Simulation Analysis and Research on the Separation and Screening of Adherent Foreign Substances in Raisins Based on Discrete Elements

Abstract

To address the issue that existing raisin foreign object removal equipment cannot eliminate surface contaminants adhered to raisins through non-washing methods, this paper proposes an adhesive foreign object removal method based on “rapid freezing–rolling extrusion separation-airflow screening”. A raisin adhesive foreign object removal device was designed based on this method. The separation and removal processes of adhesive foreign objects were analyzed and optimized through simulation, followed by device fabrication and performance testing. Starting from the separation process of raisins and adhesive foreign objects, we conducted experimental studies on quick-freezing separation, determined the most suitable separation method based on experimental results, and performed structural design of the equipment accordingly. To conduct simulation analysis and optimization, material parameters were calibrated. The working process of foreign object separation was simulated and optimized using discrete element method (DEM) simulation, verifying the equipment’s separation capability for different adhesive foreign objects while determining the optimal rotational speed of 600 r/min. Through EDEM-Fluent coupled simulation, the working process of foreign object removal was analyzed and optimized, validating the influence of flow field on foreign object removal and determining the optimal air velocity of 11 m/s. The equipment was ultimately fabricated, with further parameter optimization and comprehensive performance testing conducted. The final optimal rotational speed and air velocity were determined as 650 r/min and 11 m/s, respectively. In terms of comprehensive performance, the equipment achieved a separation rate of 93.76%, damage rate of 3.05%, residue rate of 4.28%, removal rate of 94.52%, carry-over ratio of 71:1, and processing capacity of 120 kg/h.

1. Introduction

Raisins are formed by dehydrating grape fruits through methods such as sun-drying, air-drying in a drying room, or artificial heating. Due to their unique sweet and sour taste, rich nutritional content, significant antioxidant activity, and potential efficacy in reducing the risk of cardiovascular and cerebrovascular diseases, they are highly favored by consumers worldwide [1]. According to the data released by the International Nut and Dried Fruit Council, the main producers of raisins globally in 2024 are Turkey, China, the United States, India, Iran, Uzbekistan, Chile, South Africa, and Argentina, with a total output of 1.4 million tons. China’s raisin export volume has reached a new high of 68,500 tons. The majority of China’s raisins are produced in Turpan, Xinjiang, where the output accounts for over 90% of the national total. Among them, the green raisin “Seedless White” makes up about 90% [2]. In 2024, nearly 70% of the fresh grapes in Turpan Prefecture were processed into raisins.

The current processing methods for removing foreign objects from raisins are mainly based on manual picking of the objects. Some adopt mechanized processing methods. However, most raisin processing factories perform preliminary processing to remove some foreign objects and substandard raisins, and then rely on manual sorting to remove the impurities that the machines fail to eliminate before putting them on the market for sale. Only some dark-colored raisins undergo cleaning and drying treatment during the processing [3]. Dark raisins have a distinct color characteristic, and their color changes are not significant after cleaning. Therefore, in the processing of dark raisins, the cleaning and drying procedures are commonly used. However, after green raisins are cleaned, the residual moisture on the surface is prone to penetrate into the fruit flesh, causing the moisture content of the raisins to increase. After drying, their texture becomes softer and the taste deteriorates. Moreover, during storage, the residual moisture will significantly accelerate the browning process of green raisins and cause severe clumping [4].

At present, discrete element simulation has been widely applied in the agricultural field. Researchers employ the discrete element method, by establishing contact models and motion equations among particles, to predict and characterize the macroscopic mechanical behavior and microscopic movement mechanism of particles. Xu Y et al. [5] proposed using the discrete element method to simulate the straw grinding process. Through single-factor simulation experiments, they obtained the effects of the number of hammers, the thickness of the hammer heads, and the gap between the hammer and the screen on the amount of particle grinding and power consumption. Yuan H et al. [6] developed an automatic rice filling device for lotus root and glutinous rice. They conducted a simulation of the filling process using the discrete element method and optimized the parameters of the device, including the feeding speed, filling height, funnel diameter, amplitude, and frequency. Wang L et al. [7] used the discrete element method to study the relationship between the advancing speed of the plowshare furrow opener and the opening angle of the blades, and determined the optimal structure to achieve the minimum furrowing resistance. Zhang P et al. [8] took into account the high excavation resistance of ginger blocks and designed a dedicated ginger block excavation device. They also analyzed the mechanical characteristics of the excavation device and the soil fragmentation mechanism, and determined the key parameters that affect the excavation resistance and soil fragmentation. The key parameters were optimized through discrete element simulation. Huang S et al. [9] conducted a simulation of the wear degree of the fluid on the pump flow area in the centrifugal pump using the EDEM-Fluent coupling method. Wei Z et al. [10] aimed to reduce the high damage rate and bruise rate of potatoes during the mechanized harvesting process of potatoes. They proposed the wave-shaped separation screen for separation and, based on the discrete element method, clarified the separation mechanism and mechanical properties of potatoes being crushed by soil blocks on the wave-shaped separation screen. Qing Y et al. [11] designed a self-cleaning device for the cutter deck of a rice seed harvester, and constructed a simulation model for the cleaning airflow of the collecting pipe based on the coupling of Fluent and EDEM. They studied the effects of the inlet pressure of the nozzle, the angle of the gas inflow, and the height of the nozzle outlet on the self-cleaning rate. They determined the optimal cleaning parameters to maximize the self-cleaning rate and solved the problem of seed retention in the existing rice harvesters. Wu Nan et al. [12] aimed to address the issue of high impurity rate of the harvested shortleaf pine after the operation of the harvesting device, and thus designed a shortleaf pine air net cleaning device. Using the EDEM-Fluent coupling method, with vibration amplitude, frequency, and wind speed as experimental factors and the cleaning rate and loss rate of the genus as evaluation indicators, they conducted a simulation analysis of the working process and determined the optimal parameter combination.

To address the existing technological challenges in raisin foreign object removal equipment, particularly the lack of non-aqueous separation methods and the inability to detach adhered foreign object, this study focuses on the separation of stems, branches, stones, and plastic contaminants adhered to raisins. Based on theories of rapid freezing, rolling separation, and material screening, we investigated the separation process between raisins and adhered foreign objects. After calibrating various material parameters, discrete element method (DEM) simulations and EDEM-Fluent coupled simulations were conducted to evaluate separation rate and screening rate, thereby determining optimal system parameters. Following equipment fabrication, comprehensive testing was performed to validate the rationality of structural design and parameter settings, as well as to assess the equipment’s overall performance capabilities.

2. Materials and Methods

2.1. Experiment on the Separation of Raisins from Adhered Foreign Object

2.1.1. Experimental Materials

The experimental samples were bulk raisins from Turpan City, Xinjiang Uygur Autonomous Region, China, with the specific cultivar being “Seedless White”. The foreign objects included multiple types of endogenous and exogenous foreign object commonly found in bulk raisins, such as stems, branches, stones, and plastic. The raisins and various foreign objects are shown in Figure 1: stem: the thin stem connecting the branch and raisins on the raisin fruit cluster; branch: the branches on the raisin fruit cluster; and stones and plastic: common foreign objects mixed in during the drying and transportation processes. Their proportions varied. To effectively determine the proportion of each foreign object, an electronic balance was used for weighing. The statistics showed that stems accounted for 62.21%, branches for 24.37%, stones for 9.66%, and plastic for 3.76% of the foreign objects, as shown in Figure 2.

To provide a more intuitive description of the characteristic information of raisins and various foreign objects, their dimensions and masses were measured using a vernier caliper and an electronic balance. Statistical analysis was then conducted to calculate the mean values and error ranges, with specific parameters presented in

Table 1. Size and mass parameters of raisins and associated foreign objects.

