Abstract
This paper uses information fusion and neural net technology as theoretical basis for building a fused neural network model and a neural network fault diagnosis for a fan. In the model, the homogeneous information is fused by the most closest clustering algorithm and the multi-source information is composed by the artificial neural network technology. And then the fused results are used as an input source for neural network diagnosis. In such a way, the intelligent diagnosis is realized and the effect is good.
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.
