LBNL Fault Detection and Diagnostics Datasets
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.
Citation Formats
TY - DATA
AB - 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.
AU - Granderson, Jessica
A2 - Lin, Guanjing
A3 - Chen, Yimin
A4 - Casillas, Armando
A5 - Im, Piljae
A6 - Jung, Sungkyun
A7 - Benne, Kyle
A8 - Ling, Jiazhen
A9 - Gorthala, Ravi
A10 - Wen, Jin
A11 - Chen, Zhelun
A12 - Huang, Sen
A13 - Vrabie, Draguna
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Renewable Energy Laboratory
DO - 10.25984/1881324
KW - Commercial Buildings
KW - Fault Detection and Diagnostics
KW - HVAC
KW - Brick Schema
KW - Algorithm testing
KW - Performance evaluation
KW - AHU
KW - RTU
KW - Fan coil
KW - VAV box
KW - Chiller plant
KW - Boiler plant
KW - AC
KW - fault detection
KW - diagnostics
KW - detection
KW - benchmark
KW - building
KW - building energy
KW - building energy efficiency
KW - energy efficiency
KW - building efficiency
KW - air handler unit
KW - heating
KW - cooling
KW - heating and cooling
LA - English
DA - 2022/08/01
PY - 2022
PB - Lawrence Berkeley National Laboratory
T1 - LBNL Fault Detection and Diagnostics Datasets
UR - https://doi.org/10.25984/1881324
ER -
Granderson, Jessica, et al. LBNL Fault Detection and Diagnostics Datasets. Lawrence Berkeley National Laboratory, 1 August, 2022, Open Energy Data Initiative (OEDI). https://doi.org/10.25984/1881324.
Granderson, J., Lin, G., Chen, Y., Casillas, A., Im, P., Jung, S., Benne, K., Ling, J., Gorthala, R., Wen, J., Chen, Z., Huang, S., & Vrabie, D. (2022). LBNL Fault Detection and Diagnostics Datasets. [Data set]. Open Energy Data Initiative (OEDI). Lawrence Berkeley National Laboratory. https://doi.org/10.25984/1881324
Granderson, Jessica, Guanjing Lin, Yimin Chen, Armando Casillas, Piljae Im, Sungkyun Jung, Kyle Benne, Jiazhen Ling, Ravi Gorthala, Jin Wen, Zhelun Chen, Sen Huang, and Draguna Vrabie. LBNL Fault Detection and Diagnostics Datasets. Lawrence Berkeley National Laboratory, August, 1, 2022. Distributed by Open Energy Data Initiative (OEDI). https://doi.org/10.25984/1881324
@misc{OEDI_Dataset_5763,
title = {LBNL Fault Detection and Diagnostics Datasets},
author = {Granderson, Jessica and Lin, Guanjing and Chen, Yimin and Casillas, Armando and Im, Piljae and Jung, Sungkyun and Benne, Kyle and Ling, Jiazhen and Gorthala, Ravi and Wen, Jin and Chen, Zhelun and Huang, Sen and Vrabie, Draguna},
abstractNote = {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.},
url = {https://data.openei.org/submissions/5763},
year = {2022},
howpublished = {Open Energy Data Initiative (OEDI), Lawrence Berkeley National Laboratory, https://doi.org/10.25984/1881324},
note = {Accessed: 2025-05-30},
doi = {10.25984/1881324}
}
https://dx.doi.org/10.25984/1881324
Details
Data from Aug 1, 2022
Last updated Feb 12, 2024
Submitted Aug 8, 2022
Organization
Lawrence Berkeley National Laboratory
Contact
Jessica Granderson
Authors
Research Areas
Keywords
Commercial Buildings, Fault Detection and Diagnostics, HVAC, Brick Schema, Algorithm testing, Performance evaluation, AHU, RTU, Fan coil, VAV box, Chiller plant, Boiler plant, AC, fault detection, diagnostics, detection, benchmark, building, building energy, building energy efficiency, energy efficiency, building efficiency, air handler unit, heating, cooling, heating and coolingDOE Project Details
Project Name Fault Detection and Diagnostics: Test Datasets and Prioritization Methods
Project Number FY22 AOP 3.2.6.1.