Dimension Parameter	Raisin	Stem	Branch	Stone	Plastic
Length (mm)	19.82 ± 1.85	8.61 ± 0.83	22.32 ± 6.73	3.87 ± 1.04	8.24 ± 1.24
Breadth (mm)	7.64 ± 1.24	1.27 ± 0.43	2.02 ± 1.24	3.87 ± 1.04	4.39 ± 0.64
Height (mm)	6.32 ± 1.02	1.27 ± 0.43	2.02 ± 1.24	3.21 ± 0.56	2.47 ± 0.34
Weight (g)	1.32 ± 0.21	0.11 ± 0.04	3.17 ± 0.33	3.27 ± 0.31	1.97 ± 0.31

.

The experimental samples were divided into two groups: one group consisted of stem-attached and branch-attached raisins that were not removed from bulk raisins; the other group comprised raisins adhered to various foreign objects due to prolonged storage or improper preservation. To create samples with different adhesion degrees, raisins were mixed with foreign objects and placed into multiple containers under 60% relative humidity (RH) and 20 °C for 5, 10, and 15 days. This process induced varying degrees of adhesion between raisins and foreign objects, as illustrated in Figure 3.

2.1.2. Experimental Design

Raisins are sugar-rich agricultural products, with Thompson seedless raisins typically exhibiting a moisture content of 10–20%. The predominant sugar components in raisins are glucose and fructose [13]. Due to the relatively low solubility of glucose, prolonged storage or improper preservation conditions lead to gradual sugar precipitation on the raisin surface, forming visible sugar crystals. This not only deteriorates the visual texture but also causes the surface sugars to dissolve under temperature fluctuations, creating a highly viscous syrup-like layer. This layer facilitates adhesion between raisins or between raisins and foreign objects, making separation difficult. Elevated temperature and humidity exacerbate this adhesion phenomenon.

Previous studies have demonstrated that polymers generally undergo a glass transition from rubbery to glassy states as temperature decreases. In the glassy state, polymer chain segment motion is frozen, allowing only small-scale molecular movements and minimal deformation under external forces [14]. Although raisins themselves are not polymers, their sugar components exhibit glass transition behavior under specific conditions. Water acts as a plasticizer that reduces the glass transition temperature (Tg) of raisins [15]. Foods with moisture content below 20% typically achieve complete glass transition, while those above 20% or low-concentration solutions form partially crystalline glassy states [16]. Glassy sugars exhibit relatively ordered molecular arrangements, forming quasi-solid structures. When subjected to external forces like impact or stretching, these structures lack plastic deformation capacity, leading to stress concentration-induced cracks that propagate rapidly, resulting in brittle fracture. For sugar solutions, slow cooling allows sufficient molecular diffusion for ordered crystallization, whereas rapid cooling increases system viscosity sharply, hindering molecular motion and lattice arrangement, thereby achieving glassy states.

Based on these findings, the experiment first employed rapid freezing to bring prepared samples to target temperatures of 0 °C, −10 °C, −20 °C, −30 °C, −40 °C, and −50 °C. Textural properties were then analyzed using a TA-XT Plus Texture Analyzer (Stable Micro Systems, UK, shown in Figure 4). Raisin samples were placed on the analyzer platform and subjected to compression tests under different freezing conditions using a cylindrical probe (TA/36R) at a test speed of 1.0 mm/s with auto-trigger mode. Average hardness values were recorded for each temperature condition. Tensile tests were conducted to measure the average pulling force required to separate raisins from foreign objects, serving as an adhesion indicator. Finally, combining textural data and adhesion results, separation experiments were performed using two common manual methods—percussive tapping and rolling compression (rubbing)—to determine the optimal freezing temperature and separation technique.

2.1.3. Evaluation Metrics

Indicator 1: changes in raisin texture characteristics. During the quick-freezing treatment and subsequent restoration to ambient temperature, both raisins and foreign objects undergo changes in their texture characteristics. Variations in texture properties after quick-freezing directly influence separation rate, while post-restoration texture changes affect raisin quality and sensory mouthfeel. To improve evaluation accuracy, the average hardness is proposed as the primary metric for assessing texture characteristics.

Indicator 2: adhesion state between raisins and foreign objects after quick-freezing. The adhesion state between raisin samples and foreign objects varies depending on the quick-freezing temperature applied. Different adhesion states directly impact the force required for separation and the overall separation effectiveness. To quantitatively evaluate adhesion conditions, the average tensile force is introduced as the evaluation metric for adhesion states.

Indicator 3: separation rate and material integrity after different separation methods. Two separation methods—tapping and rolling compression—were employed to detach foreign objects from raisins. The separation performance was evaluated using two metrics: separation rate (S) and material integrity. The separation rate (S) is calculated as the ratio of the difference between the total sample mass ($M_1$) and the mass of raisins still adhering to foreign objects ($M_2$) to the total sample mass ($M_1$), as shown in Equation (1). This metric quantifies the effectiveness of separation methods in detaching foreign objects from raisins.

$$S={\displaystyle \frac{M_1-M_2}{M_1}}\times 100\%$$

(1)

Material integrity encompasses two key parameters—surface damage extent and foreign residue retention extent—quantified respectively by the damage rate (B) and residue retention rate (R). The damage rate (B) is defined as the ratio of the total mass of damaged raisins ($M_3$) to the total mass of the sample ($M_1$), as shown in Equation (2). This metric evaluates the degree of raisin damage caused by mechanical or physical interactions during separation. The residue retention rate (R) represents the ratio of the total mass of raisins containing residual foreign objects ($M_4$) to the total mass of the sample ($M_1$), as presented in Equation (3). This parameter assesses the effectiveness of separation methods in minimizing foreign object retention. A comprehensive evaluation of separation performance across different techniques is conducted using three indicators: separation rate, damage rate, and residue retention rate.

$$B={\displaystyle \frac{M_3}{M_1}}\times 100\%$$

(2)

$$R={\displaystyle \frac{M_4}{M_1}}\times 100\%$$

(3)

2.1.4. Analysis of Experimental Results

The experimental results of the average hardness of raisins are presented in

Table 2. Average hardness of raisins after rapid freezing (g).

Quick-Freezing Temperature (°C)	0-Day	5-Day	10-Day	15-Day
0	1360.34	1352.29	1323.46	1307.17
−10	1742.53	1727.10	1709.89	1692.33
−20	2125.62	2103.57	2074.23	2049.89
−30	2483.92	2455.64	2422.12	2398.21
−40	2697.77	2672.09	2646.67	2623.45
−50	2727.14	2701.78	2679.90	2640.91

. The findings indicate that as the freezing temperature decreased, the hardness of raisins significantly increased. Under the 0-day mixed state, the average hardness of raisins gradually rose from 1360.34 g at 0 °C to 2727.14 g at −50 °C. Similarly, under the 15-day mixed state, the average hardness increased from 1307.17 g at 0 °C to 2640.91 g at −50 °C. This phenomenon aligns with glass transition theory: under low-temperature conditions, the sugars in raisins enter a glassy state where molecular chain segment motion is frozen, leading to increased hardness. At −40 °C and −50 °C, the average hardness values approached their maximums (2697.77 g and 2727.14 g, respectively), indicating superior structural stability of raisins at these temperatures. After restoration to room temperature, the hardness measurements of raisins showed relatively close values, suggesting minimal impact of rapid freezing on raisin hardness, as shown in

Table 3. Average hardness of raisins after restoration to ambient temperature (g).

Quick-Freezing Temperature (°C)	0-Day	5-Day	10-Day	15-Day
0	1079.53	1073.17	1058.13	1041.18
−10	1081.45	1077.33	1061.47	1046.09
−20	1084.78	1082.89	1064.08	1049.45
−30	1085.59	1080.21	1068.76	1055.72
−40	1086.71	1083.91	1070.22	1057.33
−50	1090.46	1083.91	1071.80	1063.61

.

