Research on Signal Processing and Sensor Fusion Technology in Electrical Engineering Automation

This study introduces an electrical measurement system grounded in multi-sensor fusion. Through the incorporation of information fusion techniques and parallel computing strategies, the system achieves reconstruction and optimization. The system is designed with a dynamic clustering algorithm that effectively merges data from various sensors, thereby enhancing both the precision and real-time performance of the measurements. To validate the system’s effectiveness, this paper conducts simulations and carries out detailed data analysis of the simulation outcomes. The findings demonstrate that the proposed sensor fusion approach substantially increases the measurement accuracy of the electrical measurement system while maintaining robust stability in challenging environments. Furthermore, the system’s parallel computing capabilities notably boost processing efficiency, reducing the time required for data handling. These outcomes indicate that the signal processing and sensor fusion technologies explored in this research hold significant potential for applications in electrical engineering automation, offering a solid theoretical foundation and technical support for future engineering implementations.