A method for establishing a crank driving torque fluctuation prediction model and a prediction method

Abstract

The present application relates to a kind of crank driving moment fluctuation prediction model establishing method and prediction method.The establishment method of the prediction model is: using Lagrange equation to carry out rigid body dynamics modeling to the multi-link rod system of multi-link press;Solve when no load, the crank driving moment under different crank angular displacement of multi-link rod system in a movement cycle;Standard deviation is sought to multiple crank driving moments;Adjust the mass of each multi-link rod system component, obtain the standard deviation corresponding to crank driving moment;Establish the prediction model related to driving moment and mass parameter;According to the comparison between the results obtained from prediction model solution and simulation calculation, if the accuracy is within the error allowable range, then output prediction model.The present application can observe the slope parameter in the prediction model by establishing the prediction model, and intuitively sort the influence of component mass change on crank driving moment, to provide favorable reference for mechanical press rod system design.

Description

Technical Field

[0001] This invention relates to a method for establishing a model, and more particularly to a method for establishing a prediction model of crank drive torque fluctuation, and a method for predicting the influence of the mass of the multi-link press rod system on the crank drive torque fluctuation using the prediction model established by the method. Background Technology

[0002] The crank is a key component in the transmission system of a multi-link mechanical press. When designing a mechanical press, the driving torque on the crank must be carefully considered. The driving torque on the crank must not be too large, and the driving torque on the crank during operation must not exhibit excessive fluctuations.

[0003] Existing methods for analyzing the driving torque of a crankshaft in a mechanical press mainly include experimental and simulation methods. Experimental methods involve designing appropriate experiments, using sensors to obtain data related to the crankshaft's driving torque, and then processing this data to obtain the actual driving torque. However, experimental methods have a long data acquisition process and are time-consuming. Simulation methods utilize simulation software to build a virtual prototype model, setting kinematic pairs and constraints to simulate actual motion, and then performing simulation solutions to obtain the crankshaft's driving torque data. However, simulation methods require adjusting the target parameters and recalculating each time multiple sets of data are obtained, which is cumbersome. Existing methods can only obtain the crankshaft's driving torque data, and there is a significant workload involved when obtaining multiple sets of data under different parameters. Furthermore, existing methods cannot intuitively reflect the impact of changes in the mass of each component in the linkage system on the fluctuation of the crankshaft's driving torque, and they cannot accurately predict the changes in the fluctuation of the crankshaft's driving torque when the mass of the linkage system changes.

[0004] Therefore, it is necessary to develop a method for predicting the impact of multi-link pressure mechanism component quality on crank drive torque fluctuation. Summary of the Invention

[0005] To address the technical problem that existing methods cannot intuitively reflect the impact of changes in the mass of each component in the linkage system on the crank driving torque fluctuation, and cannot accurately predict the changes in the crank driving torque fluctuation when the linkage mass changes, this invention provides a method for establishing a crank driving torque fluctuation prediction model, and a method for predicting the impact of linkage mass on crank driving torque fluctuation in a multi-link press using the prediction model established by the above method.

[0006] This invention is implemented using the following scheme: a method for establishing a prediction model of crank drive torque fluctuation, which is a method for establishing a prediction model of the influence of the mass of each component of a multi-link press on the crank drive torque fluctuation. The method for establishing the prediction model includes the following steps:

[0007] (1) Rigid body dynamics modeling of the multi-link system of the multi-link press is performed using the Lagrange equation:

[0008]

[0009] In the formula, q is a generalized coordinate function of the configuration of the multi-link system as a function of time; Let q be the first derivative with respect to time. Let q be the second derivative of q with respect to time; n represents the total number of components in the multi-link system, starting from 1, with the first component being a crank and the last component being a slider; m i Let R be the mass of the i-th component. i Let J be the centroid coordinates of the i-th component. i Let θ be the moment of inertia of the i-th component. i Let be the angular displacement of the i-th component, g be the acceleration due to gravity, and R be the angular displacement. iy M represents the y-axis component of the centroid coordinate of the i-th component. o Let F be the driving torque of the crank, and R be the load. ny Let y be the component of the centroid coordinate of the nth component in the y-direction.

[0010] (2) Based on the parameters of the rigid body dynamics model, obtain the corresponding parameter values ​​from the multi-link press and substitute them into the rigid body dynamics model. Divide the crank angular displacement θ1 of the crank in one motion cycle into multiple equal parts, and solve for the crank driving torque X of the multi-link system under different crank angular displacements θ1 in the motion cycle when unloaded, i.e., when F = 0. k The value of k ranges from 1 to N, where N represents the number of equal divisions of the crank angular displacement θ1 during the motion cycle.

[0011] (3) The driving torque X of N cranks k Calculate the standard deviation S;

[0012] (4) Adjust the mass parameters of each component, repeat the operation of solving the crank driving torque and its standard deviation in steps (2) and (3) to obtain multiple sets of mass parameters and their corresponding standard deviations of crank driving torque;

[0013] (5) Establish a prediction model s for the relationship between crank drive torque and mass parameters using a multiple linear regression model:

[0014]

[0015] In the formula, Let β be the mass variable of member i in the multi-link system, and β0 be the intercept of the multiple linear regression model; βi The slope parameter of the multiple linear regression model corresponding to the quality of the i-th component is calculated using the following formula:

[0016] [β0β1…β i ] T =(G T G) －1 G T S'

[0017] G is a matrix arrangement of multiple sets of quality parameters, and S' is a standard deviation matrix composed of the standard deviations S of the crank driving torque corresponding to multiple sets of quality parameters in step (4).

[0018] (6) Take the known Will The solution obtained by substituting the prediction model s is compared with the result obtained by simulation calculation to verify its accuracy. If the accuracy is within the allowable error range, the prediction model is output; otherwise, return to step (4).

