A multitask-aided transfer learning-based diagnostic framework for bearings under inconsistent working conditions.
(2020)
Journal Article
HASAN, M.J., SOHAIB, M. and KIM, J.-M. 2020. A multitask-aided transfer learning-based diagnostic framework for bearings under inconsistent working conditions. Sensors [online], 20(24): deep learning, artificial neural networks and sensors for fault diagnosis, article 7205. Available from: https://doi.org/10.3390/s20247205
Rolling element bearings are a vital part of rotating machines and their sudden failure can result in huge economic losses as well as physical causalities. Popular bearing fault diagnosis techniques include statistical feature analysis of time, frequ... Read More about A multitask-aided transfer learning-based diagnostic framework for bearings under inconsistent working conditions..