. / Intelligent fault diagnosis for on-line condition monitoring in smart distribution networks. Proceedings: IEEE International Conference on Condition Monitoring and Diagnosis, CMD 2012. IEEE Institute of Electrical and Electronic Engineers , 2012. pp. 946-949
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    title = "Intelligent fault diagnosis for on-line condition monitoring in smart distribution networks",
    abstract = "Partial discharge (PD) measurements can be regarded as an effective and reliable tool for on-line condition monitoring and asset management of high voltage (HV) apparatus. Recently, a novel application is observed in the monitoring of falling trees on covered-conductor (CC) overhead distribution lines. In this paper, Rogowski and Pearson coils are used as sensors to detect PDs for this specific application. These sensors are non-intrusive and superior to the conventional PD detecting methods. In the next stage of future developments, the wired sensor will be converted into a wireless one. The challenges faced while implementing future wireless technology are also described here. In future, the wireless sensors will be integrated into distribution management system (DMS) to detect and localize the falling trees. The proposed intelligent fault diagnosis system will improve the safety of CC lines and make them more attractive to utilities due to reduced maintenance costs and visual inspection work. In addition, the reliability of the distribution system will improve which is one of the significant characteristics of the future smart distribution networks.",
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    Hashmi, M, Lehtonen, M & Hänninen, S 2012, Intelligent fault diagnosis for on-line condition monitoring in smart distribution networks. in Proceedings: IEEE International Conference on Condition Monitoring and Diagnosis, CMD 2012. IEEE Institute of Electrical and Electronic Engineers , pp. 946-949, IEEE International Conference on Condition Monitoring and Diagnosis, CMD 2012, Bali, Indonesia, 23/09/12. https://doi.org/10.1109/CMD.2012.6416309

    Intelligent fault diagnosis for on-line condition monitoring in smart distribution networks. / Hashmi, Murtaza; Lehtonen, M.; Hänninen, Seppo.

    Proceedings: IEEE International Conference on Condition Monitoring and Diagnosis, CMD 2012. IEEE Institute of Electrical and Electronic Engineers , 2012. p. 946-949.

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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    AU - Hänninen, Seppo

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    N2 - Partial discharge (PD) measurements can be regarded as an effective and reliable tool for on-line condition monitoring and asset management of high voltage (HV) apparatus. Recently, a novel application is observed in the monitoring of falling trees on covered-conductor (CC) overhead distribution lines. In this paper, Rogowski and Pearson coils are used as sensors to detect PDs for this specific application. These sensors are non-intrusive and superior to the conventional PD detecting methods. In the next stage of future developments, the wired sensor will be converted into a wireless one. The challenges faced while implementing future wireless technology are also described here. In future, the wireless sensors will be integrated into distribution management system (DMS) to detect and localize the falling trees. The proposed intelligent fault diagnosis system will improve the safety of CC lines and make them more attractive to utilities due to reduced maintenance costs and visual inspection work. In addition, the reliability of the distribution system will improve which is one of the significant characteristics of the future smart distribution networks.

    AB - Partial discharge (PD) measurements can be regarded as an effective and reliable tool for on-line condition monitoring and asset management of high voltage (HV) apparatus. Recently, a novel application is observed in the monitoring of falling trees on covered-conductor (CC) overhead distribution lines. In this paper, Rogowski and Pearson coils are used as sensors to detect PDs for this specific application. These sensors are non-intrusive and superior to the conventional PD detecting methods. In the next stage of future developments, the wired sensor will be converted into a wireless one. The challenges faced while implementing future wireless technology are also described here. In future, the wireless sensors will be integrated into distribution management system (DMS) to detect and localize the falling trees. The proposed intelligent fault diagnosis system will improve the safety of CC lines and make them more attractive to utilities due to reduced maintenance costs and visual inspection work. In addition, the reliability of the distribution system will improve which is one of the significant characteristics of the future smart distribution networks.

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    KW - wireless sensors

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    Hashmi M, Lehtonen M, Hänninen S. Intelligent fault diagnosis for on-line condition monitoring in smart distribution networks. In Proceedings: IEEE International Conference on Condition Monitoring and Diagnosis, CMD 2012. IEEE Institute of Electrical and Electronic Engineers . 2012. p. 946-949 https://doi.org/10.1109/CMD.2012.6416309