Efficient and Low-Loss Cleaning Method for Non-Uniform Distribution of Threshed Materials Based on Multi-Wing Curved Combination Air Screen in Computational Fluid Dynamics/Discrete Element Method Simulations

Abstract

During the operation of the longitudinal axis flow threshing device of a combine harvester, the threshed materials form accumulations and blockages on both sides of the screen surface, severely affecting the harvesting process. To evenly distribute the materials on the screen and solve the blockage issue, a multi-wing curved combination centrifugal fan is designed to match the mass distribution of the threshed materials. The movement mechanism of rice threshed materials in the cleaning shoe of a longitudinal axis flow combine harvester is investigated using the coupled CFD-DEM simulation method. The cleaning efficiency and performance of the traditional straight-blade fan screen device and the newly designed cleaning device are compared and analyzed, and field tests are conducted. The results show that the trajectory of the threshed materials cleaned by the device equipped with the multi-wing curved combination centrifugal fan is consistent with the mass distribution of the materials separated by the longitudinal axis flow threshing device. The absolute value of the centroid velocity of the material group in the X/Y direction is greater than that of the traditional fan, indicating that the movement speed of the particle group in the optimized fan is greater than that of the traditional fan. Therefore, in the actual cleaning process, the optimized fan’s air flow distribution more effectively accelerates the movement speed of the threshed materials, increasing the amount of materials cleaned per unit time, thereby improving the cleaning efficiency. Field comparative tests show that the designed cleaning device reduced the cleaning loss rate by up to 25.00% and the impurity content rate by 32.20%, achieving efficient and low-damage cleaning of the combine harvester. The study demonstrates the effectiveness of the proposed method for evenly distributing the materials and provides important reference for the study of other piled particle distribution systems.

1. Introduction

The cleaning device is the “digestive system” of the combine harvester, directly affecting the harvesting performance and efficiency. The mainstream combine harvesters in the world mainly use the longitudinal axis flow threshing drum in combination with a fan for cleaning [1,2,3]. Under the action of air flow and the vibration of the screen, the grain threshing mixture is separated, with the grains being transported to the grain tank and the impurities being blown out of the cleaning shoe. Due to the structure of the longitudinal axis flow drum and the cleaning fan, the threshed materials tend to form a non-uniform distribution trend on the screen surface. Additionally, the crop density in the field can affect the cleaning process, leading to the risk of local accumulation and even blockage of the materials on the screen. Therefore, it is necessary to improve and analyze the wind-screen-type cleaning device equipped with a longitudinal axis flow threshing mechanism to enhance the cleaning performance and efficiency.

Numerous studies have investigated the distribution trend of the materials on the screen surface. The longitudinal axis flow threshing device has the advantages of high threshing efficiency and good performance [3] and is widely used in mainstream models worldwide, including CLAAS, CASE, John Deere, New Holland, etc. [4,5]. Due to the cylindrical longitudinal axis flow drum’s rotational movement, the materials are thrown outward by centrifugal force. However, the materials on both sides of the drum are affected by the cleaning shoe wall and fall directly when they hit the wall, causing more materials to accumulate on both sides of the screen. Ultimately, this leads to a saddle-shaped distribution trend with high sides and low center on the screen, and due to the rotation direction of the drum, the mass of the materials on both sides is inconsistent. This makes the cleaning process difficult for traditional cleaning devices that solely pursue uniform air volume in the horizontal direction of the cleaning shoe, leading to insufficient air volume in areas with concentrated materials, causing difficulty for grains to pass through the screen, reduced cleaning efficiency, and rapid increase in impurity content. In areas with less material, excessive air volume leads to increased grain loss.

To address the poor cleaning performance caused by uneven material distribution, domestic and foreign researchers have conducted extensive theoretical and experimental studies on wind-screen-type cleaning devices. Currently, researchers have adopted three approaches to solve this problem, including cleaning screen profiling, guiding the threshed materials, and using cleaning fans with uneven air output. In terms of cleaning screen profiling research, the TUCANO and AVERO series combine harvesters produced by the German CLAAS company (Harsewinkel, Germany) are designed with 3D cleaning vibrating screens, which transport concentrated materials to areas with relatively fewer materials through the inclined floating conveying of the screen surface [6]. At the same time, the 3D cleaning vibrating screen installed on the TUCANO cleaning screen adjusts the posture of the vibrating screen in real-time according to the ground slope, using the method of keeping the vibrating screen level with the ground to reduce the unevenness of the materials on the screen. In the AVERO series, a rolling baffle was added to the 3D cleaning device, forming a “4D” cleaning screen. When the combine harvester passes through a slope, the feed rate changes [7]. The “4D” cleaning device in AVERO adjusts the speed of the rolling baffle in real-time according to the threshing output, maintaining the feed rate of the threshed materials in the cleaning shoe within a certain range. The CX8.90-type combine harvester produced by the New Holland company (New Holland, PA, USA) uses the self-developed Opti-Clean™ System [2], where the fan and the speed of the thrasher can be automatically adjusted when going uphill or downhill, which can increase the cleaning efficiency by 30% in areas with severe ground undulations; at the same time, it uses a pre-screen board with a steep slope in combination with adjustable cascade multi-block screens to tackle the problem of materials tilting and accumulating on one side during hill harvesting.

Research on the guidance of threshed materials includes the following. In 2020, Xu Lizhang’s team from Jiangsu University [8] developed an automatic adjustment device for the guide strips on the return board to address the issue of material accumulation on the sieve surface during the rice cleaning process, enhancing the lateral distribution capability of the materials on the sieve. In 2022, Jiang Tao [9] designed a material dispersion and guidance device for the rapeseed cleaning screen, improving the rapeseed harvesting performance. In 2022, Shu Caixia et al. [10] addressed the issues of high loss rates and insufficient cleaning efficiency in the cyclone separation cleaning device for rapeseed combine harvesters by developing a guided double-cylinder cyclone separation cleaning device with flow guiding and secondary settling functions. Some related studies have also designed cleaning fans with uneven air output to improve cleaning efficiency. Chen Ni et al. [11] from Jinhua Vocational and Technical College, targeting the uneven distribution of materials along the width of the transverse axial flow threshing device, designed a conical centrifugal cleaning fan, which has a conical impeller with a larger end at the feeding end and a smaller end at the discharge end. This fan can use non-uniform airflow to compensate for the uneven initial distribution of materials on the longitudinal vibrating screen of the transverse axial flow threshing device, and it can convert the pressure difference generated into transverse wind speed.

Although the German CLAAS company, the American CASE (Little Rock, AR, USA), and New Holland combine harvesters are equipped with intelligent uniform distribution devices, the cleaning device space of large European and American harvesters is relatively large, and the multi-degree-of-freedom screening mechanism is huge, complex, and expensive. Compared to the mainstream Chinese models, small and medium-sized combine harvesters (with an annual sales volume of 50,000 units) are limited by the size of the machine, and it is not possible to implement the layout of guide strips and related distribution devices. Although the related distribution devices of small and medium-sized models have applied for relevant patents and published literature, the physical prototypes are still in the experimental design stage, and the test data are mostly from bench tests, not yet applied to the actual field harvesting of combine harvesters. There is still a lot of work to be done before they can be put into practical use. In addition, the design of domestic uneven air fans is mainly for the transverse axial flow threshing device, but there are few reports on the design of cleaning fans for the longitudinal axial flow threshing device. The uneven air cleaning fans designed above cannot effectively solve the cleaning problem of materials being high on both sides and low in the middle in the cleaning shoe.

