Mining Scraper Conveyors Chain Drive System Lightweight Design: Based on DEM and Topology Optimization

Abstract

For the issue of excessive mass in the chain drive system of long-distance scraper conveyors, this paper proposes a method to optimize the scraper chains by integrating discrete element simulation (DEM) with topological optimization. The aim is to reduce the system’s mass while maintaining its transportation capacity and structural integrity. The SGZ1000 model scraper conveyor with a length of 400 m was selected as the research object. Studies have demonstrated that for 56 × 187 mm scraper chains, a non-equally spaced configuration (6p-8p-6p, where p represents the chain link pitch) outperforms an equally spaced configuration (6p). While ensuring the conveying capacity of the scraper chains, the optimized configuration reduces the number of scrapers in chains of equal length by 11.11%. For a 400 m scraper conveyor, adopting the 6p-8p-6p scraper spacing reduces the number of scrapers by 72 and decreases the mass by 6357.6 kg. Additionally, utilizing topologically optimized scrapers further reduces the total mass by 10,131.4 kg. Compared to the original chain drive system, the optimized scraper chains have reduced the mass by 26.2%, significantly lowering the no-load energy consumption of the long-distance scraper conveyor.

1. Introduction

The scraper conveyor, as the core equipment for coal mining [1], has seen its length increase from 200–300 m to over 500 m with the construction of super-long fully-mechanized mining face coal mines [2]. To meet the rapidly growing demand for the transportation capacity of scraper conveyors, the width of the middle trough, the diameter of the chain, and the mass of the scraper of scraper conveyors are continuously increasing. This leads to an increase in the energy consumption of the scraper conveyor when transporting the same volume of coal, as well as an increase in the production cost for enterprises [3].

When the scraper conveyor is in operation, the chain drives a large number of scrapers to move synchronously, and the coal in the middle trough is pushed by the scrapers, thus achieving the continuous transportation of coal [4]. When the width of the middle trough increases, the resistance that the scrapers encounter while pushing the materials will also increase accordingly. To ensure that the scrapers have sufficient strength and prevent them from bending or being damaged during the movement, the thickness of the scrapers is usually increased. This increases the mass of the scraper and results in a rise in the no-load energy consumption of the chain drive system. Currently, the chain diameter of the world’s longest 600 m scraper conveyor developed by China National Coal Zhangjiakou Coal Mining Machinery Co., Ltd. has reached 65 mm, and the mass of a single scraper exceeds 120 kg. The mass of just the scrapers in the chain drive system exceeds 144,000 kg, which seriously affects the no-load energy consumption of the scraper conveyor. Reducing the no-load mass of the scraper conveyor’s chain drive system is an effective strategy to reduce the no-load energy consumption of the scraper conveyor [5]. Since 2020, many scholars and scraper conveyor manufacturing enterprises have carried out a great deal of exploration [6,7,8,9]. They mainly conduct research from two aspects: reducing the mass of the scraper itself and decreasing the friction coefficient of the scraper. Limited by traditional machining methods and costs, these new technologies have not been widely applied in scraper conveyors. Topology optimization, as the most reliable method for achieving structural light weighting [10,11], has been widely verified and applied in fields such as aerospace [12,13]. In order to better apply topology optimization technology to actual production, how to better combine topology optimization with the actual production process and achieve the integration of design and manufacturing, as well as how to further improve the efficiency and accuracy of multi-objective optimization algorithms and achieve more complex multi-objective trade-offs, and other research, has become a new hotspot in the current field of topology optimization [14,15]. Applying topology optimization technology to scrapers holds the promise of reducing the no-load energy consumption of the chain drive system of scraper conveyors and promoting low-carbon coal mining [16].

To address the issue of excessive mass in the chain drive system of the scraper conveyor, this paper conducts lightweight research from two aspects: first, reducing the number of scrapers by optimizing the scraper spacing; second, lowering the structural mass of the scrapers themselves through topological optimization. While ensuring the conveying capacity and structural strength of the scraper chains, this approach reduces their mass, thereby lowering the no-load energy consumption of the chain drive system. This study provides guidance for the design of long-distance and low-energy-consuming scraper conveyors in the future.

