Advancing Fault Detection in HVAC Systems: Unifying Gramian Angular Field and 2D Deep Convolutional Neural Networks for Enhanced Performance

Efficiency and comfort in buildings rely on on well-functioning HVAC systems. However, system faults can compromise performance. Modern data-driven fault detection methods, considering diverse techniques, encounter challenges in understanding intricate interactions and adapting to dynamic conditions...

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Principais autores:	Wunna Tun, Kwok-Wai (Johnny) Wong, Sai-Ho Ling
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2023-09-01
Colecção:	Sensors
Assuntos:	heating, ventilation and air conditioning (HVAC) Gramian angular field (GAF) convolutional neural networks (CNNs) fault detection and diganosis (FDD) HVAC SIMulation PLUS (HVACSIM+)
Acesso em linha:	https://www.mdpi.com/1424-8220/23/18/7690
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