Servo dynamic characteristic matching degree quantitative adjustment method, device, equipment and medium

Abstract

The application relates to a servo dynamic characteristic matching degree quantitative adjustment method, device, equipment and medium, wherein the method comprises the following steps: building a machine tool shaft model according to a preset motor servo control system structure and a preset mechanical transmission system structure; based on the machine tool shaft model, an input and tracking error transfer function in a complex frequency domain is established by taking a position instruction as an input signal; the transfer function is optimized, and based on the optimized transfer function, a continuous step signal is combined with a delay theorem to obtain a tracking error model in a time domain through inverse pull type transformation; the tracking error model in the time domain is substituted into a servo dynamic characteristic matching characteristic value expression to obtain a quantitative relationship between a position loop proportional amplification coefficient and a servo dynamic characteristic matching characteristic value, and the servo dynamic characteristic matching degree is quantitatively adjusted based on the quantitative relationship. Therefore, the problems of low optimization precision caused by the lack of mathematical relationship between parameters in a servo control system and a matching degree in related technologies are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of servo control, and in particular relates to a servo dynamic characteristic matching degree quantitative adjustment method, device, equipment and medium. BACKGROUND

[0002] With the rapid development of high-end manufacturing industry, the requirements for machining precision and efficiency of complex curved surface are higher and higher. Dynamic performance is a decisive factor of machining efficiency and precision of machine tools. Numerical control machine tools show a trend of high speed, high precision and combination. Therefore, optimization of dynamic performance of machine tools is very important. Servo dynamic characteristic matching degree is one of the important factors affecting the dynamic performance of multi-axis linkage numerical control machine tools. Compared with optimizing other dynamic performance of machine tools, servo dynamic characteristic matching optimization has the advantages of low cost and simplicity, and can significantly improve the machining precision of complex curved surface. Therefore, servo dynamic characteristic matching optimization of machine tools is a key link of dynamic performance optimization of multi-axis linkage numerical control machine tools, and has become one of the most effective means to improve the machining precision of complex curved surface of machine tools.

[0003] With the in-depth research on servo dynamic characteristics of multi-axis linkage numerical control machine tools, the relationship between various parameters in servo control feeding system of machine tools and servo dynamic characteristic matching degree is gradually clear. At present, the research on the influence of servo dynamic characteristic matching degree on the machining precision of multi-axis linkage numerical control machine tools usually adjusts the position loop proportional gain coefficient of each axis to control the servo dynamic characteristic matching degree, and explores the relationship between servo dynamic characteristic matching degree and machining precision of machine tools.

[0004] The related art usually focuses on the influence mechanism of servo dynamic characteristic matching degree on machining precision of machine tools and the sensitivity of dynamic performance test to servo dynamic characteristic matching degree, and does not give a specific servo dynamic characteristic matching degree quantitative adjustment method, lacks mathematical relationship between various parameters in servo control system and matching degree, and leads to low precision when optimizing servo dynamic characteristic matching degree. SUMMARY

[0005] The present application provides a servo dynamic characteristic matching degree quantitative adjustment method, device, equipment and medium to solve the problem that related art lacks mathematical relationship between various parameters in servo control system and matching degree, leading to low precision when optimizing servo dynamic characteristic matching degree. The quantitative relationship between position loop proportional amplification coefficient and servo dynamic characteristic matching characteristic value can be obtained, and the quantitative adjustment of servo dynamic characteristic matching degree is realized based on the obtained quantitative relationship.

[0006] The first aspect embodiment of the application provides a servo dynamic characteristic matching degree quantitative adjustment method, comprising the following steps: building a machine tool shaft model according to a preset motor servo control system structure and a preset mechanical transmission system structure; based on the machine tool shaft model, establishing a transfer function between an input and a tracking error in a complex frequency domain with a position instruction as an input signal; optimizing the transfer function, and based on the optimized transfer function, combining a continuous step signal with a delay theorem to obtain a tracking error model in a time domain through inverse Laplace transform; and substituting the tracking error model in the time domain into a servo dynamic characteristic matching characteristic value expression to obtain a quantitative relationship between a position loop proportional amplification coefficient and the servo dynamic characteristic matching characteristic value, and based on the quantitative relationship, quantitatively adjusting the servo dynamic characteristic matching degree.

[0007] Optionally, in some embodiments, the optimizing the transfer function comprises: obtaining a machine tool shaft system structure parameter order of magnitude in the machine tool shaft model; and optimizing the transfer function according to the machine tool shaft system structure parameter order of magnitude.

