Detecção e diagnóstico de falhas em sistemas HVAC e sua relação com o desempenho energético de edificações: uma análise bibliométrica

Vollständiger Abstract

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Heating, ventilation, and air conditioning systems (HVAC) play an important role in the energy performance of buildings and faults in their components can compromise operational efficiency, increasing energy consumption. This study analyzed the scientific literature on fault detection and diagnosis (FDD) in HVAC systems and its relationship with building energy performance, seeking to understand the evolution of the topic and its main trends. A bibliometric analysis was conducted using publications indexed in the Web of Science database, covering the period from 2016 to 2026. Scientific production increased throughout the period, with a concentration of publications in journals focused on energy and buildings. Among the most frequent terms were fault detection, diagnosis, energy efficiency, HVAC system, model, and strategy. In recent years, approaches related to machine learning, prediction, prognostics, optimization, and predictive control have become more prominent. The results indicate that research has broadened its focus from fault identification and diagnosis to studies that also address prediction, prognostics, optimization, and control, strengthening the connection between FDD and building energy performance.