Archivio Istituzionale della RicercaThis paper discusses the performance improvement that a neural network can provide to a contactless distance sensor based on the measurement of the time of flight (TOF) of a ultrasonic (US) pulse. The sensor, which embeds a correction system for the temperature effect, achieves a distance accuracy (rms) better than 0.5 mm over 0.5 m by using a two-level neural network that processes the US echo in order to correctly determine the TOF in the presence of environmental acoustic noise.
Ultrasonic distance sensor improvement using a two-level neural network / Carullo, Alessio; Ferraris, Franco; Graziani, S; Grimaldi, U; Parvis, Marco. - STAMPA. - 1:(1995), pp. 828-833. (Intervento presentato al convegno 1995 IEEE Instrumentation and Measurement Technology Conference tenutosi a Whaltam, MA, USA nel 23-26 Apr.) [10.1109/IMTC.1995.515430].
Ultrasonic distance sensor improvement using a two-level neural network
CARULLO, Alessio;FERRARIS, Franco;PARVIS, Marco
1995
Abstract
This paper discusses the performance improvement that a neural network can provide to a contactless distance sensor based on the measurement of the time of flight (TOF) of a ultrasonic (US) pulse. The sensor, which embeds a correction system for the temperature effect, achieves a distance accuracy (rms) better than 0.5 mm over 0.5 m by using a two-level neural network that processes the US echo in order to correctly determine the TOF in the presence of environmental acoustic noise.
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https://hdl.handle.net/11583/2499106
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