Characteristic Study and Time-Domain Discrete- Wavelet-Transform Based Hybrid Detection of Series DC Arc Faults

By Xiu Yao, Luis Herrera, Shengchang Ji, Ke Zou, Jin Wang. IEEE transactions on power electronics, 2014

209 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/49f5ba41d36131d0a3de4a98b4018837415b19e5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Nikola L. Georgijevic
2. M. Jankovic
3. Srdjan Srdic
4. Z. Radaković
5. Mohammed Khorshed Alam
6. F. Khan
7. Jay Johnson
8. J. Flicker

Citations in the corpus

• A Comprehensive Review of Catastrophic Faults in PV Arrays: Types, Detection, and Mitigation Techniques (2015, methodology): “, wavelet transformation and neural network analysis) to avoid any nuisance tripping and unwanted down time [32], [41].”
• The Detection of Series Arc Fault in Photovoltaic Systems Based on the Arc Current Entropy (2016, methodology): “The experimental study of dc arc characteristics is presented in [12], where the influence of arc length, electrodes diameter, dc-source voltage,”