To enhance the comparative analysis of varying adhesion degrees between raisins and foreign objects, samples mixed under specific conditions for 5, 10, and 15 days were utilized in experiments. The results demonstrated that, with prolonged mixing duration, the moisture content of raisins increased, accompanied by sugar exudation. Furthermore, the average hardness of raisins decreased under different quick-freezing temperatures.

Experimental results of adhesion states between raisins and different foreign objects are illustrated in Figure 5a–e. As the quick-freezing temperature gradually decreased from 0 °C to −50 °C under various mixing durations, the average tensile forces required for separating different adhesion states exhibited an initial rapid increase, followed by a gradual decrease. Taking the unmixed raisin–stem adhesion separation as an example, the average tensile force was 910.56 mN at 0 °C, which increased to 2311.03 mN when the temperature dropped to −30 °C. A notable decrease in average force occurred between −30 °C and −40 °C due to the glass transition of precipitated sugar in this temperature range, which enhanced brittleness and reduced interfacial adhesion between sugar and raisin/foreign objects. This transition facilitated crack initiation at the bonding interface during separation, thereby lowering the required tensile force. A slight further reduction was observed at −50 °C.

From the perspective of mixing durations, under identical freezing temperatures, the average separation force generally increased with prolonged contact time across all adhesion types. This upward trend was more pronounced at 5 and 10 mixing days compared with 15 days, indicating that extended contact enhanced adhesion integrity and bonding strength between raisins and foreign objects. Among different foreign objects, raisin–stem adhesion required the highest separation force, while raisin–stone adhesion demanded the lowest, suggesting that adhesion strength correlates with the surface roughness and contact area of foreign objects. Notably, when stems naturally adhered to raisin ends, the tensile force showed no significant increase with temperature reduction, implying minimal impact of freezing temperature on this specific adhesion configuration.

The experiment employed two separation methods: tapping and rolling extrusion. The results of separation rate, damage rate, and residue rate are presented in Figure 6, Figure 7 and Figure 8, respectively. At −40 °C, the rolling extrusion method achieved a separation rate of 88.02%, which was significantly higher than the 72.36% obtained by the tapping method. As temperature decreased, separation rate gradually improved, indicating that rapid freezing enhances separation effectiveness. The rolling extrusion method demonstrated a lower average damage rate (7.32%) and residue rate (3.58%) compared with the tapping method (12.55% and 6.91%, respectively), suggesting reduced damage to raisins and fewer foreign object residues. The tapping method’s concentrated impact force leads to excessive localized stress, thereby increasing the risk of material damage.

In summary, the optimal approach is the combination of quick-freezing treatment at −40 °C and rolling extrusion separation. This method ensures the integrity of raisins while achieving efficient separation of adhered foreign objects. After restoration to ambient temperature, it exerts minimal impact on the raisins themselves, thereby preserving their quality.

2.2. Structural Design of the Removal System

2.2.1. Integral Structural Design

The elimination system was comprehensively designed in accordance with the scheme requirements, incorporating four critical modules: a rolling extrusion separation module, a sorting module, a visual inspection module, and a fine rejection module. These key modules were integrated into a unified system using aluminum profiles as the structural framework and supported by corresponding connectors, as illustrated in Figure 9. The operational workflow proceeds as follows: First, quick-frozen materials are introduced through the inlet of the separation module, where rolling extrusion mechanisms effectively disentangle adhered foreign objects. Subsequently, the separated materials enter the sorting module via its designated inlet, enabling differential screening of raisins and contaminants through vibratory or sieving actions. Finally, residual raisins still adhering to foreign objects or incompletely separated impurities undergo precision rejection via the integrated visual inspection and fine rejection module, thereby completing the full-cycle elimination task.

2.2.2. Rolling Extrusion Separation Module Design

Based on the design requirements of the separation system and experimental results of adhered foreign object separation, this paper proposes a rolling–squeezing separation module to achieve effective separation of adhered foreign objects. The module design includes structural design of the inner and outer housing for the rolling unit, structural design of the squeezing unit, and drive system design for the separation mechanism.

The housing of the rolling–squeezing separation module adopts a double-layer configuration (Figure 10). The inner housing and the upper section of the outer housing feature a frustum-shaped geometry with a slope angle of 66°, while their lower sections adopt a cylindrical form. All components are fabricated from 304 stainless steel, with overall dimensions measuring 570 mm × 294 mm × 294 mm. The frustum design facilitates natural downward flow and gradual dispersion of materials under gravity. The conical inclined surface effectively guides materials into the interstitial gap between the inner and outer housings, preventing accumulation or blockage that could compromise separation efficiency.

The outer surface of the inner housing incorporates regularly distributed protruding structures. These protrusions increase the contact area and frictional force with materials, generate agitation effects during rotation to enhance separation efficiency, and maintain structural integrity under operational loads. The outer housing remains stationary through fixation to an external framework, ensuring process stability and controllability. The inner housing rotates via a shaft supported by bearing blocks at its top end. A uniform interstitial gap of 9 mm is maintained between the inner and outer housings. This gap allows the passage of raisins and adhered foreign objects while avoiding excessive compression that could damage the products.

A feed inlet with dimensions of 62 mm × 28 mm is integrated into the sidewall of the outer housing to ensure stable material input. At the bottom of the inner housing, four material collection plates are strategically positioned. After separation, materials fall into the interstitial gap at the housing base, where the collection plates guide them toward the discharge outlet, completing the collection process.

The squeezing module serves as the core mechanism for rolling–squeezing separation in this system, with its overall structure illustrated in Figure 11a. Composed of multiple squeezing modules, the assembly includes components such as a flexible squeezing head, compression spring, fixed column, sliding sleeve, and upper/lower fasteners. A composite buffering mechanism is primarily employed to ensure thorough separation of adhered foreign objects while preventing material damage. The individual module structure, shown in Figure 11b, features a flexible material coating on the exterior of the squeezing head, with its interior connected to the sliding sleeve via a compression spring and mounted on fasteners. When materials enter the squeezing module, the flexible surface layer initially deforms to absorb the transient impact generated during raisin-shell squeezing. Subsequently, the spring system provides secondary buffering through axial displacement, reducing peak stress on the raisin surface. Additionally, the squeezing module connects to the rotating shaft via shaft couplings and bearing blocks. The axial floating movement of the spring-loaded sliding sleeve, under centrifugal force generated by motor rotation, creates a compound motion trajectory that enables comprehensive rolling–squeezing action on the raisins.

The drive structure of the rolling extrusion separation module adopts a motor-driven system integrated with belt transmission. The motor transfers power to the rotating shaft via the belt transmission mechanism, thereby driving the inner housing and extrusion module to perform rotational motion, which generates the necessary centrifugal force for the extrusion process. Additionally, the rotating shaft employs a smooth shaft design and is securely connected to on-shaft components through shaft support seats. This configuration ensures structural simplicity while facilitating convenient disassembly and maintenance. The entire rolling extrusion module is fixedly mounted on an aluminum profile frame, providing robust support for the entire assembly. The module dimensions are 790 mm × 360 mm × 360 mm, with its structure illustrated in Figure 12a.

The operational process of the rolling extrusion separation module is depicted in Figure 12b. When raisins enter the separation module through the feed inlet, the combined action of inner housing rotation and the extrusion module effectively separates adhered foreign materials from the raisins. Subsequently, a material collection baffle directs the separated materials into the discharge outlet, completing the collection process.

