A Dynamic-SUGPDS Model for Faults Detection and Isolation of Underground Power Cable Based on Detection and Isolation Algorithm and Smart Sensors
Open accessAbstract
This paper proposes a SUGPDS model based on Detection and Isolation algorithm and smart sensors, namely micro phasor measurement unit, smart sensing and switching device, phasor data concentrator, and ZigBee technology, etc. for the identification, classification, and isolation of the various fault occurs in the underground power cable in the distribution system. The proposed SUGPDS is a quick and smart tool in supervising, managing, and controlling various faults and issues and maintaining the reliability, stability, and uninterrupted flow of electricity. First, the SUGPDS model is analyzed using a distributed parameter approach. Then, the proper arrangement of the system required for the implantation of SUGPDS is demonstrated using figures. The Phasor data concentrator plays an essential role in developing the detection and classification report for identification and classification. Finally, smart sensing and switching device installed at a different location isolated the faulty phase from a healthy network. This approach helps to decrease power consumption. Hence, SUGPDS has super abilities compared to the underground power distribution system. The effectiveness of the proposed method and model is demonstrated via figures and tables.
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A film on the sensor cover, such as water, ice, dust, snow, or salt, can prevent objects from being detected (false negatives), from being seen (false positives), or from being correctly classified.
“A film on the sensor cover, such as water, ice, dust, snow, or salt, can prevent objects from being detected (false negatives), from being seen (false positives), or from being correctly classified [40,41].”
From Sensor-Based Prognostic Health Management of Advanced Driver Assistance System for Autonomous Vehicles: A Recent Survey (2022) · cites this paper as [41]
Section 2.1.3 describes classifying underground power-cable faults from electrical measurements, not detecting objects through a sensor cover. A search for sensor-cover films, water, ice, dust, snow, salt, false positives, and false negatives found no passage addressing the claimed effects. (LLM, conf=0.76)
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Flagged first, then by citations
Research works printed but not linked: 1
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- Authors
- Rajpoot, S. C., Pandey, C., Rajpoot, P. S., Singhai, S. K., & Sethy, P. K.
- Affiliations
- Sambalpur University (IN)
- Corresponding author
- Pandey, Chanki
- Venue
- Journal of Electrical Engineering & Technology
- Published
- 2021-03-17
- Volume
- 16
- Issue
- 4
- Pages
- 1799-1819
- ISSN
- 1975-0102 (ISSN-L)
- 2093-7423
- PMC
- PMC7968141
- OpenAlex
- W3138596490
- Cited by
- 17
- References
- 46
- Citations by year
- 2025: 5 · 2024: 4 · 2023: 2 · 2022: 5 · 2021: 1
- FWCI
- 1.34
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of Electrical Engineering and Technology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Power Systems Fault Detection
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Power System Optimization and Stability
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electrical Fault Detection and Protection
- Keywords
- underground power cables, fault detection and isolation, smart grid, phasor data concentrator, micro-phasor measurement units, ZigBee, fault classification, distribution networks, distributed parameter modeling, energy consumption reduction
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