[0019] This invention also provides a method for predicting the influence of the linkage mass on the crank drive torque fluctuation of a multi-link press, the prediction method comprising the following steps:

[0020] (1) The crank driving torque fluctuation prediction model is established using the above-mentioned method.

[0021] (2) The mass of each component of the linkage is brought into the crank driving torque fluctuation prediction model to predict the crank driving torque fluctuation.

[0022] Compared with the prior art, the beneficial effects of the present invention are:

[0023] (1) In this invention, the mechanical press rod system is mathematically modeled. By processing the model in a program, the driving torque data of the mechanical press crank can be obtained conveniently and quickly. Compared with the experimental method, it is more efficient and convenient.

[0024] (2) In this invention, by modifying the parameters in the model program, multiple sets of crank driving torque data associated with the mass parameters of different rod components can be obtained at once. Compared with ADAMS, which modifies the mass parameters sequentially and performs simulation calculations, this method is simpler and more effective.

[0025] (1) In this invention, by establishing a predictive model of the influence of changes in the mass of the rod system components on the fluctuation of the crank driving torque, the influence of changes in the mass of the components on the crank driving torque can be intuitively sorted by observing the slope parameter in the predictive model, providing a useful reference for the design of the rod system of mechanical presses.

[0026] (4) In this invention, by establishing a predictive model of the influence of the mass change of the rod system components on the crank driving torque fluctuation, the crank driving torque under different component masses can be predicted by modifying the mass parameters in the predictive model, which provides a useful reference for the design of the rod system of mechanical presses. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of the linkage system of the multi-link press of Embodiment 2 of the present invention, which is a type of elbow-lever mechanical press.

[0028] Figure 2 for Figure 1 A flowchart illustrating the method for establishing a predictive model of the impact of the mass of multi-link pressure mechanism components on the crank drive torque fluctuation in the middle linkage system. Detailed Implementation

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] It should be noted that when a component is said to be "installed on" another component, it can be directly on the other component or it may be in a component that is centered on it. When a component is said to be "set on" another component, it can be directly set on the other component or it may also be in a component that is centered on it. When a component is said to be "fixed to" another component, it can be directly fixed to the other component or it may also be in a component that is centered on it.

[0031] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the specification of this invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "or / and" as used herein includes any and all combinations of one or more of the associated listed items.

[0032] Example 1

[0033] This embodiment introduces a method for predicting the influence of linkage mass on crank driving torque fluctuation in a multi-link press, belonging to the field of linkage optimization design methods for multi-link mechanical presses. The basic steps are as follows: Simplify the linkage structure of the multi-link mechanical press and establish a simplified diagram of the linkage mechanism; perform kinematic modeling and analysis of the multi-link press mechanism based on known linkage parameters and the simplified diagram; perform rigid body dynamics modeling of the multi-link press linkage using the Lagrange equation; solve the dynamic equation mathematical model based on the kinematic solution results and known inertial parameters to obtain the crank driving torque data; calculate the standard deviation of the driving torque data obtained from the dynamic model solution; adjust the mass parameters and repeat the above operations to solve the crank driving torque and its standard deviation to obtain multiple sets of mass parameters and their corresponding standard deviations of driving torque; establish a prediction model related to the driving torque and mass parameters using the principle of multiple linear regression; compare the results of the prediction model solution with the results obtained from simulation calculations to verify its accuracy. If the accuracy is within the allowable error range, output the prediction model to obtain an ideal prediction model.

[0034] In this embodiment, the prediction method includes the following steps:

[0035] I. Establish a prediction model for crank drive torque fluctuation;

[0036] 2. Incorporate the mass of each component of the linkage into the crank driving torque fluctuation prediction model to predict the crank driving torque fluctuation.

[0037] When establishing a prediction model for the fluctuation of crank driving torque, a method for establishing such a model can be used. This method involves establishing a prediction model for the influence of the mass of each component of a multi-link press on the fluctuation of crank driving torque, and specifically includes the following steps.

[0038] (1) Rigid body dynamics modeling of the multi-link system of the multi-link press is performed using the Lagrange equation:

[0039]

[0040] In the formula, q is a generalized coordinate function of the configuration of the multi-link system as a function of time; Let q be the first derivative with respect to time. Let q be the second derivative of q with respect to time; n represents the total number of components in the multi-link system, starting from 1, with the first component being a crank and the last component being a slider; m i Let R be the mass of the i-th component. i Let J be the centroid coordinates of the i-th component. i Let θ be the moment of inertia of the i-th component.i Let be the angular displacement of the i-th component, g be the acceleration due to gravity, and R be the angular displacement. iy M represents the y-axis component of the centroid coordinate of the i-th component. o Let F be the driving torque of the crank, and R be the load. ny Let y be the component of the centroid coordinate of the nth component in the y-direction.

[0041] (2) Based on the parameters of the rigid body dynamics model, obtain the corresponding parameter values ​​from the multi-link press and substitute them into the rigid body dynamics model. Divide the crank angular displacement θ1 of the crank in one motion cycle into multiple equal parts, and solve for the crank driving torque X of the multi-link system under different crank angular displacements θ1 in the motion cycle when unloaded, i.e., when F = 0. k The value of k ranges from 1 to N, where N represents the number of equal divisions of the crank angular displacement θ1 during the motion cycle.

[0042] (3) The driving torque X of N cranks k Find the standard deviation S.

[0043] S is a known value. In this embodiment, the standard deviation S is:

[0044] In the formula, For the driving torque X of N cranks k The average value.

[0045] (4) Adjust the mass parameters of each component, and repeat the operation of solving the crank driving torque and its standard deviation in steps (2) and (3) to obtain multiple sets of mass parameters and their corresponding standard deviations of crank driving torque.

