基于模糊理论的多传感器数据融合测量

Measurement of multi-sensor data fusion method based on fuzzy theory

  • 摘要: 针对多传感器数据融合过程中,各传感器可靠度估计困难的问题和如何对各传感器测量数据进行融合,提出了一种基于模糊理论的多传感器数据融合方法并研究了它在测量中的应用过程。该方法首先利用容许函数计算各传感器测量数据间的一致性以剔除系统误差数据,然后将测量数据进行模糊化,最后用模糊贴近度获得多传感器测量的数据融合结果。该方法计算简单,客观地反映了各传感器测量数据的一致性和可靠程度。测量应用实例验证了其在工程中的可行性,体现了稳定性和可靠性高的传感器在测量数据融合中的优越性,运算过程简洁、快速、有效,便于实时测量操作。

     

    Abstract: In order to determine the reliability of each sensor and how to fuse the data measured by sensors, a multi-sensor data fusion method based on fuzzy theory is proposed and its measurement application is studied. Firstly, the sensors consistency is obtained from the admissible function and the measurement error data are deleted. Then the measurement data are fuzzied. Finally, the fusion result could be produced on the basis of fuzzy similarity degree. The method is computationally simple and can objectively reflect the reliability and consistency between these sensors. A measurement example proves that the method is feasible, it can give higher priority to stable and reliable sensor, and it is simple and efficient for real-time measurement.

     

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