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| Rahmanian- Koushkaki, Hossein; Karparvarfard, Seyyed Hossein; Mortezaei, Alireza. |
| A microcontroller based instrumentation package was designed, developed and mounted on an 81 kW Massey Ferguson 399 (MF-399) tractor. This package continuously measures and monitors various performance parameters of the tractor and implement. These parameters were: actual forward speed, theoretical forward speed, slip, fuel consumption and implement draft. The package comprised of four components: power supply, transducers, data acquisition, and display unit. Power was taken from the tractor battery. The data acquisition system was capable of scanning the data at 0.1 s intervals. The system performed well during the field operations and the results obtained showed that the accuracies of the transducers were acceptable. |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Data acquisition; Draft; Fuel consumption; MF-399 tractor; Microcontroller. |
| Ano: 2015 |
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/3029 |
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| Okoko, Paul; Umani, Kingsley Charles; Onwe, David Nwabueze. |
| Selection and matching of appropriate tillage implements for a given farming operation are dependent on the data available on draft parameters for the particular tillage implement. Spring tine cultivator is one of the primary tillage implements commonly used by farmers in the study location. Performance information of spring tine cultivator is vital to enable the cost of tillage operation to be reduced. Field experiments were performed using spring tine cultivator and tractor at three tillage depths (10, 20 and 30 cm) and five tractor speeds (3.6, 5.4, 7.2, 9.0 and 10.8 km/hr) to determine the implement travel speed. The effects of tillage depth and implement travel speed on draft force, unit draft, vertical specific draft, horizontal specific draft and... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Tillage; Draft; Unit draft; Specific draft; Coefficient of pull; Tractor; Spring tine cultivator. |
| Ano: 2023 |
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/7061 |
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| Marey,Samy; Aboukarima,Abdulwahed; Almajhadi,Yousef. |
| ABSTRACT This study examines the capability of an artificial neural network (ANN) approach using a backpropagation-learning algorithm to predict performance parameters for a chisel plow at three field sites with differing soils. The draft force, effective field capacity (EFC), fuel consumption rate (FC), overall energy efficiency (OEE), and rate of plowed soil volume (SVR) were predicted at varying plowing speeds, plowing depths, soil moisture contents, soil bulk densities, soil texture indexes, and tractor powers. Collected field data was divided into a training set (for predicting the required parameters) and testing set (for model validation). For the ANN algorithm, the number of hidden layers, neurons, and transfer functions were varied to construct... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Backpropagation-learning algorithm; Draft; Fuel consumption; Overall energy efficiency. |
| Ano: 2020 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162020000600719 |
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