[0046] The quality parameter adjustment was performed by adjusting each parameter individually and then combining all the adjusted parameters to obtain data, with a combination number of 2. n , where n is the total number of components in the multi-link system.

[0047] (5) Establish a prediction model s for the relationship between crank drive torque and mass parameters using a multiple linear regression model:

[0048]

[0049] In the formula, Let β be the mass variable of member i in the multi-link system, and β0 be the intercept of the multiple linear regression model; β i The slope parameter of the multiple linear regression model corresponding to the quality of the i-th component is calculated by the following formula: [β0β1…β i ] T =(G T G)－1 G T S'

[0050] G is a matrix arrangement of multiple sets of quality parameters, and S' is a standard deviation matrix composed of the standard deviations S of the crank driving torque corresponding to the multiple sets of quality parameters in step (4).

[0051] s is an unknown value, the value we need to find. We obtain some parameters from the known values; these parameters, β, reflect the predictive model s as a function of quality. Based on the changing pattern, we only need to substitute different... This allows us to obtain the corresponding s without the tedious steps mentioned earlier. For example, similar to elementary school students learning 1+2+...+n, finding s initially involves adding each element one by one, which is cumbersome. Later, they discover the pattern and realize the above formula equals n×(n+1) / 2. When encountering similar problems, they no longer need to add each element individually; they can directly substitute them into the later formulas to get the result. The prediction model is analogous to this later formula.

[0052] (6) Take the known Will The solution obtained by substituting the prediction model s is compared with the result obtained by simulation calculation to verify its accuracy. If the accuracy is within the allowable error range, the prediction model is output; otherwise, return to step (4).

[0053] The accuracy evaluation criterion μ is as follows:

[0054] In the formula, s0 is the value calculated by the simulation of the verification model. In this embodiment, μ ≤ 5%.

[0055] This invention proposes a method for establishing a predictive model of the impact of component mass changes on crank driving torque fluctuations in a multi-link press mechanism. For a specific type of press with a fixed link length parameter, it is necessary to study the influence of changes in the mass of each component in the linkage system on the fluctuation of crank driving torque, and to establish a predictive model for this effect. In practical operation, the mass parameters of this mature press are used as initial values, with fluctuations of a certain percentage above and below as boundary limits. Within these limits, the mass parameters are adjusted to obtain multiple sets of correlated crank driving torque data, and the standard deviation data corresponding to each set of driving torques is calculated. Based on these data, a multiple linear regression predictive model is established.

[0056] The method for establishing a predictive model of the influence of the mass of multi-link pressure mechanism components on the fluctuation of crank driving torque according to the present invention can be implemented as software, such as a standalone app or embedded software that can be called at any time, and applied to a computer terminal. The computer terminal includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The computer terminal can also be a smartphone, tablet, laptop, etc., capable of executing programs. In some embodiments, the processor can be a central processing unit (CPU), controller, microcontroller, microprocessor, or other data processing chip. The processor is typically used to control the overall operation of the computer device. In this embodiment, the processor is used to run program code stored in the memory or process data. When the processor executes the program, it can implement the steps of the method for establishing a predictive model of the influence of the mass of multi-link pressure mechanism components on the fluctuation of crank driving torque according to the present invention.

[0057] Example 2

[0058] In this embodiment, a multi-link press is illustrated using an elbow-type mechanical press as an example. Please refer to [link / reference]. Figure 1 The lever system of the elbow-type mechanical press includes a crank 11, an upper pull rod 12, a tripod 13, a lower push rod 15, and a slider 16.

[0059] One end of crank 11 is rotatably connected to the frame of the multi-link press, and the hinge point between crank 11 and the frame is defined as hinge point zero. A rectangular coordinate system is established with hinge point zero as the center, the horizontal direction of the ground as the X-axis, and the vertical direction perpendicular to the horizontal direction of the ground as the Y-axis. The other end of crank 11 is rotatably connected to one end of upper pull rod 12, and the corresponding hinge point is defined as hinge point one 1. The other end of upper pull rod 12 is rotatably connected to the first corner of tripod 13, and the corresponding hinge point is defined as hinge point two 2. The second corner of tripod 13 is rotatably connected to the frame, and the corresponding hinge point is defined as hinge point three 3. The third corner of tripod 13 is rotatably connected to one end of lower push rod 15, and the corresponding hinge point is defined as hinge point four 4. The other end of lower push rod 15 is rotatably connected to the center of slider 16, and the corresponding hinge point is defined as hinge point five 5.

[0060] Therefore, it means that crank 11 is connected to the frame through hinge point zero, upper pull rod 12 is connected to crank 11 through hinge point one, tripod 13 is connected to upper pull rod 12 through hinge point two, tripod 13 is connected to the frame through hinge point three, tripod 13 is connected to lower push rod 15 through hinge point four, and lower push rod 15 is connected to slider 16 through hinge point five.

[0061] Please see Figure 2The method for establishing a prediction model of the influence of the mass of multi-link pressure mechanism components on the fluctuation of crank driving torque is applied to the establishment of a prediction model of the influence of the mass change of the linkage components of an elbow-type mechanical press on the fluctuation of crank driving torque, including the following steps:

[0062] (1) Based on the known parameters and structural diagram of the rod system, the kinematic model of the press mechanism is performed and analyzed.