2.2.3. Sieving Module Design

According to the design requirements, the sieving module employs airflow-based screening. By utilizing the different suspension velocities between raisins and foreign objects, the system achieves precise separation of foreign objects through fine control of the airflow. The overall structure is depicted in Figure 13a, and the working process is illustrated in Figure 13b.

The feeding section is equipped with a feed inlet to regulate the entry point of materials into the screening zone, ensuring unobstructed material flow while directing the post-screening material to designated positions. The air-blowing system, a pivotal component of the screening module, comprises a high-speed blower and precision airflow control assemblies. Its airflow volume and pressure are adjustable to meet specific screening requirements. The screening zone is partitioned by baffles into three channels for segregating materials with distinct terminal velocities. The entire module design emphasizes operational ease and maintenance simplicity. Constructed from 304 stainless steel, it exhibits excellent corrosion resistance and durability. Modularization of components facilitates straightforward disassembly and cleaning.

2.3. Material Parameter Calibration

2.3.1. Density Determination

The density of raisins and foreign objects was indirectly determined by measuring their mass and volume. Each sample was first weighed and then attached to a 10 g iron block using a fine string. The sample-iron assembly was submerged in a graduated cylinder, and the volume displacement was calculated by measuring the difference in liquid levels before and after submersion. The net volume of the sample was obtained by subtracting the volume contributed by the 10 g iron block. Density was calculated using the formula $\rho =m/V$. This procedure was repeated ten times for each material, and the averaged results for raisin and foreign object densities are presented in

Table 4. Density of raisins and foreign objects.

Materials	Raisin	Stem	Branch	Stone	Plastic
Density (kg/${\mathrm{m}}^3$)	900	89	89	2500	910

.

2.3.2. Shear Modulus, Elastic Modulus, and Poisson’s Ratio Determination

To determine the intrinsic parameters such as Poisson’s ratio, shear modulus, and elastic modulus of raisins and various foreign objects, uniaxial compression tests were conducted using a texture analyzer. The experimental protocol involved setting a compression speed of 10 mm/min with a loading displacement of 4 mm, and each test was repeated ten times. Intrinsic parameters including Poisson’s ratio, shear modulus, and elastic modulus for raisins, foreign objects, and stainless steel were calculated from measurements of height and diameter changes before and after uniaxial compression, with the averaged results presented in

Table 5. Physical property parameters of materials.

Dimension Parameter	Raisin	Stem	Branch	Stone	Stone
Length (mm)	19.82 ± 1.85	8.61 ± 0.83	22.32 ± 6.73	3.87 ± 1.04	8.24 ± 1.24
Breadth (mm)	7.64 ± 1.24	1.27 ± 0.43	2.02 ± 1.24	3.87 ± 1.04	4.39 ± 0.64
Height (mm)	6.32 ± 1.02	1.27 ± 0.43	2.02 ± 1.24	3.21 ± 0.56	2.47 ± 0.34
Weight (g)	1.32 ± 0.21	0.11 ± 0.04	3.17 ± 0.33	3.27 ± 0.31	1.97 ± 0.31

.

2.3.3. Coefficient of Restitution Determination

The coefficient of restitution (COR), serving as a core parameter for evaluating an object’s ability to recover its original configuration after collision, holds a pivotal position in the study of collision dynamics within multibody systems [17]. It is defined as the ratio of the normal relative velocity of the objects along the contact interface before and after collision [18], specifically the ratio of the separation velocity after collision to the approach velocity before collision. Based on this definition, the mathematical expression for the coefficient of restitution is formulated as follows:

$$e={\displaystyle \frac{\left|v_2\right|}{\left|v_1\right|}}$$

(4)

where $v_1$ and $v_2$ denote the velocities of the experimental material before and after the collision, respectively. Based on the kinematic principles of free fall, the velocities before and after the collision can be calculated using the following equations:

$$v_1=\sqrt{2g{h}_1}$$

(5)

$$v_2=\sqrt{2g{h}_2}$$

(6)

In the equation, $h_1$ represents the initial drop height of the material before collision, and $h_2$ denotes the vertical distance from the collision plane to the highest point reached by the material after rebounding. Consequently, the final expression for the coefficient of restitution is formulated as:

$$e=\sqrt{{\displaystyle \frac{h_2}{h_1}}}$$

(7)

This study employed the free-fall experimental method [19], with the experimental principle illustrated in Figure 14. The rebound heights of raisins and various foreign objects after collision were measured using a height gauge, with 304 stainless steel plates, raisins, stems, branches, stones, plastics, and other materials serving as experimental contact base plates. To ensure data reliability, raisin particles were freely released from a fixed height $h_1$ = 150 mm, and the entire process was recorded by a high-speed camera in a plane perpendicular to the falling direction, as shown in Figure 14. Each experimental group was repeated 10 times, and the maximum rebound height of raisin particles was recorded to calculate the mean value $h_2$. Finally, the COR for raisins and various foreign objects were determined using the COR calculation formula. The COR values were as follows: 0.48 for raisin–raisin collisions, 0.32 for raisin–stem/branch collisions, 0.44 for raisin–stone collisions, 0.35 for raisin–plastic collisions, 0.53 for raisin–304 stainless steel collisions, 0.20 for stem/branch–stem/branch collisions, 0.36 for stem/branch–stone collisions, 0.35 for stem/branch–plastic collisions, 0.47 for stem/branch–304 stainless steel collisions, 0.50 for stone–stone collisions, 0.45 for stone–plastic collisions, 0.63 for stone–304 stainless steel collisions, 0.46 for plastic–plastic collisions, and 0.50 for plastic–304 stainless steel collisions.

2.3.4. Determination of the Coefficient of Friction

The friction coefficient, as a critical parameter characterizing the frictional properties between material surfaces, is primarily determined by key factors including surface topography characteristics, material properties, ambient temperature, and normal load [20]. This study employs the inclined plane method to measure the static friction coefficients of raisins and various foreign objects [21]. Prior to experimentation, a measurement apparatus was constructed using aluminum alloy and positioned on a horizontal plane to ensure ideal horizontal orientation. The static friction coefficient between raisins and 304 stainless steel was measured first. The test sample was placed on the stainless steel surface with one end of the measurement plate secured. The inclination angle was gradually adjusted using an angular regulation device, and the critical angle was recorded immediately upon observing the initiation of sample sliding, as illustrated in Figure 15.

To determine the frictional characteristics between raisins and foreign objects such as stems, branches, stones, and plastics, test plates were fabricated by securing various heterogeneous materials onto their surfaces using adhesives, with identical experimental conditions maintained during measurements [22]. Each experimental group was replicated ten times, and mean values of static friction coefficients between different materials were obtained through statistical analysis. Static friction angles between raisin particles and stainless steel plates, raisin particles and stems, raisins and branches, raisins and stones, and raisins and plastics were measured. The static friction coefficients between raisins and stainless steel plates/stems/branches/stones/plastics were subsequently calculated using Equations (8) and (9).

$$\left\{\begin{array}{c}{F}_1=Gsin\theta \hfill \\ F_2=Gcos\theta \hfill \\ F_1-f=0\hfill \\ F_2-F_N=0\hfill \\ f=\mu F_N\hfill \end{array}\right.$$

(8)

$$\mu ={\displaystyle \frac{f}{F_N}}={\displaystyle \frac{F_1}{F_2}}={\displaystyle \frac{Gsin\theta }{Gcos\theta }}=tan\theta$$

(9)

In the equation, $F_1$ represents the component of gravitational force along the inclined plane, G denotes gravitational force, $\theta$ is the inclination angle of the plane, $F_2$ corresponds to the applied pressure, f indicates frictional force, $F_N$ signifies the normal support force, and $\mu$ is the static friction coefficient.

