The invention discloses an instrument quality
inspection method and
system based on an incremental 3D
Gaussian point cloud, relates to the technical field of defect detection, and solves the problem that a two-dimensional detection result is difficult to accurately map to a three-dimensional
Gaussian model. According to the embodiment of the invention, the instrument and the defect area are identified through the YOLO target detection
algorithm, the sparse
point cloud is generated by using the SfM technology, the 3D
Gaussian primitive set is initialized, the rapid model construction is realized by using the incremental optimization
algorithm, and the details of the defect area are enhanced by using the semantic
perception density control technology. And a 2D detection result is accurately mapped to a 3D space in combination with a multi-view semantic fusion
algorithm, and a target digital twin instrument model is constructed. According to the invention, three-dimensional
visualization of industrial
product defect detection is realized, the modeling speed and the data updating speed are improved, the model size is compressed, the efficiency, the accuracy and the
visualization capability of industrial detection are improved, and the method is suitable for various scenes such as product quality detection,
predictive maintenance, remote cooperation and the like.