A sample power system was modelled using MATLAB ... network structure and learning algorithm before choosing it for a practical application. The scope of ANN is wide enough and can be explored more.

Timely identification of potential fault risks based on equipment operation data can facilitate accurate maintenance and enhance production safety and efficiency. This study conducts fault detection ...

Abstract: This paper focuses on the vital task of utilizing Machine Learning techniques for fault detection and fault classification in electrical power transmission lines. It employs two distinct ...

In the first stage, signals are processed using ... a classification task. Furthermore, a multitask learning (MTL) based CNN is used in the next stage for the classification of the input data.

This paper is mainly emphasized on the classification of Power faults using machine learning along with artificial neural networks.Three models were considered, and all were analysed with different ...

The production of electrical energy based on wind power using ... to train fault detection algorithms. Figure 1. Supervised learning for fault diagnostics Supervised learning can be classified into ...

A machine learning project focused on developing an artificial neural network (ANN) for efficient fault detection and classification in power distribution systems. The model is designed to accurately ...

An international research team has developed a novel PV fault detection method based ... “The model is trained using the Adam optimizer with a learning rate of 0.0001 and categorical cross- ...

This study conducts fault detection and classification modeling using operational data from industrial equipment provided by a manufacturing enterprise. First, the raw data underwent data cleaning, ...