The rice cleaning process involves interactions between materials, between materials and the cleaning screen, and between the airflow and materials, with a significant amount of mass, momentum, and energy exchange. Simply analyzing the airflow field without materials or the vibration screen alone cannot fully and accurately reflect the wind-screen selection process. Therefore, it is essential to analyze the combined action of the airflow and the vibration screen to accurately reflect the cleaning process. The popularity of computational fluid dynamics coupled with the discrete element method (CFD-DEM) has been increasing over the last few decades due to its accuracy in modeling multiphase solid–fluid flows [12,13,14,15]. In 2017, Mohammad et al. [16] analyzed the mass and flow rate of corn in screw conveyors based on discrete element modeling and validated the reliability of the simulations through experiments. In 2017, Lu Xiuqiang [17] conducted gas–solid two-phase flow coupled simulations of the motion of threshed wheat in the cleaning chamber and obtained the optimal combination of working parameters for a buckwheat cleaning device. In 2020, Yuan Jianbo et al. [18] used the CFD-DEM method to simulate the separation process of rice and threshing mixtures in the airflow cylindrical screen of rice–wheat combine harvesters and validated the simulation results with experiments using real threshing mixtures on a test bench, which showed consistency with the simulations. In 2020, Xu Lizhang et al. [19] conducted numerical simulations of rice wind screen cleaning devices under multiple working conditions using computational fluid dynamics and discrete element method coupling. In 2022, Shi Ruijie et al. from Gansu Agricultural University [20] studied the compound cleaning mechanism of the flaxseed combine harvester in hilly and mountainous areas, obtaining the motion trajectories and separation laws of each component. In 2023, Ma Zheng et al. [21] used variable amplitude screens to evenly distribute the rice materials on the sieve surface and established a material distribution model at different guide slot heights. Related studies have conducted gas–solid two-phase flow simulations for the cleaning process of various grains, but a complete material component model and accurate feed model have not been established. Therefore, analyzing the motion trend of materials under increased feed rates within the same cleaning shoe structure is essential for studying cleaning efficiency and performance.

Existing research mainly has the following two gaps: (a) There are few reports on the design of non-uniform airflow fans for longitudinal axial-flow threshing devices, which have not effectively solved the issue of uneven distribution of threshed material in the cleaning chamber, with higher distribution on both sides and lower in the middle, resulting in high impurity content and loss. (b) Although current studies using CFD-DEM technology have explored particle movement patterns, they have not established a complete model of threshed material composition and accurate feed rate model, nor have they considered the uneven distribution trend of threshed material. Therefore, it is necessary to design a non-uniform airflow fan for longitudinal axial-flow threshing devices and investigate the distribution of threshed material using CFD-DEM coupled simulations. The innovation of this study lies in improving the structure of the fan impeller, designing a non-uniform airflow fan based on the uneven distribution patterns of the threshed material, and using CFD-DEM numerical simulation methods to differentially set up particle factories to simulate the distribution trends of the threshed material. This study aims to microscopically analyze the movement trends and cleaning performance of threshed material in the cleaning chamber. The goal of this research is to design a new type of cleaning fan structure to address the uneven distribution of threshed material in longitudinal axial-flow threshing devices and further explore the movement process of multi-component threshed material in the cleaning chamber under the coupled excitation of airflow lifting and vibrating screening. This will demonstrate the scientific basis of the fan design and improve cleaning performance and efficiency.

2. Materials and Methods

2.1. Design of the Multi-Wing Curved Combination Multi-Air-Duct Cleaning Device

The cleaning fan is a critical factor influencing the efficiency and performance of cleaning [22]. Agricultural cleaning fans typically feature dual-sided air intake, with the impeller length equal to that of the drum [23]. To address the issue of excessive suction caused by overly long impellers, multiple coaxially driven fans are commonly employed [24]. This study adjusts fan sizes based on material concentration to address uneven distribution. The specific design steps include determining the fan positions based on the distribution of threshed materials, designing the dimensions of the fan casing and impeller.

2.1.1. Calculation of the Required Air Volume for the Cleaning Fan

Based on the air volume required for different regions within the cleaning shoe, a cleaning fan is designed for a combine harvester with an input rate of 7 kg/s.

The size of the air volume must be determined based on the proportion of impurities in the threshed materials. Tests on the distribution pattern of materials below the transverse flow device were conducted at the Key Laboratory of Modern Agricultural Equipment and Technology, Jiangsu University. The arrangement of the test receiving boxes divided the materials into different regions. The seven receiving boxes located below the transverse flow threshing drum divided the materials in the cleaning shoe into seven longitudinal regions, as shown in Figure 1. This division method allows the mass of the materials to be cleaned to correspond to different areas of the cleaning fan’s horizontal outlets.

Summing up the mass of materials in each column of the seven regions (①–⑦) as shown in Figure 1, and along the forward direction, the distribution pattern of materials in the transverse direction of the cleaning shoe is derived, as shown in Figure 2. It can be observed that, with different gaps in the concave plate [25], the materials show a trend of being more abundant on both sides and less in the middle along the transverse direction of the cleaning shoe. This indicates that the distribution trend of materials on the cleaning screen in the transverse direction is consistent during the process of concave plate gap variation.

Based on the weights of the materials distributed along the width of the cleaning shoe, as calculated in Figure 2, referring to the agricultural machinery design manual [23,26], the fan air volume V_fan is calculated using Equation (1). The calculated required air volume for different regions of the fan’s horizontal outlets is shown in

Table 1. Theoretical estimation of air outlet airflow volume.

Cleaning Shoe Transverse Area Number	①	②	③	④	⑤	⑥	⑦
Threshed materials mass/g	1238.18	1055.00	987.49	890.35	798.34	882.89	1148.08
Required air volume theoretical value of the outlet (m3/s)	0.44	0.38	0.35	0.32	0.29	0.32	0.41

.

$$V_{fan}=\frac{{\beta }_f·Q_f}{{\mu }_f·{\rho }_f}$$

(1)

In this equation, β_f represents the proportion of impurities in the threshed materials. Q_f denotes the total feed rate of the machine in kg/s; μ_f is the mixed concentration ratio that includes impurities as well as air flow, and ρ_f stands for the density of air.

Taking the 4LZ-6.0 type combine harvester as the test prototype, the fan structure is designed to meet the requirements of this model. On this model, the outer diameter of the fan casing should not exceed 400 mm, the total width of the upper outlets is 1000 mm, and the total width of the lower outlets is 1060 mm. Based on the material distribution pattern corresponding to Figure 2, the casing is divided into three regions, and three sub-fans are designed. This design primarily considers the following two aspects: (1) Materials are mainly locally accumulated on both sides of the cleaning shoe, and two sub-fans corresponding to the width of these areas are designed to focus on cleaning the regions with higher mass. (2) Considering the complexity of the manufacturing processes, a single fan is used to clean the region in the middle of the cleaning shoe, where the mass of materials is relatively low. The regions corresponding to the sub-fans designed in the study and the distribution of materials in the cleaning shoe are shown in Figure 3, with the sub-fans labeled as Fan I, Fan II, and Fan III.

