Monitoring a Hydraulically-Driven Feed Roll System with Sensors on aPrototype Pull-Type Forage Harvester
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<abstract> <b><sc>Abstract. </sc></b>An experimental hydraulic drive was designed for a pull-type F41 Dion forage harvester to control and measure the rotational speed and applied load of feedrolls. Three types of sensors were placed on the experimental harvester: (1)Â four hydraulic pressure sensors to measure pressure in the input and output lines of the feedroll and header motors; (2) three integrated tachometers to measure motor speed, and (3) a potentiometer-based sensor to measure crop mass flow. Data was collected using a National Instruments USB 6216<sup>TM</sup> device and LabView<sup>TM</sup> code. Pressure drop of the motor depended on mass flowrate of the crop material being conveyed. Power consumption increased with increasing rate of forage throughput. Increased forward speed decreased the specific energy requirements of the header and feedroll motors. The feedroll opening measurements using the potentiometer sensor were correlated with the experimental mass flowrate measured by weighing the forage wagon. Correlation coefficients were R<sup>2</sup> = 0.97 and R<sup>2</sup> = 0.59 at length of cut (LOC) of 15 and 9.5 mm, respectively. An analysis of variance indicated that both feedroll opening and throughput were affected by forward speed (p <0.01). These experimental results can allow for the optimization of the size of the drive components and facilitate the development of a throughput monitoring system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it