GB/T 21355-2022 in English

GB/T21355-2022, as an equivalent adopted standard of ISO16371-1:2011, specifies the classification system for industrial computed radiography (CR) detection systems based on storage phosphor imaging plates (IP). The standard establishes a 6-level classification system (IP1/Y~IP6/Y) by quantifying the two core parameters of signal-to-noise ratio (SNR) and basic spatial resolution.

1. Signal-to-noise ratio measurement

Use the step exposure method or the step wedge method, and calculate by the formula SNRN=I_meas/σ_PSL100, where σ_PSL100 needs to be calibrated according to the 88.6μm reference pixel.

2. Spatial resolution determination

Three methods are recommended:

• MTF method: Obtain the modulation transfer function through a sharp-edge test block and take the value corresponding to MTF20%
• Dual-wire method: Use a dual-wire image quality meter according to ISO19232-5, and the resolution limit corresponds to 1/2 of the unsharpness
• Convergent line pair method: The minimum identifiable number of line pairs is converted into resolution

Staff qualification requirements

Inspection personnel must comply with ISO9712 qualification certification, with special emphasis on professional training in IP processing, scanning parameter setting and image interpretation.

Quality control process

1. Regularly use the CR module (including T target, dual-wire image quality meter, etc.) to verify system performance
2. Monitor image decay effects and control exposure-reading time interval
3. Establish IP artifact archives and implement numbering management

Main improvements compared to the 2008 version:

• Added IP erasure effect verification requirements (residual signal <1%)
• Introduced the concept of ISO sensitivity (S_ISO) to quantify system response characteristics
• Improve the detection method of aliasing phenomenon

The standard clearly defines the equivalence comparison principle between CR system and film system for the first time, providing a basis for the transition from traditional detection to digitalization.