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Filtering by: Creator / Contributor Gianluca Manca Remove constraint Creator / Contributor: Gianluca Manca Keyword Fluid Catalytic Cracking (FCC) Remove constraint Keyword: Fluid Catalytic Cracking (FCC)

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  • Fluid Catalytic Cracking (FCC) Alarm Dataset

    Description:
    This dataset contains simulation data from a Fluid Catalytic Cracking (FCC) unit, specifically designed for alarm flood classification and alarm management research. The dataset is derived from a high-fidelity MATLAB-based FCC simulation model that has been enhanced with realistic process variations and a comprehensive alarm system. Key features of the dataset include: Size: 1,600 simulation runs across 16 different abnormal situations (100 runs per disturbance) Time Resolution: Process data sampled at 60-second intervals File Structure: In the timeseriesdata, each run includes three CSV files: process.csv: Contains 25 process variables (temperatures, pressures, flows, etc.) valves.csv: Contains 11 valve position variables disturbances.csv: Contains 15 variables related to disturbances and ambient conditions For the alarmseriesdata, each run consists of a single file alarms.csv: Contains 57 alarm status variables (low, high, low-low, high-high) The dataset captures realistic process dynamics with: Added measurement noise to all variables (e.g., 1% for level, 0.01°C for temperature) Comprehensive alarm configuration with thresholds based on operating limits 16 different abnormal situations including valve failures, catalyst deactivation, and equipment issues This dataset addresses the gap in publicly available alarm data for process industries and provides a valuable resource for developing and evaluating alarm management techniques, particularly alarm flood classification methods.
    Keyword:
    Alarm Flood Classification, Fluid Catalytic Cracking (FCC), and Process Simulation
    Publisher:
    Date Uploaded:
    2025-05-07
    Date Modified:
    2025-05-12
    License:
    Creative Commons BY Attribution 4.0 International
    Resource Type:
    Dataset