DocumentCode :
293359
Title :
A neural measurement system for a moving object using magnetic sensors
Author :
Akutagawa, Masatake ; Kinouchi, Yohsuke ; Nagashino, Hirofumi
Author_Institution :
Dept. of Electr. & Electron. Eng., Tokushima Univ., Japan
Volume :
1
fYear :
1995
fDate :
20-24 Mar 1995
Firstpage :
409
Abstract :
Measurement using magnetic fields is one of the most useful methods to gauge the movement of a living body etc. Estimation of the position and direction of a magnet attached to a object from flux density distribution around it is an inverse problem. Though analytical methods are used to solve these problems, they need a lot of calculations to get a convergent solution. In this paper, the authors apply the back propagation neural networks to solve this inverse problem, and their applicability and accuracy are examined. As a result of computer simulations, we obtain an accuracy reading of 0.91% for position error and 0.19° as an average value
Keywords :
backpropagation; computerised instrumentation; magnetic sensors; neural nets; position measurement; back propagation neural networks; direction estimation; flux density distribution; inverse problem; living body movement; magnetic fields; magnetic sensors; moving object; neural measurement system; position estimation; Artificial neural networks; Density measurement; Electric variables measurement; Inverse problems; Magnetic analysis; Magnetic field measurement; Magnetic flux; Magnetic sensors; Neural networks; Position measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium., Proceedings of 1995 IEEE Int
Conference_Location :
Yokohama
Print_ISBN :
0-7803-2461-7
Type :
conf
DOI :
10.1109/FUZZY.1995.409711
Filename :
409711
Link To Document :
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