Applications of state estimation in multi-sensor information fusion for the monitoring of open pit mine slope deformation |
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Authors: | Hua Fu Yin-ping Liu Jian Xiao |
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Affiliation: | Faculty of Electrical and Control Engineering, Liaoning Technical University, Fuxin 123000, China |
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Abstract: | The traditional open pit mine slope deformation monitoring system can not use the monitoring information coming from many
monitoring points at the same time, can only using the monitoring data coming from a key monitoring point, and that is to
say it can only handle one-dimensional time series. Given this shortage in the monitoring, the multi-sensor information fusion
in the state estimation techniques would be introduced to the slope deformation monitoring system, and by the dynamic characteristics
of deformation slope, the open pit slope would be regarded as a dynamic goal, the condition monitoring of which would be regarded
as a dynamic target tracking. Distributed Information fusion technology with feedback was used to process the monitoring data
and on this basis Klman filtering algorithms was introduced, and the simulation examples was used to prove its effectivenes.
Supported by Liaoning Province Technology Key Project(2007231003, 2006220019); Liaoning Province Talent Fund Projects(2005219005,
2007R24); Liaoning Province Innovative Team Projects(2007T071, 2006T076) |
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Keywords: | multi-sensor information fusion the side slope distortion the state estimation Klman filter algorithm |
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