Abstract
In the applications of water regime monitoring, incompleteness, and inaccuracy of sensor data may directly affect the reliability of acquired monitoring information. Based on the spatial and temporal correlation of water regime monitoring information, this paper addresses this issue and proposes an information fusion method to implement data rectification. An improved Back Propagation (BP) neural network is used to perform data fusion on the hardware platform of a stantion unit, which takes Field-Programmable Gate Array (FPGA) as the core component. In order to verify the effectiveness, five measurements including water level, discharge and velocity are selected from three different points in a water regime monitoring station. The simulation results show that this method can recitify random errors as well as gross errors significantly.
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Supported by the National Natural Science Foundation of China (No. 60774092, No. 60901003) and the Specialized Research Fund for the Doctoral Program of Higher Education (No. 20070294027)
Communication author: Wang Huibin, born in 1967, male, Ph.D., Professor.
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Zhang, Z., Xu, L., Li, H.H. et al. An information fusion method for sensor data rectification. J. Electron.(China) 29, 148–157 (2012). https://doi.org/10.1007/s11767-012-0753-7
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DOI: https://doi.org/10.1007/s11767-012-0753-7
Key words
- Information fusion
- Sensor data rectification
- Back Propagation (BP) neural network
- Field-Programmable Gate Array (FPGA)