The widths of the casings for the three sub-fans are 260 mm, 440 mm, and 200 mm. The sub-fans are spaced 80 mm apart from each other for ease of installation. The widths corresponding to the fans are consistent with the material distribution trend in Figure 2. Fan I and Fan III correspond to the positions on both sides where materials are concentrated. The region in the middle of the cleaning shoe where the mass of materials is relatively low is larger; hence, the transverse width corresponding to Fan II is wider.

2.1.2. Multi-Duct Centrifugal Fan Volute and Impeller Combination Design

The casing design employs an upper and lower air duct structure to pre-clean the threshed materials for improved efficiency [16]. The dimensions of the multi-air-duct fan casing are determined using the unequal edge element method. With the casing structure established, the diameter and width of the impeller are determined. Based on the outer diameter, the casing profile can be designed. According to the material mass in the regions corresponding to the three sub-fans calculated from Table 1, the main parameters of the developed fan are shown in

Table 2. The main parameters of multi-fan coaxial drive cleaning fan volute.

Design Variable	Fan I	Fan II	Fan III
Casing width Bk/mm	260	440	200
Inlet diameter D0/mm	300	300	300
Impeller outer diameter D2/mm	360	340	360
Outlet height Sf/mm	240	240	240
Casing shell extension size Af/mm	56	56	56
R1 = D2/2 + Af/8/mm	187	177	187
R2 = D2/2 + (3/8)Af/mm	201	191	201
R3 = D2/2 + (5/8)Af/mm	215	205	215
R4 = D2/2 + (7/8)Af/mm	229	219	229
Compression stroke φf/°	72.24	91.10	72.24
Centrifugal radius R5/mm	207	195	207
Horizontal distance Lf/mm	46	42.86	46
Vertical distance Hf/mm	184.23	173.62	184.23
Theoretical air volume of sub-fan/(m3/s)	0.82	1.00	0.69

.

The cleaning impeller adopts the double-suction agricultural fan impeller commonly used on combine harvesters as the design basis. By increasing the number of blades, changing the shape and layout of the blades, the overall pressure of the impeller is reduced, improving the uniformity of pressure distribution. This blade arrangement can also increase the static pressure of the fan, reducing the vortex turbulence caused by the air intake on both sides of the fan, thereby extending the service life of the impeller [27].

Based on the design results of the casing and impeller, the impellers of the three sub-fans have the same structure and are coaxially arranged, but the widths and outer diameters of the impellers are differentially adjusted according to the mass of the material regions. The outer diameter of Fan II is reduced, and the width is increased to adapt to the wider central area; the outer diameter of Fan I is increased, and the width is wider than that of Fan III to cope with the high mass of materials in the wide area; the outer diameter of Fan III is the same as that of Fan I, with the smallest width to adapt to the narrow and high-mass-material area. The multi-wing curved combination centrifugal fan cleaning device is shown in Figure 4.

2.2. Multi-Solid Phase Rice Harvest Residue Gas–Solid Two-Phase Flow Coupled Simulation

The process of crop cleaning involves complex interactions between airflow, particles, and the sieve surface which cannot be accurately simulated by analyzing either the airflow or the vibrating screen alone. To accurately reflect the cleaning process, it is necessary to analyze the combined effects of the airflow and the vibrating screen. Previous gas–solid two-phase flow simulation studies did not establish complete models of particle composition and feed rate. The CFD-DEM coupling method simulates the fluid using FLUENT (Version 15.0, ANSYS Inc., Canonsburg, PA, USA) and the particles using EDEM (Version 2.7, DEM Solutions Ltd., Edinburgh, UK), achieving the coupling of gas–solid two-phase flow. This method tracks the motion of particles and calculates the forces and positional changes, reflecting the interactions between particles and with the fluid. The coupling process includes meshing the flow channel model in ICEM, setting boundary conditions and time steps for airflow simulation in FLUENT, establishing particle parameters and contact models in EDEM, and finally, through a coupling interface, exchanging computational results between FLUENT and EDEM, updating particle positions and airflow forces to complete the coupled computation. The specific coupling procedure is shown in Figure 5.

The continuity equation and momentum equation of the gas phase can be expressed as Equations (2) and (3):

$$\frac{\partial \epsilon \rho }{\partial t}+\nabla ·\rho \epsilon u=0$$

(2)

$$\frac{\partial \epsilon \rho }{\partial t}+\nabla ·\rho \epsilon u\mu =-\nabla \rho +\nabla ·(\mu \epsilon \nabla u)+\rho \epsilon g-S$$

(3)

where ε, ρ, u, m, and S are the volume fraction term, gas density (kg·m⁻³), gas velocity (m·s⁻¹), coefficient of viscosity (Pa·s⁻¹), and momentum sink (kg·m·s⁻¹), respectively.

The contact model is a fundamental basis of the discrete element method (DEM), and the essence of the particle collision contact model is the analysis result of the contact mechanics of particles under quasi-static conditions. It is important to note that although the particle contact relationship is nonlinear, the principle of approximate superposition is still required. In the EDEM software, the default contact model is the Hertz–Mindlin model [28], also known as the “elastic–damping–friction contact mechanics model”. This study employs the Hertz–Mindlin contact model to investigate the motion patterns of the harvested residues within the multi-duct cleaning device, which can be expressed as Equations (4)–(7).

$${\overrightarrow{F}}_{cni}=\frac{4}{3}{E}^{\ast }{(R^{\ast })}^{1/2}{\alpha }^{3/2}$$

(4)

$${\overrightarrow{F}}_{dni}=-2\sqrt{\frac{5}{6}}\beta \sqrt{S_n{m}^{\ast }}{v}_n^{rel}$$

(5)

$${\overrightarrow{F}}_{cti}=-S_t\delta$$

(6)

$${\overrightarrow{F}}_{dti}=-2\sqrt{\frac{5}{6}}\beta \sqrt{S_t{m}^{\ast }}{v}_t^{rel}$$

(7)

where ${\overrightarrow{F}}_{\mathit{cni}}$, E*, R*, and α represent the normal contact force between particles (N), the equivalent elastic modulus (Pa), the equivalent particle radius (m), and the amount of normal overlap, respectively. ${\overrightarrow{F}}_{\mathit{dni}}$, β, S_n, m*, and $v_n^{\mathit{rel}}$ represent the normal damping force between particles (N), a coefficient, the normal stiffness (N/m), the equivalent mass (kg), and the normal component of the relative velocity (m/s), respectively. ${\overrightarrow{F}}_{cti}$, S_t, and δ represent the tangential contact force between particles (N), the tangential stiffness (N/m), and the amount of tangential overlap, respectively. ${\overrightarrow{F}}_{\mathit{dti}}$ and $v_t^{\mathit{rel}}$ represent the tangential damping force between particles (N) and the tangential component of the relative velocity (m/s), respectively [29].

2.2.1. Establishment of Flow Channel Models and Mesh Division

Figure 6 illustrates the flow channel model constructed using Solidworks (Version 2016, Dassault Systems S.A., Waltham, MA, USA), which includes six air inlets, one outlet, a louver screen, and a vibrating plate, with the direction from the front to the rear of the vibrating screen defined as the positive direction of the X-axis, the direction from the right to the left side of the vibrating screen defined as the positive direction of the Z-axis, and the direction from the upper to the lower side of the vibrating screen defined as the positive direction of the Y-axis [30].

