Advance and prospect of machine learning based fault detection and diagnosis in air conditioning systems
Y Guo, Y Liu, Y Wang, Z Wang, Z Zhang… - … and Sustainable Energy …, 2024 - Elsevier
Fault detection and diagnosis (FDD) are crucial aspects of maintaining efficient and energy-
saving heating ventilation and air conditioning (HVAC) systems. Conditions such as …
saving heating ventilation and air conditioning (HVAC) systems. Conditions such as …
[HTML][HTML] Exploring the comprehensive integration of artificial intelligence in optimizing HVAC system operations: A review and future outlook
With the rapid development of the artificial intelligence (AI) technology, its application in
optimizing heating, ventilation and air-conditioning (HVAC) systems operation is becoming …
optimizing heating, ventilation and air-conditioning (HVAC) systems operation is becoming …
Sensor fault diagnosis and correction for data center cooling system using hybrid multi-label random Forest and Bayesian Inference
J Wang, Y Tian, Z Qi, L Zeng, P Wang, S Yoon - Building and Environment, 2024 - Elsevier
The measurement biases in working sensors significantly hampers the effective operation
and control of cooling systems in the data center. However, previous studies only focus on …
and control of cooling systems in the data center. However, previous studies only focus on …
An interpretable graph convolutional neural network based fault diagnosis method for building energy systems
G Li, Z Yao, L Chen, T Li, C Xu - Building Simulation, 2024 - Springer
Due to the fast-modeling speed and high accuracy, deep learning has attracted great
interest in the field of fault diagnosis in building energy systems in recent years. However …
interest in the field of fault diagnosis in building energy systems in recent years. However …
Adaptive fusion graph convolutional network based interpretable fault diagnosis method for HVAC systems enhanced by unlabeled data
Q Deng, Z Chen, W Zhu, Z Li, Y Yuan, Y Wang - Energy and Buildings, 2024 - Elsevier
Fault diagnosis is critical in maintaining the operational stability and reliability of Heating,
Ventilation, and Air Conditioning (HVAC) systems, which are crucial for ensuring indoor …
Ventilation, and Air Conditioning (HVAC) systems, which are crucial for ensuring indoor …
[HTML][HTML] Active learning concerning sampling cost for enhancing AI-enabled building energy system modeling
Abstract Machine learning is widely recognized as a promising data-driven modeling
technique for the model-based control and optimization of building energy systems …
technique for the model-based control and optimization of building energy systems …
Semi-supervised CWGAN-GP modeling for AHU AFDD with high-quality synthetic data filtering mechanism
Supervised learning methods demonstrated high classification accuracy for air handling unit
(AHU) automated fault detection and diagnosis (FDD) scenarios with well-shaped training …
(AHU) automated fault detection and diagnosis (FDD) scenarios with well-shaped training …
Effects of various information scenarios on layer-wise relevance propagation-based interpretable convolutional neural networks for air handling unit fault diagnosis
Deep learning (DL), especially convolutional neural networks (CNNs), has been widely
applied in air handling unit (AHU) fault diagnosis (FD). However, its application faces two …
applied in air handling unit (AHU) fault diagnosis (FD). However, its application faces two …
Extraction method of typical IEQ spatial distributions based on low-rank sparse representation and multi-step clustering
Indoor environment quality (IEQ) is one of the most concerned building performances during
the operation stage. The non-uniform spatial distribution of various IEQ parameters in large …
the operation stage. The non-uniform spatial distribution of various IEQ parameters in large …
Enabling efficient cross-building HVAC fault inferences through novel unsupervised domain adaptation methods
Y Lei, C Fan, H He, Y **e - Building and Environment, 2025 - Elsevier
Transfer learning-based methods have been proposed in the building field to integrate
operational data from multiple buildings for data-driven model development and thereby …
operational data from multiple buildings for data-driven model development and thereby …