Preprocessing and Modeling of Radial Fan Data for Health State Prediction

Florian Christian Holzinger, Michael Kommenda

Research output: Chapter in Book/Report/Conference proceedingsConference contribution


Monitoring critical components of systems is a crucial step towards failure safety. Affordable sensors are available and the industry is in the process of introducing and extending monitoring solutions to improve product quality. Often, no expertise of how much data is required for a certain task (e.g. monitoring) exists. Especially in vital machinery, a trend to exaggerated sensors may be noticed, both in quality and in quantity. This often results in an excessive generation of data, which should be transferred, processed and stored nonetheless. In a previous case study, several sensors have been mounted on a healthy radial fan, which was later artificially damaged. The gathered data was used for modeling (and therefore monitoring) a healthy state. The models were evaluated on a dataset created by using a faulty impeller. This paper focuses on the reduction of this data through downsampling and binning. Different models are created with linear regression and random forest regression and the resulting difference in quality is discussed.

Original languageEnglish
Title of host publicationComputer Aided Systems Theory – EUROCAST 2019 - 17th International Conference, Revised Selected Papers
EditorsRoberto Moreno-Díaz, Alexis Quesada-Arencibia, Franz Pichler
Number of pages7
ISBN (Print)9783030450922
Publication statusPublished - 2020
Event17th International Conference on Computer Aided Systems Theory, eurocast - Las Palmas, Gran Canaria, Spain
Duration: 17 Apr 201922 Apr 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12013 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference17th International Conference on Computer Aided Systems Theory, eurocast
CityLas Palmas, Gran Canaria
Internet address


  • Binning
  • Machine learning
  • Radial fan
  • Sampling


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