Material taking machine luffing mechanism hinge point design method based on improved particle swarm optimization
By improving the particle swarm optimization algorithm to optimize the hinge position of the luffing mechanism of the scraper reclaimer, the problems of low design efficiency and large limitations were solved, the wire rope tension was minimized, and the design process became more efficient and accurate.
Patent Information
- Application Number
- CN202511347484.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-19
- Publication Date
- 2025-11-07
AI Technical Summary
The existing scraper reclaimer's variable amplitude mechanism design is inefficient and has significant limitations, requiring repeated trials to find the optimal solution.
An improved particle swarm optimization algorithm is adopted. By establishing a mathematical model and force equations for the luffing mechanism of the scraper reclaimer, the hinge point position is optimized. The coordinates of hinge points B and C are optimized using the improved particle swarm optimization algorithm to minimize the wire rope tension. Combined with boundary and geometric constraints, a fast and efficient design is achieved.
The design minimizes the tension of the wire rope in the luffing mechanism of the scraper reclaimer, making the design process more efficient and accurate. The optimized hinge point position reduces the maximum tension of the wire rope by 30%.
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Figure CN120911301A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The application belongs to the technical field of transport equipment in the bulk material transportation industry, and particularly relates to a reamer-variable mechanism hinge point design method based on an improved particle swarm algorithm BACKGROUND
[0002] The reamer is widely used in the bulk material transportation industry such as coal, chemical industry, metallurgy and electric power. The reamer has the characteristics of large weight, high technical integration, flexible application scene and many design variables, and the design of the variable mechanism is one of the most critical problems in the overall design of the reamer. In the past, the design of the variable mechanism mostly adopted the method of engineering experience combined with finite element modeling simulation, which would have the phenomenon of low design efficiency, great limitation and unreasonable design. With the continuous development of intelligent algorithms, a large number of intelligent algorithms are applied to the traditional design industry. The optimal scheme that the design personnel used to find through repeated tests can now be quickly calculated with the help of intelligent algorithms and the rapid calculation ability of computers, so that the design process is more efficient and accurate. SUMMARY
[0003] The technical problem to be solved by the application is that the design of the variable mechanism in the past mostly adopts the method of engineering experience combined with finite element modeling simulation, which would have the phenomenon of low design efficiency, great limitation and unreasonable design. With the continuous development of intelligent algorithms, a large number of intelligent algorithms are applied to the traditional design industry. The optimal scheme that the design personnel used to find through repeated tests can now be quickly calculated with the help of intelligent algorithms and the rapid calculation ability of computers, so that the design process is more efficient and accurate.
[0004] The purpose of the application is achieved in the following manner: A reamer-variable mechanism hinge point design method based on an improved particle swarm algorithm, The method comprises the following steps: S1: according to the working principle of the reamer and the positions of the hinge points, a mathematical model of the variable mechanism of the reamer is established, and a hinge point force equation is established according to the force conditions of the hinge points; wherein the hinge points include three hinge points, namely hinge point A, hinge point B and hinge point C; the hinge point A is a variable rotation point of the reamer arm, the hinge point B is a position point of the gantry fixed pulley, and the hinge point C is a position point of the upper movable pulley of the reamer arm; S2: list the related parameter equations, determine the related parameters according to the actual demand and working conditions, take the size of the steel wire rope tension of the variable mechanism as the objective function, take the coordinates B(x, y) of the hinge point B and the horizontal coordinate x of the hinge point C as the design variables, take the coordinate point boundary limit and the geometric limit of the mathematical model as the constraint conditions, and obtain a multivariable equation with the minimum value of the steel wire rope tension as the objective function, S3: coordinates of the hinge point B (Bx, By), the horizontal coordinate of the hinge point C (Cx), and the angle between the line connecting the hinge points B and C and the scraper arm member (θ) are determined. , , The three parameter values are used as initial design values, and the improved particle swarm optimization algorithm is used to optimize the three parameter values to determine the optimal values of the three parameters.