Utilizing the ICEM (Version 15.0, ANSYS Inc., Canonsburg, PA, USA) mesh division software, non-structured meshing was conducted on the flow channel models [30]. Local mesh refinement was applied to complex structures such as the louver screen and tail screen to enhance the quality of the mesh division. The resulting mesh count ranged from 3,259,753 to 3,411,259 elements, and the mesh files were saved as MSH format for subsequent parameter setting.

2.2.2. EDEM Particle Finite Element Settings

As the simulation in EDEM requires the modeling of the simulation objects, it is necessary to categorize the composition of the harvested materials and determine the proportion of each component. This study used the rice variety “Zhen Dao 10” as the experimental material, and the residues collected below the tangential–longitudinal flow threshing device during the experiment were manually sieved to identify the following five main components. Figure 7 presents the physical images of each component. The mass of each component was weighed, and the proportion of that component within the entire residue is depicted in Figure 8.

Particle Model Construction for the Five Identified Components. The established components require the overlapping and combining of multiple spherical particles to meet the requirements of their true shapes [31,32,33].

(1)

Establishment of Multi-solid Phase Models in the EDEM Environment

In this study, a particle replacement method is adopted for the granular components of larger sizes to achieve particle filling. This approach not only ensures that the models represent the actual components of the harvested materials within the cleaning shoe but also allows for a reduction in the mesh size of the cleaning shoe flow channel model, thereby enhancing mesh quality.

Figure 7 and Figure 8 reflect that plump grains account for 78% of the entire residue, and a traditional nine-sphere model is used for their establishment. If the particle filling method were adopted, it would result in a sharp increase in computational load, and the impact on the simulation results for plump grains would not be significant. Therefore, a method of stacking spherical particles is used for modeling plump grains. The traditionally used ellipsoidal model is shown in Figure 9 (1), with the major axis being 6.80 mm and the minor axis being 3.00 mm. Considering the special shape of shriveled grains, the latter are also modeled using the particle replacement method. Consequently, the entire composition of the residues, long-stem stalks, short-stem stalks, light impurities, and shriveled grains, is modeled using the particle replacement method. The dimensional parameters of each component of the residues are presented in

Table 3. Structure size of the threshed material.

Threshed Material Component	Parameter	Value/mm	Filler Particle Diameter/mm
Shrunken grains	Width	5.96	0.25
	Thickness	3.42
	Inner diameter	1.03
Long stalks	Inner diameter	4.69	0.50
	Outer diameter	3.96
	Length	50.00
Short stalks	Inner diameter	4.69	0.50
	Outer diameter	3.96
	Length	30.00
Light impurities	Diameter	0.20	0.30
	Length	<20

.

The established models of the five types of harvested residue components are shown in Figure 9.

In the EDEM environment, the mechanical properties of the material particles and their contact coefficients with other objects are inputted. Based on relevant references [7,30,31,34,35], the material mechanics and contact coefficients are summarized in

Table 4. Mechanics parameters of materials.

Parameter	Poisson’s Ratio	Elastic Modulus/MPa	Density/kg/m3
Plump grains	0.3	8.24	1190
Shrunken grains	0.35	1.35	778
Long stalks	0.4	0.23	623
Short stalks	0.4	0.23	628
Light impurities	0.3	0.1	623
Cleaning screen	0.3	7000	7800

and

Table 5. Coefficient of interactions.

No.	Parameter	Recovery Coefficient	Static Friction Coefficient	Rolling Friction Coefficient
1	Plump grains—Plump grains	0.46	0.61	0.02
2	Plump grains—Shrunken grains	0.35	0.63	0.02
3	Plump grains—Short stalks	0.37	0.35	0.02
4	Plump grains—Cleaning screen	0.47	0.34	0.01
5	Shrunken grains—Shrunken grains	0.38	0.66	0.02
6	Shrunken grains—Short stalks	0.32	0.46	0.02
7	Shrunken grains—Cleaning screen	0.36	0.37	0.01
8	Short stalks—Short stalks	0.33	0.34	0.02
9	Short stalks—Cleaning screen	0.36	0.31	0.01
10	Shrunken grains—Long stalks	0.37	0.35	0.02
11	Long stalks—Long stalks	0.32	0.46	0.02
12	Long stalks—Cleaning screen	0.33	0.34	0.02
13	Light impurities—Long stalks	0.36	0.31	0.01
14	Light impurities—Cleaning screen	0.32	0.30	0.01
15	Light impurities—Light impurities	0.31	0.32	0.02
16	Light impurities—Long stalks	0.35	0.37	0.02
17	Light impurities—Short stalks	0.35	0.37	0.02
18	Light impurities—Shrunken grains	0.32	0.42	0.02

, respectively.

(2)

Particle Factory Settings

The distribution of the particle factory in the EDEM environment is consistent with the trend of the distribution of residues below the tangential–longitudinal flow. The cumulative distribution of materials in the horizontal direction of the cleaning shoe, as shown in Figure 2, is adopted. A particle factory, which is a polygonal virtual area in the EDEM software used for generating particles and is as wide as the cleaning screen, is established 20 mm above the vibrating plate and 100 mm away from the left wall of the cleaning shoe [30,36].

Through experimental testing, the ratio of the feed rate of the combine harvester to the residues in the cleaning shoe is 9:4. Combining the proportion of residue components shown in Figure 8, as well as the density and moisture content of each component, the number of particles that need to be generated in the particle factory is calculated. The feed rate of the combine harvester is set at 7 kg/s, and the feed rate of residues in the cleaning shoe is established. In EDEM, seven particle generation areas with an area of 150 × 280 mm² are set, with numbers corresponding to those in Figure 2. These seven areas represent the cumulative sum of the residues in the longitudinal direction of the cleaning screen in Figure 2, thus forming a distribution trend of “more on both sides and less in the middle” in the horizontal direction of the cleaning shoe. The number of particles of each component generated in a single area per unit time (1 s) is shown in

Table 6. The number of particles produced in each particle factory in the cleaning shoe at a feed rate of 7 kg/s.

Particle Factory No.	Plump Grains (Grains/s)	Shrunken Grains (Grains/s)	Long Stalks (Stalks/s)	Short Stalks (Stalks/s)	Light Impurities (Items/s)
1	14,213	729	108	617	11,684
2	12,110	621	92	526	9955
3	11,335	581	86	492	9318
4	10,220	524	78	444	8401
5	9164	470	70	398	7533
6	10,135	520	77	440	8331
7	13,179	676	100	572	10,833

.

2.2.3. Coupled Simulation Settings

The MSH file is imported into the Fluent software for the numerical simulation parameter settings of the gas phase, using the standard κ-ε turbulence model with the solution method set to Pressure Based and Transient. The working pressure is set at 1 atmosphere, and the acceleration due to gravity is directed negatively along the Y-axis with a magnitude of 9.81 m/s² [7,30]. The MSH file is then imported into the EDEM software for the numerical simulation parameter settings of the solid phase, with the same gravity settings [7,30]. The inlet boundary condition is set as a velocity inlet. After setting the rotational speed for each fan, CFD simulations are conducted to obtain the velocity distribution at the outlets of each fan [27]. The average outlet velocity of each fan is then used as the inlet velocity for this study. The inlet velocities for the outlets are set according to the speeds listed in

Table 7. Air outlet velocity setting parameters.

