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 …

Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice

E Zio - Reliability Engineering & System Safety, 2022 - Elsevier
We are performing the digital transition of industry, living the 4th industrial revolution,
building a new World in which the digital, physical and human dimensions are interrelated in …

State-of-the-art on research and applications of machine learning in the building life cycle

T Hong, Z Wang, X Luo, W Zhang - Energy and Buildings, 2020 - Elsevier
Fueled by big data, powerful and affordable computing resources, and advanced algorithms,
machine learning has been explored and applied to buildings research for the past decades …

[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 …

[HTML][HTML] Challenges and opportunities of AI-enabled monitoring, diagnosis & prognosis: A review

Z Zhao, J Wu, T Li, C Sun, R Yan, X Chen - Chinese Journal of Mechanical …, 2021 - Springer
Abstract Prognostics and Health Management (PHM), including monitoring, diagnosis,
prognosis, and health management, occupies an increasingly important position in reducing …

Study on deep reinforcement learning techniques for building energy consumption forecasting

T Liu, Z Tan, C Xu, H Chen, Z Li - Energy and Buildings, 2020 - Elsevier
Reliable and accurate building energy consumption prediction is becoming increasingly
pivotal in building energy management. Currently, data-driven approach has shown …

A review of data-driven fault detection and diagnosis methods: Applications in chemical process systems

N Md Nor, CR Che Hassan… - Reviews in Chemical …, 2020 - degruyter.com
Fault detection and diagnosis (FDD) systems are developed to characterize normal
variations and detect abnormal changes in a process plant. It is always important for early …

[HTML][HTML] Multi-step short-term power consumption forecasting with a hybrid deep learning strategy

K Yan, X Wang, Y Du, N Jin, H Huang, H Zhou - Energies, 2018 - mdpi.com
Electric power consumption short-term forecasting for individual households is an important
and challenging topic in the fields of AI-enhanced energy saving, smart grid planning …

[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 …