[0005] The step 1 specifically comprises: S1.1: according to the working principle of the scraper reclaimer, the luffing mechanism is simplified, the coordinates of the hinge point A are set as the origin coordinates, and the coordinates of each hinge point are respectively A (Ax, Ay), B (Bx, By), C (Cx, Cy), the angle between the line connecting the hinge points B and C and the scraper arm member is denoted as θ, and the angle between the scraper arm and the horizontal reference line is denoted as φ; the initial position of the scraper is set as horizontal, and when the hinge point C rotates around the fixed hinge point A, the new coordinates of the hinge point B are Bx = Ax + L cos φ, By = Ay + L sin φ, and the new coordinates of the hinge point C are Cx = Ax + L cos (φ + θ), Cy = Ay + L sin (φ + θ). , , , , , , , , , S1.2: according to the force condition in the working of the scraper reclaimer, a force diagram of the luffing mechanism is established, the horizontal component of the force acting on the hinge point A is Fx, the vertical component is Fy, the force acting on the luffing wire is T, the weight of the scraper is G, the bending moment of the weight of the scraper arm on the hinge point A is M, and the force equation of the hinge point is Fx = T cos θ - M sin θ, Fy = T sin θ + M cos θ. , , , , , .
[0006] The step 2 specifically comprises: S2.1: an equation of the related parameters is established; , , , , , , , , , , , , Distance from hinge point A to hinge point B, Distance from hinge point A to new coordinate after rotating a certain angle Distance from hinge point A to new coordinate after rotating a certain angle Distance from hinge point A to new coordinate after rotating a certain angle Distance from hinge point A to new coordinate after rotating a certain angle Using hinge point coordinate angle method to solve , Value is: Angle value of the scraper arm and the line connecting hinge points A and B, Angle value of the scraper arm and the line connecting hinge points B and C; Based on the above equations, now there are parameters, , , , , G, Accordingly, the force on the steel wire rope of the scraper mechanism is: S2.2 Determine the objective function: The weight of the scraper arm G is calculated according to the design output, Half of the length of the scraper arm, determined according to the design yard width, the amplitude angle of the scraper arm Changes with work, The range is usually obtained according to the material accumulation angle and design requirements, and the coordinate of hinge point A is set as the origin coordinate, then =0, =0, the initial position of the scraper is horizontal, so the horizontal coordinate of hinge point C =0, so ， ， ，G， ， Not as a design variable, finally get the minimum value of the target function of the amplitude mechanism steel wire rope tension: , From the above formula, now there are three variables that affect the objective function, respectively, the coordinate of hinge point A , the horizontal coordinate of hinge point C, optimizing these three key parameters can get the minimum value of the steel wire rope tension, therefore, select these three parameters as the design variables of this method, the expression is: S2.3: determining constraint conditions; S2.3.1: boundary constraint condition Since the hinge point B is on , It has a boundary itself, so the hinge point B coordinate Also has upper and lower limit boundaries, and for the same reason, the hinge point C horizontal coordinate also has upper and lower limit boundaries on the scraper arm, and the constraint formula can be expressed as: S2.3.2: geometric constraint condition: According to the simplified geometric model of the amplitude changing mechanism, through the three-edge limiting relationship, the constraint formula is obtained as: .
[0007] The S3 specifically comprises: Initialize the particle swarm parameters, set the particle swarm size and the maximum number of iterations; Initialize the random position and speed of each particle; Calculate the fitness of each particle; Get the individual optimal value of the particle And the group optimal value of the particle ; Improve the particle swarm algorithm, update the inertia weight and the learning factor; this method adopts adaptive inertia weight, dynamically adjusts According to the current optimal solution , which is set by the following formula: In order to balance the ability before and after the learning factor, Set it as a function that decreases with iteration, Set it as a function that increases with iteration, expressed as: Update the position and speed of each particle; Compare the current And Update the group optimal value of the particle ; Meet the set conditions, the particle reaches the global optimum or reaches the maximum number of iterations, output the result.
[0008] The beneficial effects of the present application: under certain design conditions, the present application takes the minimum value of the steel wire rope tension of the scraper reclaimer amplitude changing mechanism as the objective function, can quickly obtain the hinge point geometric coordinate value, and has high accuracy through verification, is a reliable and effective hinge point position design optimization method of the scraper reclaimer amplitude changing mechanism. BRIEF DESCRIPTION OF DRAWINGS
[0009] Figure 1 is a schematic diagram of a scraper reclaimer.
