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 language | English |
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Title of host publication | Procedings of 7. IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes |
Publication date | 2009 |
Pages | 1402-1407 |
ISBN (Print) | 978-3-902661-46-3 |
DOIs | |
Publication status | Published - 2009 |
Event | 7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes - Barcelona, Spain Duration: 30 Jun 2009 → 3 Jul 2009 Conference number: 7 http://safeprocess09.upc.es/ |
Conference
Conference | 7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes |
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Number | 7 |
Country/Territory | Spain |
City | Barcelona |
Period | 30/06/2009 → 03/07/2009 |
Internet address |
Keywords
- Health monitoring
- Diagnosis
- Signal processing
- Animal husbandry
- Stochastic automata
- Fault diagnosis and monitoring