Calibration of charge amplifiers using metrological grade analog-to-digital converters
Bibliographic record
Abstract
The calibration of charge amplifiers is important for vibration/acceleration standards. Almost every national metrology institute that maintains its national vibration standards has the calibration capability for charge amplifiers. The National Research Council Canada (NRC) provides such services that establish a direct link between a client's precision equipment, or transfer standard, and the Canadian national vibration standard. To help manufacturers and users of precision instruments achieve the highest possible levels of measurement quality and productivity, a new calibration system for charge amplifiers is currently under development at the Metrology Research Centre at the NRC. The calibration system uses metrological grade analog-to-digital converters (digitizers) to replace the voltmeters and phase meter in the current calibration system, with the benefit that non-periodic and non-sinusoidal signals can be used as input signals for the calibration of charge amplifiers. A direct application of such an approach is the calibration of charge amplifiers for shock acceleration where the input signal is approximately a half-sine pulse. In this paper, the technical details of the calibration system are presented. The selection of system parameters such as maximum sampling rate, analog-to-digital converter resolution, and input noise floor are discussed. An approach that is different to the one commonly used and recommended in IEEE 1057-1994 (R2001): IEEE Standard for Digitizing Waveform Recorders is proposed. The technical challenges of the approach are first addressed, followed by detailed discussions on how to overcome these challenges. In particular, the selection of the sample length is considered with the focus on noise analysis based on Allan variance. The measurement results of the calibration system used to calibrate a charge amplifier at 1 kHz are presented for various measurement times. With a reasonable longer measurement time, the system can achieve ultra-low calibration uncertainties both for gain and phase difference.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".