	Traditional Fan Air Velocity (m3/s)	Optimized Fan Air Velocity (m3/s)
		Outlet I	Outlet II	Outlet III
Upper outlet	22	23	21	23
Lower outlet	16	21	18	21

. The inlet numbers that enter the cleaning shoe correspond to those marked in Figure 2. A traditional fan is used as a control fan, and the outlet boundary condition of the model is set as a pressure outlet with a relative pressure of 0 Pa. The louver screen opening is set at 55°, the vibrating screen displacement in the X direction is 12 mm, in the Y direction is 10 mm, and the vibration frequency is set at 6 Hz for the working parameter combination.

After establishing a coupling relationship between the Fluent and EDEM software using a UDF (User Defined Function) program, the Eulerian–Eulerian model is employed for the gas–solid two-phase flow numerical simulation. Finally, the coupled gas–solid two-phase flow time steps are matched: the Fluent computation time step is set at 4 × 10⁻⁴ s, and the EDEM computation time step is set at 4 × 10⁻⁶ s, with the total numerical simulation time being 1 s [30]. The Fluent computation time is 50 times that of the EDEM computation time, and the Rayleigh time is 50% of the FLUENT computation time.

2.3. Experiment of Multi-Wing Curve Combined Multi-Duct High-Efficiency Cleaning Device

The designed multi-wing curve combined centrifugal fan was tested for the airflow within the cleaning shoe to determine if the wind speed near the sieve surface meets the cleaning requirements. On this basis, the cleaning fan was integrated into the combine harvester and field tests were conducted. The actual harvesting requirements were verified by detecting and analyzing the rice harvesting cleaning loss rate and kernel impurity rate.

2.3.1. The Air Velocity Test of Multi-Wing Curve Combined Centrifugal Fan

The developed multi-aerodynamic curve combination centrifugal cleaning fan (optimized fan) was integrated into the combine harvester, with the cleaning shoe measuring 1200 mm in length and 1100 mm in width, and the cleaning screen surface positioned 200 mm below the concave surface of the threshing drum. The test measurement points were primarily distributed at three locations, before, in the middle, and after the screen, using a handheld hot-wire anemometer to manually measure the air velocity at the points [24], as shown in the on-site test diagram in Figure 10. For comparison, a conventional straight-blade fan was used as a control fan, and the same measurement method was applied.

To facilitate the comparison of the air velocity distribution trends within the cleaning shoe between the two types of fans, a coordinate system was established within the cleaning shoe, with the midpoint of the front end of the cleaning screen, 100 mm above the screen surface, set as the coordinate origin. The horizontal direction parallel to the front end of the screen was designated as the Y-axis, the longitudinal direction as the X-axis, and the upward direction perpendicular to the screen as the Z-axis [37].

Nine horizontal measurement points were evenly set along the X-axis, with coordinates of 0, 150, 300, 450, 600, 750, 900, 1050, 1200 mm. Seven horizontal measurement points were evenly set along the X-axis, with coordinates of −450, −300, −150, 0, 150, 300, and 450 mm. A single-plane measurement point was set at a height of 100mm in the Z-axis, with the measurement point layout shown in Figure 11.

2.3.2. High-Efficiency Cleaning Device Cleaning Performance Test

The cleaning loss performance detection test of the multi-aerodynamic curve combination centrifugal fan was conducted in the experimental field of Jiangsu Agricultural Expo Park in Jurong City, Zhenjiang, Jiangsu Province. A flat field was selected, and the crop variety was Zhen Dao 10, with an average plant height of 96 cm, average panicle length of 16.3 cm, thousand-grain weight of 36 g, yield of 10,755 kg/hm², straw-to-grain ratio of 1.98, straw moisture content of 57%, and grain moisture content of 26%. The forward speed was chosen as the variable to reflect different levels of harvest feed rate. Tests were conducted with low, medium, and high forward speeds, controlled approximately at 0.5 m, 1.0 m/s, and 1.3 m/s, respectively, with a combine harvester cutting width of 2.2 m, corresponding to feed rates of 3.52 kg/s, 7.05 kg/s, and 9.16 kg/s.

During the test, the harvest trial integrated with the multi-aerodynamic curve combination centrifugal fan was first conducted. A net bag with a width equal to that of the sub-fan was arranged behind the cleaning shoe to catch the cleaning ejecta. The grains screened out from the net bag were considered the cleaning loss at that location corresponding to the sub-fan. The cleaning loss test area in the experiment is shown in Figure 12. Since the grain impurity content could not be separately distinguished, the overall grain impurity content was used as the grain impurity level for this test.

3. Results and Discussion

3.1. CFD-DEM Coupled Simulation Results

3.1.1. Comparison of Tramp Material Motion Trends and Cleaning Performance Analysis

A particle count statistical area was set up in the cleaning shoe, as shown in Figure 13. The first statistical area is located at the grain feeding auger, counting the grains that pass through the sieve, as well as the long-stem stalks, short-stem stalks, and light impurities that pass through the sieve with the grains. The ratio of the sum of the masses of long-stem stalks, short-stem stalks, and light impurities to the mass of grains in this area is the impurity rate; a second area was designed at the outlet to count the number of grains expelled outside the cleaning shoe [7,30,34]. Therefore, this area is not considered when calculating the cleaning loss rate and grain impurity rate.

After counting and calculation, the cleaning loss rate of the multi-aerodynamic curve combination centrifugal fan (optimized fan) was 0.86%, and the grain impurity rate was 1.41%. In contrast, the traditional straight-blade centrifugal fan (traditional fan) had a cleaning loss rate of 1.13% and a grain impurity rate of 2.07%. Compared to the traditional fan, the optimized fan’s cleaning loss rate decreased by 23.73%, and the grain impurity rate decreased by 31.68%. The above data indicate that the optimized fan has improved the cleaning performance.

To more clearly analyze the motion process of tramp materials in the cleaning shoe, six moments of the tramp material distribution in the cleaning shoe were selected, at 0.02, 0.2, 0.4, 0.6, 0.8, and 1.0 s, as shown in Figure 14. In the figure, yellow particles represent grains, brown particles represent shriveled grains, dark blue particles represent light impurities, blue particles represent short-stem stalks, and green particles represent long-stem stalks.

From Figure 14, the following conclusions can be drawn:

(1)

During the process where tramp materials fall from the particle factory onto the fish scale screen (0–0.2 s), in both types of fans, the particles of each component are affected by the airflow from the upper channel and fall in a diagonal waterfall pattern. There is a clear stratification and diffusion phenomenon among the five types of particles, with grain particles having the least backward inclination degree and being distributed at the bottom layer, while light impurities have the greatest backward inclination degree and are already floating above the vibrating screen [30].

(2)

Starting from 0.4 s, grains in both types of fans begin to pass through the sieve, and impurities start to move towards the outside of the cleaning shoe driven by the airflow. Between 0.4 and 0.6 s, grains further stratify and pass through the sieve to the grain feeding auger and the secondary impurity auger. Both types of fans have impurities accompanying the grains through the sieve, including long-stem stalks, short-stem stalks, and light impurities. However, there are some noticeable differences; the optimized fan shows a trend where the tramp materials on both sides move further away, while those in the middle move closer, especially for the light impurities; the traditional fan shows a consistent movement distance for the tramp materials, which is mainly related to the distribution trend of higher wind speeds on both sides and lower in the middle of the optimized fan.