2. Optimization of Scraper Spacing

2.1. Mining Scraper Conveyors Chain Drive System

Figure 1 shows that the chain drive system of the scraper conveyor consists of scrapers, a round-link chain, and sprockets. The scrapers are relatively fixed to the round-link chain and are collectively known as scraper chains. When the scrapers move synchronously with the chains, they provide thrust to the coal on the middle trough, thereby achieving coal transportation [17]. Currently, the distance La between adjacent scrapers is usually an integer multiple of the chain link pitch. To ensure the conveying capacity of the scraper conveyor, the distances between adjacent scrapers are kept equal and relatively small, which results in a large number of scrapers being attached to the chain. This configuration significantly increases the no-load running resistance of the chain drive system of the scraper conveyor [18]. The total mass (M_a) of the scrapers of a scraper conveyor with a length (L) can be calculated as follows:

$$M_a={\displaystyle \frac{2L}{L_a}}M$$

(1)

where M is the mass of the scraper, kg; L_a is the spacing between adjacent scrapers, m.

There are two ways to reduce the total mass of the scrapers in the chain drive system:

(1)

Increasing the spacing between adjacent scrapers;

(2)

Reducing the mass of the scrapers.

The spacing between the scrapers of a scraper conveyor is typically around 1 m. Changes in this spacing directly affect the conveying capacity of the scraper chains. To address this, we employ the DEM analysis to optimize both the spacing and arrangement of the scrapers. Under the constraint of maintaining the conveying capacity, we aim to alter the combination form of the scraper spacing. This adjustment indirectly increases the average spacing between adjacent scrapers. As a result, the number of scrapers used in the chain drive system is reduced.

2.2. Scraper Spacing Optimization Scheme

The SGZ1000 scraper conveyor with a length of 400 m is taken as an example. The matching round-link chain has a specification of 56 × 187 mm. Each scraper weighs 88.3 kg. There are six chain links pitched between adjacent scrapers, and the scrapers’ spacing is 1.122 m. Figure 2a shows that the spacing between adjacent scrapers is evenly distributed, representing the conventional arrangement method of scrapers in current scraper conveyors. This paper proposes increasing the average spacing between scrapers by optimizing the combination form of the scraper spacing. Figure 2b,c demonstrate non-uniform spacing combination schemes that group scrapers into groups of three, thereby increasing the average spacing between scrapers.

A simulation model of the scraper conveyor’s material conveying capacity is established using the DEM to analyze changes in conveying capacity under different scraper arrangement schemes. The scraper spacing schemes are detailed in

Table 1. Scraper spacing combination schemes.

Combination Scheme	Scraper Spacing 1	Scraper Spacing 2	Scraper Spacing 3
1	4p	6p	10p
2	4p	10p	6p
3	6p	4p	10p
4	6p	10p	4p
5	10p	4p	6p
6	10p	6p	4p
7	6p	8p	6p
8	6p	6p	8p
9	8p	6p	6p
10	4p	8p	8p
11	8p	4p	8p
12	8p	8p	4p

.

2.3. Conveying Capacity Under Different Schemes

Figure 3 shows the simulation model, which consists of a middle trough, scraper chains, a coal guard plate, and piled bulk coal. The coal guard plate is designed to provide support for the piled bulk coal, preventing it from spilling beyond the middle trough. First, a large volume of coal is piled in the middle trough. Then, different scraper spacing combination schemes are selected to simulate the transportation of coal materials. To ensure consistency across different simulation schemes, the following parameters are controlled to be the same: the number of chain links, the number of scrapers, the initial position of the scraper chains, the moving speed of the scraper chains, and the moving distance. The parameter settings of the simulation model are listed in

Table 2. Parameter settings of the simulation model.