[0010] Figure 2 is a mathematical model analysis diagram of the luffing mechanism of the scraper reclaimer.
[0011] Figure 3 is a mechanical analysis diagram of the luffing mechanism of the scraper reclaimer.
[0012] Figure 4 is a flow chart of the design method.
[0013] Figure 5 is a comparison diagram of the calculation of the standard particle swarm algorithm and the calculation of the improved particle swarm algorithm.
[0014] Figure 6 is a comparison diagram of the tension of the luffing steel wire rope of the scraper reclaimer before and after optimization.
[0015] Among them, 1 is a fixed end walking system; 2 is a portal frame; 3 is a scraper mechanism, 4 is a luffing mechanism, and 5 is a swing end walking system. DETAILED DESCRIPTION
[0016] The present application will be further described in detail below in conjunction with the drawings and specific embodiments.
[0017] It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same technical meaning as understood by those skilled in the art to which the present application belongs.
[0018] The present application provides a luffing mechanism hinge point design method for a reclaimer based on an improved particle swarm algorithm, comprising the following steps: S1. Establishing a mathematical model and a mechanical analysis model of the luffing mechanism of the scraper reclaimer; according to the working principle of the scraper reclaimer and the positions of the hinges, a mathematical model of the luffing mechanism of the scraper reclaimer is established and a hinge force equation is established according to the force conditions of the hinges; wherein the hinges include three hinges, which are hinge A, hinge B and hinge C; hinge A is the luffing rotation point of the scraper arm, hinge B is the position point of the fixed pulley of the portal frame, and hinge C is the position point of the movable pulley on the scraper arm; S1.1 According to the working principle of the scraper reclaimer, the luffing mechanism is simplified, the coordinate of A hinge point is set as the origin coordinate, and the coordinates of the hinge points are respectively: A (0, 0, 0), B (L, 0, 0), C (L, H, 0), wherein L is the length of the scraper arm, and H is the height of the scraper arm; the value of the included angle between the line connecting hinge B and hinge C and the scraper arm component is denoted as , the angle between the scraper arm and the horizontal reference line is denoted as , the initial position of the scraper is horizontal, when the hinge point C rotates around the fixed hinge point A, the new coordinates are: S1.2 According to the force condition in the working of the scraper reclaimer, the horizontal component of the force acting on the hinge point A is , the vertical component is ; the force of the luffing wire is , the weight of the scraper is G; the bending moment of the weight of the scraper arm on the hinge point A is ; the force equation of the hinge point is obtained as: .
[0019] S2. Determine the objective function: S2.1 Establish the equation of the relevant parameters; Use the formula for calculating the area of a triangle to obtain as: is the tension of the wire to the hinge point; According to the coordinates of the hinge points A, , B, the distance method is used to solve , , The value of is: where, is the distance from the hinge point A to the hinge point B, is the distance from the hinge point A to the new coordinate after rotating a certain angle, is the distance from the hinge point A to the new coordinate after rotating a certain angle; Using the hinge point coordinate angle method, we get , The value of is: is the angle value of the scraper arm and the line connecting the hinge points A and B, is the angle value of the scraper arm and the line connecting the hinge points B and C; Combining the above equations, we now have parameters, , Accordingly, the force of the steel wire rope of the scraper mechanism is:
[0020] S2.2 Determine the objective function; The self-weight G of the scraper arm is calculated according to the designed output, is half of the length of the scraper arm, which is determined according to the designed width of the stockyard, and the amplitude angle of the scraper arm changes with the work, and the amplitude angle is usually determined according to the material accumulation angle and design requirements, and the origin coordinate is set as the coordinate of the A hinge point, then =0, =0, the initial position of the scraper is horizontal, so the horizontal coordinate of the C hinge point =0, so ， ， ，G， ， Without being designed as a variable, the objective function of the minimum value of the steel wire rope tension of the amplitude mechanism is finally obtained: From the above formula, there are now three variables that affect the objective function, which are the coordinates of the hinge point B , the horizontal coordinate of the hinge point C, and the optimization of these three key parameters can obtain the minimum value of the steel wire rope tension, therefore, the three parameters are selected as the design variables of the method, and the expression is: S2.3 Determine the constraint condition; S2.3.1 Boundary constraint condition Since the hinge point B is on the , it has a boundary itself, so the coordinates of the hinge point B also have upper and lower limit boundaries, and the horizontal coordinate of the hinge point C also has upper and lower limit boundaries on the scraper arm, and the constraint formula can be expressed as: S2.3.2 Geometric constraint condition: According to the simplified geometric model of the amplitude mechanism, the constraint formula is obtained through the three-edge limiting relationship:
[0021] S3: Apply improved particle swarm optimization algorithm to optimize the hinge point position.
