Prediction Model for Wheat Grain Losses in Header of Simulator by Using Dimensional Analysis Approach

Abstract

Introduction One of the problems which considered in recent years for grain harvesting is loss of wheat during production until consumption and tenders the offers for prevention of its especially in harvesting times by combine harvesting machine. Grain harvesting combines are good examples of an operation where a compromise must be made. One would expect increased costs because of natural loss before harvesting, because of cutter bar loss, because of threshing loss, because of greater losses over the sieve and because of the reduced forward speed necessary to permit the through put material to feed passed the cylinder. The ability to recognize and evaluate compromise solutions and be able to predict the loosed grain is a valuable trait of the harvesting machine manager. By understanding the detailed operation of machines, be able to check their performance, and then arrive at adjustments or operating producers which produce the greatest economic return. Voicu et al. (2007) predicted the grain loss in cleaning part of the combine harvester by using the laboratory simulator based on dimensional analysis method. The obtained model was capable to predict the grain loss perfectly. Soleimani and Kasraei (2012) designed and developed a header simulator to optimize the combine header in rapeseed harvesting. Parameters of interest were: forward speed, cutter bar speed and reel index. The results showed that all the factors were significant in 5% probability. Also in the case of forward speed was 2 km h-1, cutter bar speed was 1400 rpm and reel index was 1.5, the grain loss had minimum quantity. The main purpose of this research was to develop an equation for predicting grain loss in combine header simulator. Modeling of the header grain loss was conducted using dimensional analysis approach. Effective factors on grain loss in combine header unit were: forward speed, reel speed and cutter bar height. Materials and Methods For studying the effective parameters on head loss in grain combine harvester, a header simulator with the following components was built in Biosystems Engineering Department of Shiraz University. Reel unit The reel size was 120 cm length and 100 cm diameter. This reel was removed from an old combine header and installed on a fixed bed. For changing the rotational speed of the reel, an electrical inverter (N50-007SF, Korea) was used. Cutter bar unit The cutter bar length was 120 cm. Knifes were installed on this section. Reciprocating motion was transmitted to the cutter bar through a slider crank attached to a variable speed electric motor (1.5kw, 1400 rpm, Poland). The motor was fixed on the bed. Feeder unit This section was consisted of a rail and a virtual ground. This ground was a tray that the wheat stems were staying on it manually. The rail was the path of virtual ground. Treatments consisted of three levels of rotational speed of reel (21, 25 and 30 rpm), three levels of forward speed of virtual ground (2, 3 and 4 km h-1), three levels of cutter bar height (15, 25 and 35 cm) and three replications. In other words, 81 tests were done. The basis of choosing levels of treatments was combine harvester manuals and driver’s experiences. The dependent variable (H.L) was calculated as below: (1) Where L.G is the mass of loss grains and H.G is the mass of harvested grains. Results and Discussion Generally results of ANOVA test showed that the cutter bar height, rotational speed of reel and forward speed had significant effect on head loss. Also interaction of rotational speed and forward speed, cutter bar height and forward speed had significant effect on head loss. These findings were based on Soleimani and Kasraei (2012) research. Therefore, the cutter bar height, rotational speed of reel and forward speed were three independent parameters on head loss as a dependent parameter. By results of laboratory data, the equation for predicting grain loss by header simulator was obtained. Conclusions The statistical results of F- test in 5% probability showed that there were no significant difference between measured and predicted amounts for laboratory data.

Keywords

• combine
• laboratory simulator
• modeling
• wheat