Parameter Settings of the Simulation Model	Value
The width of the middle trough	1000
The length of the middle trough (mm)	12,000
The speed of the scraper chain (m/s)	1.5
Chain specification (mm)	56 × 187
Coal particle diameter (mm)	20
Total mass of piled bulk coal (kg)	1767
Static friction coefficient between coal and coal	0.42
Coefficient of kinetic friction between coal and coal	0.11
Static friction coefficient between coal and metal	0.53
Coefficient of kinetic friction between coal and metal	0.31

.

The coal particle density in the simulation model is 1340 kg/m³, the coal particle radius R = 10 mm, the elastic modulus is taken as 1.6 GPa, and the Poisson’s ratio is 0.25 [19]. The contact effect between coal particles uses the Hertz–Mindlin model. The discrete element simulation mesh size is taken as 2R, with a total of 305,613 grids.

The scraper chains with equal scraper spacing (6p-6p-6p) were taken as the control group. According to the simulation model in Figure 3, the movement speed and state distribution of coal particles at different times during the process of the scraper chain moving from one end of the middle trough to the other are simulated.

Their simulation results are shown in Figure 4a–d, which correspond to the 5th, 7th, 9th, and 13th seconds of the simulation model, respectively. At the 5th second, the scraper chains traversed the piled bulk coal and propelled the coal particles forward using the scrapers. When the amount of coal particles exceeded the conveying capacity of the scraper chains, some coal particles slid to both sides of the middle trough as the scraper chains moved. At the 13th second, the scraper chains completely disengaged from the middle trough, leaving the remaining coal particles, which exceeded the maximum conveying capacity of the scraper chains, on the middle trough. Based on this simulation process, simulation calculations were conducted for 12 groups of scraper chain schemes.

Following the completion of the simulation, the mass variation curves of the coal particles were compared across different conveying schemes. The conveying capacity of the different scraper chain schemes was evaluated based on the final residual mass of the piled bulk coal within the same conveying time.

The simulation results for different scraper chain schemes are shown in Figure 5. During the period from the 9th to the 13th second, the scraper chains gradually disengaged from the middle trough, and the mass of the remaining coal particles on the middle trough declined steadily. Once the scraper chains had completely left the middle trough, the mass of the remaining coal particles remained constant. Based on the initial and final coal particle masses in the trough, the conveyor efficiency ratios (K) for the different scraper chain schemes were calculated.

$$K=(m_1-m_2)/m_1$$

(2)

where m₁ is the mass of the initial coal, kg; m₂ is the mass of the end coal, kg.

Material conveying simulation was conducted for different scraper spacing combination schemes in Table 1, and the variation law of material mass with time under different scraper spacing combination schemes was compared. When the scraper chain in the simulation model detaches from the middle trough, the coal particles pushed by the scraper chain fall off the middle trough, and the mass of the coal particles in the simulation model decreases. Initially, the total mass of coal particles in different models is equal. After being conveyed by different combinations of scraper chains, the remaining mass of coal particles varies. The conveying capacity of the scraper is analyzed based on the remaining mass of coal particles. In Figure 5a, the combination scheme 1–6 corresponds to the simulation results of different scraper combination spacings from groups 1 to 6 in Table 1. In Figure 5b, combination scheme 7–12 corresponds to the simulation results of different scraper combination spacings from groups 7 to 12 in Table 1.

The overall coal conveying capacity of these scraper chain schemes is lower than that of the control group. Schemes 7 and 8, arranged with different combination spacings of 6p, 6p, and 8p, show stable fluctuations in coal conveying capacity between 10 and 12 s, with an overall capacity higher than that of the control group. Schemes 9–12, arranged with different combination spacings of 4p, 8p, and 8p, demonstrate relatively stable fluctuations in coal conveying capacity between 10 and 12 s. Some of these schemes performed better than the control group, while others performed worse.

The simulation results, which were statistically analyzed, are shown in

Table 3. Analysis of simulation results.

