Abstract
Induction motors are widely used in various industries for production processes due to their inherent characteristics like high reliability, robustness, low cost and ease of construction and operation. However, while in operation they face harsh and severe conditions imposed on them by the electrical, mechanical, thermal and environmental stresses which give rise to abnormalities in machine parameters such as voltages and currents. If the motor drive is allowed to continue to run under such situations, it will lead to catastrophic failure of the motor disrupting the production process and huge loss of revenue. Hence, an intelligent drive control method based on Hybrid Artificial Intelligence (AI) technique of Neuro-Genetic Algorithm is proposed in this paper for condition monitoring, fault diagnosis and evaluation of induction motor without any additional information. The hybrid architecture of Back Propagation Neural Network (BPN) to get the desired output fast and with Genetic Algorithm to overcome the computational complexity and time consuming process involved in BPN.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