The rolling friction coefficient of materials was measured using the inclined plane rolling method [23]. During experiments, materials were placed on a test plate with an inclination angle $\beta$, where $\beta$ = 30° was determined through preliminary trials. To ensure full conversion of gravitational potential energy into work conducted against frictional forces, materials were clamped with tweezers and released from a fixed position (L = 50 mm) with an initial velocity of 0 m/s. The rolling distance D along the horizontal direction upon cessation of motion served as the evaluation metric. Ten replicate experiments were conducted, and the rolling friction coefficient $\eta$ was calculated using Equation (10). The static and rolling friction coefficients obtained from relevant studies [24] and experimental results are presented in

Table 6. Friction coefficient between materials.

Materials	Static Friction Coefficient	Dynamic Friction Coefficient
Raisin–Raisin	0.50	0.04
Raisin–Stem/Branch	0.52	0.20
Raisin–Stone	0.50	0.02
Raisin–Plastic	0.50	0.04
Raisin–Stainless steel	0.45	0.12
Stem/Branch–Stem/Branch	0.58	0.25
Stem/Branch–Stone	0.45	0.08
Stem/Branch–Plastic	0.52	0.08
Stem/Branch–Stainless steel	0.47	0.10
Stone–Stone	0.43	0.05
Stone–Plastic	0.45	0.02
Stone–Stainless steel	0.45	0.11
Plastic–Plastic	0.52	0.15
Plastic–Stainless steel	0.45	0.12

.

$$GLsin\beta =G\left(Lcos\beta +D\right)\eta$$

(10)

2.4. DEM Simulation of Separation Processes

2.4.1. Modeling of Raisins and Foreign Objects

DEM is a numerical computational approach designed to simulate the dynamic behavior of granular systems. Its essence lies in treating the granular system as an aggregate composed of numerous discrete particles and predicting/characterizing the macroscopic mechanical behavior and microscopic motion mechanisms of particles by establishing contact models and motion equations between particles. EDEM 2022 is a discrete element software that enables rapid construction of granular discrete element models for various research objects, facilitating simulation analysis of particle motion processes.

Since raisins, stems, branches, stones, and plastics are all non-spherical particles (with raisins being particularly complex), to ensure the authenticity of EDEM simulation results, stems, branches, stones, and plastics were 3D-modeled using Solidworks 2023, while raisins were 3D-modeled using 3ds Max 2023. The established 3D models were then converted to STL format and imported into EDEM for 3D mesh generation. The “multi-sphere aggregation method” and non-spherical particle automatic filling tool were employed, with the smoothing value set to 5 and the minimum sphere radius adjusted to 0.5 mm, to perform multi-sphere filling for achieving a more realistic discrete element model that simulates morphological characteristics. The 3D model is shown in Figure 16a, and the discrete element model is presented in Figure 16b. Based on the established discrete element models of raisins and various foreign objects, a discrete element model of post-adhesion materials was constructed, as illustrated in Figure 16c.

2.4.2. Establishment of the Adhesion Model

The adhesion between raisins and foreign object, combined with sugar approaching vitrification after quick-freezing, creates a raisin–sugar–foreign object structural configuration. Separation mechanisms involve three potential pathways: fracture of the sugar layer under external force, interfacial detachment due to weak adhesion at sugar–surface interfaces, or surface delamination caused by strong adhesion under mechanical stress. Experimental validation through rolling extrusion demonstrated reduced residue and damage rates, justifying the exclusion of the third mechanism in simulations. Consequently, the Hertz–Mindlin with bonding contact model was implemented to simulate adhesive interactions between raisins and foreign object, as depicted in Figure 17.

The simulation employing the Hertz–Mindlin with bonding contact model necessitates the determination of parameters including inter-particle contact radius (R), normal stiffness per unit area ($K_n$), shear stiffness per unit area ($K_t$), critical normal stress (${\sigma }_c$), and critical shear stress (${\tau }_c$) [25]. In the raisin–sugar–foreign object system where sugar acts as the bonded component, the sugar-related parameters are challenging to measure experimentally. Consequently, this study adopts theoretically calculated values as model parameters. According to Hertz contact theory, the contact radius formula is presented in Equations (11)–(13).

$$R=\sqrt[3]{{\displaystyle \frac{3F_n{R}_{eff}}{4E^{*}}}}$$

(11)

$${\displaystyle \frac{1}{R_{eff}}}={\displaystyle \frac{1}{R_1}}+{\displaystyle \frac{1}{R_2}}$$

(12)

$${\displaystyle \frac{1}{E^{*}}}={\displaystyle \frac{1-{v_1}^2}{E_1}}+{\displaystyle \frac{1-{v_2}^2}{E_2}}$$

(13)

In the equation, $F_n$ denotes the average tensile force at separation, $R_{e}ff$ represents the effective radius of curvature, $E^{*}$ indicates the equivalent elastic modulus, $R_1$ corresponds to the radius of curvature at the raisin contact point, $R_2$ signifies the radius of curvature at the foreign object contact point, $v_1$ is the Poisson’s ratio of the raisin, $v_2$ denotes the Poisson’s ratio of the foreign object, $E_1$ represents the elastic modulus of the raisin, and $E_2$ corresponds to the elastic modulus of the foreign object. The normal stiffness per unit area $K_n$ is calculated as shown in Equation (14).

$$K_n={\displaystyle \frac{4}{3}}{E}^{*}\sqrt{R}$$

(14)

The calculation of the tangential stiffness per unit area ($K_t$) is presented in Equations (15) and (16).

$$K_t={\displaystyle \frac{8G^{*}\sqrt{R}}{2-v}}$$

(15)

$${\displaystyle \frac{1}{G^{*}}}={\displaystyle \frac{2\left(1+v_1\right)}{E_1}}+{\displaystyle \frac{2\left(1+v_2\right)}{E_2}}$$

(16)

In the formula, $G^{*}$ represents the equivalent shear modulus. The critical normal stress ${\sigma }_c$ and the critical tangential stress ${\tau }_c$ are calculated as shown in Equations (17) and (18).

$${\sigma }_c={\displaystyle \frac{F_n}{\pi R^2}}$$

(17)

$${\tau }_c={\displaystyle \frac{{\sigma }_c}{\sqrt{3}}}$$

(18)

2.4.3. Model Simplification

Before conducting simulations of the separation process, it is necessary to simplify the entire model by reducing secondary features, slits, geometric details, and connection configurations. This model simplification aims to decrease computational complexity and shorten solution time while preserving the primary functional components (inlet, inner/outer shells, squeeze head, and outlet). The rolling extrusion module was accordingly simplified, with its simplified 3D model and simulation model presented in Figure 18a and Figure 18b, respectively.

2.4.4. EDEM Simulation

The operational process of the rolling extrusion module was simulated using EDEM. First, discrete element and bonding models for raisins and foreign objects were incorporated, with parameters including contact radius, Poisson’s ratio, density, elastic modulus, restitution coefficient, static friction coefficient, and rolling friction coefficient being configured. The rolling extrusion module model was also added with its material properties and interfacial coefficients (restitution, static friction, rolling friction) with the materials. Second, particle factory dimensions and position were defined, with materials comprising raisins bonded to stems, branches, stones, and plastic fragments. The total input rate was set to 300 kg/h, with foreign object bonding ratios corresponding to actual proportions in bulk raisins (Figure 2). All materials were configured to fall at 0 m/s. Third, contact models between raisins, various foreign objects, and the rolling extrusion module walls were established using the Hertz–Mindlin with bonding model. Finally, rotational speeds of the rolling components were set to 200 r/min, 400 r/min, 600 r/min, and 800 r/min, with a time step of $2\times {10}^{-7}$ s, data recording interval of 0.02 s, and total simulation duration of 3 s.

