Fault detection and diagnosis of large-scale HVAC systems in buildings using data-driven methods: A comprehensive review
MS Mirnaghi, F Haghighat - Energy and Buildings, 2020 - Elsevier
Abnormal operation of HVAC systems can result in an increase in energy usage as well as
poor indoor air quality, thermal discomfort, and low productivity. Building automated systems …
poor indoor air quality, thermal discomfort, and low productivity. Building automated systems …
A comprehensive review: Fault detection, diagnostics, prognostics, and fault modeling in HVAC systems
This review study examines the latest research and developments in the fault detection and
diagnostics of Heating Ventilation and Air Conditioning (HVAC) systems. This review …
diagnostics of Heating Ventilation and Air Conditioning (HVAC) systems. This review …
[HTML][HTML] Predictive maintenance enabled by machine learning: Use cases and challenges in the automotive industry
A Theissler, J Pérez-Velázquez, M Kettelgerdes… - Reliability engineering & …, 2021 - Elsevier
Recent developments in maintenance modelling fueled by data-based approaches such as
machine learning (ML), have enabled a broad range of applications. In the automotive …
machine learning (ML), have enabled a broad range of applications. In the automotive …
Tomek link and SMOTE approaches for machine fault classification with an imbalanced dataset
EF Swana, W Doorsamy, P Bokoro - Sensors, 2022 - mdpi.com
Data-driven methods have prominently featured in the progressive research and
development of modern condition monitoring systems for electrical machines. These …
development of modern condition monitoring systems for electrical machines. These …
[HTML][HTML] Digital twin enabled fault detection and diagnosis process for building HVAC systems
The emerging concept of digital twins outlines the pathway towards intelligent buildings.
Although abundant building data carries an overwhelming amount of information, if not well …
Although abundant building data carries an overwhelming amount of information, if not well …
Integrating model-driven and data-driven methods for power system frequency stability assessment and control
With increase of practical power system complexity, power system online stability
assessment and control is more and more important. Application of the traditional model …
assessment and control is more and more important. Application of the traditional model …
An intelligent fault diagnosis method of rolling bearings based on short-time Fourier transform and convolutional neural network
Q Zhang, L Deng - Journal of Failure Analysis and Prevention, 2023 - Springer
The rolling bearing is the key component of rotating machinery, and fault diagnosis for
rolling bearings can ensure the safe operation of rotating machinery. Fault diagnosis …
rolling bearings can ensure the safe operation of rotating machinery. Fault diagnosis …
Digital twin-based cyber-attack detection framework for cyber-physical manufacturing systems
Smart manufacturing (SM) systems utilize run-time data to improve productivity via intelligent
decision-making and analysis mechanisms on both machine and system levels. The …
decision-making and analysis mechanisms on both machine and system levels. The …
Fault diagnosis for open‐circuit faults in NPC inverter based on knowledge‐driven and data‐driven approaches
L Kou, C Liu, G Cai, J Zhou, Q Yuan… - IET Power …, 2020 - Wiley Online Library
In this study, the open‐circuit faults diagnosis and location issue of the neutral‐point‐
clamped (NPC) inverters are analysed. A novel fault diagnosis approach based on …
clamped (NPC) inverters are analysed. A novel fault diagnosis approach based on …
[HTML][HTML] Integrating PCA and structural model decomposition to improve fault monitoring and diagnosis with varying operation points
Fast and efficient fault monitoring and diagnostics methods are essential for fault diagnosis
and prognosis tasks in Health Monitoring Systems. These tasks are even more complicated …
and prognosis tasks in Health Monitoring Systems. These tasks are even more complicated …