Combination Scheme	Residual Mass (kg)	Conveying Ratio (%)
1	1053.32	40.4
2	1030.17	41.7
3	1044.17	40.9
4	1014.13	42.6
5	1011.44	42.8
6	1002.82	43.3
7	980.58	44.5
8	987.19	44.1
9	982.03	44.4
10	1016.60	42.5
11	1012.22	42.7
12	983.38	44.3

. Initially, the mass of coal particles in the middle trough was 1767 kg. At the end of the simulation for the control group, the mass of the remaining coal particles was 991.58 kg. After being conveyed by the scraper chains, its mass was reduced by 43.9%. The comparison results show that the scraper chains of Scheme 7 are the optimal scheme. The comparison results of the conveying capacity with the control group are shown in Figure 6a,b. At the end, the mass of the remaining coal particles was 980.58 kg, and their mass was reduced by 44.5%, which demonstrates better performance than the control group.

This scheme improves the average spacing of the scrapers while ensuring the conveying capacity of the scraper chains. The scraper spacing of the scraper chains in Scheme 7 is 6p-8p-6p. Compared with the original scraper chains with an equal spacing of 6p, the average scraper spacing is increased by 11.11%. The total mass of the scrapers in the original scraper conveyor was 62,959.0 kg. After changing the scraper spacing, the total mass of the scrapers was reduced by 6995.4 kg. The effect of reducing the mass of the chain drive system by optimizing the spacing of the scrapers is obvious.

On the other hand, the chain of the scraper conveyor is of a large mass. When installing the chain underground, hundreds of meters of chain are composed of numerous small sections of chain joined together through connecting links. Now, the small sections of the scraper chain before leaving the factory have been changed to a non-uniform arrangement and are still connected through connecting links, which will not cause problems in the installation and maintenance of the scraper chain. The tensioning of the chain is achieved by the tensioning cylinder pushing the tail sprocket. The meshing transmission form between the sprocket and the chain link remains unchanged, and the tensioning adjustment method of the chain remains the same. The non-equal spacing arrangement of the scrapers will not affect the meshing transmission process of the chain or the tensioning adjustment of the chain drive system.

3. Topological Optimization

3.1. Determine the Scraper Load

By optimizing the scraper spacing, the number of scrapers in the chain drive system of the scraper conveyor is indirectly reduced, while the mass of each individual scraper remains unchanged. To further reduce the no-load mass of the chain drive system, a topological optimization method is proposed to improve the scraper structure and reduce the self-mass of the scrapers. To determine the load and constraint conditions during the topological optimization of the scraper, a scraper conveying load model was established. Figure 7 shows that the scraper mainly bears the coal-pushing resistance along the movement direction and the pressure of a part of the coal material falling above the scraper. The magnitudes of both loads are related to the height of the piled bulk coal [20].

Determine the maximum average height (h) of the piled bulk coal on the middle trough based on the maximum conveying capacity (Q) of the scraper conveyor:

$$Q=3.6Bhv\gamma$$

(3)

where B is the length of the scraper, m; v is the running speed of the scraper chains, m/s; and γ is the density of the piled bulk coal, kg/m³.

According to the spacing between adjacent scrapers, the coal-pushing mass (M_c) of a single scraper can be calculated as follows:

$$M_c=B{L}_{a}h\gamma$$

(4)

Correspondingly, the coal-pushing resistance (F_c) and the pressure (F_s) of the piled bulk coal on the scraper are respectively:

$$F_c=\mu M_{c}g$$

(5)

$$F_s=\gamma B(h-c)bg$$

(6)

where μ is the friction coefficient between the coal and the middle trough; c is the height of the scraper, m; b is the width of the scraper, m; and g is the acceleration due to gravity, m/s².

Figure 8 illustrates that the scraper in the scraper conveyor consists of an upper scraper and a lower scraper. The upper scraper serves as the primary load-bearing component, primarily responsible for coal-pushing resistance, while the lower scraper is mainly used for nut installation. Both the upper and lower scrapers are mounted onto the flat ring through bolt connections. Typically, the mass of the upper scraper is significantly greater than that of the lower scraper; therefore, the upper scraper is selected for topological optimization.

