Abstract
The combined problem of fault detection and classification (referred to as fault diagnosis) of Direct Current (DC) electric motors via a simple, yet powerful, technique based on an Artificial Neural Network (ANN) is proposed. The ability of an ANN in identifying patterns with high fidelity—without the need of any rigorous mathematical model of the system under investigation—leads to an excellent diagnosis performance, even for faults that result in almost indistinguishable output system responses (both in time and in frequency domain). The flexibility and speed of the presented method indicate that it can easily be applied to on-line fault diagnosis as well.
Sign-in/Register to access full text options 
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.
