中文摘要：

为提高能源互联网环境下多源数据融合的精度和抗干扰能力,针对多传感器系统进行数据采集和监测时易受众多客观因素影响的问题,提出基于时间窗口和自适应加权的数据融合方法。采用支持度函数构造传感器支持度矩阵,检验测量数据之间的关联和支持程度;通过深度挖掘时间窗口中的蕴含信息,实行时间窗口蕴含值退出机制,有效剔除测量偏差较大的传感器;在此基础上,利用自适应加权因子排除前期测量差异和强干扰对系统一致性测度的影响,使测量精度和系统的稳定性进一步得到保证。案例分析结果表明,与传统的融合方法相比,该方法具有较好的融合效果,所构建的模型可为多源数据融合方法的评价机制提供一种新的视角。

英文摘要：

To improve the accuracy of multi-source data fusion and the ability of anti-interference in the energy network,and to deal with the influence of objective factors when multi-sensor systems are used to obtain and monitor data,we present a data fusion approach,based on time window and the adaptive weights.Sensor support degree matrix is constructed with support degree function,so that it can test the link and the support degree between the measured data.Through deeply mining of the information in the time windows,and executing exit mechanism for time window values,it can effectively eliminate the deflection sensors with more bias.Furthermore,by ruling out early measurement difference and the influence of strong interference on the system consistency measure by using the adaptive weighted factors,the measurement precision and the stability of the system can be further guaranteed.Results in case analysis show that this approach has good fusion effect,compared with the traditional fusion approaches,and the new model provides a new perspective for the evaluation mechanism of multiple source data fusion methods.