DocumentCode :
2518376
Title :
A neural network for fast-response ultrasonic distance sensors
Author :
Ferraris, F. ; Grimaldi, U. ; Parvis, M. ; Graziani, S.
Author_Institution :
Dipartimento di Elettronica, Politecnico di Torino, Italy
fYear :
1993
fDate :
18-20 May 1993
Firstpage :
631
Lastpage :
635
Abstract :
Ultrasonic techniques can provide a cost effective solution for distance measurements, but frequently suffer from poor resolution and acoustic noise. A new approach based on neural networks to process the echo signal is described. It permits the improvement of the resolution of distance measuring systems by employing ultrasonic techniques and requires a negligible computing time, even though the network is implemented without special purpose hardware. The results obtained with inexpensive piezoelectric transducers and a neural network are described. The neural network performance is compared with that of traditional techniques. A sub-millimeter resolution is obtained even in the presence of some acoustic noise, which could prevent other simple detection strategies
Keywords :
acoustic noise; computational complexity; distance measurement; neural nets; piezoelectric transducers; ultrasonic applications; ultrasonic transducers; acoustic noise; computing time; distance measurements; echo signal; fast-response ultrasonic distance sensors; piezoelectric transducers; sub-millimeter resolution; Acoustic measurements; Acoustic noise; Acoustic sensors; Costs; Distance measurement; Neural networks; Signal processing; Signal resolution; Time measurement; Ultrasonic imaging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation and Measurement Technology Conference, 1993. IMTC/93. Conference Record., IEEE
Conference_Location :
Irvine, CA
Print_ISBN :
0-7803-1229-5
Type :
conf
DOI :
10.1109/IMTC.1993.382566
Filename :
382566
Link To Document :
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