MIMU传感器网络数据处理与融合工作机制方案

Huang Wenye, Zhang Yumin, Sheng Wei, W. Xiaogang, Liu Lipeng
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摘要

针对工程环境对敷设范围大、工作时间长、精度高、可靠性高等要求,提出了一种能够有效获取采集信息并满足实时数据传输功能的传感器网络框架模型。同时,提出了一种数据处理和融合方案,从静态采集数据中去除趋势项和粗误差项。采用趋势试验和ADF试验数据满足稳定性要求。然后采用多冗余数据融合机制对预处理后的数据进行融合。最后,利用Allan方差法分析了陀螺的随机噪声特性,并对数据质量和融合效果进行了评价。实验结果表明,所设计的传感器网络能够有效采集实时信息,数据处理和融合工作机制能够有效降低噪声,提高数据质量。
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Data Processing and Fusion Working Mechanism Scheme of MIMU Sensor Network
Aiming at the engineering environment that requires a wide range of laying, long working hours, high accuracy and reliability, a sensor network framework model was proposed, which can effectively acquire the collected information and meet the real-time data transmission function. At the same time, a data processing and fusion scheme was proposed to remove trend and gross error terms from the static collected data. The trend test and ADF test data are used to meet the stability requirements. Then a multi-redundancy data fusion mechanism is applied for data fusion of preprocessed data. Finally, via the Allan variance method, the random noise characteristics of the gyro was analyzed, and the data quality and fusion effect are evaluated. Experimental results show that the designed sensor network can effectively collect real-time information, and the data processing and fusion working mechanism can effectively reduce noise and improve data quality.
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