Author:
Moldovan Ovidiu Gheorghe,Ghincu Remus Vladimir,Moldovan Alin Octavian,Noje Dan,Tarca Radu Catalin
Abstract
The main objective of this paper is to investigate how a failure in the functioning of a normal electrical system represented by a three-phase asynchronous motor will modify the voltages and currents present in the system and if it is possible to design a system that is able to automatically detect the fault, based on the use of modern data acquisition system and powerful computer processing capabilities. The detection of faulty signals is realised using Feedforward Artificial Neural Networks.
Publisher
Agora University of Oradea
Subject
Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Flexible system architecture used to collect and store signals acquired by IoT devices;2024 16th International Conference on Electronics, Computers and Artificial Intelligence (ECAI);2024-06-27
2. Proposal of a Machine Learning Predictive Maintenance Solution Architecture;INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL;2024-05-04
3. Image Classification of Roughness using Feed Forward Artificial Neural Network;2023 17th International Conference on Engineering of Modern Electric Systems (EMES);2023-06-09
4. An Experimental Study on the Railway Track Surface Fault Detection with Automation;2023 17th International Conference on Engineering of Modern Electric Systems (EMES);2023-06-09