[0063] (2) In this embodiment, the known linkage is a type of elbow-type mechanical press linkage. A simplified diagram of the known linkage structure can be found here. Figure 1 Establish a Cartesian coordinate system with hinge point o as the origin. The known parameters are L1, L2, L3, L4, L5, x3, y3, θ, and e. Specifically, L1 is the length of crank 11; L2 is the length of upper pull rod 12; L3 is the length between hinge points 2 and 3 of the tripod; L4 is the angle between hinge points 3 and 4 of the tripod; L5 is the length of lower push rod 15; x3 is the x-component of the coordinate of hinge point 3 in the Cartesian coordinate system; y3 is the y-component of the coordinate of hinge point 3 in the Cartesian coordinate system; θ is the angle formed by hinge points 2 and 3 and 4 with hinge point 3 as the vertex; e is the offset, i.e., the difference in the x-component of the coordinate of hinge point 5 and hinge point 3 in the Cartesian coordinate system. Other parameters mainly include x... i y i ,α,α i ,γ, Specifically, x i y i Let α represent the x and y coordinates of hinge point i in the Cartesian coordinate system; α is the angle between crank 11 and the horizontal direction; α1 is the angle between crank 11 and upper pull rod 12; α2 is the angle between upper pull rod 12 and the line connecting hinge point 2 and hinge point 4; α3 is the angle between the line connecting hinge point 2 and hinge point 3 and the vertical direction; α4 is the angle between the line connecting hinge point 3 and hinge point 4 and lower push rod 15; α5 is the angle between lower push rod 15 and the vertical direction; γ is the angle formed by hinge point 2 and hinge point 3 and hinge point 1 with hinge point 3 as the vertex. Let the angle between hinge point 3 and hinge point 1 and hinge point 3 and the vertical direction be the angle formed by the hinge point 1 and hinge point 3 with the hinge point 3 as the vertex.

[0064] Based on the simplified diagram of the mechanism and the geometric relationships it embodies, the unknown parameters are represented by known parameters. Specifically, the expressions for each unknown parameter are as follows:

[0065]

[0066]

[0067]

[0068]

[0069]

[0070]

[0071]

[0072]

[0073] α4=θ+α3-α5 (1-9)

[0074] m = |[x3,y3]-[x1,y1]| (1-10)

[0075] n = |[[x3,y3]| (1-11)

[0076]

[0077]

[0078] (3) Use the Lagrange equation to perform rigid body dynamics modeling of the press rod system.

[0079] The Lagrange rigid body dynamics modeling expression for the linkage system of a mechanical press is as follows:

[0080]

[0081] In the formula,

[0082] q is a generalized coordinate; For generalized velocity; m i Let J be the mass of component i in the linkage system; i R is the moment of inertia of component i in the linkage system; ix Let R be the coordinates of the centroid of member i in the rod system; ix R represents the x-component of the centroid coordinate of member i in the rod system. iy Let θ be the component of the centroid coordinate of member i in the rod system along the y-direction; i Let be the angular displacement of member i in the linkage system; where i is the member number, n is the total number of members, and the slider is numbered n; g is the acceleration due to gravity; M o is the crank driving torque; F is the load.

[0083] The crank 11, upper pull rod 12, tripod 13, lower push rod 15, and slider 16 are a total of 5 components, n=5. Substituting into equations (2-1) and (2-2), specifically, the expression for the rigid body dynamics model of the lever system of an elbow-type mechanical press is as follows:

[0084]

[0085] In the formula,

[0086] In the formula, q is a generalized coordinate; For generalized velocity; m i For the mass of component i in the linkage system, the elbow-type mechanical press has a total of 5 components; J i R is the moment of inertia of component i in the linkage system; ix Let R be the coordinates of the centroid of member i in the rod system; ix R represents the x-component of the centroid coordinate of member i in the rod system. iy Let θ be the component of the centroid coordinate of member i in the rod system along the y-direction; i Let be the angular displacement of component i in the linkage system; where i is the component number in the linkage system, and the slider is numbered 5; g is the acceleration due to gravity; M o F is the crank driving torque; F is the load, which is set to 0 here, i.e., no load.

[0087] (4) Solve the dynamic equations based on the kinematic solution results and known inertial parameters to obtain the data of the crank-driven torque of the rod system;

[0088] This embodiment focuses on the rigid body dynamics equation of the lever system of an elbow-type mechanical press. Specifically, the expression of the rigid body dynamics equation of the lever system of an elbow-type mechanical press is as follows;

[0089]

[0090] In the formula,

[0091] In the formula, q is the generalized coordinate with the angular displacement of the crank as the generalized coordinate, q = α; M o Let be the crank driving torque, and be an unknown quantity.

[0092] Based on the kinematic analysis results in step (1), specifically, the expression for the position of the center of mass of each component in the formula is:

[0093]

[0094]

[0095]

[0096]

[0097] R5 = [x5, y5] (3-7)

[0098] The angular displacement expressions for each component in equation (3-2) are as follows:

[0099] θ1=α (3-8)

[0100] θ2=α+α1-σ1 (3-9)

[0101] θ3=α3+σ2 (3-10)

[0102] θ4=α5+σ3 (3-11)

[0103] θ5=0 (3-12)

[0104] In equations (3-8) to (3-12), σ i For a fixed constant angular displacement.

[0105] Substituting equations (3-2) to (3-12) into (3-1), the crank driving torque M can be solved. o .

[0106] (5) Calculate the standard deviation of the driving torque data obtained from the dynamic solution.

[0107] In this embodiment, for a lever-type mechanical press, the crank driving torque M obtained in step (4) is used. o The standard deviation of the resulting data is calculated. The crank driving torque M, obtained in step (4), is... o The standard deviation of the data can be calculated using the standard deviation formula. Specifically, the expression for calculating the standard deviation is as follows: In the formula, N is the data volume of the crank drive torque result obtained in step (4), and X k Let X be the k-th data value, and let X be the average value of this set of data.

[0108] (6) Adjust the mass parameters and repeat the operation of solving the crank drive torque and its standard deviation in steps (4) and (5) to obtain multiple sets of mass parameters and their corresponding drive torque standard deviation results.

[0109] (7) Establish a prediction model s for the relationship between crank driving torque and mass parameters using a multiple linear regression model:

[0110]

[0111] In the formula, Let β be the mass variable of member i in the multi-link system, and β0 be the intercept of the multiple linear regression model; β i Let be the slope parameter of the multiple linear regression model corresponding to the quality of the i-th component.

