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LBNL Fault Detection and Diagnostics Datasets
OwnerNational Renewable Energy Laboratory (NREL) - view all
Update frequencyunknown
Last updatedabout 1 year ago
Format
Overview

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.

ACAHUAlgorithm testingBoiler plantBrick SchemaChiller plantCommercial BuildingsFan coilFault Detection and DiagnosticsHVACPerformance evaluationRTUVAV boxair handler unitbenchmarkbuildingbuilding efficiencybuilding energybuilding energy efficiencycoolingdetectiondiagnosticsenergy efficiencyfault detectionheatingheating and cooling
Additional Information
KeyValue
dcat_issued2022-08-01T06:00:00Z
dcat_modified2022-11-08T22:00:09Z
dcat_publisher_nameLawrence Berkeley National Laboratory
guidhttps://data.openei.org/submissions/5763
ib1_trust_framework[]
language
Files
  • ZIP
    LBNL FDD Datasets
  • PDF
    Inventory of LBNL FDD Datasets.pdf
  • ttl
    LBNL FDD Datasets Semantic Models.ttl
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