[0008] Optionally, in some embodiments, the optimized transfer function is:

[0009]

[0010] wherein H(s) is the optimized transfer function, K pp is the position loop proportional amplification coefficient.

[0011] Optionally, in some embodiments, the preset motor servo control system adopts a PID control structure; and the preset mechanical transmission system adopts a screw nut or a worm gear structure.

[0012] Optionally, in some embodiments, the quantitative relationship is:

[0013]

[0014] wherein ξ yx is the servo dynamic characteristic matching characteristic value, K ppx is the x-axis position loop proportional amplification coefficient, K ppy is the y-axis position loop proportional amplification coefficient, and τ is a servo period.

[0015] The second aspect embodiment of the application provides a servo dynamic characteristic matching degree quantitative adjustment device, comprising: a building module configured to build a machine tool shaft model according to a preset motor servo control system structure and a preset mechanical transmission system structure; an establishing module configured to establish a transfer function between an input and a tracking error in a complex frequency domain based on the machine tool shaft model and taking a position instruction as an input signal; an optimization module configured to optimize the transfer function, and based on the optimized transfer function, combine a continuous step signal with a delay theorem to obtain a tracking error model in a time domain through inverse Laplace transform; and an adjustment module configured to substitute the tracking error model in the time domain into a servo dynamic characteristic matching characteristic value expression to obtain a quantitative relationship between a position loop proportional amplification coefficient and the servo dynamic characteristic matching characteristic value, and based on the quantitative relationship, quantitatively adjust the servo dynamic characteristic matching degree.

[0016] Optionally, in some embodiments, the optimization module is further configured to: obtain a machine tool shaft system structure parameter order of magnitude in the machine tool shaft model; and optimize the transfer function according to the machine tool shaft system structure parameter order of magnitude.

[0017] Optionally, in some embodiments, the optimized transfer function is:

[0018]

[0019] wherein H(s) is the optimized transfer function, K pp is the position loop proportional amplification coefficient.

[0020] Optionally, in some embodiments, the preset motor servo control system adopts a PID control structure; and the preset mechanical transmission system adopts a screw nut or a worm gear structure.

[0021] Optionally, in some embodiments, the quantitative relationship is:

[0022]

[0023] wherein ξ yx is the servo dynamic characteristic matching characteristic value, K ppx is the x-axis position loop proportional amplification coefficient, K ppy is the y-axis position loop proportional amplification coefficient, and τ is a servo period.

[0024] The third aspect embodiment of the application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and the processor executes the program to implement the servo dynamic characteristic matching degree quantitative adjustment method as described in the above embodiments.

[0025] The fourth aspect of the present application provides a computer readable storage medium, which stores a computer program. The program is executed by a processor to implement the servo dynamic characteristic matching degree quantitative adjustment method according to the above-mentioned embodiments.

[0026] Therefore, the embodiments of the present application have the following beneficial effects:

[0027] 1. There is no quantitative servo dynamic characteristic matching degree adjustment method based on servo control system parameters at present. The embodiments of the present application first propose a method for directly adjusting the servo dynamic characteristic matching degree between two axes based on the position loop proportional amplification coefficient, thereby providing theoretical support for optimizing the servo dynamic characteristic matching degree by adjusting the servo control system parameters.

[0028] 2. A simple time-domain tracking error model of a machine tool axis system of the same type and similar specifications compared with the embodiments of the present application is given, thereby providing theoretical support for the research based on the tracking error model.

[0029] 3. The mathematical relationship between the parameters in the servo control system and the servo dynamic characteristic matching eigenvalue is determined, and the obtained conclusion is verified by experiments.

[0030] Additional aspects and advantages of the present application will be in part apparent and in part pointed out hereinafter. BRIEF DESCRIPTION OF DRAWINGS

[0031] The above-mentioned and / or additional aspects and advantages of the present application will become apparent and easy to understand from the following description of the embodiments taken in conjunction with the following drawings, in which:

[0032] Figure 1 A flowchart of the servo dynamic characteristic matching degree quantitative adjustment method according to the embodiments of the present application is shown;

[0033] Figure 2 An overall structure schematic diagram of an AC turntable type five-axis linkage numerical control machine tool according to one specific embodiment of the present application is shown;

[0034] Figure 3 A motor servo control system model schematic diagram according to one specific embodiment of the present application is shown;

[0035] Figure 4 A mechanical transmission system model schematic diagram according to one specific embodiment of the present application is shown;

[0036] Figure 5 A tracking error comparison simulation experiment result schematic diagram according to one specific embodiment of the present application is shown;

[0037] Figure 6A roundness test result schematic diagram when the x-axis and y-axis servo control system parameters are completely consistent according to one specific embodiment of the present application is provided;

[0038] Figure 7 A block schematic diagram of a servo dynamic characteristic matching degree quantitative adjustment device according to an embodiment of the present application is provided.