[0112] In this embodiment, a predictive model is established for the crank driving torque and mass parameters of a lever-type mechanical press. The lever-type mechanical press has a total of 5 components. Specifically, the predictive model expression for the lever-type mechanical press is as follows: s=β0+β1m1+β2m2+β3m3+β4m4+β5m5 (6-2)

[0113] In the formula, m1, m2, m3, m4, and m5 represent the masses of crank 11, upper pull rod 12, tripod 13, lower push rod 15, and slider 16, respectively; β1, β2, β3, β4, and β5 represent the slope parameters corresponding to the masses m1, m2, m3, m4, and m5 in the multiple linear regression prediction model, respectively; and β0 is the overall parameter of the intercept.

[0114] Based on the principle of multiple linear regression, specifically, the parameter β in the formula... i The expression is as follows:

[0115] [β0β1β2β3β4β5] T =(G T G) －1 G T S' h×1’ (6-3)

[0116] In the formula, G is the matrix arrangement of the multiple sets of quality parameters mentioned in step (6), and S' h×1 This is the matrix arrangement of the multiple sets of standard deviations obtained in step (6). Specifically, G and S' h×1 The expression is as follows:

[0117]

[0118]

[0119] In the formula, h is the number of data sets obtained in step (6), and m h1 m h2 m h3 m h4 m h5 These are the mass parameters of crank 11, upper pull rod 12, tripod 13, lower push rod 15, and slider 16 in the h-th data set. h Let be the standard deviation of the crank drive torque obtained from the h-th group of data. Substituting equations (6-4) and (6-5) into equation (6-3), the parameter β can be solved. i The solved parameter β i Substituting into equation (6-2), a predictive model relating the crank drive torque and mass parameters of an elbow-type mechanical press can be obtained.

[0120] By analyzing the mass m of each component in the prediction model iThe corresponding slope parameter β i By comparing and ranking them one-to-one, the influence of mass changes of each component in the linkage system of an elbow-type mechanical press on the fluctuation of crank driving torque can be ranked. By changing the mass parameters of each component in the prediction model and solving for the corresponding s-values, the fluctuation of crank driving torque under this set of mass parameters can be predicted.

[0121] (8) Compare the results of the prediction model with the results of the simulation calculation to verify its accuracy. If the accuracy is within the allowable error range, output the prediction model; otherwise, return to step (6).

[0122] In this embodiment, a predictive model relating the crank driving torque and mass parameters of a lever-type mechanical press is validated using ADAMS to establish a validation model. Of course, in other embodiments, other software with dynamic simulation capabilities can also be used to establish validation models.

[0123] A dynamic simulation model with the same dimensional parameters as in this embodiment but variable mass parameters is constructed using ADAMS parametric modeling. Reasonable mass parameter values ​​are randomly input for simulation. The resulting crank-drive torque curve is derived, and its standard deviation is calculated. The predicted standard deviation of the model under the same mass parameters is compared with the standard deviation of the crank-drive torque curve obtained from the simulation to verify the accuracy of the prediction model. Specifically, the expression for verification and comparison is as follows:

[0124] In the formula, s is the predicted value of the prediction model, and s0 is the simulation calculation value of the verification model. When the accuracy evaluation standard μ of the prediction model is not greater than 5%, the prediction model is considered to have high reference value; if it is greater than 5%, return to step (6) to add more sets of result data to build the prediction model and improve the accuracy of the prediction model.

[0125] This embodiment of the invention provides a more detailed explanation of the technical solution by specifying the parameters for establishing a predictive model for a lever-type mechanical press.

[0126] Example 1:

[0127] By performing steps (1) and (2), the coordinates and angles of each hinge point are obtained using known parameters. Specifically, the known parameters in steps (1) and (2) are shown in Table 1 below:

[0128] Table 1. Example 1: Geometric parameters of the lever system in an elbow-type mechanical press.

[0129]

[0130] Perform step (3) to establish the following dynamic model of the lever system of the elbow-type mechanical press:

[0131] In the formula,

[0132] Step (4) involves solving the dynamic equations based on the kinematic results and known inertial parameters to obtain the data on the crank-driven torque of the linkage system. Specifically, the relationship parameters of the linkage components are shown in the table below:

[0133] Table 2 Example 1 Inertial parameters of the lever system in an elbow-type mechanical press

[0134]

[0135] Perform step (5) to calculate the standard deviation of the driving torque data obtained from the dynamic solution.

[0136] Perform step (6) to adjust the mass parameters, and repeat steps (4) and (5) to solve for the crank drive torque and its standard deviation, obtaining multiple sets of mass parameters and their corresponding drive torque standard deviation results. Specifically, the adjusted mass parameters and standard deviation data are shown in Table 3 below:

[0137] Table 3 shows the experimental parameters and standard deviation results for 32 groups in Example 1.

[0138]

[0139]

[0140] Execute step (7) to establish a prediction model for the relationship between driving torque and mass parameters using the principle of multiple linear regression. The prediction model is as follows: s=β0+β1m1+β2m2+β3m3+β4m4+β5m5

[0141] In the formula, the expression for the unknown parameter β is as follows: [β0β1β2β3β4β5] T =(G T G) －1 G T S' h×1’

[0142] Specifically, in the formula, G and S' h×1 The expression is as follows:

[0143]

[0144] In the formula, each parameter corresponds one-to-one with the data in Table 3. Specifically, the numerical solution for parameter β is obtained as follows:

[0145] β=[-4.039 74.157 120.954 84.895 172.4809 207.572] T

[0146] Specifically, in this embodiment, the prediction model expression for the relationship between the crank drive torque and mass parameters of an elbow-type mechanical press with specific numerical values ​​is as follows:

[0147] s=-4.039+74.157m1+120.954m2+84.895m3+172.481m4+207.572m5

[0148] Specifically, by comparing the factors of each mass term in the prediction model, it can be found that under the dimensional conditions of this embodiment, the influence of the mass change of each component on the crank drive torque from smallest to largest is as follows: m5 > m4 > m2 > m3 > m1.

