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Fault Detection and Diagnosis in Industry 4.0: A Review on Challenges and Opportunities [PDF]

Sensors
Integrating Machine Learning (ML) in industrial settings has become a cornerstone of Industry 4.0, aiming to enhance production system reliability and efficiency through Real-Time Fault Detection and Diagnosis (RT-FDD).
Denis Leite, Emmanuel Andrade, Diego Rativa, Alexandre M. A. Maciel   +3 more
doaj   +2 more sources

A dataset for fault detection and diagnosis of an air handling unit from a real industrial facility [PDF]

Data in Brief, 2023
This dataset was collected for the purpose of applying fault detection and diagnosis (FDD) techniques to real data from an industrial facility. The data for an air handling unit (AHU) is extracted from a building management system (BMS) and aligned with ...
Michael Ahern, Dominic T.J. O'Sullivan, Ken Bruton   +2 more
doaj   +2 more sources

Fault-Tolerant Control for Quadcopters Under Actuator and Sensor Faults [PDF]

Sensors
Fault detection and diagnosis (FDD) methods and fault-tolerant control (FTC) have been the focus of intensive research across various fields to ensure safe operation, reduce costs, and optimize maintenance tasks.
Kenji Fabiano Ávila Okada, Aniel Silva Morais, Laura Ribeiro, Caio Meira Amaral da Luz, Fernando Lessa Tofoli, Gabriela Vieira Lima, Luís Cláudio Oliveira Lopes   +6 more
doaj   +2 more sources

Comprehensive dataset for fault detection and diagnosis in inverter-driven permanent magnet synchronous motor systemszenodo [PDF]

Data in Brief
This work introduces a new, comprehensive dataset for Fault Detection and Diagnosis (FDD) in inverter-driven Permanent Magnet Synchronous Motor (PMSM) systems.
Abdelkabir Bacha, Ramzi El Idrissi, Khalid Janati Idrissi, Fatima Lmai   +3 more
doaj   +2 more sources

DML–LLM Hybrid Architecture for Fault Detection and Diagnosis in Sensor-Rich Industrial Systems [PDF]

Sensors
Fault Detection and Diagnosis (FDD) in complex industrial systems requires methods that can handle uncertain operating conditions, soft thresholds, evolving sensor behavior, and increasing volumes of heterogeneous data.
Yu-Shu Hu, Saman Marandi, Mohammad Modarres   +2 more
doaj   +2 more sources

Particle-Filter-Based Fault Diagnosis for the Startup Process of an Open-Cycle Liquid-Propellant Rocket Engine [PDF]

Sensors
This study introduces a fault diagnosis algorithm based on particle filtering for open-cycle liquid-propellant rocket engines (LPREs). The algorithm serves as a model-based method for the startup process, accounting for more than 30% of engine failures ...
Jihyoung Cha, Sangho Ko, Soon-Young Park
doaj   +2 more sources

An Automated Machine Learning Approach for Real-Time Fault Detection and Diagnosis [PDF]

Sensors, 2022
This work presents a novel Automated Machine Learning (AutoML) approach for Real-Time Fault Detection and Diagnosis (RT-FDD). The approach’s particular characteristics are: it uses only data that are commonly available in industrial automation systems ...
Denis Leite, Aldonso Martins, Diego Rativa, Joao F. L. De Oliveira, Alexandre M. A. Maciel   +4 more
doaj   +2 more sources

Machine Learning-Based Fault Diagnosis for a PWR Nuclear Power Plant

IEEE Access, 2022
In the nuclear power industry, safety and reliability are of the utmost importance. Sensors and actuators are integral components in such systems, and potential faults may adversely impact system performance.
Amine Naimi, Jiamei Deng, Paul Doney, Akbar Sheikh-Akbari, S. R. Shimjith, A. John Arul   +5 more
doaj   +1 more source

Effective Fault Detection and Diagnosis for Power Converters in Wind Turbine Systems Using KPCA-Based BiLSTM

Energies, 2022
The current work presents an effective fault detection and diagnosis (FDD) technique in wind energy converter (WEC) systems. The proposed FDD framework merges the benefits of kernel principal component analysis (KPCA) model and the bidirectional long ...
Zahra Yahyaoui, Mansour Hajji, Majdi Mansouri, Kamaleldin Abodayeh, Kais Bouzrara, Hazem Nounou   +5 more
doaj   +1 more source

Fault Detection and Isolation of a Pressurized Water Reactor Based on Neural Network and K-Nearest Neighbor

IEEE Access, 2022
Nuclear power plants (NPPs) are complex dynamic systems with multiple sensors and actuators. The presence of faults in the actuators and sensors can deteriorate the system’s performance and cause serious safety issues.
Amine Naimi, Jiamei Deng, S. R. Shimjith, A. John Arul   +3 more
doaj   +1 more source