Signal processing of on-line PDs captured by Rogowski coil for enhanced fault detection in smart distribution networks

Murtaza Hashmi (Corresponding Author), M. Lehtonen, M. Nordman, Seppo Hänninen

    Research output: Contribution to journalArticleScientificpeer-review

    9 Citations (Scopus)

    Abstract

    On-line partial discharge (PD) measurements can be used as a condition monitoring tool to detect falling/leaning trees on the covered-conductor (CC) overhead distribution networks. PD measurements conducted in the high voltage (HV) laboratory are less affected by electromagnetic disturbances (EMD). However, on the other hand, on-line/on-site PD measurements conducted in smart distribution networks are often affected by several disturbances. Extracting low level PD signal from noisy backgrounds is a major challenge for on-line condition monitoring. In this paper, wavelet transform (WT) technique is proposed as a powerful tool to de-noise on-line PD signals in CC overhead distribution lines, which are completely buried by electromagnetic interference (EMI). The on-line PD signals are captured in the laboratory environment and on-site PD measurements are simulated. The principle of denoising based on multi-resolution signal decomposition (MSD) is implemented. The validation of WT technique is carried out by comparing its effectiveness with other available filtering techniques. Rogowski coil is used as a PD sensor to capture PD signals in this specific application. In the future, the proposed method will be implemented in a real-life environment to get more stable and reliable on-line/on-site PD measurement results for enhanced fault detection in smart distribution networks.
    Original languageEnglish
    Pages (from-to)4055-4064
    Number of pages9
    JournalInternational Review of Electrical Engineering
    Volume7
    Issue number2
    Publication statusPublished - 2012
    MoE publication typeA1 Journal article-refereed

    Fingerprint

    Partial discharges
    Fault detection
    Electric power distribution
    Signal processing
    Condition monitoring
    Wavelet transforms
    Signal interference
    Decomposition

    Keywords

    • Condition monitoring
    • covered-conductor
    • electromagnetic disturbances
    • partial discharge
    • Rogowski coil
    • smart distribution networks
    • wavelet transform

    Cite this

    @article{12dcdd72b4364f3e8999b5ec8c8e1719,
    title = "Signal processing of on-line PDs captured by Rogowski coil for enhanced fault detection in smart distribution networks",
    abstract = "On-line partial discharge (PD) measurements can be used as a condition monitoring tool to detect falling/leaning trees on the covered-conductor (CC) overhead distribution networks. PD measurements conducted in the high voltage (HV) laboratory are less affected by electromagnetic disturbances (EMD). However, on the other hand, on-line/on-site PD measurements conducted in smart distribution networks are often affected by several disturbances. Extracting low level PD signal from noisy backgrounds is a major challenge for on-line condition monitoring. In this paper, wavelet transform (WT) technique is proposed as a powerful tool to de-noise on-line PD signals in CC overhead distribution lines, which are completely buried by electromagnetic interference (EMI). The on-line PD signals are captured in the laboratory environment and on-site PD measurements are simulated. The principle of denoising based on multi-resolution signal decomposition (MSD) is implemented. The validation of WT technique is carried out by comparing its effectiveness with other available filtering techniques. Rogowski coil is used as a PD sensor to capture PD signals in this specific application. In the future, the proposed method will be implemented in a real-life environment to get more stable and reliable on-line/on-site PD measurement results for enhanced fault detection in smart distribution networks.",
    keywords = "Condition monitoring, covered-conductor, electromagnetic disturbances, partial discharge, Rogowski coil, smart distribution networks, wavelet transform",
    author = "Murtaza Hashmi and M. Lehtonen and M. Nordman and Seppo H{\"a}nninen",
    year = "2012",
    language = "English",
    volume = "7",
    pages = "4055--4064",
    journal = "International Review of Electrical Engineering",
    issn = "1827-6660",
    publisher = "Praise Worthy Prize S.r.l.",
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    }

    Signal processing of on-line PDs captured by Rogowski coil for enhanced fault detection in smart distribution networks. / Hashmi, Murtaza (Corresponding Author); Lehtonen, M.; Nordman, M.; Hänninen, Seppo.

    In: International Review of Electrical Engineering, Vol. 7, No. 2, 2012, p. 4055-4064.

    Research output: Contribution to journalArticleScientificpeer-review

    TY - JOUR

    T1 - Signal processing of on-line PDs captured by Rogowski coil for enhanced fault detection in smart distribution networks

    AU - Hashmi, Murtaza

    AU - Lehtonen, M.

    AU - Nordman, M.

    AU - Hänninen, Seppo

    PY - 2012

    Y1 - 2012

    N2 - On-line partial discharge (PD) measurements can be used as a condition monitoring tool to detect falling/leaning trees on the covered-conductor (CC) overhead distribution networks. PD measurements conducted in the high voltage (HV) laboratory are less affected by electromagnetic disturbances (EMD). However, on the other hand, on-line/on-site PD measurements conducted in smart distribution networks are often affected by several disturbances. Extracting low level PD signal from noisy backgrounds is a major challenge for on-line condition monitoring. In this paper, wavelet transform (WT) technique is proposed as a powerful tool to de-noise on-line PD signals in CC overhead distribution lines, which are completely buried by electromagnetic interference (EMI). The on-line PD signals are captured in the laboratory environment and on-site PD measurements are simulated. The principle of denoising based on multi-resolution signal decomposition (MSD) is implemented. The validation of WT technique is carried out by comparing its effectiveness with other available filtering techniques. Rogowski coil is used as a PD sensor to capture PD signals in this specific application. In the future, the proposed method will be implemented in a real-life environment to get more stable and reliable on-line/on-site PD measurement results for enhanced fault detection in smart distribution networks.

    AB - On-line partial discharge (PD) measurements can be used as a condition monitoring tool to detect falling/leaning trees on the covered-conductor (CC) overhead distribution networks. PD measurements conducted in the high voltage (HV) laboratory are less affected by electromagnetic disturbances (EMD). However, on the other hand, on-line/on-site PD measurements conducted in smart distribution networks are often affected by several disturbances. Extracting low level PD signal from noisy backgrounds is a major challenge for on-line condition monitoring. In this paper, wavelet transform (WT) technique is proposed as a powerful tool to de-noise on-line PD signals in CC overhead distribution lines, which are completely buried by electromagnetic interference (EMI). The on-line PD signals are captured in the laboratory environment and on-site PD measurements are simulated. The principle of denoising based on multi-resolution signal decomposition (MSD) is implemented. The validation of WT technique is carried out by comparing its effectiveness with other available filtering techniques. Rogowski coil is used as a PD sensor to capture PD signals in this specific application. In the future, the proposed method will be implemented in a real-life environment to get more stable and reliable on-line/on-site PD measurement results for enhanced fault detection in smart distribution networks.

    KW - Condition monitoring

    KW - covered-conductor

    KW - electromagnetic disturbances

    KW - partial discharge

    KW - Rogowski coil

    KW - smart distribution networks

    KW - wavelet transform

    M3 - Article

    VL - 7

    SP - 4055

    EP - 4064

    JO - International Review of Electrical Engineering

    JF - International Review of Electrical Engineering

    SN - 1827-6660

    IS - 2

    ER -