Emerging Technologies based Use Case Development for Condition Monitoring and Predictive Maintenance of MV Cables
Kumar, Haresh; Kauhaniemi, Kimmo; Elmusrati, Mohammed; Shafiq, Muhammad (2023-11-28)
Katso/ Avaa
Tiedosto avautuu julkiseksi: : 28.11.2025
Kumar, Haresh
Kauhaniemi, Kimmo
Elmusrati, Mohammed
Shafiq, Muhammad
IEEE
28.11.2023
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe202401102280
https://urn.fi/URN:NBN:fi-fe202401102280
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vertaisarvioitu
©2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
©2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Tiivistelmä
Condition monitoring (CM) and predictive maintenance (PM) techniques can provide a system to achieve a high quality of service with minimal maintenance costs. Using CM -based data, repairing assets is possible based on predictions of the occurrence of faults in assets. Underground medium voltage (MV) cables are vulnerable to deterioration due to stress factors and degradation of the insulating material that lead to cable failure. The gradual deterioration produces incipient faults that lead to MV cable breakdown if not diagnosed at early stages. Efficient diagnosis avoids unscheduled outages and partial discharge (PD) analysis is the most effective method for CM and diagnostics of MV cables. The health of the MV cable can be monitored by collecting and processing a huge amount of data. A use case is developed that shows how data is transferred using emerging technologies to the supervisory control and data acquisition (SCADA) system for diagnostic purposes.
Kokoelmat
- Artikkelit [2922]