Fault Diagnosis of a Robot Manipulator Based on an ARX-Laguerre Fuzzy PID Observer. - Farzin Piltan; Muhammad Sohaib; Jong-Myon Kim (RiTA, 2017)

Fault Diagnosis of a Wireless Sensor Network Using a Hybrid Method. - Farzin Piltan; Jong-Myon Kim (PDCAT, 2018)

Robust Composite High-Order Super-Twisting Sliding Mode Control of Robot Manipulators. - Shahnaz Tayebi-Haghighi; Farzin Piltan; Jong-Myon Kim (Robotics, 2018)

Bearing Fault Diagnosis by a Robust Higher-Order Super-Twisting Sliding Mode Observer. - Farzin Piltan; Jong-Myon Kim (Sensors, 2018)

Bearing Fault Diagnosis Using an Extended Variable Structure Feedback Linearization Observer. - Farzin Piltan; Jong-Myon Kim (Sensors, 2018)

Advanced fuzzy-based leak detection and size estimation for pipelines. - Farzin Piltan; Jong-Myon Kim (J. Intell. Fuzzy Syst., 2020)

Robot manipulator active fault-tolerant control using a machine learning-based automated robust hybrid observer. - Farzin Piltan; Alexander E. Prosvirin; Jong-Myon Kim (J. Intell. Fuzzy Syst., 2020)

Blade Rub-Impact Fault Identification Using Autoencoder-Based Nonlinear Function Approximation and a Deep Neural Network. - Alexander E. Prosvirin; Farzin Piltan; Jong-Myon Kim (Sensors, 2020)

Crack Localization of Pipelines Using Machine Learning and Fuzzy Digital Twin. - Farzin Piltan; Jong-Myon Kim (ICTC, 2021)

An Adaptive-Backstepping Digital Twin-Based Approach for Bearing Crack Size Identification Using Acoustic Emission Signals. - Farzin Piltan; Jong-Myon Kim (ISDA, 2021)

Fault Diagnosis of Bearings Using an Intelligence-Based Autoregressive Learning Lyapunov Algorithm. - Farzin Piltan; Jong-Myon Kim (Int. J. Comput. Intell. Syst., 2021)

Deep Learning-Based Adaptive Neural-Fuzzy Structure Scheme for Bearing Fault Pattern Recognition and Crack Size Identification. - Farzin Piltan; Bach Phi Duong; Jong-Myon Kim (Sensors, 2021)

Crack Size Identification for Bearings Using an Adaptive Digital Twin. - Farzin Piltan; Jong-Myon Kim (Sensors, 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)

Hybrid Rubbing Fault Identification Using a Deep Learning-Based Observation Technique. - Alexander E. Prosvirin; Farzin Piltan; Jong-Myon Kim (IEEE Trans. Neural Networks Learn. Syst., 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)

Leak detection and localization for pipelines using multivariable fuzzy learning backstepping. - Farzin Piltan; Jong-Myon Kim (J. Intell. Fuzzy Syst., 2022)

A Hybrid Leak Localization Approach Using Acoustic Emission for Industrial Pipelines. - Yangde Gao; Farzin Piltan; Jong-Myon Kim (Sensors, 2022)

A Novel Image-Based Diagnosis Method Using Improved DCGAN for Rotating Machinery. - Yangde Gao; Farzin Piltan; Jong-Myon Kim (Sensors, 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)

LDDNet: A Deep Learning Framework for the Diagnosis of Infectious Lung Diseases. - Prajoy Podder; Sanchita Rani Das; M. Rubaiyat Hossain Mondal; Subrato Bharati; Azra Maliha; Md Junayed Hasan; Farzin Piltan (Sensors, 2023)

Bearing Fault Diagnosis Using a Hybrid Fuzzy V-Structure Fault Estimator Scheme. - Farzin Piltan; Jong-Myon Kim (Sensors, 2023)