[0022] S3.1 Algorithm principle Now the general PSO algorithm mathematical model can be expressed as: in a D-dimensional space, a group of N particles form a group, fly at a certain speed, each particle moves its position when searching, and its speed is constantly updated. The particles gradually approach the optimal position, and finally tend to the optimal solution. The space position of the ith particle is represented by the formula The velocity of the ith particle is represented by the formula The optimal solution of the ith particle is represented by the formula The optimal solution of the entire group is represented by the formula When the particle i is updated to the t generation, its position and velocity are updated using the following formula: + The current generation particle i historical global optimal position is represented by the formula The current generation particle i historical optimal position is represented by the formula The inertia weight is represented by the formula Two random numbers between 0 and 1. Prevent particles from crossing the maximum search boundary during algorithm iteration, set the maximum particle speed, the current time particle speed in a certain dimension After updating, the maximum speed is exceeded The current speed is limited to .
[0023] S3.1 Algorithm steps Initialize particle swarm parameters, set particle swarm size and maximum iteration number; Initialize the random position and speed of each particle; Calculate the fitness of each particle; Get the individual optimal value of the particle And the group optimal value of the particle ; Improved particle swarm algorithm, update inertia weight and learning factor; this method uses adaptive inertia weight, which dynamically adjusts According to the current optimal solution, set it by the following formula: To balance the ability of learning factors before and after, set As a function of iteration decreasing, Set as a function of iteration increasing, represented as: updating the position and velocity of each particle; comparing the current and updating the population optimal value of the particle ; satisfying the set condition, the particle reaches the global optimum or reaches the maximum iteration number, and the result is output.
[0024] Embodiment: According to the actual use condition, the value of non-optimized parameter and the initial key parameter of improved particle swarm algorithm are determined.
[0025] (1) The working conditions and design parameters of the scraper reclaimer of Huadian Pingjiang Power Plant are selected in this paper, among which the key parameters such as the length of the scraper arm, the weight of the scraper, and the amplitude angle can be set by the designer. The A hinge point is (x0, y0), the B hinge point is (x1, y1), and the C hinge point is (x2, y2). The initial parameters of the improved particle swarm algorithm are set, and the designer reasonably sets them according to the difficulty of problem solving. All parameter settings are shown in the following table: =0, =0), and the longitudinal coordinate of the C hinge point is =0. The initial parameters of the improved particle swarm algorithm are set, and the designer reasonably sets them according to the difficulty of problem solving. All parameter settings are shown in the following table: (2) According to the working principle and mathematical simplified model of the amplitude mechanism of the reclaimer, the following formulas are obtained: (1) (2) (3) According to the force condition and force diagram of the amplitude mechanism of the reclaimer, the following formulas are obtained: (4) According to the hinge point position relationship of the reclaimer, the hinge point distance formula, and the hinge point angle formula, the following formulas are obtained: wherein, is the distance from the hinge point A to the hinge point B, is the distance from the hinge point A to the new coordinate after rotating a certain angle, is the distance from the hinge point A to the new coordinate after rotating a certain angle; is the angle value of the scraper arm and the line connecting the hinge points A and B, The angle value of the scraper arm and the connecting line of hinge points B and C.
[0026] (5) The target function with the steel wire rope tension as the optimization objective is obtained according to the above formula, and the expression is: , Where the scraper length = 2 , the scraper weight is G , the amplitude angle , and other key parameters can be set by the designer, the A hinge point is =0, =0, and the C hinge point longitudinal coordinate =0.
