Name / Edward Gulski / Session / 6
Company / Delft University of Technology / Block / 3
Address / Mekelweg 4, 2628CD Delft / Question n° / Selected 10 minutes
The Netherlands / Language used on the floor / English
Phone / +31 152784660 / Accompanying visuals on file / TUD_Gulski_A1_author_ALPHA6_BLOK 3.ppt
e-mail /
DATAMINING FOR DECISION SUPPORT OF CBM OF POWER CABLES
2) With regard to technical aspects relevant information is needed for AM decision support depends on several asset-related parameters, such the insulation and system aging of a component and the probability of an over-voltage, e.g. as a result of switching activities.
3) From a technical point of view, multiple scenarios can be found to influence the performance of assets. For example, scenarios could be in- or decreasing maintenance and inspection intervals, replacement or refurbishment, but also about changing the maintenance strategy from condition based (CBM) to time based (TBM) or corrective maintenance (CM).
4) With regard to distribution power cables the technical information needed for asset management (AM) decision support is not only dependant on diagnostics applied to the cable section but it is also dependent on several asset-related effects such as network operation and cable construction.
5) Taking into account the specific utility situation, the search among different available on-site methods for best and optimal solution comparison analysis has to be done . For example, evaluating the above mentioned parameters can be helpful in making proper selection among different methods. In particular, those methods showing largest and centrally located curve are suitable to meet the defined requirements. In Nuon particular case, the DAC 50-500 Hz methods show the best fitting to aspects as defined by the utility.
6) Based on 4 years systematic field measurements in the Netherlands on new and service aged PILC power cable results of PD occurrence are shown. Moreover based on the practical experiences for most frequently occurring PILC accessories types acceptance threshold values have been determined.
7) Based on 2 years systematic field measurements in the Netherlands on new and service aged XLPE power cables, results of PD occurrence are shown. Moreover, based on the practical experiences (Nuon, Alkmaar utility), a cable specimen under test is considered to have passed the PD-free requirements when PDIV > 1.3 U0 and PDEV > 1.1 U0. On the contrary, in dependence on the type of the joint, termination a certain levels of PD can be accepted in the cable accessories.
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9) This process provides three outcomes (A, B and C) of the data mining approach. Outcome (A) refers to new knowledge about ageing mechanisms of power cable components and outcome (B) to recommended maintenance activities on power cable components, resulting from the database analysis. Due to the large amount of measurement data stored in the software data system, operating norms and criteria are continuously updated and fed back to workers in the field as determined by result (C).
10) Schematic structure of a diagnostics database to support condition assessment of power cables.
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12) PD levels as observed at U0 for PILC database population of two different type of cable splices; (a) splice type resin insulated with the norm 4.7nC; (b) splice type oil filed with the norm 8.2 nC
13) Example of using knowledge rules and database to support the decision process of asset managers in making distinction between cable networks with different insulation conditions; the reed marked cable section shows increased insulation degradation as defined by the knowledge rules.