[0149] Execute step (8) to compare the results of the prediction model with the results of the simulation calculation to verify their accuracy. If the accuracy is within the allowable error range, output the prediction model; otherwise, return to step (6).

[0150] Randomly set the mass of each component The value of m is set here. p =[80 45 300 100 150], substituting into the prediction model, we obtain the predicted standard deviation of the crank drive torque fluctuation evaluation standard, i.e., the crank drive torque curve, s = 85223.851.

[0151] The corresponding dynamic model is constructed using ADAMS, and the driving torque curve of the crank is output through simulation calculation. The driving torque curve obtained from the simulation is exported as a data table (see Table 4).

[0152] Table 4

[0153]

[0154]

[0155]

[0156] The standard deviation of the simulated driving torque curve data was calculated to verify the accuracy of the prediction model. The simulated standard deviation values ​​of the crank drive torque curve are as follows:

[0157] Based on the above results, the accuracy of the prediction model is verified as follows:

[0158] If the accuracy evaluation standard μ of the prediction model is no greater than 5%, the prediction model is considered to have high reference value.

[0159] Example 2:

[0160] After performing steps (1) and (2), the coordinates and angles of each hinge point are obtained using known parameters. Specifically, the known parameters in steps (1) and (2) are shown in Table 5 below:

[0161] Table 5 Example 2 Geometric parameters of the lever system in an elbow-type mechanical press

[0162]

[0163]

[0164] Perform step (3) to establish the following dynamic model of the lever system of the elbow-type mechanical press:

[0165] In the formula,

[0166] Step (4) is executed to solve the dynamic equations based on the kinematic solution results and known inertial parameters, thereby obtaining the data of the crank-driven torque of the linkage system. Specifically, the relationship parameters of the linkage components are shown in Table 6 below.

[0167] Table 6 Example 2: Inertial parameters of the lever system in an elbow-type mechanical press.

[0168]

[0169] Perform step (5) to calculate the standard deviation of the driving torque data obtained from the dynamic solution.

[0170] Perform step (6) to adjust the mass parameters, and repeat steps (4) and (5) to solve for the crank drive torque and its standard deviation, obtaining multiple sets of mass parameters and their corresponding drive torque standard deviation results. Specifically, the adjusted mass parameters and standard deviation data are shown in Table 7 below.

[0171] Table 7 shows the experimental parameters and standard deviation results for 32 groups in Example 2.

[0172]

[0173]

[0174] Execute step (7) to establish a prediction model for the relationship between driving torque and mass parameters using the principle of multiple linear regression. The prediction model is as follows: s=β0+β1m1+β2m2+β3m3+β4m4+β5m5

[0175] In the formula, the expression for the unknown parameter β is as follows: [β0β1β2β3β4β5] T =(G T G) －1 G T S' h×1’

[0176] Specifically, in the formula, G and S' h×1 The expression is as follows:

[0177]

[0178] In the formula, each parameter corresponds one-to-one with the data in Table 3. Specifically, the numerical solution for parameter β is obtained as follows:

[0179] β=[368.131 67.137 120.525 137.062 343.906 423.044] T

[0180] Specifically, in this embodiment, the prediction model expression for the relationship between the crank drive torque and mass parameters of an elbow-type mechanical press with specific numerical values ​​is as follows:

[0181] s=368.131+67.137m1+120.525m2+137.062m3+343.906m4+423.044m5

[0182] Specifically, by comparing the factors of each mass term in the prediction model, it can be found that under the dimensional conditions of this embodiment, the influence of the mass change of each component on the crank drive torque from smallest to largest is as follows: m5 > m4 > m3 > m2 > m1.

[0183] Execute step (8) to compare the results of the prediction model with the results of the simulation calculation to verify their accuracy. If the accuracy is within the allowable error range, output the prediction model; otherwise, return to step (6).

[0184] Randomly set the mass of each component The value of m is set here. p =[61 55 211 103 197], substituting into the prediction model, we obtain the predicted standard deviation of the crank drive torque fluctuation evaluation standard, which is also the crank drive torque curve.

[0185] The corresponding dynamic model is constructed using ADAMS, and the driving torque curve of the crank is output through simulation calculation. The driving torque curve obtained from the simulation is exported as a data table as shown in Table 8.

[0186] Table 8

[0187]

[0188]

[0189]

[0190] The standard deviation of the simulated driving torque curve data was calculated to verify the accuracy of the prediction model. The simulated standard deviation values ​​of the crank drive torque curve are as follows:

[0191] Based on the above results, the accuracy of the prediction model is verified as follows:

[0192] If the accuracy evaluation standard μ of the prediction model is no greater than 5%, the prediction model is considered to have high reference value.

[0193] Example 3:

[0194] By performing steps (1) and (2), the coordinates and angles of each hinge point are obtained using known parameters. Specifically, the known parameters in steps (1) and (2) are shown in Table 0 below:

[0195] Table 9. Geometric parameters of the lever system in Example 3 of an elbow-type mechanical press.

[0196]

[0197] Perform step (3) to establish the following dynamic model of the lever system of the elbow-type mechanical press:

[0198] In the formula,

[0199] Step (4) is executed to solve the dynamic equations based on the kinematic solution results and known inertial parameters, thereby obtaining the data of the crank-driven torque of the linkage system. Specifically, the relationship parameters of the linkage components are shown in Table 10 below.

[0200] Table 10 Example 3: Inertial parameters of the lever system in an elbow-type mechanical press.

