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  Published Paper Details:

  Paper Title

ENGINE FAULT DETECTION USING NEURAL NETWORKS

  Authors

  Parikshith H,  Keerthi Vaidyanath HR,  Sneha M,  R N Sai Madhav

  Keywords

Neural Networks, Fault Detection, Wavelet Neural networks, RBF Neural Networks.

  Abstract


A number of fault detection systems for vehicle maintenance, repair have been developed in recent years. These systems are used for diagnosing variety of faults in the vehicle and are available at service level. A wavelet neural networks model is constructed based on wavelet frame theory and neural networks technology. The model is validated through the testing that simulates the faults of engine. RBF neural networks are trained to detect and diagnose the faults, and also to indicate fault size, by recognising the different fault patterns occurring in the dynamic data.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2204497

  Paper ID - 218597

  Page Number(s) - e304-e307

  Pubished in - Volume 10 | Issue 4 | April 2022

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Parikshith H,  Keerthi Vaidyanath HR,  Sneha M,  R N Sai Madhav,   "ENGINE FAULT DETECTION USING NEURAL NETWORKS", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.10, Issue 4, pp.e304-e307, April 2022, Available at :http://www.ijcrt.org/papers/IJCRT2204497.pdf

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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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