18518712. SERIES ARC-FAULT DETECTION APPARATUS AND METHOD simplified abstract (ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE)
Contents
- 1 SERIES ARC-FAULT DETECTION APPARATUS AND METHOD
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SERIES ARC-FAULT DETECTION APPARATUS AND METHOD - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
SERIES ARC-FAULT DETECTION APPARATUS AND METHOD
Organization Name
ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE
Inventor(s)
SERIES ARC-FAULT DETECTION APPARATUS AND METHOD - A simplified explanation of the abstract
This abstract first appeared for US patent application 18518712 titled 'SERIES ARC-FAULT DETECTION APPARATUS AND METHOD
Simplified Explanation
The present invention is a series arc-fault detection apparatus and method that utilizes a deep learning inference model to estimate whether an arc-fault occurs based on signal data generated from a current signal detected by a current transformer.
- Signal processing unit generates signal data for estimation by a deep learning inference model.
- Inference unit estimates whether an arc-fault occurs based on the deep learning inference model through the signal data generated by the signal processing unit.
Potential Applications
The technology can be applied in various industries where arc-fault detection is crucial, such as electrical systems in buildings, industrial machinery, and power distribution networks.
Problems Solved
1. Early detection of arc-faults can prevent electrical fires and equipment damage. 2. Traditional arc-fault detection methods may have limitations in accuracy and efficiency, which this technology aims to improve.
Benefits
1. Improved safety by quickly identifying and responding to arc-faults. 2. Enhanced reliability of electrical systems. 3. Potential cost savings by preventing damage and downtime due to arc-fault incidents.
Potential Commercial Applications
Enhancing arc-fault detection systems in residential, commercial, and industrial settings for improved safety and reliability.
Possible Prior Art
Prior art in arc-fault detection includes traditional methods such as overcurrent protection devices and arc-fault circuit interrupters. However, the use of deep learning inference models for arc-fault detection is a novel approach that may offer improved accuracy and efficiency.
Unanswered Questions
How does the deep learning inference model improve arc-fault detection compared to traditional methods?
The deep learning inference model can analyze complex patterns in the signal data to accurately identify potential arc-faults, which may be challenging for traditional methods that rely on predefined rules and thresholds.
What are the potential limitations or challenges of implementing this technology in real-world applications?
Some potential challenges could include the need for extensive training data to optimize the deep learning model, as well as ensuring the reliability and robustness of the system in various operating conditions and environments.
Original Abstract Submitted
The present invention relates to a series arc-fault detection apparatus and method, and the series arc-fault detection apparatus according to some embodiments of the present invention includes a signal processing unit configured to generate signal data for estimation by a deep learning inference model by signal-processing a current signal detected by a current transformer and an inference unit configured to estimate whether an arc-fault occurs based on the deep learning inference model through the signal data generated by the signal processing unit.
