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LBNL Fault Detection and Diagnostics Datasets
Dataset

LBNL Fault Detection and Diagnostics Datasets

Jessica Granderson, Guanjing Lin, Yimin Chen, Armando Casillas, Piljae Im, Sungkyun Jung, Kyle Benne, Jiazhen Ling, Ravi Gorthala, Jin Wen, …
2022
DOI: https://doi.org/10.25984/1881324
url
https://data.openei.org/files/5763/Inventory of LBNL FDD Data Sets_FCU.pdfView
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Abstract

AHU air handler unit Algorithm testing Array benchmark Boiler plant Brick Schema building building efficiency building energy building energy efficiency Chiller plant Commercial Buildings cooling detection diagnostics energy efficiency Fan coil fault detection Fault Detection and Diagnostics heating heating and cooling HVAC Performance evaluation RTU VAV box
These datasets can be used to evaluate and benchmark the performance accuracy of Fault Detection and Diagnostics (FDD) algorithms or tools. It contains operational data from simulation, laboratory experiments, and field measurements from real buildings for seven HVAC systems/equipment (rooftop unit, single-duct air handler unit, dual-duct air handler unit, variable air volume box, fan coil unit, chiller plant, and boiler plant). Each dataset includes a .pdf file to document key information necessary to understand the content and scope, multiple csv files containing all the time-series data for faults at different severity levels and one fault-free case, and a ttl file to visualize the data according to BRICK schema. The dataset was created by LBNL, PNNL, NREL, ORNL and Drexel University.

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