Structure of winnowing equipment

Winnowing equipment for machine-harvested L. barbarum is shown in Fig. 1. The equipment consisted of a mechanical transmission system, winnowing sys­tem, and control system. The mechanical transmission system consisted of an input conveyor, output conveyor, electric motors, and drive systems; the winnowing system consisted of a fan, electronic speed regulator, and lithium battery; and the control system consisted of a controller, electronic speed governors, and relays.

Operating principle of winnowing equipment

As shown in Fig. 2, ripe fruit in the horizontal airflow was subjected to three forces: gravity G , horizontal airflow force P , and buoyancy F _B . Because the buoyancy has a slight influence on the movement of ripe fruit in the horizontal airflow compared with the gravity and horizontal airflow force, it can be ignored ( Liu, 2013 ). After simplification, the angle α between the resultant force of gravity and horizontal airflow force and the gravity can be obtained. When ripe fruit entered the horizontal airflow, its movement under the resultant force was parabolic and the distance of the movement of ripe fruit was related to the angle α ( Liu, 2013 ). The larger the angle α , the farther the distance; the smaller the angle α , the closer the distance. The tangent of angle α can be expressed as the ratio of P to G and is calculated as follows ( Liu, 2013 ).

Mechanical transmission system

Because machine-harvested L. barbarum was trans­­ported on the conveyors and we needed to adjust the input conveyor speed, the design of the input conveyor and output conveyor was highly important. The two transmission shafts were parallel, the rotation direction of the two transmission shafts was the same, and the input conveyor speed was ≤ 20 m/s; thus, the open drive mode can be selected ( Qiu, 2011 ). As the transmission power W was<500 kW, the belt of the input conveyor and output conveyor was made of anti-static flat belt ( Qiu, 2011 ). The design equations [2-8] were referred to this book ( Qiu, 2011 ). The effective tensile force was obtained as follows:

The horizontal airflow model was established based on C++ in Microsoft Visual Studio. Because the size of ripe fruit was approximately consistent and the horizontal airflow parameters ( e.g. , velocity, density, and viscosity) were basically constant, the free flow resistance model was adopted ( Hu, 2010 ). To accurately simulate the movement of ripe fruit in the horizontal airflow, its buoyancy and free flow resistance force should be considered ( Liu et al. , 2015 ; Liu, 2018 ; Yu et al. , 2018 ). The equations [9-12] were referred to Hu (2010). The equations of the buoyancy F _B and the free flow resistance force F _d are as follows:

Ningqi 7 was selected as the experiment variety. The following instruments were used: 1) an elec­tronic vernier caliper (type: AIRAJ second-generation product; range: 0-300 mm; precision: 0.01 mm; manufactured by Qingdao Yigou Hardware Tools Co., Ltd., China); 2) a digital illuminometer (type: PM6612L; manufactured by Shenzhen New Huayi Instrument Co., Ltd., China); 3) a tachometer (type: DT2236B; manufactured by Shenzhen Sanpo Ins­trument Co., Ltd., China); 4) a digital anemometer (type: PM6252B; manufactured by Shenzhen New Huayi Instrument Co., Ltd., China).

The winnowing equipment was used to remove as many impurities as possible ( e.g. , unripe fruit, flowers, and leaves) in machine-harvested L. barbarum while removing as little ripe fruit as possible. The purpose of the experiment was to investigate the performance of the winnowing equipment; therefore, the rate of impurity change Y ₁ and the clearance rate of ripe fruit Y ₂ were selected as performance indices in the experiment. Corresponding equations to calculate these indices are as follows:

The regression model of the rate of impurity change (response) using codes of all factors as variables was as follows:

The response surface methodology was used to analyze the effects of all factors on the rate of impurity change; the response surface results of the regression equation (Eq. [15]) are shown in Fig. 6. As shown in Table 5, the airflow speed, input conveyor speed, and input-output conveyor distance each had an extremely significant effect on the rate of impurity change. The interaction effect between the airflow speed and input conveyor speed was significant. As shown in Fig. 6a, as the airflow speed increased, the rate of impurity change first increased rapidly and then decreased slowly. As shown in Fig. 6b, as the input-output conveyor distance increased, the rate of impurity change first increased slowly and then decreased slowly. As shown in Fig. 6c, as the input conveyor speed increased, the rate of impurity change first increased slowly and then decreased slowly.

The response surface methodology was used to ana­lyze the effects of all factors on the clearance rate of ripe fruit; the response surface results of the regression equation (Eq. [16]) are shown in Fig. 7. As shown in Table 6, the airflow speed, input conveyor speed, and input-output conveyor distance each had an extremely significant effect on the clearance rate of ripe fruit. The interaction effect between the airflow speed and input conveyor speed was significant. As shown in Fig. 7a, as the airflow speed increased, the clearance rate of ripe fruit first decreased lowly and then increased rapidly; in Fig. 7b, as the input-output conveyor distance increased, the clearance rate of ripe fruit first decreased rapidly and then increased rapidly; and in Fig. 7c, as the input conveyor speed increased, the clearance rate of ripe fruit first decreased rapidly and then increased rapidly.

After prediction, the optimal parameter combination was determined to be an airflow speed of 5.52 m/s, input conveyor speed of 0.5 m/s, and input-output conveyor distance of 265.04 mm.

The field experiment was completed on June 28, 2018 and 15 groups were conducted in this experiment to eliminate random errors. The chosen experiment parameter combination was an airflow speed of 5.52 m/s, input conveyor speed of 0.5 m/s, and input-output conveyor distance of 265.04 mm. As depicted in Fig. 8, a high-speed camera (type: OLYMPUS i-speed TR; manufactured by Keymed (Medical & Industrial Equipment) Co., Ltd., UK) was used to record the winnowing process; the duration was 200 ms, the interval was 40 ms, and we used 1000 f/s ( Torregrosa et al. , 2014 ; Liang et al. , 2018 ). Red, green, purple, and blue points were used to indicate the respective positions of the ripe fruit, unripe fruit, flower, and leaf every 40 ms. The field experiment showed that the rate of impurity change and the clearance rate of ripe fruit were 89.74% and 8.71%, respectively.