A review of data-driven fault detection and diagnostics for building HVAC systems

Z Chen, Z O'Neill, J Wen, O Pradhan, T Yang, X Lu… - Applied Energy, 2023 - Elsevier
With the wide adoption of building automation system, and the advancement of data,
sensing, and machine learning techniques, data-driven fault detection and diagnostics …

A review of computing-based automated fault detection and diagnosis of heating, ventilation and air conditioning systems

J Chen, L Zhang, Y Li, Y Shi, X Gao, Y Hu - Renewable and Sustainable …, 2022 - Elsevier
Abstract Faults in Heating, Ventilation, and Air Conditioning (HVAC) systems of buildings
result in significant energy waste in building operation. With fast-growing sensing data …

Artificial intelligence-based fault detection and diagnosis methods for building energy systems: Advantages, challenges and the future

Y Zhao, T Li, X Zhang, C Zhang - Renewable and Sustainable Energy …, 2019 - Elsevier
Artificial intelligence has showed powerful capacity in detecting and diagnosing faults of
building energy systems. This paper aims at making a comprehensive literature review of …

[HTML][HTML] A review of data mining technologies in building energy systems: Load prediction, pattern identification, fault detection and diagnosis

Y Zhao, C Zhang, Y Zhang, Z Wang, J Li - Energy and Built Environment, 2020 - Elsevier
With the advent of the era of big data, buildings have become not only energy-intensive but
also data-intensive. Data mining technologies have been widely utilized to release the …

Practical issues in implementing machine-learning models for building energy efficiency: Moving beyond obstacles

Z Wang, J Liu, Y Zhang, H Yuan, R Zhang… - … and Sustainable Energy …, 2021 - Elsevier
Implementing machine-learning models in real applications is crucial to achieving intelligent
building control and high energy efficiency. Over the past few decades, numerous studies …

An explainable one-dimensional convolutional neural networks based fault diagnosis method for building heating, ventilation and air conditioning systems

G Li, Q Yao, C Fan, C Zhou, G Wu, Z Zhou… - Building and …, 2021 - Elsevier
Due to the frequently changed outdoor weather conditions and indoor requirements,
heating, ventilation and air conditioning (HVAC) experiences faulty operations inevitably …

Generative adversarial network for fault detection diagnosis of chillers

K Yan, A Chong, Y Mo - Building and Environment, 2020 - Elsevier
Automatic fault detection and diagnosis (AFDD) for chillers has significant impacts on energy
saving, indoor environment comfort and systematic building management. Recent works …

Unsupervised learning for fault detection and diagnosis of air handling units

K Yan, J Huang, W Shen, Z Ji - Energy and Buildings, 2020 - Elsevier
Supervised learning techniques have witnessed significant successes in fault detection and
diagnosis (FDD) for heating ventilation and air-conditioning (HVAC) systems. Despite the …

[HTML][HTML] Chiller faults detection and diagnosis with sensor network and adaptive 1D CNN

K Yan, X Zhou - Digital Communications and Networks, 2022 - Elsevier
Computer-empowered detection of possible faults for Heating, Ventilation and Air-
Conditioning (HVAC) subsystems, eg, chillers, is one of the most important applications in …

Deep learning-based fault diagnosis of variable refrigerant flow air-conditioning system for building energy saving

Y Guo, Z Tan, H Chen, G Li, J Wang, R Huang, J Liu… - Applied Energy, 2018 - Elsevier
The fault diagnosis of air-conditioning systems is of great significance to the energy saving
of buildings. This study proposes a novel fault diagnosis approach for building energy …