In response to the problems of multiple data sources, inconsistent description forms, and low utilization in helicopter assembly production lines, research was conducted on multi-source data perception and fusion application technology for helicopter assembly production lines. Firstly, the connotation and overall framework of multi-source data perception and fusion technology in production line operation were defined, including the construction of a multi-source data collection system for production lines, the construction of a multi-source data fusion model, the construction of a multisource data analysis and prediction model for assembly processes, and the application module for multi-source data analysis in production lines. Secondly, based on the multi-source data from actual assembly lines, we planned to adopt standardized production Internet of things (IOT) technology, ontology based semantic description methods, and multi-source data based quality mapping technology to provide feasible solutions for perception and fusion technology in production lines. Finally, the application measures of the above technologies in virtual operation process, including analysis of production line operation status, monitoring of equipment usage status, and improvement of assembly quality were elaborated, which provided a data foundation for the digital twin construction and virtual efficient operation of helicopter assembly production lines.