基于分数阶微分的多传感器检测数据融合算法

为了解决制造系统中各生产信息采样节点设备性能和工作环境的不同带来的检测数据间差异性,直接影响着制造管理系统工作可靠性与决策科学性的重要问题,提出应用基于分数阶微分算子的多传感器检测数据融合算法融合生产信息测量误差的新理念。选择检测仪器性能或工作环境作为检测数据的影响因子,应用分数阶微积分理论推导出基于分数阶微分的多传感器检测数据的融合处理算法模型,并应用物联网下的多传感器检测数据的融合处理实例验证了算法的可行性和优越性。实验结果表明:与动态的加权算法和平均值算法相比,本文算法不仅具有融合精度更高、融合值稳健性更好的优点,还具备增强检测信息强度提升系统工作可靠性的功能。

The algorithm for Multi-sensors Detection Data Fusion Based on Fractional Differential

Because the equipment performance and working environment of each production information sampling node in the manufacturing system have difference, it directly affects the operation reliability and decision-making scientific of the manufacturing management system, in order to solve this important problem, new concept using multi-sensor detection data fusion algorithm based on fractional order differential operator to fusion the production information measurement errors is proposed. Chose the performance of the instrument or the working environment as the influence factor of the detection data, multi-sensor detection data fusion algorithm model based on fractional differential under fractional calculus theory is deduced, using the multi-sensor detection data fusion experiment under the Internet of Things, the feasibility and superiority of the algorithm are verified. The experimental results shows that compared with the dynamic weighted algorithm and the mean value algorithm, this algorithm not only has the advantages of higher fusion precision and better fusion value robustness, but also has the function of enhancing the detection information intensity to enhance the reliability of the system''s work.