Publication2024
Time Frequency Analysis Based Fault Detection in PV Array Using Scaling Basis Chirplet Transform
The record
- Type
- Publication
- Date
- 1 December 2024
- Level
- National
- Journal
- Engineering Reports
- Volume
- 6
- Issue
- 12
- Published
- 1 December 2024
- DOI
- 10.1002/eng2.13016
- Scopus ID
- 85205877005
- ISSN
- 25778196
- Authors
- 5
- Open access
- Yes
- Citations
- 4
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
7 Ensure access to affordable, reliable, sustainable and modern energy for all
Time-frequency analysis using scaling basis chirplet transform with machine learning achieves 99% fault detection accuracy in photovoltaic arrays, minimizing energy losses and preventing system damage.
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-2.5 Green economy, energy transition and climate resilience
Renewable energy system reliability and maintenance directly support clean energy transition and green economy.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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Provenance
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “Time Frequency Analysis Based Fault Detection in PV Array Using Scaling Basis Chirplet Transform”. Kortex.