Research on an Adaptive Weighted Fusion Algorithm Under the Edge Computing Framework of Power Internet of Things

Abstract

In the power system, each province has nearly millions of sensors, and a large amount of data is generated. In the process of multi-sensor data collection, there are many problems such as inaccurate monitoring accuracy, waste of collection nodes, and zero drift of the sensor itself, which affect the inaccurate data reporting of the central station and the inaccurate execution of feedback information. At the same time, the sensor cannot do it once Acquisition, multiple applications, especially in power distribution rooms, station areas and other areas with high environmental requirements. There are distribution automation, electricity information collection, and dozens of sensor terminals such as temperature and humidity, smoke, video, robots, etc. Highly accurate information collection and environment configuration. To this end, an improved adaptive weighted fusion algorithm is proposed to achieve accurate terminal collection and data fusion upload based on the edge side of the power IoT edge computing framework. The design scheme can improve the accuracy of terminal data collected in power distribution rooms, station areas and other regions. Simulation and experiment proves the effectiveness of the algorithm in terms of acquisition accuracy and data fusion.