(3)

During the time t = 0.8–1.0 s, impurities above the fish scale screen move like flowing water towards the outside of the cleaning shoe, being expelled by the airflow. However, the trend of tramp materials moving further on both sides and closer in the middle of the optimized fan gradually decreases, and the distribution trends on the sieve of both types of fans become more consistent, which is related to the continuous fall of tramp materials from the particle factory; grains show a continuous trend of passing through the sieve, with impurities still accompanying the grains through the sieve; the tramp materials show a continuous cleaning trend.

Randomly selecting two moments (t = 0.6 s, 1.0 s) for the top view of particle motion, i.e., looking down from above the cleaning screen, it is clear to see the distribution trend of the tramp materials in the cleaning shoe of both types of fans on the screen, as shown in Figure 15.

Consistent with the analysis of tramp material motion trends, at 0.6 s, the top view shows that the light impurities on both sides of the optimized fan screen move much further than those in the middle area, while the traditional fan shows the entire group of tramp material particles moving in a straight line; as time progresses to t = 1.0 s, the difference in particle movement distance on the optimized fan screen decreases over time, which is related to the continuous feed of particles, but compared to the traditional fan, there is still a distribution trend where both sides move further than the middle distance. Combined with the analysis results in Section 2.1.1, this distribution trend of the optimized fan is consistent with the distribution trend of tramp materials below the axial flow, thus the motion trend of tramp materials in the cleaning shoe under the action of the optimized fan is beneficial for the cleaning of non-uniform distribution of tramp materials below the axial flow expulsion device.

3.1.2. Analysis of the Mass Distribution Pattern and Cleaning Performance Comparison of Residual Particles

In this study, to provide a visual comparison of the grain cleaning capabilities between traditional and optimized fans, the mass distribution pattern of residual particles was utilized to assess the separation efficiency. Four time instances, specifically 0.4 s, 0.6 s, 0.8 s, and 1.0 s, were selected to statistically analyze the mass distribution of short and long stems, as well as light impurities, at each moment for both traditional and optimized fans. These data were used to represent the mass distribution of residual particles, as depicted in Figure 16.

From Figure 16, the following conclusions can be drawn:

(1)

The mass of residual particles at various locations of the traditional fan gradually increases over time, with the distribution tending to form a “higher on both sides, lower in the middle” pattern near Grid 4. At 0.4 s, the total mass of residual particles is relatively small, with the main components accumulating in Grids 0–6, where the mass along the horizontal sides is slightly higher than that in the central region. By 0.6 s, the mass of residual particles begins to increase, primarily accumulating in the horizontal sides of Grid 4, with the central region of Grid 6 starting to accumulate residual mass, forming a horizontal protrusion on the mass distribution surface. There is almost no accumulation of residual mass in the rear longitudinal (Grids 8–11) region. At 0.8 s, the protrusion on the mass distribution surface at the horizontal sides of Grid 4 becomes more pronounced, with the main distribution trend remaining largely unchanged from 0.6 s. At 1.0 s, the mass in the horizontal sides of Grid 4 reaches its peak, with a horizontal protrusion appearing near Grid 2 corresponding to Grid 4; the mass protrusion in the central region of Grid 6 almost disappears, and a small amount of residual particles appears in the region corresponding to Grids 8–11. Overall, residual particles move towards the sides under the centrifugal effect of the threshing drum, and their distribution trend matches the analysis of the separated material motion trend in Section 2.1.1. The rear longitudinal section has a smaller distribution of residual mass, and a protrusion appears in the central horizontal region at both 0.6 s and 0.8 s.

(2)

For the optimized fan, the mass of residual particles at various locations also increases over time, with the main components accumulating near Grid 4. At 0.4 s, the total mass of residual particles is relatively small, with the main components accumulating in Grids 0–6, and the mass of each part is relatively even. At 0.6 s, the mass of residual particles begins to increase, primarily accumulating in the central region of Grid 4, with a more uniform horizontal mass distribution in the area behind Grid 4 and a small amount of residual particles appearing in the horizontal sides of the rear longitudinal (Grids 8–11) region. At 0.8 s, the distribution of residual particles becomes more pronounced in the transverse central region near the longitudinal rear (Grids 8–11), with the primary distribution trend showing little difference compared to that at 0.6 s. At 1.0 s, the mass in the central region of Grid 4 reaches its peak, and a relatively larger amount of residual particles appears in the horizontal sides corresponding to Grids 8–11. Overall, the mass distribution surface of the optimized fan is more even, with no significant abrupt changes except for the mass protrusion in the central region of Grid 4.

(3)

By comparing the mass distribution of residual particles between the traditional and optimized fans, it is observed that the traditional fan exhibits a saddle-like distribution trend in areas where residual mass is concentrated, with a protrusion in the central horizontal region of Grid 6. In contrast, the optimized fan shows a smaller difference in mass between the concentrated area and the sides and a more uniform mass distribution in other areas. This indicates that the optimized fan has better lateral mass distribution capability, which indirectly suggests that it mitigates the problem of particle lateral screening difficulty. The traditional fan has almost no accumulation of residual particles in the rear longitudinal section before 0.8 s, while the optimized fan shows some accumulation at 0.6 s and a relatively larger mass of residual particles at 1.0 s in this area. This suggests that the optimized fan has a generally larger mass of residual particles in the rear longitudinal section, indicating that the cleaning performance of the optimized fan is superior to that of the traditional fan.

3.1.3. Analysis of the Dispersion of Tramp Material Particle Groups

In this study, the movement speed of the centroid of the particle groups within the cleaning shoe is used to measure the cleaning efficiency. The centroid movement speed of the particle group is the sum of the instantaneous velocity vectors of all particles of that type within the cleaning shoe [30]. The sum of the instantaneous movement speed vectors of each component of the tramp materials is calculated, which represents the centroid movement speed of the particle group for each component. The centroids of plump grains, shriveled grains, short-stem stalks, and light impurities from the optimized fan and the traditional fan were statistically compared. Since the particle groups exhibit a small range of movement speed variation in the horizontal direction of the cleaning screen, only the centroid movement patterns in the longitudinal direction of the cleaning screen and along the height of the cleaning shoe are analyzed, as shown in Figure 17. Additionally, due to the low number of long-stem stalks and their dispersed movement, a continuous centroid movement pattern is not formed, so the analysis of the centroid movement of long-stem stalks is not conducted here.

The following conclusions can be drawn from Figure 17:

(1)

As shown in Figure 17a,b, the grains exhibit a decreasing trend along the X direction, meaning the movement speed of grains along the longitudinal direction of the cleaning screen (opposite to the forward speed) gradually decreases. The grain particle groups show a trend of increasing first and then decreasing in speed along the Y direction (the direction of falling from the drum). The maximum speed occurs at 0.52 s with an absolute value of 2.46 m/s in the X direction and at 0.44 s with an absolute value of 1.47 m/s in the Y direction.

