For rice ratooning, the lateral bud germination of the rice stubble after the first harvesting can be used to continue the next growing season, but the first harvesting machinery will crush and damage the rice stubble, resulting in the reduction of yield in the ratooning season. Lifting the rolled stubble can reduce this loss, and thus a double-chain finger grain lifter was designed in this study. Then, a kinematic model and motion trajectory curve of the grain lifter was established. The influence law of the chain speed, chain spacing and the number of fingers of the rear lifting chain was determined. Furthermore, taking into account the success rate and the rate of secondary damage of the lifting, a full-factor bench test was performed. The best operating characteristics of the grain lifter are: chain speed of 345 r/min, adjacent chain spacing of 300 mm, and the number of gears and fingers on the rear lifting chain of 3. The success rate and the secondary damage rate of the lifting is 90.05% and 1.72%, respectively. A field verification test was conducted, with an average success rate of 55%. The results of this study can provide valuable reference for the lifting technology of rolled rice stubble and promote the whole mechanized production of ratoon rice.
Aiming at the poor performance and low efficiency of moist fertilizers, a cam-linkage self-cleaning fertilizer apparatus is designed. The cam-linkage mechanism matched with the self-cleaning device is applied to scrape off the residuals, and the structural parameters of flute cam in the wheel are obtained by using the polar equations. The physical characteristics of Stanley compound fertilizer, Kingenta compound fertilizer and Kingenta dual-effect nitro-fertilizer are analyzed to build the discharging model and obtain the key parameters, such as the wheel diameter, the groove number. The trajectory of fertilizer is introduced for the scraper plate. To evaluate the performance, a full factorial experiment including fertilizer types, moisture content and rotating speed is conducted, taking the discharging and coefficient of variation as the evaluation indicators. The results show that in the rotation of 10-50 r/min, the cam-linkage self-cleaning fertilizer apparatus could discharge compound fertilizers with a moisture content less than 8%, and the coefficient of variation is 0.12% -8.21%. In addition, the relationship between the rotating speed and the discharging has the linear relationship, and the determination coefficient R² are more than 0.974. This study helps promoting the deep fertilization technology and equipment in southern rice regio
As a highly productive rice, ratoon rice is widely planted worldwide, but the rolling of rice stubble in mechanical harvesting severely limits its total yield; based on this, some scholars have proposed rolled rice stubble righting machines. However, limited by the uncertainty of the field environment, the machine’s localization accuracy of the target needs to be improved. To address this problem, real-time detection of rolled rice stubble rows is a prerequisite. Therefore, this paper introduces a deep learning method for the first time to achieve this. To this end, we presented a novel approach to improve a model that is used for the simplification of Mask R-CNN, which does not require any modules to be added or replaced on the original model. Firstly, two branches in the second stage were deleted, and the region proposals output from the stage was used directly as the mask generation region, and segmentation performance was substantially improved after a simple optimization of the region proposals. Further, the contribution of the feature map was counted, and the backbone network was simplified accordingly. The resulting SMR-RS model was still able to perform instance segmentation and has better segmentation performance than Mask R-CNN and other state-of-the-art models while significantly reducing the average image processing time and hardware consumption.
The performance of hole-type metering device influenced the adaption of different rice varieties in the mechanical direct hill-drop seeding technology, and the stepless adjustable sowing amount hole-type metering wheel was designed to solve this problem. The mechanical characteristics of different seeds were analyzed to acquire the parameters including hole diameter, depth, number, diameter of metering wheel and jogger slider mechanism, and the performance of metering wheel was tested on JPS-12 experimental bench by using Yongyou 12, Huanghuazhan and Wanxiang youhuazhan varieties. The hole depth and rotating speeds of metering wheel were the independence variance, the average seed numbers per hole, the coefficient of variance and the cavity rate were taken as the evaluation indexes. The results showed that the metering wheel could sow 3.58~7.82 seeds per hole with less than 40% of the coefficient of variance in average seeds number per hole and less than 5% of the cavity rate, and the regression model of average seed numbers per hole was built by employing the length of seeds, the rotating speed of metering wheel and the hole depth. The correlation coefficient was 0.952, the prediction error of regression mode was 0.32~11.35% by the field experiment. This study could be used for designing the hole-type metering device for rice.
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