Design & Simulation of Automatic Control and Operation of Agricultural Wide-Span Implement Carrier (WSIC)
Bibliographic record
Abstract
Abstract. Automatic control of an Agricultural Wide-Span Implement Carrier (WSIC) used for cranberry harvesting includes the implement vertical positioning and rotation, and the displacement and rotation of the mobile carriage. These operations currently rely on a human operator and they involve several sequential steps that would benefit from automation. Moreover, adjusting the harvester head position relative to the crop can be a demanding task for the operator. An electro-hydraulic simulation of the WSIC was developed using Automation Studio Software with the following objectives: (1) To develop and implement a programmable logic controller (PLC) which is used to regulate the sequence; (2); To design an electrohydraulic automatic control of header height and the rotation of harvester using proportional-integral-derivative (PID) control and (3) To avoid mistakes of direct design and implementation in the industrial and production processes before fabrication. The simulation process is based on the hydraulic pump characteristics obtained through the existing hydraulic system analysis. Hydraulic and electric components such as proportional hydraulic value and sensor for adjusting the harvester height and speed in proportion; and PLC were chosen based on Automation Studio™ libraries components structured with international standards. The designed system is reliable and meets the design expectations. Furthermore, the simulation results show good performance for positioning of cylinders with a very small error relative to the set point and also for hydraulic motor speed response with different predefined resistance load applied on the hydraulic motor. The results indicated that the proposed approach has great potential to improve the design and operation of the WSIC.
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.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".