[0027] Then the target function with the steel wire rope tension as the minimum value is obtained: , , Where the design optimization variables are the coordinates of the hinge point B , and the horizontal coordinate of the hinge point C , which can be expressed as: (6) Determine the constraint conditions: including boundary constraints and geometric constraints.
[0028] Boundary constraints: , Geometric constraints: (7) Determine the main parameters and main improvement methods of the improved particle swarm algorithm, and solve.
[0029] (9) According to the difficulty of solving this problem, set the particle swarm size N to 35, and the iteration number is set to 50 according to experience. If it cannot be converged, increase the convergence number.
[0030] (9) Determine the inertia weight, and set the initial value to 0.8. According to the quality of the current optimal solution, dynamically adjust , adopt adaptive inertia weight, and the adjustment formula is as follows: The optimal value in the iteration t times of particles is The worst value in the iteration t times of particles is , The maximum (initial) inertia weight and the minimum (terminal) inertia weight are
[0031] (10) Determine the learning factor , The initial values are respectively set to 1.5 and 2, and then the incremental function and the decremental function are respectively used to balance the algorithm in Self-learning and Learning ability to the outside world. The function is expressed as: (11) The parameters are brought into the velocity and particle position updating formula, and the optimal solution is obtained by calculation.
[0032] The group optimal value of the entire particle swarm after iteration t times is obtained .
[0033] (12) Finally, the optimal value of the luffing mechanism hinge point position coordinates of the reclaimer is obtained, and the optimization iteration process of the improved particle swarm algorithm is shown in Figure 5 It can be seen that the optimization result starts to converge after about 20 iterations, which indicates that the initial setting parameters of the particle swarm are reasonable, and the improved particle algorithm converges faster and cannot fall into a local optimal solution. The performance of the improved algorithm is obviously improved.
[0034] (13) Result evaluation: the optimization results of the design parameters are shown in the following table, and the optimized parameters are brought into the objective function, then the results are visualized, and compared with the results of the original design parameters, it can be seen from Figure 6 that: with the increase of the luffing angle, the tension of the steel wire rope first decreases and then increases, and the maximum stress point appears when the amplitude angle is 40°, and the curves of the two remain consistent, indicating the correctness and effectiveness of the optimization calculation, and the optimized hinge point position reduces the maximum tension of the steel wire rope by 30%.
[0035] Variable / mm / mm / mm Initial value 20256 26950 31350 After optimization 23400 27500 30450 The above only describes the preferred embodiments of the present application, and it should be noted that for those skilled in the art, without departing from the overall concept of the present application, some changes and improvements can be made, which should also be considered as the protection scope of the present application.
Claims
1. A method for designing the hinge point of a reclaimer luffing mechanism based on an improved particle swarm algorithm, characterized in that: the method comprises the following steps: S1: according to the working principle of the scraper reclaimer and the positions of the hinge points, a mathematical model of the scraper reclaimer luffing mechanism is established, and according to the force conditions of the hinge points, a force equation of the hinge points is established; wherein the hinge points include three hinge points, which are hinge point A, hinge point B and hinge point C; hinge point A is the luffing rotation point of the scraper arm, hinge point B is the position point of the gantry fixed pulley, and hinge point C is the position point of the upper movable pulley of the scraper arm; the step 1 specifically comprises: S2: list the relevant parameter equation, combined with the actual demand and working conditions to determine the relevant parameters, to the amplitude of the steel wire rope tension as the objective function, to the coordinates B of the hinge point B ( , ) and the horizontal coordinate of the hinge point C These three parameters are design variables, and the coordinate point boundary limit and mathematical model geometric limit are constraint conditions. The multivariable equation with the minimum value of the steel wire rope tension as the objective function is obtained. S3: coordinates B of the hinge point B (x, y), the horizontal coordinate of the hinge point C (x), and the vertical coordinate of the hinge point C (y) , ) These three parameter values are used as initial design values, and the improved particle swarm optimization algorithm is used to optimize the three parameter values of the hinge point to determine the optimal values of the three parameters.
