无损检测技术在航空发动机叶片故障自动检测中的应用

Application of Non-Destructive Testing Technology in Automatic Fault Detection of Aircraft Engine Blades

针对航空发动机叶片复杂的失效机理和精准快速检测的需求,研究了无损检测技术在叶片缺陷自动识别中的应用。通过综合选择超声检测与涡流检测方法,优化多传感器阵列布置,集成深度学习、数字孪生等智能算法,构建了航空发动机叶片自动化无损检测系统。攻克了高灵敏传感器设计、自适应聚焦成像、智能缺陷识别等关键技术,实现了叶片亚毫米级微小缺陷的快速准确检出。研究表明,该系统的检测灵敏度较传统方法有明显提高,为保障航空发动机安全可靠运行提供了重要支撑。

This article focuses on the complex failure mechanism of aircraft engine blades and the need for precise and rapid detection,and studies the application of non-destructive testing technology in automatic identification of blade defects.By comprehensively selecting ultrasonic testing and eddy current testing methods,optimizing the layout of multiple sensor arrays,integrating intelligent algorithms such as deep learning and digital twinning,an automated nondestructive testing system for aircraft engine blades has been constructed.We have overcome key technologies such as high sensitivity sensor design,adaptive focusing imaging,and intelligent defect recognition,achieving rapid and accurate detection of sub millimeter level small defects in blades.Research has shown that the detection sensitivity of this system is significantly improved compared to traditional methods,providing important support for ensuring the safe and reliable operation of aircraft engines.