GB/T 34874.6-2020 in English

GB/T34874.6-2020 specifies the standardized method for the detection of workpiece geometric dimensions using X-ray 3D dimension measuring machines based on industrial CT technology. This standard is applicable to industrial CT systems with 3D measurement capabilities, covering the full process from scan preparation to data analysis.

1. Tomography

Multi-angle projection acquisition through X-ray tube requires flat-panel detector calibration. The standard recommends that the tube voltage stability should be controlled within ±0.5% and the current fluctuation ≤1%.

2. 3D Image Reconstruction

When using reconstruction algorithms such as FDK, attention should be paid to cone angle compensation. For high-density materials (such as titanium alloys), it is recommended to use algebraic reconstruction technology to reduce artifacts.

3. Surface extraction technology

The standard specifies two threshold determination methods:
- Global threshold method: Applicable to uniform materials
- Local adaptive method: Applicable to composite material workpieces

Equipment selection

The energy of the X-ray source should be selected according to the material penetration requirements:
- Light metals (aluminum, etc.): 80-150kV
- Heavy metals (steel, etc.): 225-450kV

Measurement preparation

Note when installing:
- Use a low-density fixture (such as carbon fiber) to fix the workpiece
- Ensure that the thickness of the measured area is ≤ the maximum penetration capability of the equipment

Uncertainty control

It is recommended to use a step-type standard for system verification, and the material should be consistent with the measured object. Typical influencing factors include:
- Voxel size error (±0.5μm)
- Temperature drift (1μm/℃)

Compared with the 2017 version, this standard is mainly upgraded:
1. Added Multi-material workpiece measurement specifications
2. Improved GPS matrix correspondence
3. Refined wall thickness analysis algorithm requirements

Future development trends will focus on:
- Artificial intelligence-assisted defect recognition
- Real-time dynamic measurement technology
- Multimodal data fusion