[0039] Figure 8 A structural schematic diagram of an electronic device according to an embodiment of the present application is provided. DETAILED DESCRIPTION

[0040] Embodiments of the present application are described in detail below with reference to the accompanying drawings, in which the same or similar numerals indicate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present application, and cannot be understood as a limitation of the present application.

[0041] A servo dynamic characteristic matching degree quantitative adjustment method, device, electronic device and storage medium of an embodiment of the present application are described below with reference to the accompanying drawings. In view of the problem that related technologies mentioned in the background art lack mathematical relationships between parameters in a servo control system and matching degrees, resulting in low precision when optimizing the servo dynamic characteristic matching degree, the present application provides a servo dynamic characteristic matching degree quantitative adjustment method. In the method, a machine tool shaft model is built according to a preset motor servo control system structure and a preset mechanical transmission system structure, an input and tracking error transfer function in a complex frequency domain is established based on the machine tool shaft model with a position instruction as an input signal, the transfer function is optimized, a tracking error model in a time domain is obtained by inverse Laplace transform based on the optimized transfer function by combining a continuous step signal and a delay theorem, and a quantitative relationship between a position loop proportional amplification coefficient and a servo dynamic characteristic matching eigenvalue is obtained by substituting the tracking error model in the time domain into a servo dynamic characteristic matching eigenvalue expression, and the servo dynamic characteristic matching degree is quantitatively adjusted based on the quantitative relationship. Thus, the problem that related technologies lack mathematical relationships between parameters in a servo control system and matching degrees, resulting in low precision when optimizing the servo dynamic characteristic matching degree, is solved, the quantitative relationship between the position loop proportional amplification coefficient and the servo dynamic characteristic matching eigenvalue can be obtained, and the quantitative adjustment of the servo dynamic characteristic matching degree is realized based on the obtained quantitative relationship.

[0042] Specifically, Figure 1 A flowchart of a servo dynamic characteristic matching degree quantitative adjustment method provided by an embodiment of the present application is shown.

[0043] As Figure 1 shown, the servo dynamic characteristic matching degree quantitative adjustment method includes the following steps:

[0044] In step S101, a machine tool axis model is built according to a preset motor servo control system structure and a preset mechanical transmission system structure.

[0045] Optionally, in some embodiments, the preset motor servo control system adopts a PID control structure; and the preset mechanical transmission system adopts a screw nut or a worm gear structure.

[0046] Specifically, the machine tool axis system participating in the motion is composed of a motor servo control system and a mechanical transmission system. At present, various types of machine tool axis systems are applied to multi-axis linkage numerical control machine tools, and the influencing factors of the servo dynamic characteristics matching degree of different machine tool axis systems are also different. Therefore, this paper takes a certain AC rotary table type five-axis linkage numerical control machine tool and its machine tool axis system as an example, and the structure diagram of the machine tool is shown in Figure 2 .

[0047] The motor servo control system in the machine tool axis system can be composed of a permanent magnet synchronous motor (PMSM) and a classic PID three-loop control method, and the specific structure is shown in Figure 3 .

[0048] Among them, K pp is the position loop proportional gain coefficient; K pv is the speed loop proportional gain coefficient; K pi is the current loop proportional gain coefficient; T iv is the speed loop integral time constant; T ii is the current loop integral time constant; L a is the armature inductance, R a is the armature resistance, K t is the motor torque coefficient, K e is the motor back electromotive force constant, J e is the equivalent rotational inertia of the motor and the screw.

[0049] The mechanical transmission system mainly adopts screw nut transmission or worm gear transmission, and the specific structure is shown in Figure 4 , Figure 4 is a mechanical transmission system model schematic diagram, wherein Figure 4 (a) is a schematic diagram of the mechanical transmission system of the translational axis, Figure 4 (b) is a block diagram of the mechanical transmission system of the translational axis after Laplace transformation, Figure 4 (c) is a schematic diagram of the mechanical transmission system of the rotational axis, Figure 4 (d) is a block diagram of the mechanical transmission system of the rotational axis after Laplace transformation, and the control mode of the machine tool axis system is not lost generality and is considered to adopt the most commonly used position instruction control mode.

