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 …

Common human errors in design, installation, and operation of VAV AHU control systems–A review and a practitioner interview

N Torabi, HB Gunay, W O'Brien, T Barton - Building and Environment, 2022 - Elsevier
While the emphasis of fault detection and diagnostic (FDD) research has been on hard faults
(eg, stuck/leaking/broken valve or damper), soft faults or, in general, human errors account …

Transfer learning-based strategies for fault diagnosis in building energy systems

J Liu, Q Zhang, X Li, G Li, Z Liu, Y Xie, K Li, B Liu - Energy and Buildings, 2021 - Elsevier
Data-driven fault detection and diagnosis (FDD) in building energy systems is typically
limited by the quantity and quality of training data. These methods can be only used for …

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 …

A novel image-based transfer learning framework for cross-domain HVAC fault diagnosis: From multi-source data integration to knowledge sharing strategies

C Fan, W He, Y Liu, P Xue, Y Zhao - Energy and Buildings, 2022 - Elsevier
Data-driven classification models have gained increasing popularity for fault detection and
diagnosis (FDD) tasks considering their advantages in implementation flexibility and …

Building fault detection data to aid diagnostic algorithm creation and performance testing

J Granderson, G Lin, A Harding, P Im, Y Chen - Scientific data, 2020 - nature.com
It is estimated that approximately 4–5% of national energy consumption can be saved
through corrections to existing commercial building controls infrastructure and resulting …

Improved convolutional neural network chiller early fault diagnosis by gradient-based feature-level model interpretation and feature learning

G Li, L Chen, C Fan, J Gao, C Xu, X Fang - Applied Thermal Engineering, 2024 - Elsevier
For chillers, fault diagnosis (FD) is important for maintaining system reliability and
performance. Deep learning methods, such as convolutional neural network (CNN), have …

Using discrete Bayesian networks for diagnosing and isolating cross-level faults in HVAC systems

Y Chen, J Wen, O Pradhan, LJ Lo, T Wu - Applied Energy, 2022 - Elsevier
Fault detection and diagnosis (FDD) technologies are critical to ensure satisfactory building
performance, such as reducing energy wastes and negative impacts on occupant comfort …

Review on fault detection and diagnosis feature engineering in building heating, ventilation, air conditioning and refrigeration systems

G Li, Y Hu, J Liu, X Fang, J Kang - IEEE Access, 2020 - ieeexplore.ieee.org
Faults are inevitable in building energy systems, such as heating, ventilation, air
conditioning and refrigeration systems. With the increasing utilization of these systems, their …

Interpretable mechanism mining enhanced deep learning for fault diagnosis of heating, ventilation and air conditioning systems

K Chen, S Chen, X Zhu, X Jin, Z Du - Building and Environment, 2023 - Elsevier
Various faults in the heating, ventilation, and air conditioning (HVAC) systems may lead to
high energy consumption and maintenance costs. Reliable fault detection and diagnosis …