Proceedings
Authors
| Filter results4 paper(s) found. |
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1. Spatial Modelling Of Agricultural Crops For Parallel Loading OperationsThere is a trend in agricultural engineering towards high-performance harvesting machines with growing operating width and throughput. As much as performance and throughput are rising, the transportation units are characterized by increasing transportation volume. If harvesting and transport are combined in parallel operation (e.g. self-propelled forage harvester), the driver of the harvesting machine and the driver of the transport unit has to pay highest attention to the loading process.... G. Happich, T. Lang, H. Harms |
2. Generic ISOBUS Compliant Precision Agriculture Functionality In A Proprietary Terminal ConceptDue to increasing investment costs for agricultural resources crop input management precise application technologies are exceedingly gaining interests for customers. One approach for increasing efficiency is using common GPS-devices for reducing over- and underlaps during application processes, and to adjust application rate based on predefined application maps. Driven by this, implement manufacturers are heading towards machinery, which is able to control application rate and activate... G. Happich |
3. A Dual Motor Actuator Used To Detach Fruit By Shaking Limbs Of Fruit TreesMechanizing the fruit removal operation during fresh-market apple harvesting will result in considerable cost savings for fruit growers. This study introduces a mechanical fruit removal technique that uses a unique limb shaking mechanism called a Dual Motor Actuator (DMA). The DMA was developed as an infinitely variable end-effector that applies rhythmic motions to a fruiting limb to remove fruit. The novelty of the DMA design is the use of two eccentrics mounted to electric motors... M. De kleine, M. Karkee, Q. Zhang, K. Lewis |
4. Deep Learning Prediction of Methane Production in Mesophilic and Thermophilic Anaerobic DigestionAnaerobic digestion (AD) converts organic waste into methane-rich biogas but forecasting methane yield is difficult due to nonlinear dynamics. This study compares Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Temporal Convolutional Network (TCN), and Temporal Fusion Transformer （TFT） models for predicting methane production rate (MPR, L/L/d) under mesophilic (37°C) and thermophilic (55°C) conditions. Lab-scale reactor data with features including hydraulic retention... C. Chou, A. Liu |