Statistical analysis of large amount of power cables diagnostic data

P Cichecki, E Gulski, JJ Smit, RA Jongen, F Petzold

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

    1 Citation (Scopus)


    In this contribution statistical analysis were applied to evaluate condition of serviced aged MV power cables systems. Analysis were based on large number of diagnostic data as obtained from the on-site inspections of 89 mass insulated power cables, 26 XLPE insulated power cables and 126 mixed-insulated power cable. Statistical analysis input data was represented with several diagnostic parameters regarding to partial discharges phenomenon (PD). Investigated parameters were obtained with application of damped AC (DAC) diagnostic system during on-site tests. After a survey of all relevant parameters describing condition of the particular cable system components, sub-groups of different cable accessories were created (e.g. joints, termination, insulation types) For proper interpretation of collected data related to cable insulation condition as well as different accessories condition, categorization based on such diagnostic parameters e.g. PDIV (partial discharge inception voltage), PD occurrence, and PD mappings was assumed. Moreover investigated statistically PD parameters were employed to estimate experience norms and measuring criteria. Based on knowledge rules and estimated statistically norms example of so called ldquoexperimental condition indexrdquo was used to indicate overall condition of discussed MV power cables systems.
    Original languageUndefined/Unknown
    Title of host publicationProceedings of 2008 International conference on condition monitoring and diagnosis CMD 2008
    Editors s.n.
    Place of PublicationPiscataway
    PublisherIEEE Society
    Number of pages5
    ISBN (Print)978-1-4244-1621-9
    Publication statusPublished - 2008
    Event2008 International conference on condition monitoring and diagnosis, CMD 2008, Beijing China - Piscataway
    Duration: 21 Apr 200824 Apr 2008

    Publication series



    Conference2008 International conference on condition monitoring and diagnosis, CMD 2008, Beijing China


    • conference contrib. refereed
    • Conf.proc. > 3 pag

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