(2)

Comparing the speeds of the grain particle groups between the optimized fan and the traditional fan, it is found that the absolute values of the centroid speeds of grains in both X/Y directions in the optimized fan are greater than those in the traditional fan. The absolute speed deviation of grains in the X direction range from 0.05 m/s to 0.28 m/s, with significant deviations occurring during 0.40–0.54 s and 0.60–0.94 s. The maximum absolute velocity of grains of the optimized fan is 1.06% higher than that of the traditional fan. Similarly, the absolute speed deviation of grains in the Y direction range from 0.02 m/s to 0.25 m/s, with noticeable deviations during 0.40–0.58 s, 0.70–0.84 s, and 0.86–1.0 s. The maximum absolute velocity of grains in the Y direction of the optimized fan is 3.52% higher than that of the traditional fan. The maximum absolute velocity in the Y direction of the optimized fan is greater than in the X direction, and the total duration of significant deviations is longer in the Y direction than in the X direction. This indicates that the improvement of the airflow field in the optimized fan has a greater impact on the Y direction than the X direction.

(3)

Analyzing the movement patterns of shriveled grains along with impurities, it can be seen from Figure 17c,d that the impurity particle groups exhibit a decreasing trend along the X direction, meaning the movement speed of impurities along the longitudinal direction of the cleaning screen (opposite to the forward speed) first increases, then decreases, and finally tends to be stable. Within the range of 0.40–0.54 s, the speed of the impurity particle groups gradually increases due to the simultaneous action of the upper and lower air outlets, causing impurities to move quickly towards the back of the cleaning screen. At the 0.60 s position, the speed tends to be stable, indicating that after 0.60 s, the airspeed from the upper air outlet gradually decreases, and the impurities tend to stabilize in speed under the airflow from the lower air outlet. In the Y direction, the movement speed of short-stem stalks and light impurities is in a stable state; due to the small volume of shriveled grains and low floating coefficient, the absolute value of their movement speed is higher than that of light impurities and short-stem stalks.

(4)

Comparing the speeds of the impurity particle groups between the optimized fan and the traditional fan, it is found that the absolute values of the centroid speeds of shriveled grains, short-stem stalks, and light impurities in both X/Y directions in the optimized fan are greater than those in the traditional fan. The absolute speed deviations of shriveled grains, short-stem stalks, and light impurities in the X direction range from 0.15 to 1.61 m/s, 0.03 to 1.70 m/s, and 0.49 to 1.54 m/s, respectively, with the optimized fan’s maximum speed being 16.71%, 3.48%, and 4.92% higher than the traditional fan’s absolute values; similarly, the corresponding deviations in the Y direction range from 0.02 to 0.32 m/s, 0.04 to 0.73 m/s, and 0 to 0.49 m/s, respectively, with the optimized fan’s maximum speed being 12.12%, 7.83%, and 21.14% higher than the traditional fan’s absolute values. The velocity of short stems shows the most significant deviations during the periods of 0.6–0.74 s and 0.76–0.88 s. This indicates that the improvement of the airflow field in the optimized fan has a greater impact on the X direction for shriveled grains, but for short-stem stalks and light impurities, the impact is greater on the Y direction than the X direction.

3.2. Test Results of the Multi-Aerodynamic Curve Combination Centrifugal Fan

3.2.1. Results of the Air Velocity Test for the Multi-Wing Curve Combination Centrifugal Fan

The centrifugal fan speed was set at 1300 r/min, and the fish scale screen opening was set at 30°. Digital anemometers were used to measure the wind speed at different spatial positions [37,38], and the resulting velocity distribution is shown in Figure 18.

From Figure 18, it can be observed that along the longitudinal direction of the entire cleaning shoe, the wind speed of both types of fans gradually decreases with increasing distance from the outlet. In the front section of the cleaning shoe (0–450 mm), the wind speed range for both fans is 8–14 m/s, which is the concentrated falling position of the tramp materials [39]. The wind speed of both fans can meet the requirements for stratification and dispersion of the tramp materials. In the middle section (450–900 mm), the wind speed gradually decreases, generally distributed between 8 and 10 m/s, which can keep the tramp materials in a fluidized state, meeting the requirements for gradual grain sieving and transportation of impurities to the end of the screen. In the tail section (900–1200 mm), the wind speed gradually decays to 6–7 m/s, at which point, all grains have completed sieving, and the impurities are thrown out of the cleaning shoe, completing the cleaning process. From the above analysis, it can be concluded that the wind speed decay patterns of both fans in the cleaning shoe match the screening process of tramp materials and can meet the requirements for wind speed distribution in the longitudinal direction of the cleaning shoe.

The wind speed distribution of the two fans in the transverse direction of the cleaning shoe shows an opposite trend; the optimized fan has high wind speed on both sides and low wind speed in the middle, while the traditional fan has high wind speed in the middle and low wind speed on both sides. Compared with the design requirements of the fans in this study, the wind speed distribution of the optimized fan in the transverse direction of the cleaning shoe is the same as the distribution trend of tramp materials below the longitudinal axis threshing device, meeting the initial purpose of the fan design.

3.2.2. Test Results of the High-Efficiency Cleaning Device Performance

After the test of the multi-wing curve combination centrifugal fan was completed, the traditional straight-blade centrifugal fan was replaced, and the same test method was used to compare the cleaning performance of the two types of cleaning fans. The test results are shown in Figure 19.

From Figure 19, it can be observed that with the increase of forward speed, the cleaning loss gradually increases. However, under each working condition, the combine harvester integrated with the optimized fan has a lower overall cleaning loss than that with the traditional fan. At the same forward speed, the cleaning loss under the optimized fan fluctuates less in the transverse direction of the cleaning shoe, while the cleaning loss under the traditional fan shows a trend of low loss on both sides and high loss in the middle. This distribution of cleaning loss is related to the fan’s wind speed distribution. The optimized fan has higher wind speeds on both sides (Fan I, Fan III), which can more fully blow the tramp materials on both sides, increasing the probability of grain sieving and blowing the impurities out of the cleaning shoe. The wind speed in the middle area is lower (Fan II), which avoids the excessive wind volume blowing grains out of the cleaning shoe, reducing the cleaning loss. In contrast, the traditional fan has lower wind speeds on both sides, causing grains to be carried out of the cleaning shoe with the impurities, and due to excessive wind volume in the middle, grains are blown out of the cleaning shoe, causing a higher cleaning loss.

Comparing the grain impurity rate and cleaning loss rate at forward speeds of 0.5 m/s, 1.0 m/s, and 1.3 m/s, the results are shown in

Table 8. Comparison of cleaning performance between optimized fan and traditional fan.

Field Test Results of the Cleaning Device					Coupled Simulation Performance Results
Forward Speed (m/s)	Traditional Fan Total Cleaning Loss Rate (%)	Optimized Fan Total Cleaning Loss Rate (%)	Traditional Fan Grain Impurity Rate (%)	Optimized Fan Grain Impurity Rate (%)	Forward Speed (m/s)	Traditional Fan Total Cleaning Loss Rate (%)	Optimized Fan Total Cleaning Loss Rate (%)	Traditional Fan Grain Impurity Rate (%)
0.5	0.80	0.60	2.67	1.81	/	/	/	/
1.0	1.2	0.98	2.05	1.47	1.13	0.86	2.07	1.41
1.3	1.5	1.34	1.83	1.42	/	/	/	/

. The table compares the coupled simulation results with the experimental results to verify the accuracy of the coupling.

