Oestrus Detection in Dairy Cows using Automata Modelling and Diagnosis Techniques

Ragnar Ingi Jónsson, Fabio Caponetti, Mogens Blanke, Niels Kjølstad Poulsen

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Abstract

This paper addresses detection of oestrus in dairy cows using automata-based modelling and diagnosis. Measuring lying/standing behaviour of the cows by a sensor attached to the cows hindleg, lying/standing behaviour is modelled as a stochastic automaton. The paper introduces a cow's lying-balance as a biologically inspired quantity describing how much the cow has been resting for a preceding period. A dynamic lying-balance model is identified from real data and the lying balance is used as input, together with lying/standing sensor measurements. Using different automata models for oestrus and non-oestrus conditions, with state transition probability densities identified from observations, diagnosis theory for stochastic automata is employed to obtain diagnoses of oestrus. The oestrus cases are detected using consistency based diagnosis on real data.
Original languageEnglish
Title of host publicationProcedings of 7. IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes
Publication date2009
Pages1402-1407
ISBN (Print)978-3-902661-46-3
DOIs
Publication statusPublished - 2009
Event7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes - Barcelona, Spain
Duration: 30 Jun 20093 Jul 2009
Conference number: 7
http://safeprocess09.upc.es/

Conference

Conference7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes
Number7
CountrySpain
CityBarcelona
Period30/06/200903/07/2009
Internet address

Keywords

  • Health monitoring
  • Diagnosis
  • Signal processing
  • Animal husbandry
  • Stochastic automata
  • Fault diagnosis and monitoring

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