Bearing Fault Diagnosis of Induction Motors Using a Genetic Algorithm and Machine Learning Classifiers. - Rafia Nishat Toma; Alexander E. Prosvirin; Jong-Myon Kim (Sensors, 2020)

Bearing Fault Classification of Induction Motor Using Statistical Features and Machine Learning Algorithms. - Rafia Nishat Toma; Jong-Myon Kim (ISDA, 2021)

A Deep Autoencoder-Based Convolution Neural Network Framework for Bearing Fault Classification in Induction Motors. - Rafia Nishat Toma; Farzin Piltan; Jong-Myon Kim (Sensors, 2021)

A Novel Fault Diagnosis Method Based on MADCNN for Rolling Bearings. - Yangde Gao; Farzin Piltan; Zahoor Ahmad; Rafia Nishat Toma; Jong-Myon Kim (MLIS, 2022)

Data-Driven Fault Classification of Induction Motor Based on Recurrence Plot and Deep Convolution Neural Network. - Rafia Nishat Toma; Yangde Gao; Jong-Myon Kim (MLIS, 2022)

Strict-Feedback Backstepping Digital Twin and Machine Learning Solution in AE Signals for Bearing Crack Identification. - Farzin Piltan; Rafia Nishat Toma; Dongkoo Shon; Kichang Im; Hyun-Kyun Choi; Dae-Seung Yoo; Jong-Myon Kim (Sensors, 2022)

Classification Framework of the Bearing Faults of an Induction Motor Using Wavelet Scattering Transform-Based Features. - Rafia Nishat Toma; Yangde Gao; Farzin Piltan; Kichang Im; Dongkoo Shon; Tae Hyun Yoon; Dae-Seung Yoo; Jong-Myon Kim (Sensors, 2022)

A Bearing Fault Classification Framework Based on Image Encoding Techniques and a Convolutional Neural Network under Different Operating Conditions. - Rafia Nishat Toma; Farzin Piltan; Kichang Im; Dongkoo Shon; Tae Hyun Yoon; Dae-Seung Yoo; Jong-Myon Kim (Sensors, 2022)

Transfer Learning with Domain Adaptation for Unlabelled Sensor Faulty Data Classification. - Md. Nazmul Hasan; Rafia Nishat Toma; Sana Ullah Jan; Insoo Koo (ICTC, 2024)