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在重大工程结构健康监测中,随着研究对象复杂程度的提高,往往需要获得大量观测数据才能对结构进行有效的评估,因此采用多种或多个传感器进行测量已成为必然趋势。数据融合技术就是将多个传感器的测量结果进行综合处理,从而得出比单个传感器更为准确可靠的结果。本文基于一致性算法,提出一种改进的多传感器数据融合技术,该数据融合技术属于数据级融合,它克服了一致性算法中两传感器在测量精度不同时置信距离不同的缺点,并对支持矩阵进行模糊化处理,避免了人为定义阈值而产生的主观误差。文中通过算例,验证了此方法可获得较好的结果,并且能够有效地减小由于扰动因素造成的测量数据的变化。
In the monitoring of the major engineering structures, as the complexity of the research object increases, it is often necessary to obtain a large amount of observational data to effectively evaluate the structure. Therefore, it is an inevitable trend to use multiple or multiple sensors to measure. Data fusion techniques combine the measurements of multiple sensors to produce more accurate and reliable results than a single sensor. Based on the consistency algorithm, an improved multi-sensor data fusion technology is proposed in this paper. The data fusion technology is a data-level fusion. It overcomes the shortcomings that the two sensors have different confidence distances when the measurement accuracy is different, Fuzzy processing, to avoid the subjective error caused by human-defined threshold. In this paper, an example is given to verify that this method can achieve better results and can effectively reduce the variation of measurement data due to disturbance factors.