A Gaussian-process-model-based approach for robust, independent, and implementation-agnostic validation of complex multi-variable measurement systems: application to SAR measurement systems
by Bujard et al.
Resource-efficient and robust validation of complex measurement systems that would require millions of test permutations for comprehensive coverage is an unsolved problem. In the paper, a general, robust, trustworthy, efficient, and comprehensive validation approach based on a Gaussian Process model (GP) of the test system has been developed that can operate system-agnostically, prevents calibration to a fixed set of known validation benchmarks, and supports large configuration spaces. The approach includes three steps that can be performed independently by different parties: 1) GP model creation, 2) model confirmation, and 3) model-based critical search for failures. The new approach has been applied to two systems utilizing different measurement methods for compliance testing of radiofrequency-emitting devices according to two independent standards, i.e., IEC 62209-1528 for scanning systems and IEC 62209-3 for array systems. The results demonstrate that the proposed measurement system validation is practical and feasible. It reduces the effort to a minimum such that it can be routinely performed by any test lab or other user and constitutes a pragmatic approach for establishing validity and effective equivalence of the two measurement device classes.
- Linux
- Mac OS
- Windows 10, 11
The GUI generally runs wherever the tkinter GUI framework is available, even though rendering inconsistencies may occur on some platforms.
pip install git+https://github.com/ITISFoundation/publication-IEC62209.git
Run the python3 executable:
iec62209-gui
or import as a package into your python code
import iec62209