Rafia Nishat Toma

Publication Activity (10 Years)

Years Active: 2020-2022
Publications (10 Years): 8

Top Topics

Induction Motor

Tennessee Eastman

Machine Learning

Top Venues

Publications

Rafia Nishat Toma, Yangde Gao, Farzin Piltan, Kichang Im, Dongkoo Shon, Tae Hyun Yoon, Dae-Seung Yoo, Jong-Myon Kim
Classification Framework of the Bearing Faults of an Induction Motor Using Wavelet Scattering Transform-Based Features. Sensors 22 (22) (2022)
Rafia Nishat Toma, Yangde Gao, Jong-Myon Kim
Data-Driven Fault Classification of Induction Motor Based on Recurrence Plot and Deep Convolution Neural Network. MLIS (2022)
Rafia Nishat Toma, Farzin Piltan, Kichang Im, Dongkoo Shon, Tae Hyun Yoon, Dae-Seung Yoo, Jong-Myon Kim
A Bearing Fault Classification Framework Based on Image Encoding Techniques and a Convolutional Neural Network under Different Operating Conditions. Sensors 22 (13) (2022)
Yangde Gao, Farzin Piltan, Zahoor Ahmad, Rafia Nishat Toma, Jong-Myon Kim
A Novel Fault Diagnosis Method Based on MADCNN for Rolling Bearings. MLIS (2022)
Farzin Piltan, Rafia Nishat Toma, Dongkoo Shon, Kichang Im, Hyun-Kyun Choi, Dae-Seung Yoo, Jong-Myon Kim
Strict-Feedback Backstepping Digital Twin and Machine Learning Solution in AE Signals for Bearing Crack Identification. Sensors 22 (2) (2022)
Rafia Nishat Toma, Jong-Myon Kim
Bearing Fault Classification of Induction Motor Using Statistical Features and Machine Learning Algorithms. ISDA (2021)
Rafia Nishat Toma, Farzin Piltan, Jong-Myon Kim
A Deep Autoencoder-Based Convolution Neural Network Framework for Bearing Fault Classification in Induction Motors. Sensors 21 (24) (2021)
Rafia Nishat Toma, Alexander E. Prosvirin, Jong-Myon Kim
Bearing Fault Diagnosis of Induction Motors Using a Genetic Algorithm and Machine Learning Classifiers. Sensors 20 (7) (2020)