X-ray 3D tomography imaging is closely related to computer technology. It is a inspection technique for reshaping the distribution map of automotive die casting flaw physical characteristics based on X-ray data. This technology can visually represent the three-dimensional shape of the cavity in the casting, and can simultaneously realize the dimension measurement and defect quality control of the casting in a single inspection process, and improve the inspection efficiency of complex aluminum castings.
X-ray micro-computed tomography is used to detect a clear view of the interior of the casting and to classify the coloring according to the volumetric form of the hole defect. The technology enables rapid non-destructive analysis, greatly reducing inspection time and cost. X-ray computed tomography (Computed tomography, CT) technology can accurately measure and model air hole defects and fatigue cracks. In the inspection image, the outer surface of the casting is transparent, and the pore defect part is granular.
The CT experimental results show that the number of projections plays an important role in the size accuracy. The dimensional accuracy measurement method of ring castings mainly expresses the prior information of key coordinate points through length and angle, and introduces the polar coordinates into the deterministic positioning deviation analysis algorithm CT to reconstruct the appearance size and wall thickness of castings. The steps of information processing and error decomposition are reduced, making the calculation process simpler.
The 3D learning defect automatic recognition method adopts the formal closed operation and template matching method to extract the defect candidate area, and then generates an accurate defect segmentation code based on the local matching method, and finally calculates 29 features, including geometric features and gray-level co-occurrence matrix texture, using fast random the forest classifier classifies the candidate regions as defect-free or defect-free. The system tested 49 porosity defects on CT scan images in 31 industrial castings, with an accuracy as high as 94%. Reasonably allocate hardware resources, improve the overall efficiency of the production line, and integrate X-ray computed tomography reconstruction and image processing. After the image processing step, high-resolution tomographic imaging of potential defect areas in the automotive aluminum casting and low-resolution reconstruction of other casting areas are performed. This method can quickly complete the defect inspection of the whole casting, and meet the requirements of the casting production cycle. The CT inspection technology is close to the industrial reality.
In the X-ray 3D imaging technology, the scan time is mainly optimized for CT, because the foundry only needs to know whether the casting has fatal defects, which is enough for screening, so the quality of defect reconstruction is secondary. However, with the popularization of precision castings, the dimensional tolerances of castings have stricter acceptance criteria, so the future X-ray 3D imaging will develop in three aspects: full size, high precision, and high timeliness.
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