Deep learning-based molten pool image geometric feature extraction method and system
A technology of geometric features and extraction methods, applied in the field of laser welding technology and deep learning, can solve problems such as low accuracy of molten pool extraction and inconsistent image brightness, and achieve strong anti-interference ability, accurate edge information, and good anti-interference ability.
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[0080] The overall flow chart of the method for extracting geometric features of molten pool images based on deep learning in the present invention is as follows figure 1 As shown, it includes the following steps:
[0081] Step S101: Reference figure 2 The schematic diagram of on-line monitoring of laser welding is shown, using the Qianyanlang 5KF20 high-speed camera and its equipped infrared lighting system and filter system to collect images of the molten pool during the laser welding process, and from the dynamic video of the molten pool every 5 frames Extract the molten pool image to obtain a clear original image set of the molten pool;
[0082] Step S102: Using image processing algorithms such as image grayscale and Gaussian filtering algorithm to image 3 The original image of the molten pool shown in (a) is filtered and denoised to reduce the interference of salt and pepper noise in the image. The image processing results are as follows image 3 as shown in (b);
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Description
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Application Information
- IPC
- G06T7/00; G06T7/11; G06T7/13; G06T7/194; G06T7/62; G06N3/04; G06N3/08; G06T5/00
- CPC
- G06T7/0004; G06T7/11; G06T7/13; G06T7/194; G06T7/62; G06N3/08; G06T2207/20081; G06T2207/20084
- Inventors
- 许桢英; 李奇灵