[0050] Contrast Figure 4 (b) and Figure 4 (d) of the mechanical transmission system of the translation axis and the rotation axis are consistent. Therefore, only the matching degree of the servo dynamic characteristics between the translation axes is taken as an example to analyze and illustrate the method. Figure 4 The physical meanings of the symbols in the formula are as follows, J1 is the rotational inertia of the driving shaft; J2 is the rotational inertia of the driven shaft; T m is the output torque of the motor; θ m is the output angle of the motor; T2 is the driving torque of the driven shaft; T h is the output torque of the driven shaft transmitted to the ball screw; θ h is the output angle of the driven shaft driving the ball screw; K2 is the torsional stiffness coefficient of the driven shaft; D2 is the damping coefficient of the driven shaft; M t is the mass of the moving platform; D t is the damping coefficient of the moving platform; X t is the output displacement of the moving platform; f t is the load resistance of the moving platform; i is the reduction ratio of the first-stage speed reducer from the driving shaft to the driven shaft; i h is the reduction ratio of the ball screw, and for single-threaded screw, i h = 2π / P h , wherein P h is the pitch of the ball screw.

[0051] In step S102, based on the machine tool shaft model, the transfer function between the input and the tracking error in the complex frequency domain is established with the position command as the input signal.

[0052] Combined with the system block diagrams of Figure 3 and Figure 4 (b), the complete translation axis system structure can be obtained. The tracking error size is determined by two inputs, i.e., the input position command and the existing disturbance torque at the time. In the actual machine tool working process, the influence of the input position command on the tracking error size is reflected in the profile error, and the influence of the disturbance torque (mainly composed of the cutting force) on the tracking error size is reflected in the roughness and waviness. Since the profile error is mainly studied and analyzed in the embodiments of the application, the influence of the disturbance torque is not considered when the tracking error is mathematically modeled. From the machine tool shaft system structure shown in Figure 3 and Figure 4 , the transfer function H(s) between the input position command X i (s) and the tracking error E(s) in the complex frequency domain can be obtained, and after being simplified into the form of the simplest fraction, the transfer function H(s) is:

[0053]

[0054] , wherein G1(s) and G2(s) are:

[0055]

[0056]

[0057] In the typical machine tool axis system structure of the AC rotary table type five-axis linkage numerical control machine tool in the embodiments of the present application, the sizes of various parameters are shown in Table 1. The embodiments of the present application consider that for the same type and the same specification of five-axis linkage numerical control machine tools, if the machine tool axis system is similar to the structure shown in the example, the sizes of various parameters in the system are of the same order of magnitude as the sizes of various parameters in Table 1.

[0058] Table 1

[0059]

[0060]

[0061] In step S103, the transfer function is optimized, and based on the optimized transfer function, the continuous step signal is combined with the delay theorem to obtain a tracking error model in the time domain through inverse Laplace transformation.

[0062] Optionally, in some embodiments, the transfer function is optimized, including: obtaining the order of magnitude of the machine tool axis system structure parameters in the machine tool axis model; and optimizing the transfer function according to the order of magnitude of the machine tool axis system structure parameters.

[0063] Since the zero-pole form of such a high-order expression cannot be directly given by existing mathematical methods, and directly using such a complex expression to represent the tracking error will bring great difficulty to the quantitative relationship between the control system parameters and the matching characteristic values of the servo dynamic characteristics. Therefore, the above formula is simplified by combining the actual application scenario with the mathematical analysis method.

[0064] The approximate simplification method of "ignoring relatively small quantities by order of magnitude analysis, and then extracting the main influencing factors" is widely used in engineering physics and experimental physics. In the method, the idea of this approximate simplification method is borrowed, and the machine tool tracking error model of the same type and similar specification is simplified without loss of generality.

