Cargando…

A labeled dataset for building HVAC systems operating in faulted and fault-free states

Open data is fueling innovation across many fields. In the domain of building science, datasets that can be used to inform the development of operational applications - for example new control algorithms and performance analysis methods - are extremely difficult to come by. This article summarizes t...

Descripción completa

Detalles Bibliográficos
Autores principales: Granderson, Jessica, Lin, Guanjing, Chen, Yimin, Casillas, Armando, Wen, Jin, Chen, Zhelun, Im, Piljae, Huang, Sen, Ling, Jiazhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10235024/
https://www.ncbi.nlm.nih.gov/pubmed/37264019
http://dx.doi.org/10.1038/s41597-023-02197-w
Descripción
Sumario:Open data is fueling innovation across many fields. In the domain of building science, datasets that can be used to inform the development of operational applications - for example new control algorithms and performance analysis methods - are extremely difficult to come by. This article summarizes the development and content of the largest known public dataset of building system operations in faulted and fault free states. It covers the most common HVAC systems and configurations in commercial buildings, across a range of climates, fault types, and fault severities. The time series points that are contained in the dataset include measurements that are commonly encountered in existing buildings as well as some that are less typical. Simulation tools, experimental test facilities, and in-situ field operation were used to generate the data. To inform more data-hungry algorithms, most of the simulated data cover a year of operation for each fault-severity combination. The data set is a significant expansion of that first published by the lead authors in 2020.