Draft measurement of five tyne duck foot plough in clay soil

Manikandan, G.; Shridar, B.; Jesudas, D. M.

doi:10.31018/jans.v13isi.2780

Cited by 2 publications

(1 citation statement)

References 5 publications

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“…This same trend was observed in previous studies [57,58]. However, in other research papers [55,[67][68][69][70][71][72], the inverse relationship between the initial soil moisture content and horizontal force was observed. The drop in horizontal force caused by increased soil moisture content can be attributable to both the change in soil resistance and the decrease in soil failure force [67].…”

Section: Pearson's Correlation Coefficients For Explanatory Variablessupporting

confidence: 89%

Modification of Values for the Horizontal Force of Tillage Implements Estimated from the ASABE Form Using an Artificial Neural Network

et al. 2023

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The famous empirical model for the horizontal force estimation of farm implements was issued by the American Society of Agricultural Biological Engineers (ASABE). It relies on information on soil texture through its soil texture adjustment parameter, which is called the Fi -parameter. The Fi-parameter is not measurable, and the geometry of the plow through the machine parameter values are not measurable; however, the tillage speed, implement width, and tillage depth are measurable. In this study, the Fi-parameter was calibrated using a regression technique based on a soil texture norm that combines the sand, silt, and clay contents of a soil with R2 of 0.703. A feed-forward artificial neural network (ANN) with a backpropagation algorithm for training purposes was established to estimate the modified values of the horizontal force based on four inputs: working field criterion, soil texture norm, initial soil moisture content, and the horizontal force (which was estimated by the ASABE standard using the new—Fi-parameter). Our developed ANN model had high values for the coefficient of determination (R2) and their values in the training, testing, and validation stages were 0.8286, 0.8175, and 0.8515, respectively that demonstrated the applicability for the prediction of the modified horizontal forces. An Excel spreadsheet was created using the weights of the established ANN model to estimate the values of the horizontal force of specific tillage implements, such as a disk, chisel, or moldboard plows. The Excel spreadsheet was tested using data for a moldboard plow; in addition, a good prediction of the required horizontal force with a percentage error of 10% was achieved. The developed Excel spreadsheet contributed toward a numerical method that can be used by agricultural engineers in the future. Furthermore, we also concluded that the equations presented in this study can be formulated by any of computer language to create a simulation program to predict the horizontal force requirements of a tillage implement.

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Section: Pearson's Correlation Coefficients For Explanatory Variablessupporting

confidence: 89%

Modification of Values for the Horizontal Force of Tillage Implements Estimated from the ASABE Form Using an Artificial Neural Network

et al. 2023

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Modeling and FEM Analysis of Shovel of 5-Tyne Duck Foot Cultivator

Awachat¹,

Sheikh²

2022

IJARSCT

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For soil preparation Cultivator is important agricultural equipment. As an important agriculture equipment for soil preparation cultivator is used in which stress are form due to contact with soil where tyne and shovel works as actual member of cultivator which is direct contact with soil. We can reduce the stress from changing the design of tine or shovel of cultivator. The main objective of this analysis is to analyze the forces developed on shovel during operation. To analyze this Shovel using FEM, firstly a proper CAD model has been developed using CATIA cad software. Then by using ANSYs software FEM analysis have been done to determine the stresses.

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Draft measurement of five tyne duck foot plough in clay soil

Cited by 2 publications

References 5 publications

Modification of Values for the Horizontal Force of Tillage Implements Estimated from the ASABE Form Using an Artificial Neural Network

Modification of Values for the Horizontal Force of Tillage Implements Estimated from the ASABE Form Using an Artificial Neural Network

Modeling and FEM Analysis of Shovel of 5-Tyne Duck Foot Cultivator

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