[0201]

[0202]

[0203] Perform step (5) to calculate the standard deviation of the driving torque data obtained from the dynamic solution.

[0204] Perform step (6) to adjust the mass parameters, and repeat steps (4) and (5) to solve for the crank drive torque and its standard deviation, obtaining multiple sets of mass parameters and their corresponding drive torque standard deviation results. Specifically, the adjusted mass parameters and standard deviation data are shown in Table 11 below:

[0205] Table 11 shows the experimental parameters and standard deviation results for 32 groups in Example 3.

[0206]

[0207] Perform step (7) to establish a prediction model for the relationship between driving torque and mass parameters using the principle of multiple linear regression. The prediction model is as follows: s=β0+β1m1+β2m2+β3m3+β4m4+β5m5.

[0208] In the formula, the expression for the unknown parameter β is as follows: [β0β1β2β3β4β5] T =(G T G) －1 G T S' h×1 Specifically, in the formula, G and S' h×1 The expression is as follows:

[0209]

[0210] Each parameter in the formula corresponds one-to-one with the data in Table 3. Specifically, the numerical solution for parameter β is obtained as follows:

[0211] β=[153.528 71.225 159.246 115.179 168.224 197.641] T

[0212] Specifically, in this embodiment, the prediction model expression for the relationship between the crank drive torque and mass parameters of an elbow-type mechanical press with specific numerical values ​​is as follows:

[0213] s=153.528+71.225m1+159.246m2+115.179m3+168.224m4+197.641m5

[0214] Specifically, by comparing the factors of each mass term in the prediction model, it can be found that the influence of the mass change of each component on the crank driving torque, from smallest to largest, is as follows: m5 > m4 > m2 > m3 > m1.

[0215] Execute step (8) to compare the results of the prediction model with the results of the simulation calculation to verify their accuracy. If the accuracy is within the allowable error range, output the prediction model; otherwise, return to step (6).

[0216] Randomly set the mass of each component The value of m is set here. p=[66 132 346 103 305], substituting into the prediction model, we obtain the predicted standard deviation of the crank drive torque fluctuation evaluation standard, i.e., the crank drive torque curve, as s = 143334.361.

[0217] The corresponding dynamic model is constructed using ADAMS, and the driving torque curve of the crank is output through simulation calculation. The driving torque curve obtained from the simulation is exported as a data table (see Appendix Table 12).

[0218] Table 12

[0219]

[0220]

[0221]

[0222] The standard deviation of the simulated driving torque curve data was calculated to verify the accuracy of the prediction model. The simulated standard deviation values ​​of the crank drive torque curve are as follows:

[0223]

[0224] Based on the above results, the accuracy of the prediction model is verified as follows:

[0225]

[0226] If the accuracy evaluation standard μ of the prediction model is no greater than 5%, the prediction model is considered to have high reference value.

[0227] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A method for establishing a prediction model of crank driving torque fluctuation, wherein the mass of each component of the multi-link system of a multi-link press affects the prediction model of crank driving torque fluctuation, characterized in that... The method for establishing the prediction model includes the following steps: (1) Using the multiple constraints of the multi-link mechanism and the Lagrange equation, the multi-link system of the multi-link press is modeled as a rigid body dynamics model, and the rigid body dynamics model is obtained: ； In the formula, ; q For the generalized coordinate function of the configuration of a multi-link system as a function of time; for q The first derivative with respect to time, for q The second derivative with respect to time; n This indicates the total number of components in the multi-link system. n The values ​​start from 1, and the first component is a crank and the last component is a slider; m i For the first i The mass of each component R i For the first i The centroid coordinates of each component J i For the first i The moment of inertia of each component θ i For the first i angular displacement of each component g It is the acceleration due to gravity. R iy For the first i The centroid coordinates of each component y Components in direction, M o The driving torque of the crank is... F For load, R ny For the first n The centroid coordinates of each component y Components in direction; (2) Based on the parameters of the rigid body dynamics model, obtain the corresponding parameter values ​​from the multi-link press and substitute them into the rigid body dynamics model to determine the crank angular displacement of the crank in one motion cycle. θ 1. Divide into multiple equal parts, and solve for the no-load condition. F When =0, the multi-link system has different crank angle displacements during the motion period. θ Crank drive torque at 1 X k ; k The value ranges from 1 to N , N Indicates the crank angular displacement during the aforementioned motion cycle. θ 1. The number of equal parts that have been divided; (3) To N crank driving torque X k Calculate the standard deviation S ; (4) Adjust the mass parameters of each component, and repeat the operation of solving the crank driving torque and its standard deviation in steps (2) and (3) to obtain multiple sets of mass parameters and their corresponding standard deviations of crank driving torque; (5) Establish a prediction model for the relationship between crank driving torque and mass parameters using a multiple linear regression model. s : ； In the formula, In the multi-link system i The mass variable of the component β 0 represents the intercept of the multiple linear regression model; β i For the first i The slope parameter of the multiple linear regression model corresponding to the mass of each component is calculated using the following formula: ； G It is a matrix arrangement of multiple sets of quality parameters. S’ The standard deviation of the crank drive torque corresponding to the multiple sets of mass parameters in step (4) S The standard deviation matrix is ​​composed of; (6) Take the known ones ,Will Substitute into the prediction model s The solution obtained is then compared with the simulation result to verify its accuracy. If the accuracy is within the allowable error range, the prediction model is output; otherwise, return to step (4).

2. The method for establishing a crank-driven torque fluctuation prediction model according to claim 1, characterized in that, Standard deviation S for: ； In the formula, for N Crank drive torque corresponding to each crank angular displacement X k The average value.

3. The method for establishing a crank-driven torque fluctuation prediction model according to claim 1, characterized in that, The quality parameter adjustment in step (4) is as follows: data is obtained by adjusting each parameter individually and combining all the adjusted parameters, with a combination number of 2. n ,in n This represents the total number of components in the multi-link system.