2. The method for retractor hinge point design of a reclaimer according to claim 1, characterized in that: the step 2 specifically comprises: S1.1: Based on the working principle of the scraper reclaimer, its amplitude changing mechanism is simplified. The coordinates of hinge point A are set as the origin coordinates, and the coordinates of each hinge point are as follows: A( , ), B ( , ), C ( , The angle between the line connecting hinge point B and hinge point C and the scraper arm component is denoted as . The angle between the scraper arm and the horizontal baseline during luffing is denoted as . With the scraper initially positioned horizontally, when hinge point C rotates angularly around fixed hinge point A, the new coordinates... The location is: S1.2: According to the force condition in the working of the scraper reclaimer, the force diagram of the luffing mechanism is established, the horizontal component force acting on the hinge point A is , the vertical component force is ; the force of the luffing steel wire rope is , the self weight of the scraper is G; the bending moment of the self weight of the scraper arm on the hinge point A is ; the hinge force equation is obtained as follows: 。 3. The method for the design of the retractor mechanism hinge point of the reclaimer according to claim 1, characterized in that: S2.1: establishing a related parameter equation; S2.2: determining a target function: Using the formula for the area of a triangle, we find that is For the tension of the wire rope The length of the perpendicular line to the hinge point; According to the hinge point A, , the coordinates of B, using the coordinate distance method to solve , , The value is: wherein, is the distance from hinge point A to hinge point B, is the distance from hinge point A to the new coordinates after rotating a certain angle, is the distance from hinge point A to the new coordinates after rotating a certain angle, is the distance from hinge point A to the new coordinates after rotating a certain angle, is the distance from hinge point A to the new coordinates after rotating a certain angle, Using the revolute joint coordinate angle method, the solution is obtained , The value is: is the angle value of the squeegee arm with respect to the line connecting the hinge points A, B, is the angle value of the squeegee arm with respect to the line connecting the hinge points B, C, Combining the above equations, now have parameters, , , , , G, , according to which the force of the scraper mechanism steel wire rope is: S2.3: determining a constraint condition; Scraper arm self-weight G, according to the design output calculation, Half of the length of the scraper arm, according to the design yard width to determine the scraper arm luffing angle With the work changes, luffing angle The range is usually according to the material accumulation angle and design requirements, and set the A hinge point coordinates as the origin coordinates, then =0, =0, the initial position of the scraper is horizontal, then the horizontal coordinate of C hinge point =0, so ， ， ，G， ， Not as a design variable, finally get the minimum value of the luffing mechanism wire rope tension objective function: ， From the above equation, there are three variables that have influence on the objective function, which are the coordinates of the hinge point B , the horizontal coordinate of the hinge point C. The minimum value of the steel wire rope tension can be obtained by optimizing these three key parameters. Therefore, these three parameters are selected as the design variables of the method, and the expression is as follows: S2.3.1: a boundary constraint condition S2.3.2: a geometric constraint condition: Since the hinge point B is on the upper side of the line itself has a boundary, so the hinge point B coordinate also has upper and lower boundary limits, and for the same reason, the hinge point C horizontal coordinate also has upper and lower boundary limits on the scraper arm, and the constraint formula can be expressed as: according to a simplified geometric model of the luffing mechanism, a constraint formula is obtained through a three-edge limiting relationship as: the S3 specifically comprises: 。 4. The method for design of the hinge point of the luffing mechanism of the reclaimer based on the improved particle swarm algorithm according to claim 1, characterized in that: initializing particle swarm parameters, setting the particle swarm size and the maximum number of iterations; initializing the random position and speed of each particle; calculating the fitness of each particle; updating the position and speed of each particle; obtaining an individual optimum value of the particle and a population optimum value of the particle ; Improved particle swarm algorithm, update inertia weight and learning factor; The method uses adaptive inertia weight, which dynamically adjusts according to the current optimal solution , is set by the following formula: To balance the learning factor before and after the ability, set a function that decreases with iterations, a function that increases with iterations, denoted as: satisfying the set conditions, the particle reaches the global optimum or reaches the maximum number of iterations, and the result is output. Comparing the current and , update the population optimal value of particles ;