The SGZ1000 scraper conveyor has a conveying capacity of 3000 t/h, featuring a round link chain with a specification of 56 × 187 mm and a scraper with a specification of 985.8 × 116.0 × 180.6 mm. Calculations revealed that when the pitch of a single scraper is set to 8p, the corresponding coal-pushing resistance is 4293.7 N, and the pressure exerted by the coal on the scraper is 456.9 N. These values are utilized as the load constraint conditions for the scraper, and structural topological optimization is conducted to minimize the overall mass of the scraper.

3.2. Scraper Topological Analysis

Topology optimization is an advanced structural optimization design method that primarily determines the optimal material distribution within a given design space under constraints such as loads and boundary conditions, using mathematical algorithms. The basic principle of topology optimization involves discretizing the structure into a finite number of elements and employing optimization algorithms to continuously remove material units that contribute less to structural performance while retaining those that are critical to performance. This ensures that the structure achieves its target performance while satisfying various constraints. Applying topology optimization technology to the scraper of a mining scraper conveyor can help improve the scraper structure and reduce its mass.

The commonly used topological optimization methods at present include the homogenization method, variable density method, level set method, etc. Among them, the homogenization method is one of the earliest proposed topological optimization methods, which was born in the 1980s. Both the variable density method and the level set method are improvements based on this method. The variable density method has a mature algorithm and is widely used in industry, supported by rich cases and experience. This paper selects the variable density method to conduct topological optimization analysis on the scraper structure. Different lightweight targets are selected to perform topological analysis on the upper scraper. The topological results are presented in Figure 9. The finite element analysis of the scraper was carried out by using ANSYS 2019 simulation analysis software, and the structural topology of the target scraper was optimized according to the simulation structure. The finite element model of the scraper used tetrahedral mesh elements with a mesh size of 5 mm, totaling 484,169 nodes. The mesh model of the scraper is shown in Figure 9. Figure 10 shows the load constraint model of the scraper. The chain link is in coordination with the chain link hole of the scraper and is relatively fixed to the chain link through the pre-tightening force of the bolts. The arc surface of the chain link hole of the scraper is set with a fixed constraint, and the coal pushing side of the scraper is set with a load constraint.

Different lightweight targets were selected to conduct topological analysis on the upper scraper. The topological results are shown in Figure 11a–f. As the mass ratio of the topological structure to the original structure decreases, the difference between the topological scraper and the original structure gradually increases. Compared with the original structure, the topological scraper has significantly removed the non-contact surface of the scraper while retaining the main load-bearing surface and installation position. It still maintains the ability to push coal with the scraper.

3.3. Optimization of the Scraper’s Topological Structure

Considering the dynamic load effect of the scraper conveyor, the lightweight design of the scraper is not suitable for being too extreme. Generally, topology optimization can achieve a weight reduction of 20% to 30% in the initial design stage without significantly sacrificing structural performance [21]. Therefore, for the scraper’s topological optimization, a conservative approach is adopted, aiming to reduce its mass by 25%. The corresponding topologically optimized structure of the scraper is shown in Figure 12.

The structure obtained from topological optimization features a large number of irregular surfaces, which cannot be directly utilized due to the limitations of traditional processing methods and the high costs associated with mass production. Consequently, further optimization of the scraper after topological optimization is necessary. Using 3D software, the structure is optimized based on the original design and the results of topological analysis. Non-essential structures are removed, and the geometry in different regions is adjusted. The optimized topological structure of the scraper is shown in Figure 13. Compared to the structure from topological analysis, the optimized scraper has a flatter overall design while retaining all key features of the topological structure and improving machinability.

Compared to the original scraper before optimization, the mass is reduced by 23.5%. The total mass of a single scraper decreases from 78 kg to 64 kg, resulting in a 17.9% reduction in mass. This light-weighting demonstrates significant effectiveness.

