基于信号介观萃取与统计分析的Q235钢熔透识别方法

Study on penetration recognition method of laser welding for Q235 steel based on signal mesoscopic extraction and statistical analysis

激光焊接熔透检测是实现智能化焊接制造的重要环节.如何穿透匙孔上方阻挡物、突破介观尺度下匙孔内熔透特征区域的准确寻位提取以及对复杂光学检测信号的有效解析,是采用直接测试法可靠识别激光焊接熔透行为的主要技术难点.文中针对Q235钢激光焊接熔透识别新方法展开研究,以孔壁荧光辐射源作为直接检测信号,利用不同物质谱段特性实现穿透遮挡使匙孔内部形态特征透视再现.利用光学成像原理获取匙孔内壁荧光倍增实像,并在一定焊接条件下,通过针孔摄取及介观寻位方式将感应芯片高精度定位至熔透特征区域直接获取信号,实现熔透有效识别信号的最大化增强.最后将检测信号通过统计学概率特征识别,实现对焊接熔透特征信息的抽象分离,并获得了可靠的熔透检测结果.

Laser welding penetration detection is an important link to realize intelligent welding manufacturing,but how to penetrate shelter objects above the keyhole,break through signal effective extraction of accurate location under the mesoscopic scale,which in the penetration feature area of the keyhole,and effectively analyze the complex optical detection signal,these are the main technical difficulties to reliably identify the penetration behavior of laser welding by direct test method.In this paper,a new method of laser welding penetration recognition of Q235 steel is studied.It includes,using the fluorescence radiation source of the keyhole inner wall as the direct detection signal,penetrating shelter objects and making the keyhole internal morphological feature perspective by using the characteristics of different material spectrum segments,obtaining fluorescence doubling image of the keyhole inner wall by using optical imaging,and making the effective penetration recognition signal maximized and enhanced by locating the sensing chip directly to the penetration feature area by pinhole uptake and mesoscopic location methods,under certain welding conditions,finally,identifiing the detection signal by statistical probability feature recognition,which realized the abstract separation of welding penetration feature information.And the method has obtained the reliable penetration detection results.