The sparameter and impedance project currently supplies calibration services to outside customers. This document outlines the procedure for the data acquition and analysis for the one port and two port impedance services.
Current Method:
Current Method:
Current Method:
Current Method:
Current Method:
Current Method:
Current Method | Issues | Replacement Strategy |
---|---|---|
Calibration of the instrument using MultiCAL | HP Basic is obsolete. The data used to correct the raw measurements is lost. New methods of calibration cannot be added easily. The lack of transfer standards to make calibration easier (requires correlated uncertainties) | The replacement of this step requires a program capable of acquiring data, calculating a correction, and storing data persitently in a searchable manner. Currently StatistiCAL and the MUF can calculate the correction, PNA grabber can acquire the data in some cases (does not have all possible VNA and PNAs) and there is no data management software option. Our approach is to create data management tools in Python (not obsolete) use the MUF or StatistiCAL through Python wrappers to calculate the correction and then integrate this with a Python based web frontend. Data acquisition can either be accomplished by using PNA grabber wrapper or a new Python acquistion program. |
Tracking and comparison of check standard data | HP Basic is obsolete. The measurement data is stored in an obsolete binary format. There is no central repository that is updated. History is not tracked or analyzed. The analysis of the check standard data is not typically saved, and when it is saved important metadata is lost. No user control or web compliance. | Intially convert the data to a non-obsolete format, create an analysis routine in Python that saves the metadata. Create a central database of previous measurements that is managed and analyzed through a web based frontend. Currently we have the basics of this process are finished. By rewritting the analysis routines in Python we have made the code modern and provided both a web based frontend and the ability to link this analysis with data acquistion and data management. |
Report Generation | Requires a human to connect the measurement data with the final report, also requires understading in at least 3 different programs. Not tied to a central database, no ability to provide real-time report generation for staff or customers. | Create a path to fill html templates with measurement data using Python library. These html reports can be tied to history and analysis for internal use. |