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  • IEEE Khan_Richardson rev-16- FINAL FORMAT

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Use of self-calibration data for multifunctional MEMS sensor prognostics

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Published
<mark>Journal publication date</mark>08/2016
<mark>Journal</mark>Journal of Micromechanical Systems
Issue number4
Volume25
Number of pages9
Pages (from-to)761-769
Publication StatusPublished
Early online date19/05/16
<mark>Original language</mark>English

Abstract

This paper proposes a solution to monitor the degradation of a multifunctional microelectromechanical systems (MEMS) sensor (MFS) and to recalibrate the sensor output accordingly. The solution is able to predict the remaining useful life based on the recalibration history. The MFS used is a dual pressure-humidity hybrid sensor where model data have been used to demonstrate the applicability and performance of the proposed method for diagnosis, self-correction, and prognosis.