Abstract
Some sensors require frequent recalibrations; therefore, calibration cost must be limited. In this paper, a new calibration technique is presented. It is a two-phase method which is based on adaptive neuro-fuzzy networks, and it shows superior performances with respect to traditional algorithms, requiring fewer calibration points and less computational power in the recalibration phase. Feasibility has been demonstrated with a pyroelectric biaxial positioning system, reaching performance to the limit of the adopted test bench, on the order of 20 mum with respect to a whole sensible area of 7 mm times 7 mm
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Instrumentation and Measurement
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
