Improved antenna design for grain bin electromagnetic imaging
Notice bibliographique
Résumé
Grain such as wheat and canola is usually stored in silos or bins, often for long periods of time. Grain can and regularly does spoil in such bins, thus monitoring the grain quality and quantity inside the bin is crucial. It is possible to monitor grain within metallic grain bins using three-dimensional ElectroMagnetic Imaging (EMI). To acquire data in EMI, multiple antennas must transmit and receive ElectroMagnetic (EM) energy within the imaging bin. These antennas subjected to significant mechanical forces, they must have a low profile. These antennas should also be easy to model in computational EM software (using a point source). Moreover, since the EMI algorithm uses linear polarization of EM fields, it is common to choose antennas that can detect a linear polarization and reject others, such as antennas that measure magnetic fields normal to the antenna’s loop and reject electric fields. This can be done through using Shielded Loop Antennas. Given their desirable physical and EM characteristics, previous grain bin imaging systems have been designed with Shielded Half Loop Antennas (SHLA). While capable of detecting primarily the tangential magnetic field at the bin wall, existing SHLA suffer from a large reflection coefficient at the antenna terminal, meaning they can be drastically improved by reducing this reflection coefficient, thus reducing noise and receiving more desired signal. Herein, we consider two methods of improving upon this design: matching circuits and improved antennas. For matching techniques, we consider passive and active circuits. Through simulation, we show how these methods can improve antenna performance. For an improved antenna design, we show that loading a SHLA with ferrite material can enhance its performance. To model the behavior of a ferrite-loaded shielded loop antenna, we develop an approximate lumped circuit model which can predict antenna resonance frequency, its reflection coefficient, and its efficiency. This model aids in the design of larger sized ferrite-backed antennas. An antenna at resonance frequency of 260 MHz is fabricated and tested in a small (labratorysized) grain bin. Its sensitivity to magnetic field and rejecting electric fields is tested in Gigahertz Transverse EM (GTEM) cell at the Electromagnetic Imaging Laboratory (EIL) of the University of Manitoba, and show that the ferrite-backed antenna increases signal strength while maintaining the rejection of normal-E fields. The small ferrite loaded shielded half-loop antenna provided a 6 18 dB improvement in signal level over existing half-loop antennas over the imaging frequencies of interest (approx 200600 MHz). Furthermore, experimental laboratory imaging tests with hard-red winter wheat indicate that the proposed antennas can be modeled more accurately using simple polarized point sources. A full 3D image of a wet-grain target set within a dry-grain background inside the enclosure shows that the improved antennas enhance the quality and accuracy of the reconstructed images, mainly where the antenna performance improvements are prominent. Based on these promising results, we designed and constructed a scaled up ferrite-backed halfloop antenna suitable for a larger industrial grain bin and at a lower frequency (a resonance of 120 MHz). Preliminary measurements of these antennas show that these larger versions not only can detect magnetic field and reject electric fields, but also increase the signal strength in the grain bin.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».