دورية أكاديمية

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

التفاصيل البيبلوغرافية
العنوان: A labeled dataset for building HVAC systems operating in faulted and fault-free states
المؤلفون: Jessica Granderson, Guanjing Lin, Yimin Chen, Armando Casillas, Jin Wen, Zhelun Chen, Piljae Im, Sen Huang, Jiazhen Ling
المصدر: Scientific Data, Vol 10, Iss 1, Pp 1-13 (2023)
بيانات النشر: Nature Portfolio, 2023.
سنة النشر: 2023
المجموعة: LCC:Science
مصطلحات موضوعية: Science
الوصف: Abstract 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.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2052-4463
Relation: https://doaj.org/toc/2052-4463
DOI: 10.1038/s41597-023-02197-w
URL الوصول: https://doaj.org/article/d8cbee367b4d4e7389baf74179a3848b
رقم الأكسشن: edsdoj.8cbee367b4d4e7389baf74179a3848b
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20524463
DOI:10.1038/s41597-023-02197-w