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 …

Similarity learning-based fault detection and diagnosis in building HVAC systems with limited labeled data

Z Chen, F Xiao, F Guo - Renewable and Sustainable Energy Reviews, 2023 - Elsevier
Abstract Machine learning has been widely adopted for fault detection and diagnosis (FDD)
in heating, ventilation and air conditioning (HVAC) systems over the past decade due to the …

Identification of typical building daily electricity usage profiles using Gaussian mixture model-based clustering and hierarchical clustering

K Li, Z Ma, D Robinson, J Ma - Applied energy, 2018 - Elsevier
This paper presents a clustering-based strategy to identify typical daily electricity usage
(TDEU) profiles of multiple buildings. Different from the majority of existing clustering …

A decision tree based data-driven diagnostic strategy for air handling units

R Yan, Z Ma, Y Zhao, G Kokogiannakis - Energy and Buildings, 2016 - Elsevier
Data-driven methods for fault detection and diagnosis of air handling units (AHUs) have
attracted wide attention as they do not require high-level expert knowledge of the system of …

Railway bridge structural health monitoring and fault detection: State-of-the-art methods and future challenges

M Vagnoli, R Remenyte-Prescott… - Structural Health …, 2018 - journals.sagepub.com
Railway importance in the transportation industry is increasing continuously, due to the
growing demand of both passenger travel and transportation of goods. However, more than …

Sensor data validation and fault diagnosis using Auto-Associative Neural Network for HVAC systems

M Elnour, N Meskin, M Al-Naemi - Journal of Building Engineering, 2020 - Elsevier
Abstract The Heating, Ventilation, and Air conditioning (HVAC) system is a major system in
buildings for conditioning the indoor environment. Sensor data validation and fault diagnosis …

A study on semi-supervised learning in enhancing performance of AHU unseen fault detection with limited labeled data

C Fan, Y Liu, X Liu, Y Sun, J Wang - Sustainable Cities and Society, 2021 - Elsevier
The fault detection and diagnosis (FDD) of air handling units (AHUs) serves as a major task
in building operation management and energy savings. Data-driven classification methods …

A review of the Digital Twin technology for fault detection in buildings

HH Hosamo, HK Nielsen, AN Alnmr… - Frontiers in Built …, 2022 - frontiersin.org
This study aims to evaluate the utilization of technology known as Digital Twin for fault
detection in buildings. The strategy consisted of studying existing applications, difficulties …