Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.726355
Title: Inline blind sensor characterisation
Author: Gillespie, Philip David
ISNI:       0000 0004 6425 3322
Awarding Body: Queen's University Belfast
Current Institution: Queen's University Belfast
Date of Award: 2017
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Abstract:
The measurement of rapidly changing temperature fluctuations is a challenging problem due to the inherent limited bandwidth of temperature sensors. This results in a measured signal that is a lagged and attenuated version of the true input signal. Compensation can be performed provided an accurate, parameterised model of the sensor is available. However, the sensor characteristics are strongly dependent on the measurement environment, which is often time-varying and cannot be determined a priori. To account for the changing characteristics, the sensor model must be estimated in-situ, thereby resulting in a blind identification problem. In this study, methods for performing blind characterisation of a two-sensor probe for fast temperature measurement are investigated and developed, with a particular focus on extending existing methods to handle second-order models.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.726355  DOI: Not available
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