Results 1 to 10 of about 227 (82)

AI in HVAC fault detection and diagnosis: A systematic review

Energy Reviews
Recent studies show that artificial intelligence (AI), such as machine learning and deep learning, models can be adopted and have advantages in fault detection and diagnosis for building energy systems.
Jian Bi, Hua Wang, Enbo Yan, Chuan Wang, Ke Yan, Liangliang Jiang, Bin Yang   +6 more
doaj   +3 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

Development and Validation of a Data-Driven Fault Detection and Diagnosis System for Chillers Using Machine Learning Algorithms

Energies, 2021
Fault detection and diagnosis (FDD) systems enable high cost savings and energy savings that could have economic and environmental impact. This study aims to develop and validate a data-driven FDD system for a chiller.
Icksung Kim, Woohyun Kim
doaj   +1 more source

Integrated Fault–Tolerant Control of a Quadcopter UAV with Incipient Actuator Faults

International Journal of Applied Mathematics and Computer Science, 2022
An integrated approach to the fault-tolerant control (FTC) of a quadcopter unmanned aerial vehicle (UAV) with incipient actuator faults is presented.
Kantue Paulin, Pedro Jimoh O.
doaj   +1 more source

An integrated methodology for fault detection, root cause diagnosis, and propagation pathway analysis in chemical process systems

Cleaner Engineering and Technology, 2021
Although the current research on fault detection and diagnosis (FDD) has made significant developments, there exists some challenges such as earlier fault detection with lower false alarms, accurate fault diagnosis without prior fault information, and ...
Md. Tanjin Amin
doaj   +1 more source

Unknown input observer design for fault detection and diagnosis in a continuous stirred-tank reactor [PDF]

E3S Web of Conferences, 2019
Early and accurate fault detection and diagnosis (FDD) minimises downtime, increases the safety and reliability of plant operation, and reduces manufacturing costs.
Al-Shatri Ali H., Arshad Ahmad, Olagoke Oladokun, Nyakuma Bemgba B.   +3 more
doaj   +1 more source

Fault Detection and Diagnosis of the Electric Motor Drive and Battery System of Electric Vehicles

Machines, 2023
Fault detection and diagnosis (FDD) is of utmost importance in ensuring the safety and reliability of electric vehicles (EVs). The EV’s power train and energy storage, namely the electric motor drive and battery system, are critical components that are ...
Mohammad Zamani Khaneghah, Mohamad Alzayed, Hicham Chaoui   +2 more
doaj   +1 more source

Challenges and Opportunities of Deep Learning Models for Machinery Fault Detection and Diagnosis: A Review

IEEE Access, 2019
In the age of industry 4.0, deep learning has attracted increasing interest for various research applications. In recent years, deep learning models have been extensively implemented in machinery fault detection and diagnosis (FDD) systems.
Syahril Ramadhan Saufi, Zair Asrar Bin Ahmad, Mohd Salman Leong, Meng Hee Lim   +3 more
doaj   +1 more source