4. The method for establishing a crank-driven torque fluctuation prediction model according to claim 1, characterized in that, Accuracy evaluation criteria μ for: ； In the formula, s 0 represents the value calculated in the simulation of the verification model.

5. The method for establishing a crank drive torque fluctuation prediction model according to claim 4, characterized in that, μ≤ 5%。 6. The method for establishing a crank-driven torque fluctuation prediction model according to claim 1, characterized in that, The multi-link press is an elbow-type mechanical press. n When =5, the linkage of the elbow-type mechanical press includes five components: crank (11), upper pull rod (12), tripod (13), lower push rod (15), and slider (16). One end of the crank (11) is rotatably connected to the frame of the multi-link press, and the hinge point between the crank (11) and the frame is defined as hinge point zero. With hinge point zero as the center, the horizontal direction of the ground is... X The axis is the vertical direction perpendicular to the horizontal direction of the ground. Y Establish a rectangular coordinate system; the other end of the crank (11) is rotatably connected to one end of the upper pull rod (12), and the corresponding hinge point is defined as hinge point one (1); the other end of the upper pull rod (12) is rotatably connected to the first corner of the tripod (13), and the corresponding hinge point is defined as hinge point two (1); the second corner of the tripod (13) is rotatably connected to the frame, and the corresponding hinge point is defined as hinge point three (3); the third corner of the tripod (13) is rotatably connected to one end of the lower push rod (15), and the corresponding hinge point is defined as hinge point four (4); the other end of the lower push rod (15) is rotatably connected to the center of the slider (16), and the corresponding hinge point is defined as hinge point five (5). The rigid body dynamics model is as follows: ； In the formula, ; The expressions for the centroid positions of each component are: ； ； ； ； ； The expressions for the angular displacements of each component are as follows: θ 1= α θ 2= α ＋ α 1- σ 1 θ 3= α 3＋ σ 2 θ 4= α 5＋ σ 3 θ 5=0 x 0 is the zero coordinate of the hinge point. x Directional components, y 0 is the zero coordinate of the hinge point. y Directional components, x 1 is the coordinate of hinge point (1) x Directional components, y 1 is the coordinate of hinge point (1) y Directional components, x 2 is the coordinate of hinge point two (2) x Directional components, y 2 is the coordinate of hinge point two (2) y Directional components, x 3 is the coordinate of the hinge point (3). x Directional components, y 3 is the coordinate of the hinge point (3). y Directional components, x 4 is the coordinate of the hinge point (4). x Directional components, y 4 is the coordinate of the hinge point (4). y Directional components, x 5 is the coordinate of hinge point five (5). x Directional components, y 5 is the coordinate of hinge point five (5). y Directional components; α The crank angular displacement is also known as the crank (11) and X The angle between the axes; α 1 is the angle between the crank (11) and the upper pull rod (12); α 3 is the line connecting hinge point two (2) and hinge point three (3) and Y The angle between the axes; α 5 is the angle between the lower push rod (15) and the vertical direction; σ 1. σ 2. σ 3 are all fixed constants; Solving the combined equations yields the crank driving torque of the multi-link system under different angular displacement sets. X k .

7. The method for establishing a crank drive torque fluctuation prediction model according to claim 6, characterized in that, σ 1 represents a fixed constant determined by the organization; it will be eliminated in subsequent calculations and has no impact on the calculation. ; σ 2 represents a fixed constant determined by the mechanism structure. This constant will be eliminated in subsequent calculations and has no impact on the calculation. The difference in angle between the line formed by the center of mass of the tripod with hinge point 2 as the vertex and hinge point 2, and the line formed by hinge point 3 and hinge point 2; σ 3 represents a fixed constant determined by the mechanism structure; it will be eliminated in subsequent calculations and has no impact on the calculation. .

8. The method for establishing a crank drive torque fluctuation prediction model according to claim 7, characterized in that, Elbow-type mechanical press rod system prediction model s Specifically: s = β 0＋ β 1 m 1＋ β 2 m 2＋ β 3 m 3＋ β 4 m 4＋ β 5 m 5； In the formula, m 1. m 2. m 3. m 4. m 5 represents the mass of the crank (11), upper pull rod (12), tripod, lower push rod (15), and slider (16), respectively. β 1. β 2. β 3. β 4. β 5 represents the quality in the multiple linear regression model. m 1. m 2. m 3. m 4. m The slope parameter corresponding to 5, β 0 is the overall parameter for the intercept; then [ β 0 β 1 … β i ] T =( G T G ) －1 G T S’ Specifically: [ β 0 β 1 β 2 β 3 β 4 β 5] T =( G T G ) －1 G T S’ h×1 ； In the formula, h The number of data sets obtained in step (4); ； ； m h1 , m h2 , m h3 , m h4 , m h5 The first h Mass parameters of crank (11), upper tie rod (12), tripod, lower push rod (15), and slider (16) in the data set; s h For the first h The standard deviation of the crank drive torque obtained from the set of data.

9. The method for establishing a crank drive torque fluctuation prediction model according to claim 1, characterized in that, The method for adjusting the quality parameters in step (4) is to add or subtract any value from the basic quality parameters, provided that the value does not exceed the original size of the basic quality parameters.

10. A method for predicting the influence of linkage mass on crank drive torque fluctuation in a multi-link press, the prediction method comprising the following steps: (1) Establish a prediction model for the fluctuation of crank driving torque; (2) Incorporate the mass of each component of the linkage into the crank driving torque fluctuation prediction model to predict the crank driving torque fluctuation; The characteristic feature is that the crank driving torque fluctuation prediction model is established using the method for establishing the crank driving torque fluctuation prediction model of the elbow-lever mechanical press as described in any one of claims 1 to 9.

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