In the field of NDT, there are mainly two detection methods: industrial CT detection and X-ray detection, both of which use X-rays to detect the interior of the object. 

The X-ray detection scheme can intuitively show the size and shape of the defects in the workpiece, so as to facilitate the judgment of the nature of the defects. The X-ray film is used as the original record of the inspection, which can be studied by multiple parties and stored for a long time, and has a high sensitivity for the non-destructive testing of thin-walled parts. In the pressure vessel welding quality inspection, there is no strict requirement on the surface finish, and the grain size has little effect on the test result. It can be used for the internal defect detection of various materials, so it is widely used in the pressure vessel welding quality inspection.

With the advent of big data, cloud computing, especially the quantum era, many enterprises have begun to study intelligent defect detection methods, eliminate the interference of human consciousness on detection results, rely on a large number of actual data as defect identification, improve efficiency and ensure detection quality. AI intelligent recognition and resolution of sample information will become a development direction in the field of industrial CT detection.