2.5. EDEM-Fluent Coupled Simulation of the Screening Process

2.5.1. Model Simplification and Meshing

On the basis of retaining the primary functional components (air inlet, air outlet, feed inlet, baffle plate, receiving plate, and receiving box), the sheet metal bending edges were simplified to right angles while removing slots, bending flanges, and machining holes. This process achieved structural simplification of the screening module to reduce model complexity. The simplified 3D model and simulation model are presented in Figure 19a and Figure 19b, respectively.

Mesh generation was performed in Fluent software 2022 by importing the simplified model and generating the surface mesh. The geometry type was configured as a geometric structure containing both fluid and solid domains. The inlet region was defined as a velocity-inlet boundary type, while the outlet region was set as a pressure-outlet boundary type. After sealing the fluid domain boundaries, the volume mesh was generated following the addition of boundary layers, achieving both surface and volume mesh generation. The final mesh counts comprised $3.43472\times {10}^6$ surface mesh elements and $3.48857\times {10}^6$ volume mesh elements. Upon completion of mesh generation, the mesh quality was evaluated and optimized using the built-in quality verification tool. The surface and volume meshes are illustrated in Figure 20a and Figure 20b, respectively.

2.5.2. EDEM-Fluent Coupled Simulation

The operational process of the screening module was simulated using EDEM-Fluent coupled calculations. In EDEM, a simplified model of raisins and four types of foreign objects was first incorporated using the multi-sphere clustering method, with material parameters including Poisson’s ratio, density, elastic modulus, restitution coefficient, static friction coefficient, and rolling friction coefficient configured. The screening module model was added with its material properties and interaction parameters (restitution coefficient, static/rolling friction coefficients) with the materials defined. Subsequently, the size and position of the particle factory were established, with material quantity and generation rate set according to the actual proportion of raisins to various foreign objects obtained from Figure 2. All materials were configured to fall with an initial velocity of 0 m/s. The contact model between raisins, foreign objects, and screening zone walls was selected as Hertz–Mindlin (no-slip) since particle separation had been achieved at this stage. Finally, the time step was set to $5\times {10}^{-6}$ s, with data recording intervals of 0.02 s and a total simulation duration of 1 s.

In Fluent, the previously generated mesh was loaded, and the solution mode was activated with transient time settings and gravity set to −9.81 m/${\mathrm{s}}^2$ in the Y-direction. Boundary conditions at the air inlet were defined with velocity values of 9 m/s, 10 m/s, 11 m/s, and 12 m/s, along with 5% turbulence intensity and 10% turbulent viscosity ratio. The compiled EDEM coupling model was loaded and connected to EDEM. The Fluent solver’s time step was configured as 20 times the EDEM time step ($1\times {10}^{-4}$ s), with 10,000 total steps and 40 iterations per time step.

3. Result

3.1. Analysis of EDEM Simulation Results for the Separation Process

By comparing the material distributions in the receiving box at different rotational speeds, it can be observed that the rotational speed exerts a significant impact on the screening rate of raisins and adhered foreign objects, with the separation process illustrated in Figure 21.

In terms of quantitative analysis, the separation rate of raisins from adhered foreign objects at different rotational speeds was evaluated by counting the number of raisin particles and adhered foreign objects in the collection bin after simulation, as presented in

Table 7. Quantity of raisin particles and raisin particles with adhered foreign objects in the collection bin at different rotational speeds.

Rotational Speed (r/min)	Number of Raisin Particles Free from Adhered Foreign Objects	Number of Raisin Particles with Adhered Foreign Objects
200	338	523
400	872	35
600	856	4
800	869	0

. At 200 r/min, the separation module demonstrated suboptimal performance, with most adhered foreign objects remaining ineffectively separated. A positive correlation between separation rate and rotational speed was observed. When operating at 400 r/min, the separation performance improved with increased dissociation of adhered foreign objects, though partial adhesion persisted. At 600 r/min, the separation rate became significant, characterized by complete dissociation of most foreign objects and absence of visibly contaminated raisins in the collection bin. However, at 800 r/min, despite maintaining a high separation rate, excessive rotational speed induced shearing between materials and separation components at the discharge outlet, resulting in material damage and elevated risk of raisin breakage.

The optimal separation performance was achieved at 600 r/min, yielding a 99.53% separation rate with only 0.47% residual adhered foreign objects.

In comprehensive analysis, the separation rate between raisins and adhered foreign object was inadequate at lower rotational speeds, resulting in a low separation rate of adhered foreign object. As the rotational speed increased to 400 r/min, the separation performance improved significantly, accompanied by an elevated separation rate of adhered foreign object. Further increasing the speed to 600 r/min achieved optimal separation conditions, where the majority of adhered foreign object could be effectively separated. However, when the rotational speed exceeded 600 r/min, although the separation rate of adhered foreign object remained high, excessively high speeds elevated the risk of raisin damage. Therefore, a rotational speed of 600 r/min was identified as the optimal parameter.

3.2. Analysis of EDEM-Fluent Coupled Simulation Results for the Screening Process

3.2.1. Flow Field Analysis

The sieving module utilizes gas flow to achieve the separation of raisins and foreign objects. Due to the varying movement patterns of airflow within the sieving zone, its impact on the materials also differs. Therefore, to enhance the working efficiency of the sieving module, it is essential to investigate the movement patterns of airflow within the sieving zone. When airflow enters the sieving zone, a pressure drop occurs, which is primarily attributed to the following factors: first, the drastic reduction in inlet area when airflow enters the sieving zone; second, energy loss occurs when airflow interacts with raisins, pedicels, branches, stones, plastics, and other materials; finally, pressure drop is also induced by the abrupt changes in airflow interface at the inlet and outlet. Consequently, the pressure within the sieving zone varies during the sieving process. The velocity contour plot and velocity vector plot of the Z-axis cross section in the sieving zone are shown in Figure 22a and Figure 22b, respectively.

During the screening process, wind pressure was simulated, and total pressure distribution cloud maps of the Z-axis section in the screening zone (Figure 23a) and dynamic pressure distribution cloud maps of the same section (Figure 23b) were captured at identical positions. Analysis of Figure 23a reveals that total pressure is highest at the air inlet, gradually decreasing toward the outlet before slightly increasing near the exit. This phenomenon occurs because airflow entering the screening zone interacts with raisins, foreign objects, and structural components (walls/baffles), causing energy exchange per the conservation of energy principle—airflow energy decreases while material energy increases, resulting in lower outlet total pressure compared with the inlet. The slight outlet pressure rise is attributed to the restricted outlet size. Examination of Figure 23b shows higher dynamic pressure at both inlet and outlet with a gradient decrease toward the center, reaching minimum values in the lower section of the device. This dynamic pressure pattern facilitates raisin–foreign object separation. Notably, pressure variations remain minimal and stable in the visual inspection and fine-removal zones beneath the screening module, indicating minimal operational interference from the screening process. This stability enhances the overall system reliability and removal performance.

3.2.2. Analysis of the Influence of Airflow Velocity on Sieving Performance

During the screening process, wind speeds of 9 m/s, 10 m/s, 11 m/s, and 12 m/s were employed to simulate the screening performance of raisins and foreign objects under different airflow conditions, as illustrated in Figure 24. By comparing the material distributions in various screening channels under different wind velocities, it was observed that wind speed exerts a significant effect on the screening rate between raisins and foreign objects.

Based on the simulation results, when the wind speed was 9 m/s, stones fell into the heavier foreign object screening channel closest to the air outlet. A portion of the heavier raisins also entered this channel, while the remaining raisins were directed into the middle raisin screening channel. However, due to the low wind speed, some fruit stems, branches, and plastic particles also entered the middle raisin channel, with the remaining light foreign object (fruit stems, branches, and plastics) falling into the lighter foreign object channel near the air outlet. The screening rate was relatively poor at this wind speed.

