Особливості створення систем контролю якості електроенергії в системах електропостачання космічних ракетних комплексах
Bibliographic record
Abstract
Purpose. Solution of electric power quality issues at space rocet complexes during the execution of launch preparation and launch cycles for the space rocket through the creation and solution of the electric power quality control system (EPQCS) as a separate structure within the power supply system of space rocet complexes PSS SRC with the provision of specified power parameters. Methodology. Review of literary sources on the subject, method of expert evaluations, method of system analysis, method of experimental research. Findings. Indicators of electricity quality, which are the most important for SRC electricity consumers, and which must be monitored, are given. The main requirements to EPQCS have been determined. In case of exceeding the permissible limits of electricity power quality indicators, EPQCS will allow to take operational measures necessary to counter off-nominal situations, by using to the management of the elements of the power supply system. Information security was carried out using a routinely adopted structural block diagram of such systems, on the basis of which the three-tier structure of the EPQCS was implemented. The algorithm and basic principles of the operation of the EPQCS in the nominal mode and the mode beyond the limits of the power quality indicators (PQI) are reviewed. A short description of the structure, as well as an example of the algorithm for managing the EPQCS subordinates, has been included. Originality. The task of a comprehensive approach to electricity power quality indicators was solved and created electric power quality control system in the SRC power supply systems. Microprocessor control means primarily provide speed in comparison with similar systems based on analog-to-digital converters. The proposed EPQCS carries out electricity quality control with the display of data on the operator's screen in real time, continuous monitoring with fixation and registration of the main parameters, as well as notification of the operator in case off-nominal situations. Practical value. Developed, manufactured and successfully passed all types of tests of the electric power quality control system for the SRC «Сyclone -4» (Brazil), and partly for the SRC «Сyclone -4М» (Canada).
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.036 | 0.012 |
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".