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@article{163227,
        author = {Akhil V A and Reshnu M and Saju P S and Dr. Rojin R.K},
        title = {Fault analysis and Predictive Maintenance of Induction Motor using Machine learning and Artificial Intelligence Algorithm},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {0},
        number = {no},
        pages = {51-55},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=163227},
        abstract = {Industries required early diagnosis of induction motor faults analysis to avoid complete failure. The use of Machine learning and Condition monitoring to detect fault has huge promise. Machine learning can be used to detect motor fault. To avoid losses, Fault detection using machine learning algorithm is an excellent method for preventive maintenance. This research develops a machine learning strategy based algorithms in order to learn the characteristics from vibration signal's frequency distribution. The status includes the parameters such as temperature, voltage, Current etc.
The aim of this project is to protect vital electrical components and to prevent a fast forward artificial neural network model to detect some of the commonly occurring electrical faults like over-voltage, Overload, single phasing, unbalance voltage, under voltage, unbalance voltage and current, ground fault, temperature and Vibration due to bearing fault and also winding faults.
},
        keywords = {Artificial Intelligence Algorithm, fault analysis, Induction motor, machine learning, Predictive maintenance.},
        month = {},
        }