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Application of Data Fusion Based on Neural Network for Displacement Sensing System(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2006年01期
Page:
28-32
Research Field:
Publishing date:

Info

Title:
Application of Data Fusion Based on Neural Network for Displacement Sensing System
Author(s):
ZHU Haimei
College of Physical Science and Technology,Yangzhou University,Yangzhou 225002,China
Keywords:
data fusion;  BP neural network;  RBF neural netwo rk;  temperature dr ift
PACS:
TP212
DOI:
-
Abstract:
The tem perature dr ift e rror is one o f the m ajor e rrors of the displacem ent senso r system. In order to improve the accuracy and stability, the output from the displacem ent senso r and the one from the temperature sensor can be fused. At present, neu ra l netwo rk has been w ide ly app lied to the area o f da ta fus ion, in w hich da ta from mu ltiple sensors arem ostly fused by BP neura l netw ork. The low training speed o f BP ne tw ork leads to the poor practicab ility, there fo re in this paper, a data fusion m ethod based on RBF neura l netwo rk is proposed for reduc ing temperature drift erro r. The outputs from the disp lacem ent sensor and tho se from the tem pera ture sensor are sent to the fusion cente r, w he re the RBF neura l netw ork is tra ined and as a resu lt the stable outpu t is obta ined. Exper iments show that the ou-t put stab ility of the disp lacem ent sensor is im proved by 4 tim es under the sam e tem perature fluctuation. It is obv ious that the proposed me thod in this paper is effective for reduc ing the drift erro r o f displacem ent sensor system.

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Last Update: 2013-04-29