Ultrasonic distance sensor improvement using a two-level neural network

被引：37

作者：

Carullo, A ^{[1
]}

Ferraris, F ^{[1
]}

Graziani, S ^{[1
]}

Grimaldi, U ^{[1
]}

Parvis, M ^{[1
]}

机构：

[1] UNIV CATANIA, DIPARTIMENTO ELETTR ELETTR & SISTEMIST, CATANIA, ITALY

来源：

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT | 1996年 / 45卷 / 02期

关键词：

D O I：

10.1109/19.492808

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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 an ultrasonic (US) pulse, The sensor, which embeds a correction system for the temperature effect, achieves a distance uncertainty (rms) of less than 0.5 mm over 0.5 m by using a two-level neural network to process the US echo and determine the TOF in the presence of environmental acoustic noise, The network embeds a ''guard'' neuron that guards against gross measurement errors, which would be possible in the presence of high environmental noise.

引用

页码：677 / 682

页数：6