Computer Simulation for Haulage Performance of Power Tiller
The presence of a large number of marginal and small land holdings in India has rendered the power tiller to be the most suitable farm equipment for field operations, in view of its compact size, profitability and versatility, but the transport work which is also required to carry the farm produce is yet to be proved. Keeping these in mind, user friendly software was developed for predicting the haulage performance of power tiller to meet requirements in educational and research organizations. The developed software requires input parameters such as power tiller, trolley and operating conditions. The developed software was validated by conducting experiments with a 6.7 kW power tiller using a suitable trolley on tarmacadam road at various payloads and road slopes. The draft, slip, fuel consumption and speed were measured and other haulage performance parameters were calculated based on measured values to validate the developed software. The results simulated by software indicate lower draft and slip in the range of 1-23 and 2-9% with respect to the experimental data, however, higher transport productivity was in the range of 3-12%.
Reliable execution of a robust soft computing workplace found on multiple neuro-fuzzy inference systems coupled with multiple nonlinear equations for exhaustive perception of tractor-implement performance in plowing process
Abstract Tendency towards computer simulations linked to agricultural machinery has enormously increased in recent years. In this regard, the principal contribution of current research was to develop soft computing simulation workplaces for performance prognostication of tractor-implement system in plowing process. Two neuro-fuzzy strategies based on multiple adaptive neuro-fuzzy inference systems (MANFIS) scenario and the MANFIS coupled with multiple nonlinear equations (MNE) scenario were executed in the workplace. Additionally, neural strategy based on artificial neural network (ANN) scenario was also fulfilled in the workplace. Operational variables of plowing depth (10–30 cm), forward speed (2–6 km/h), and tillage implement type (moldboard, disk, and chisel plow) were considered as the workplace inputs and ten performance parameters were taken as the workplace outputs. According to the obtained prognostication accuracy, simulation time, and user-friendly configuration of three scenarios (ANN, MANFIS, and MANFIS+MNE), the MANFIS+MNE was recognized as the prominent simulation scenario. According to the MANFIS+MNE workplace results, for each tillage implement, the compound effect of plowing depth and forward speed on some performance parameters (required draft force of implement, tractor rear wheel slip, fuel consumption per working hour, specific volumetric fuel consumption, tractor drawbar power, energy requirement for tillage implement, overall energy efficiency, and tractor tractive efficiency) was nonlinearly synergetic. However, it was nonlinearly antagonism in case of specific draft force and fuel consumption per tilled area. The MANFIS+MNE workplace simulation results provide opportunity for technical farmer associations involved in the decision-making of agricultural machinery management in order to gain exhaustive fundamental insights into the compound effect of plowing depth and forward speed on performance of tractor-implement systems in plowing process.
The empirical prediction of tractor-implement field performance
Abstract The performance of a two-wheel-drive tractor was measured in 14 different fields when ploughing. Gear number and the number of plough bodies were varied to search for the combination which gave optimum work rate. Tractor and plough performance were modelled using empirical relationships, the measured and predicted performance compared and reasonably good correlation found.