All Outputs (4)

Deep convolutional neural network with 2D spectral energy maps for fault diagnosis of gearboxes under variable speed. (2019)
Conference Proceeding
HASAN, M.J. and KIM, J. 2020. Deep convolutional neural network with 2D spectral energy maps for fault diagnosis of gearboxes under variable speed. In Djeddi, C., Jamil, A. and Siddiqi, I. (eds.) Pattern recognition and artificial intelligence: proceedings of the 3rd Mediterranean conference on pattern recognition and artificial intelligence (MedPRAI 2019), 22-23 December 2019, Istanbul, Turkey. Communications in computer and information science (CCIS), 1144. Cham: Springer [online], pages 106-117. Available from: https://doi.org/10.1007/978-3-030-37548-5_9

For industrial safety, correct classification of gearbox fault conditions is necessary. One of the most crucial tasks in data-driven fault diagnosis is determining the best set of features by analyzing the statistical parameters of the signals. Howev... Read More about Deep convolutional neural network with 2D spectral energy maps for fault diagnosis of gearboxes under variable speed..

A hybrid feature pool-based emotional stress state detection algorithm using EEG signals. (2019)
Journal Article
HASAN, M.J. and KIM, J.-M. 2019. A hybrid feature pool-based emotional stress state detection algorithm using EEG signals. Brain sciences [online], 9(12), article number 376. Available from: https://doi.org/10.3390/brainsci9120376

Human stress analysis using electroencephalogram (EEG) signals requires a detailed and domain‐specific information pool to develop an effective machine learning model. In this study, a multi‐domain hybrid feature pool is designed to identify most of... Read More about A hybrid feature pool-based emotional stress state detection algorithm using EEG signals..

Acoustic spectral imaging and transfer learning for reliable bearing fault diagnosis under variable speed conditions. (2019)
Journal Article
HASAN, M.J., ISLAM, M.M.M. and KIM, J.-M. 2019. Acoustic spectral imaging and transfer learning for reliable bearing fault diagnosis under variable speed conditions. Measurement [online], 138, pages 620-631. Available from: https://doi.org/10.1016/j.measurement.2019.02.075

Incipient fault diagnosis of a bearing requires robust feature representation for an accurate condition-based monitoring system. Existing fault diagnosis schemes are mostly confined to manual features and traditional machine learning approaches such... Read More about Acoustic spectral imaging and transfer learning for reliable bearing fault diagnosis under variable speed conditions..

Fault detection of a spherical tank using a genetic algorithm-based hybrid feature pool and k-nearest neighbor algorithm. (2019)
Journal Article
HASAN, M.J. and KIM, J.-M. 2019. Fault detection of a spherical tank using a genetic algorithm-based hybrid feature pool and k-nearest neighbor algorithm. Energies [online], 12(6): fault diagnosis and fault-tolerant control, article 991. Available from: https://doi.org/10.3390/en12060991

Fault detection in metallic structures requires a detailed and discriminative feature pool creation mechanism to develop an effective condition monitoring system. Traditional fault detection methods incorporate handcrafted features either from the ti... Read More about Fault detection of a spherical tank using a genetic algorithm-based hybrid feature pool and k-nearest neighbor algorithm..