When the wind speed increased to 10 m/s, the separation rate between raisins and foreign object improved, with enhanced removal rates of lighter foreign object and reduced raisin loss rates. Nevertheless, a small portion of light foreign object still entered the middle raisin channel. Further increasing the wind speed to 11 m/s resulted in more pronounced screening performance: most foreign object was effectively separated, and all raisins fell into the guide trough of the middle screening channel, and formed a single-layer structure entering the visual inspection area. However, at 12 m/s wind speed, although foreign object removal rates remained high, a small quantity of stones entered the middle raisin channel, and a few raisins migrated to the outermost lighter foreign object channel, leading to increased raisin loss.

Quantitatively, the screening rate of raisins under different wind speeds was analyzed by counting the number of raisin particles in the middle raisin channel versus other channels after simulation completion, as shown in

Table 8. The number of raisin particles in each channel under different wind speeds.

Wind Speed (m/s)	Heavy Foreign Object Passage	Raisin Channel	Less Severe Foreign Object Passage
9	8	247	0
10	3	242	0
11	0	245	0
12	0	246	7

. Similarly, the screening rate of various foreign objects was evaluated by comparing the particle counts in their respective channels with those in the middle raisin channel, also presented in

Table 9. Particle counts of various foreign matters in each channel under different wind speeds.

Wind Speed	Heavy Foreign Object Passage				Raisin Passage				Lighter Foreign Object Passage
(m/s)	Stem	Branch	Stone	Plastic	Stem	Branch	Stone	Plastic	Stem	Branch	Stone	Plastic
9	0	0	45	0	5	14	0	18	230	98	0	10
10	0	0	41	0	3	8	2	5	232	109	0	21
11	0	0	45	0	2	2	4	1	235	109	0	20
12	0	0	34	0	4	0	16	0	227	110	0	16

. At 11 m/s wind speed, the raisin screening rate reached an optimal 96.46%, with only 3.54% of foreign object entering the raisin channel.

A comprehensive analysis revealed that fruit stems and branches, due to their morphological and density characteristics, exhibited a satisfactory separation rate at relatively low wind speeds, albeit with a higher raisin loss rate. As wind velocity increased to 10 m/s, the removal rate of fruit stems and branches improved, while the raisin loss rate decreased concomitantly. For stones, their higher density enabled effective screening even at lower wind speeds; however, excessively high velocities compromised screening performance. The separation rate of plastic fragments depended on both density and shape: lighter fragments were adequately separated at lower velocities, whereas heavier fragments required elevated wind speeds for effective separation. Notably, a minor proportion of foreign objects still entered the intermediate channel due to inter-particle collisions, necessitating a fine removal module for secondary processing. Based on simulation outcomes, 11 m/s emerged as the optimal wind speed within the tested range, though this value requires experimental validation and fine-tuning using actual equipment to determine more precise parameters.

3.2.3. Particle Velocity Analysis

During the simulation analysis of raisin and foreign object screening, an optimal inlet air velocity of 11 m/s was selected for investigation. Upon entering the screening zone, raisins and foreign objects interact with the airflow, colliding with other particles, the inner walls of the screening zone, and baffles. This results in temporal velocity fluctuations characterized by a polygonal trajectory pattern over time. Ultimately, raisins and foreign objects separate into three distinct material collection channels within the screening zone. Velocity analysis of these particles provides direct insights into the screening performance of the module. The velocity variation curves obtained from simulations were imported into Origin software 2024 to generate comparative velocity profiles for raisins and various foreign objects, as illustrated in Figure 25.

During the sieving process, raisins and foreign objects are separated under the combined action of airflow. Analyzing the motion of these materials within the sieving module is crucial for enhancing the efficiency and performance of the sieving system. As shown in Figure 25 (velocity variation curve of raisin particles), the velocity of raisin particles in the sieving zone reaches its peak at 0.22 s of simulation time. Subsequently, the velocity decreases due to collisions with the baffle, deflection chutes, and other materials during the falling process. Upon reaching the lower end of the inclined deflection chute in the visual inspection zone, the velocity begins to increase again, and after passing through the precision removal zone, the particles fall into the receiving bin. According to the velocity analysis, the peak velocities of stems, branches, stones, and plastic fragments occur at 0.17 s, 0.18 s, 0.36 s, and 0.38 s of simulation time, respectively. The velocity trends for all foreign objects follow a pattern of initial increase, followed by gradual decrease until they enter the receiving bin via the sieving channel. Comparative analysis reveals that stems, branches, stones, and plastic fragments exhibit greater velocity fluctuations over time compared with raisins.

3.2.4. Trajectory Analysis of Materials During the Screening Process

During the sieving process conducted at the optimal air velocity, raisins and various foreign objects are set into motion by the airflow. Within the sieving zone, stones and heavier foreign object are directed into the heavier foreign object sieving channel under the influence of the airflow, while raisins are guided into the raisin sieving channel. Meanwhile, stems, branches, and plastic particles migrate toward the lighter foreign object sieving channel near the air outlet. Raisin particles rapidly settle into their respective sieving channels throughout the module under the combined effects of airflow velocity variations and internal pressure fluctuations. Only a minimal proportion of foreign objects enter the raisin particle channel, demonstrating the excellent performance of the sieving module. This facilitates efficient material separation through the module and significantly enhances sieving efficiency. The trajectories and velocity changes of raisins and various foreign objects are illustrated in Figure 26.

3.3. Testing and Evaluation of Sorting/Ejection Equipment for Foreign Object Removal

The overall framework of the equipment is constructed using HD-320 × 2.0 3030 aluminum profiles. All components in direct contact with materials are fabricated from 304 stainless steel. The rotating shaft of the separation module consists of chrome-plated flexible shaft made from 45# steel. The complete structural configuration of the removal equipment is illustrated in Figure 27.

3.3.1. Testing of Separation and Sieving Processes

This paper employs rolling extrusion separation and pneumatic sieving to achieve efficient separation of raisins from adhered foreign objects and subsequent sieving of the separated raisin–foreign object mixture. These two critical stages correspond to the separation process and the sieving process, respectively. In the separation process, motor speed serves as the most pivotal parameter, directly influencing the effectiveness of rolling extrusion separation. In the sieving process, the air velocity corresponding to fan speed becomes the core factor determining sieving accuracy.

Given that the optimal ranges of motor speed and air velocity obtained through simulation require adaptive adjustment to actual operating conditions, conducting practical testing is essential. Testing enables precise evaluation of the applicability of simulation-derived parameters in real-world environments, allowing for fine-tuning of motor speed and air velocity to ensure optimal performance of both separation and sieving processes, thereby enhancing the stability of the raisin foreign object removal system.

For motor speed testing, five different test speeds were set based on the simulation-optimized value of 600 r/min: 500 r/min, 550 r/min, 600 r/min, 650 r/min, and 700 r/min. Adhered foreign object-contaminated raisins were then introduced into the rolling extrusion separation module for foreign object removal. After completion, key metrics were accurately recorded from the collection bin: counts of raisins without adhered foreign objects, raisins still with adhered foreign objects, damaged raisins, and raisins with adhered foreign object fragments. These data were used to calculate separation rate, breakage rate, and residue rate, with detailed results presented in Figure 28.

In the fan wind speed testing section, based on the simulation-derived optimal wind speed of 11 m/s, three test wind speeds (10.5 m/s, 11 m/s, and 11.5 m/s) were configured. Subsequently, raisins adhered with foreign objects were introduced into the sieving module for separation. Following the sieving process, quantitative analysis was performed on key parameters including the count of foreign objects entering the raisin collection zone and the number of raisin particles migrating to the foreign object collection zone. Based on these quantified metrics, the removal rate and carry-over ratio were calculated, with experimental results detailed in Figure 29.

