The datasets contain pressure and temperature signals from the hydraulic systems of two different Kaplan turbines. The variables can be connected to the forces required to regulate the runner blades on the turbines. The datasets can therefore be used to monitor the friction in the bearings that enable the movement of the runner blades. These bearings are located in the hub of the Kaplan turbines. The datasets are also labeled with information on whether glycerol is present in the systems for lubrication.

The sampling frequency is 1 sample per minute. Each feature includes an average, minimum, and maximum value, which correspond to the statistics during that minute from the sampling as the sampling frequency in the SCADA system is higher than 1 sample per minute.

Data contains personal data

Language

English

Method and outcome

Data format / data structure

Numeric

Data collection

Mode of collection: Computer-based observation
Description of the mode of collection: The datasets were collected by SCADA systems used for monitoring the turbines.
Data collector: Fortum Sverige AB
Source of the data: Other

Geographic coverage

Geographic spread

Geographic location: Sweden

Administrative information

Responsible department/unit

Machine Elements

Contributor(s)

Fortum Sverige AB

Topic and keywords

Research area

Software engineering (Standard för svensk indelning av forskningsämnen 2011)

Control engineering (Standard för svensk indelning av forskningsämnen 2011)

Tribology (Standard för svensk indelning av forskningsämnen 2011)

Keywords

Condition monitoring, Bearings, Friction, Machine learning, Scada data, Glycerol lubrication, Hydropower, Kaplan turbine, Anomaly detection, Predictive maintenance

Publications

Published: 2025-03-12