Morlet Wavelet Features and ResNet for Arc Fault Detection: A Research Study on Research Square

2023-03-21 08:12:14 By : Ms. Angela Ni
Research On <a href='/arc-fault-detection/'>Arc Fault Detection</a> Using Morlet Wavelet Features And ResNet | Research Square



In today's fast-paced world, the demand for energy storage solutions is on the rise. The international electric market operation concept calls for professional energy storage power supply solutions to meet the needs of the market. CEJIA, with over 20 years of experience in the industry, has established a reputation for providing quality products and services at competitive prices. In this blog, we will explore the latest research in Arc Fault Detection using Morlet Wavelet Features and ResNet.

Arcing faults, which occur due to damaged insulation, loose connections, or equipment failure, can cause serious damage to electrical systems. Traditional fault detection methods involve isolating the faulty circuit manually, which can be time-consuming and costly. Arc Fault Detection (AFD) is an emerging field that uses advanced algorithms and machine learning techniques to detect, locate, and classify arcing faults in real-time.

Research On Arc Fault Detection Using Morlet Wavelet Features And ResNet | Research Square

One of the recent studies, published on Research Square, presents an AFD method based on Morlet wavelet features and ResNet, a deep learning neural network. The Morlet wavelet, a complex-valued continuous wavelet, is used to decompose the electrical signal into time-frequency domain features. ResNet, on the other hand, helps in training the AFD model using a deep convolutional neural network architecture.

The proposed AFD method outperforms traditional methods in terms of accuracy, speed, and reliability. The results show that the Morlet wavelet and ResNet-based AFD method can accurately identify and locate arcing faults even in noisy electrical signals.

CEJIA's energy storage solutions are designed to provide uninterrupted power supply while improving the efficiency and reliability of the entire electrical system. Our products are equipped with advanced safety features, including AFD, to ensure maximum protection against arcing faults.

In conclusion, Arc Fault Detection using Morlet Wavelet Features and ResNet is a promising method for identifying and locating arcing faults in real-time. CEJIA, with its extensive experience in the industry, is committed to providing high-quality energy storage solutions that meet the demands of the international electric market operation concept. With our advanced products and services, you can ensure uninterrupted power supply, maximum safety, and a more efficient and reliable electrical system.