At present, scrapers are mainly produced by casting. This paper analyzes the areas where materials can be removed through topological optimization and optimizes the structure of the scraper. The optimized scraper has a simple structure and can be processed and manufactured by existing CNC machines or by casting. Compared with the mechanical processing cost of the scraper, the electricity cost of the no-load energy consumption of the chain drive far exceeds the production cost of the scraper. The optimized scraper has extremely strong feasibility for process implementation. The optimized scraper does not affect the meshing transmission process of the chain drive system. During the actual operation of the scraper, the upper part mainly bears the coal pushing load, which is far less than the load-bearing capacity of the scraper. The lower scraper comes into contact with the middle trough and wears out. This paper conducts topological optimization on the upper scraper, which has a minimal impact on the wear life of the scraper.

3.4. Strength Analysis of the Topological Scraper Structure

Mechanical response analyses were conducted on the scrapers before and after topological optimization. Figure 14 shows that under the same load and constraint conditions, the deformations of the original scraper and the topologically optimized scraper were 0.0052 mm and 0.0075 mm, respectively. The relatively small deformation values indicate sufficient rigidity and resistance to external forces, ensuring structural stability. Typically, topological optimization removes materials that contribute less to the structural mechanical properties to achieve weight reduction. However, this process may decrease the local stiffness of the structure, leading to increased deformation under the same load [22]. The primary function of the scraper is to push materials, and the requirement for deformation accuracy of the scraper itself is not stringent. In this case, the difference in deformation of the topologically optimized scraper has minimal impact on the normal operation of the entire system and can be considered negligible.

Figure 15 shows that the maximum equivalent stresses of the original scraper and the topologically optimized scraper were 5.39 MPa and 12.19 MPa, respectively. The equivalent application comparison of the two scrapers under the same boundary constraints and the same action load. Both values were significantly lower than the material’s yield stress of 236 MPa. Although the maximum equivalent stress of the topologically optimized scraper increased, it remained within the safe range relative to the material’s bearing capacity. The structural performance of the topologically optimized scraper satisfies the actual requirements.

4. Discussion

For a 400 m scraper conveyor, arranging scrapers at an equal spacing of 6p requires 713 scrapers. When using topologically optimized scrapers, the no-load mass of the chain drive system can be reduced by 11,269.5 kg.

If scrapers are arranged at an uneven spacing of 6p-8p-6p, only 641 scrapers are needed, which is 72 fewer than the equal-spacing arrangement. This reduction in the number of scrapers results in a mass reduction of 6357.6 kg. When using topologically optimized scrapers, the mass of the scrapers can be further reduced by 10,131.4 kg. Compared to the pre-optimization state, the no-load mass of the chain drive system is reduced by a total of 26.2%, thereby significantly lowering the no-load energy consumption of the long-distance scraper conveyor.

5. Conclusions

(1)

Through DEM analysis, the conveying capacities of scraper chains under different scraper spacing combination schemes were compared. It was found that for the chain of the 56 × 187 mm specification, the non-equal spacing arrangement of 6p-8p-6p for scrapers is superior to the equal spacing arrangement of 6p. This arrangement increases the average spacing of scrapers while ensuring the conveying capacity of the scraper chains, and reduces the number of scrapers by 11.11% for scraper chains of the same length.

(2)

Through topological optimization of the scraper structure, the total mass of a single scraper is reduced by 17.9%. Compared with the original scraper, under the same load and constraint conditions, the deformation displacement and equivalent stress of the topologically optimized scraper will increase. However, relative to the bearing capacity of the material, they are still within the safe range, and the structural performance of the topologically optimized scraper can meet the actual requirements.

(3)

By adopting a non-equal spacing scraper arrangement and topologically optimized scrapers, the no-load mass of the chain drive system of a 400 m scraper conveyor can be reduced by 26.2%. This significantly reduces the no-load energy consumption of the long scraper conveyor, providing guidance for the future design of long-distance and low-energy-consumption scraper conveyors.