UBC Research Data

The CSTH Dataset Ibrahim Yousef; Sirish L. Shah; R. Bhushan Gopaluni

Description

The CSTH Simulated Benchmark Dataset is designed for time series classification and fault detection and diagnosis (FDD). It is generated using the continuous stirred tank heater (CSTH) simulation model (https://zenodo.org/records/10093059). The model represents a heating system in which hot and cold water are mixed, heated by steam, and regulated through a closed-loop control system. The dataset consists of 9,000 multivariate time series samples, each with 200 time steps and three process variables (cold water flow, tank level, and temperature). It includes both normal operating conditions (Y=0) and faulty scenarios (Y=1), where faults are introduced through instrumentation errors. The dataset is split into: i) train.pt (70%, 6,300 samples), ii) val.pt (10%, 900 samples), and iii) test.pt (20%, 1,800 samples). This dataset is processed and ready for machine learning applications.

Item Metadata

Title	The CSTH Dataset
Creator	Ibrahim Yousef; Sirish L. Shah; R. Bhushan Gopaluni
Contributor	Ibrahim Yousef
Date Issued	2025-02-03
Description	The CSTH Simulated Benchmark Dataset is designed for time series classification and fault detection and diagnosis (FDD). It is generated using the continuous stirred tank heater (CSTH) simulation model (https://zenodo.org/records/10093059). The model represents a heating system in which hot and cold water are mixed, heated by steam, and regulated through a closed-loop control system. The dataset consists of 9,000 multivariate time series samples, each with 200 time steps and three process variables (cold water flow, tank level, and temperature). It includes both normal operating conditions (Y=0) and faulty scenarios (Y=1), where faults are introduced through instrumentation errors. The dataset is split into: i) train.pt (70%, 6,300 samples), ii) val.pt (10%, 900 samples), and iii) test.pt (20%, 1,800 samples). This dataset is processed and ready for machine learning applications.
Subject	Computer and Information Science; Engineering; Time Series Classification; Fault Detection and Diagnosis; Simulated Benchmark; Process Monitoring
Type	Dataset
Date Available	2025-02-02
Provider	University of British Columbia Library
License	CC BY-NC 4.0
DOI	10.14288/1.0447959
URI	https://doi.org/10.5683/SP3/8FXNGM
Publisher DOI	https://doi.org/10.5683/SP3/8FXNGM
Rights URI	http://creativecommons.org/licenses/by-nc/4.0
Aggregated Source Repository	Dataverse

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CC BY-NC 4.0

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