Visual electro-optical multimodal data fusion and feature analysis of high-power disk laser welding

As the characteristic parameters of multi-sensing keyhole and plume reflect effectively the welding quality of high power disc lasers, high power disc laser welding of high strength steel SX780CF was used as the test object, and the dynamic image of molten pool during welding was extracted simultaneously by high speed camera and photoelectric sensor vision imaging system. The images of molten pool and metal vapor obtained by high-speed camera in laser welding experiment were processed by OpenCV. The characteristic parameters of keyhole and metal vapor are extracted by means of median filtering, binary thresholding and open operation. The relationship among keyhole shape, welding condition and welding state was explored by analyzing the variation law of keyhole area and metal vapor area curve. Two characteristic parameters of visible light intensity and reflected light intensity during laser welding were obtained by photoelectric sensor. The change law of visible light and reflected light curve is analyzed, the power spectral density of photoelectric signal is explored, and then the welding state in the welding process is judged. The on-line monitoring of welding process is realized.