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Tian_et_al_2023_Arc_Fault_AI_Review.pdf
TRANSLATING IDEA • ACTIVE
AIMS
Mathematical Biosciences
and Engineering
http://www.aimspress.com/journal/mbe
Review

Arc fault detection using artificial intelligence: Challenges and benefits

Chunpeng Tian1, Zhaoyang Xu2, Lukun Wang1 and Yunjie Liu3,*
Abstract: This systematic review aims to investigate recent developments in the area of arc fault detection. The rising demand for electricity and concomitant expansion of energy systems has resulted in a heightened risk of arc faults and the likelihood of related fires, presenting a matter of considerable concern.
Translating Idea Before vs. After Accordion
Before (Dense Academic Original)

"The rising demand for electricity and concomitant expansion of energy systems has resulted in a heightened risk of arc faults..."

After (READit Plain Meaning)

"As electricity use grows and power grids expand alongside it, dangerous electrical sparks (arc faults) and fires are much more likely to happen."

Classified Dataset Hits: concomitant (C2) → happening at the same time heightened (C1) → increased
To address this challenge, this review focuses on the role of artificial intelligence (AI) in arc fault detection, with the objective of illuminating its advantages and identifying current limitations. Through a meticulous literature selection process, a total of 63 articles were included in the final analysis. The findings of this review suggest that AI plays a significant role in enhancing the accuracy and speed of detection and allowing for customization to specific types of faults in arc fault detection. Simultaneously, three major challenges were also identified, including missed and false detections, the restricted application of neural networks and the paucity of relevant data.
Quick Reference • Passive Voice Resolver
Before (Ambiguous Passive Voice)

"...three major challenges were also identified, including missed and false detections... and the paucity of relevant data."

After (Active Subject & Antecedent Linked)

Who identified them? → The authors (Tian et al., 2023) across the 63 analyzed articles.
Active Rewrite: "By analyzing those 63 papers, the authors identified three major AI challenges: missed/false alarms, limited neural network flexibility, and a shortage (paucity) of training data."

In conclusion, AI has exhibited tremendous potential for transforming the field of arc fault detection and holds substantial promise for enhancing electrical safety.
Keywords: arc fault detection; artificial intelligence; detection methods; arc fault location; electric fire
1. Introduction

The proliferation of urbanization and industrialization has resulted in a surging demand for energy, necessitating the development of new and efficient energy systems. Nonetheless, the outdated nature of current photovoltaic and energy storage systems has given rise to numerous incidents of arc faults [1]. It has been well established that arc faults can have hazardous and disruptive consequences, a number of which are depicted in Figure 1. Perhaps the most critical of these dangers is the risk of fire, as

Easy Citation [1] • Brought to Your Text
Before (Scroll 18 Pages to Bibliography)

Reader only sees [1] and loses reading flow scrolling to the end of the PDF to check what study backs this claim.

After (Instant Inline Reference Card)
[1] Lu, S., Phung, B. T., & Zhang, D. (2018). "A comprehensive review on DC arc fault detection in photovoltaic systems." IEEE Trans. Power Delivery.
Why it's cited here: Confirms that aging solar (photovoltaic) inverters and degraded cable insulation are the primary triggers for DC series arc faults in modern grids.
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CLASSIFIED LEXICAL DATASET

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CEFR & Tier Class
C2 • Academic Tier 1
Adjective • Formal
Plain English Equivalent
"happening at the same time; accompanying"
Used when two trends expand together (e.g., electricity demand + grid size).
Verified Native Dataset Translations:
🇮🇩 Bahasa Indonesia yang menyertai / terjadi bersamaan
🇪🇸 Español simultáneo / que acompaña
🇨🇳 中文 (Simplified) 伴随的 / 同时发生的
🇯🇵 日本語 付随する / 同時に起こる
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