Abstract
Bearings are the most important part of asynchronous motor. Failure of bearing in any asynchronous machine cannot be tolerated because it increases the downtime and cost of production. In this paper, an experimental technique of fault detection and diagnosis using time domain analysis (TDA) of recorded vibration signal and neural network is discussed. Results given in this paper are based on the experimental study carried out in laboratory.
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Shrivastava, A. (2020). Detection of Induction Motor Bearing Fault Using Time Domain Analysis and Feed-Forward Neural Network. In: Mathur, G., Sharma, H., Bundele, M., Dey, N., Paprzycki, M. (eds) International Conference on Artificial Intelligence: Advances and Applications 2019. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-1059-5_40
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DOI: https://doi.org/10.1007/978-981-15-1059-5_40
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Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-1058-8
Online ISBN: 978-981-15-1059-5
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