航空发动机叶片装配执行过程智能检测及 AR 引导

To improve the intelligence level of the acro-cnginc blade assembly execution process, a method for intelligent detection and AR guidance of the acro-cnginc blade assembly execution process was proposed, which included three links: blade coding recognition, material kitting based on AR and status detection during the complete placement process. To solve the problem of lack of automatic identification and intelligent error correction, an acro-cnginc blade material management architecture based on codcrccognition was built, and an image processing based on preprocessing enhancement for blade codcimages was proposed. Baycsian error correction was used to judge the recognition results and perform post-processing for error correction, which improved the recognition accuracy of blade codes. Meanwhile, in the process of manual material kitting, AR enhanced visual information was used to assist users in quickly executing task tasks, reducing the time for selecting blade materials. In addition, an error prevention and correction system based on detection and comparison was built for blade material placement, which could avoid human errors. The intelligent detection and AR guidance method proposed for acro-cnginc blade assembly execution process could effectively reduce the consumption of human, material resources and time, which played a technical supporting role in promoting the acro-cnginc towards intelligent and automatic production.