Engine parameter outlier detection: verification by simulating PID controllers generated by genetic algorithm

  • Authors:

  • Joni Vesterback;Vladimir Bochko;Mika Ruohonen;Jarmo Alander;Andreas Bäck;Martin Nylund;Allan Dal;Fredrik Östman

  • Affiliations:

  • Department of Electrical Engineering and Energy Technology, University of Vaasa, Vaasa, Finland;Department of Electrical Engineering and Energy Technology, University of Vaasa, Vaasa, Finland;Department of Electrical Engineering and Energy Technology, University of Vaasa, Vaasa, Finland;Department of Electrical Engineering and Energy Technology, University of Vaasa, Vaasa, Finland;Wärtsilä Finland Oy, Vaasa, Finland;Wärtsilä Finland Oy, Vaasa, Finland;Wärtsilä Finland Oy, Vaasa, Finland;Wärtsilä Finland Oy, Vaasa, Finland

  • Venue:
  • IDA'12 Proceedings of the 11th international conference on Advances in Intelligent Data Analysis
  • Year:
  • 2012

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Abstract

We propose a method for engine configuration diagnostics based on clustering of engine parameters. The method is tested using simulation of PID controller parameters generated and selected using a genetic algorithm. The parameter analysis is based on a state-of-the art method using multivariate extreme value statistics for outlier detection. This method is modified using a variational mixture model which automatically defines a number of Gaussian kernels and replaces a Gaussian mixture model.