A comparative analysis of key performance indicators during the separation process under varying rotational speeds revealed the following findings: As the motor speed increased from 500 r/min to 650 r/min, the separation rate exhibited an upward trend from 89.58% to 94.67%, while both the breakage rate and residue rate remained relatively stable. At this rotational speed, the balance among separation rate, breakage rate, and residue rate reached an optimal state, showing minimal deviation from the simulation-derived optimal speed range. This validates the rationality of the simulated rotational speed parameters, and through experimental optimization, the optimal operational conditions were achieved. When the speed was further increased to 700 r/min, no significant changes were observed in separation rate, residue rate, or breakage rate.

Regarding the screening process under different air velocities, experimental data demonstrated that at 11 m/s wind speed, the screening rate reached its maximum value, accompanied by a carry-over ratio of 75:1. This outcome precisely matched the simulation-derived optimal wind speed, confirming the accuracy of the simulated air velocity parameters. This condition enabled effective separation of foreign objects from raisins while minimizing unnecessary product loss. However, at wind speeds of 10.5 m/s and 11.5 m/s, a slight decline in screening rate was observed. Both excessively high and low wind speeds reduced the carry-over ratio, leading to material waste and compromising the quality of the final raisin product. Through systematic testing of motor rotational speeds during separation and air velocities during screening, the optimal operational parameters were determined as 650 r/min for motor speed and 11 m/s for air velocity.

3.3.2. Multi-Group Quick-Frozen Material Removal Testing

To verify the optimal quick-freezing temperature proposed in this study for raisins adhered with foreign objects, which aims to effectively remove foreign objects while maximizing the removal ratio of the sorting system, multiple sets of quick-freezing experiments at different temperatures were conducted for systematic sorting validation.

The detailed testing procedure is as follows: First, bulk materials were divided into seven groups and subjected to quick-freezing at target temperatures of 0 °C, −10 °C, −20 °C, −30 °C, −40 °C, and −50 °C. Subsequently, each group of materials was sequentially placed into the sorting device for separation, sieving, and precision sorting. Finally, under different quick-freezing temperature conditions, critical parameters were statistically analyzed, including number of raisin particles without adhered foreign objects in the receiving box, number of raisin particles still adhered with foreign substances, number of damaged raisin particles, quantity of foreign objects entering the raisin collection zone, and quantity of raisin particles entering the foreign object collection zone. Based on these statistics, separation rate, breakage rate, residue rate, removal rate, and removal ratio were calculated, as shown in Figure 30. Through comprehensive comparative analysis of all statistical data, the effectiveness of the proposed optimal quick-freezing temperature was validated.

By comparing the evaluation index data under different quick-freezing temperatures, it can be observed that as the freezing temperature decreases, the separation effect between raisins and adhered foreign objects exhibits a distinct trend. When the freezing temperature gradually decreases from 0 °C, the separation rate increases progressively, peaking at 93.76% at −40 °C, after which it remains relatively stable despite further temperature reduction. This indicates that within the low-temperature range around −40 °C, freezing treatment significantly weakens the adhesion force between raisins and foreign objects, thereby enhancing the separation rate. Meanwhile, the breakage rate gradually decreases with temperature reduction, reaching 3.05% at −40 °C before stabilizing. Residue rate and removal rate data demonstrate that moderate freezing temperature reduction effectively reduces foreign object residue on raisins, though excessively low temperatures may adversely affect the residue rate (e.g., a 2.12% increase at −50 °C compared with −40 °C). The integration of visual and precision removal modules ensures removal rates above 89% across all tested temperatures, with the highest value of 94.52% achieved at −50 °C. At −40 °C, the carry-over ratio reaches 71:1, indicating low mis-removal rates and high removal accuracy at this temperature. Based on comprehensive analysis of all indicators, −40 °C emerges as the optimal freezing temperature within the tested range, effectively removing foreign objects while minimizing raisin loss, thereby validating the effectiveness of the optimized freezing temperature and separation method.

3.3.3. Overall Performance Testing of the Sorting System

Overall performance testing was conducted using the optimal motor speed, fan airflow velocity, and material freezing temperature parameters obtained from previous multiple test groups. The separated material conditions are presented in Figure 31, and the removal performance of the final raisin foreign object separation system is shown in Figure 32. As evidenced by the material conditions in Figure 31, the equipment demonstrates capability to separate adhered foreign objects from raisins. From Figure 32, it is observed that the system effectively removes the majority of foreign objects. However, due to the presence of raisins with significantly lower than average mass and a small portion of raisins still adhered with foreign objects, a minor proportion (less than 1% of the total raisin count) of raisins may still appear in the foreign object channel. This quantity is considered negligible. Through testing, the equipment achieved a material processing capacity of 120 kg/h.

4. Conclusions

From the simulation results of the separation process, it was observed that at lower rotational speeds, the separation rate between raisins and adhered foreign materials was suboptimal, with a low separation rate for adhered impurities. As the rotational speed increased to 400 r/min, the separation performance significantly improved, leading to a higher separation rate for adhered foreign materials. Further increasing the speed to 600 r/min achieved a satisfactory separation state, where most adhered impurities were effectively separated. However, when the rotational speed exceeded 600 r/min, although the separation rate for adhered impurities remained high, excessively high speeds increased the risk of raisin breakage. Regarding the screening process simulation, stem and branch fragments exhibited a favorable separation rate even at low airflow velocities due to their shape and density characteristics, but this resulted in a relatively high raisin loss rate. As the airflow velocity increased to 10 m/s, the removal rate of stems and branches improved, while the raisin loss rate decreased. For stones, their high density enabled effective screening at lower airflow velocities, but excessively high velocities compromised screening performance. The screening rate of plastic fragments depended on their density and shape: lighter plastic fragments could be separated at lower velocities, whereas heavier ones required higher velocities for effective separation. Ultimately, an airflow velocity of 11 m/s was identified as optimal.

From the perspective of the actual removal effect of the equipment and relevant experiments, the optimal actual rotational speed and the wind speed of the raisin foreign matter removal system designed in this paper are 650 r/min and 11 m/s, respectively. The equipment has a material processing capacity of 120 kg/h, with a separation rate of 93.76%, a damage rate of 3.05%, a residue rate of 4.28%, a removal rate of 94.52%, and a carry-over ratio of 71:1. It possesses the capability for automated separation and screening of adhered foreign matters, providing new ideas and methods for the development of related technologies. It can effectively enhance the purity and quality of raisin products, improve production efficiency, and reduce labor costs. However, there are still some deficiencies in this study. Subsequent research can be carried out from the following aspects: equipment processing capacity, equipment’s removal of non-rigid foreign matters, and the external structure of the equipment. First, regarding the equipment processing capacity, although the equipment’s processing capacity is higher than that of manual labor (10–20 kg/h), it is still relatively low compared with existing equipment that directly removes raisins with adhered foreign matters. Subsequent improvements to the structure are required to increase the overall processing capacity of the equipment. Second, concerning the equipment’s removal of non-rigid foreign matters, currently, the foreign matters targeted by the equipment are fruit stems, branches, stones, and plastics, while there is a lack of research on foreign matters such as nylon strips and ropes. Subsequent research can focus on foreign matters like nylon strips and ropes and combine the processing methods for rigid and non-rigid foreign matters to improve the applicability of the equipment. Finally, with regard to the external structure of the equipment, currently, the equipment only uses aluminum profiles to fix each module. In the future, the external frame can be replaced with a sheet metal enclosure and undergo corresponding surface treatment. Additionally, a visual window can be added to directly observe the operating status inside each module.