From Table 8 of the field test, it was found that the grain impurity rate of the combine harvester integrated with the optimized fan was 32.20%, 28.29%, and 22.40% lower than that of the traditional fan. This indicates that as the forward speed increases, the reduction range of the optimized fan on the grain impurity rate gradually decreases. Comparing the cleaning loss rates under the two fans, at forward speeds of 0.5 m/s, 1.0 m/s, and 1.3 m/s, the cleaning loss rate under the optimized fan decreased by 25.00%, 18.33%, and 10.67%, respectively, compared to the traditional fan. This downward trend is the same as the trend of grain impurity reduction, showing a trend of reduced cleaning performance as forward speed increases. This indicates that the optimized fan can reduce cleaning performance loss, but the trend is related to the feed rate of the combine harvester.

Comparing the experimental and coupled simulation results in Table 8, the error range is 1–12%. The main reasons for the error are the fluctuation of feed rate within a certain range caused by field crop properties and harvesting environment, while the coupling is based on ideal tramp material feed; however, within this error range, coupled simulation can provide theoretical analysis for the cleaning process.

4. Conclusions

(1)

This study designs a multi-aerodynamic curve combination centrifugal fan based on the distribution pattern of rice tramp materials below the longitudinal axial flow separation device. The fan is composed of three sub-fans with different structures. The width of the fan volute corresponds to the distribution area of the tramp materials, with larger volute diameters corresponding to areas of greater mass; the impeller diameter and width vary with the volute structure size. Through airflow field simulation, it is determined that the airflow distribution of the multi-aerodynamic curve combination centrifugal fan meets the uneven distribution trend of “more on both sides, less in the middle” below the longitudinal axial flow separation device.

(2)

Based on a feed rate of 7 kg/s, a gas–solid two-phase flow multi-solid phase rice tramp material coupling simulation model is established. The motion patterns of tramp materials under the action of traditional straight-blade centrifugal fans and multi-aerodynamic curve combination centrifugal fans with different airflow distribution trends are analyzed. The cleaning loss and grain impurity content under the action of these two types of fans are statistically compared. It is found that under the uniform airflow of the traditional fan, the cleaning loss rate and grain impurity rate of the optimized fan are reduced by 39.73% and 44.68%, respectively, compared to the traditional fan over the same operating period, indicating that the performance of the multi-aerodynamic curve combination centrifugal fan is superior to that of the traditional fan.

(3)

By comparing the mass distribution of residual particles between the traditional fan and the optimized fan, it is observed that the optimized fan exhibits smaller differences in the mass concentration between the peak points and the sides in the concentrated mass areas. Additionally, the mass distribution in other areas is more uniform, and there is greater accumulation of residual mass in the rear regions. This indicates that the optimized fan outperforms the traditional fan in both lateral and longitudinal cleaning performance.

(4)

This study uses the centroid movement velocity of particle groups in the cleaning chamber to measure cleaning efficiency. In the X direction, the maximum absolute velocity of grains in the optimized fan is 1.06% higher than that in the traditional fan; in the Y direction, it is 3.52% higher. For shriveled grains, short stems, and light impurities in the X direction, the maximum absolute velocities in the cleaning chamber of the optimized fan are 16.71%, 3.48%, and 4.92% higher, respectively, than those in the traditional fan. In the Y direction, the maximum absolute velocities of shriveled grains, short stems, and light impurities are 12.12%, 7.83%, and 21.14% higher, respectively, than those in the traditional fan. Overall, the absolute centroid velocities of grains and impurities in both the X and Y directions are greater in the optimized fan than in the traditional fan. This indicates that the particle group movement speed is higher in the optimized fan, thus effectively accelerating the movement of threshed material through more efficient airflow distribution. Consequently, the optimized fan increases the amount of threshed material cleaned per unit time, thereby improving the cleaning efficiency.

(5)

The cleaning fans studied are integrated into combine harvesters, and field tests showed that the cleaning loss rate and grain impurity rate under the action of the optimized fan decreased by up to 25.00% and 32.18% compared to those under the action of the traditional fan. Due to fluctuations in feed rate during actual harvesting, the error range compared to the coupled simulation results is 1–12%. Within this error range, coupled simulation can provide theoretical analysis support for the cleaning process.

This study is compared with other research works in this field, as shown in

Table 9. Comparison table of research works.

Reference	Main Work	Cleaning Method	Particle Simulation Generation Method	Experimental Method
This Study	Designed a multi-wing curved fan based on the characteristics of threshed material distribution and compared the movement characteristics of threshed material in the cleaning chamber with traditional fans.	Multi-wing curved fan screen	Non-uniform distribution	Field test
Numerical simulation of gas solid two-phase flow to predict the cleaning performance of rice combine harvesters [19]	Compared the movement characteristics of threshed material under different conditions through orthogonal experiments and obtained the optimal parameter combination.	Traditional fan screen cleaning	Uniform distribution	Simulated numerical analysis
BP neural network model for material distribution prediction based on variable amplitude anti-blocking screening DEM simulations [21]	Used BP neural network to predict material distribution, selected the deflector angle as the target variable for simulation, and explored the optimal working parameters.	Variable amplitude anti-blocking screening	Uniform distribution	Simulated numerical analysis
Design and Experiments of Material Uniform Dispersion and Diversion Device on Cleaning Screen Surface for Oilseed Harvesting [9]	Added a diversion device to evenly disperse and guide material on the screen surface. Analyzed the cleaning process to determine key structures and operating parameters.	Material uniform dispersion and diversion device on screen surface	Uniform distribution	Bench test

.

The commonalities among the different studies presented in the table are twofold: firstly, all studies focus on longitudinal axial-flow threshing cylinders; secondly, all employ CFD-DEM simulation methods. These studies have adopted various approaches to address the difficulty of material passing through the screen, but they have not resolved the widespread issue of the uneven distribution of threshed material in mainstream longitudinal axial-flow models. This study addresses the common issue of “more on the sides, less in the middle” distribution of threshed material in mainstream longitudinal axial-flow models by employing a multi-wing curved fan screen structure, thereby reducing the complexity of system control. Additionally, this study enhances the credibility of the results by conducting differentiated particle factory setups for numerical simulation analysis and comparative field tests.

This study demonstrates that the multi-wing curved fan screen structure significantly improves the cleaning efficiency of rice in combine harvesters at a feed rate of 7.0 kg/s. However, there are many aspects that warrant further exploration. Future research could consider optimizing the fan performance under increased feed rates, as higher feed rates may result in significant changes in material flow and distribution. Detailed analysis through CFD-DEM simulations could explore the structural parameters needed to maintain high cleaning performance under various operating conditions. Additionally, the study could investigate the different physical properties of various crops and the distribution characteristics of threshed material, testing the performance of the combined fan screen under conditions of various crops such as wheat, rapeseed, etc. The generality and adaptability of the combined fan screen could be validated through CFD-DEM simulation and field tests. Furthermore, different cleaning chamber structures could be designed for different fans to maximize their performance. Researchers could explore adjustments to the geometric shape, airflow channels, and screen layout of the cleaning chamber to further improve cleaning efficiency. By expanding these research directions, future studies will be able to more comprehensively validate the application potential of the multi-wing curved centrifugal fan and provide stronger theoretical and practical support for the design of modern agricultural machinery.