@article{MAKHILLJEAS20061212556,
    title = {Multi Neural Network Based Approach for Fault Detection and Diagnosis of A Dc Motor},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {1},
    number = {2},
    pages = {143-148},
    year = {2006},
    issn = {1816-949x},
    doi = {jeasci.2006.143.148},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2006.143.148},
    author = {Y. Selaimia,H.A. Abbassi and},
    keywords = {Fault detection and diagnosis,multi neural network,Radial Basis Function (RBF) neural network,dc motor},
    abstract = {Recently, neural networks have emerged as potential tools in the area of fault detection and diagnosis. This study explores a multi neural network based fault detection and diagnosis approach. The network architecture adopted is an RBF. The approach has been applied for detection and diagnosis of suitable parameters failures on a dc motor. The simulation results illustrated that after training of the neural networks, the system is able to detect the different failures.}
    }