[0065] The order of magnitude of each system parameter in Table 1 is denoted as O(x), that is,

[0066] O(x)=lgx,x∈{K pp ,K pv ,K pi ,…,D2,D t ,M t};

[0067] By comparing the sizes of various coefficients in Table 1, it can be seen that there is a large difference in the order of magnitude of each coefficient. When x=Tiv T ii L a J e When x = M, the value of O(x) is around -3. t i h The value of O(x) is around 2. Therefore, the input position instruction X is obtained by ignoring relatively small values. i An approximate transfer function between (s) and the tracking error E(s) is feasible. The simplification method is as follows: for two subtractive or additive subdivided minors f(x) ± g(x) in a univariate n-degree polynomial Q(x), the order-of-magnitude difference between their coefficients is denoted as:

[0068] ΔO(P f P g )=lg P f -lg P g ;

[0069] Among them, P f With P g Let P be the coefficients of the minors f(x) and g(x), respectively. Without loss of generality, assume P... f >P g And there are

[0070] f(x)±g(x)≈f(x);

[0071] stΔO(P f P g )≥2;

[0072] The simplification process is illustrated below using the coefficient of the sixth-degree term in G1(s) with respect to s as an example. Let its coefficient be denoted as P6 = P 6，1 +P 6，2 +P 6，3 +P 6，4 ,Right now

[0073] P 6，1 =T iv J e T ii L a (D t +i h 2 D2)i0 2 ;

[0074] P 6，2 =T iv J e T ii (K pi +R a (J2i) h 2 +M t )i02 ;

[0075] P 6，3 = D2J2i h 2 T ii L a T iv ;

[0076] P 6，4 = D2M t T ii L a T iv ;

[0077] From the above assumptions, it can be obtained that, since ΔO(i h 2 D2, D t )≥ 2, P 6，1 can be simplified as:

[0078] P 6，1 ≈ P 6，1 ′= T iv J e T ii L a D2i h 2 i0 2 ;

[0079] Similarly, P 6，2 can be simplified, and the simplification process is not described again. The coefficient of the 6th order term of s after simplification is:

[0080] P 6，1 ′= T iv J e T ii L a D2i h 2 i0 2 ;

[0081] P 6，2 ′= T iv J e T ii K pi (K2i h 2 + M t )i0 2 ;

[0082] P 6，3 ′= P 6，3 , P 6，4 ′= P 6，4 ;

[0083] P6′= P 6，1′+P 6，2 ′+P 6，3 ′+P 6，4 ′;

[0084] Due to ΔO(P) 6，2 ′,P)≥2,P∈{P 6，1 ′, P 6，3 ′, P 6，4 If '} always holds true, the coefficient of the 6th term of s can be further simplified to:

[0085] P6″=P 6，2 ′=T iv J e T ii K pi (K2i h 2 +M t )i0 2 ≈P6;

[0086] Similarly, G1(s) and G2(s) can be simplified to ultimately simplify the tracking error expression. The simplification process will not be detailed here; only the final simplified result is given:

[0087]

[0088] To verify the correctness of the above simplification method, two simulation experiments were conducted. The first experiment compared the tracking error before and after simplification when the input was a unit step. Figure 5 As shown in (a); secondly, when the input period is a sinusoidal response of 1s, the magnitude of the tracking error before and after simplification is compared, as shown in (a). Figure 5 As shown in (b), the analysis of the experimental results shows that the tracking errors of the motion axis system before and after simplification are very close. Even if there are slight differences, they are negligible compared to the tracking error value. Therefore, the above simplification method is completely feasible.

[0089] Next, based on the minimum time interval servo cycle of the CNC machine tool position input command, the mathematical analytical expression of the tracking error in the time domain is analyzed using the delay theorem. Due to the existence of the servo cycle, the machine tool's position command input is discrete; however, this discrete input can be considered to have a zero-order hold characteristic, therefore, the machine tool's position command input can be regarded as a continuous step input. If x... i (t) can be considered as a continuous step input and written in the following form:

[0090]

[0091] Among them, t i (i = 1, 2, 3, ..., n-2, n-1, n) represents the input time of the i-th position command of the machine tool, Axi The increment of the position command input to the machine tool for each servo cycle. The expression of the tracking error E(s) in the complex frequency domain can be obtained by the delay theorem:

[0092]

[0093] The tracking error in the time domain can be obtained by converting the tracking error in the complex frequency domain to the time domain:

[0094]

[0095]

[0096] So far, the above formula gives the tracking error model of the machine tool axis affected by the input position command in the time domain under the position control mode using the three-ring PID control based on the P-PI-PI structure.

[0097] In step S104, the time-domain tracking error model is substituted into the servo dynamic characteristic matching eigenvalue expression to obtain the quantitative relationship between the position loop proportional amplification coefficient and the servo dynamic characteristic matching eigenvalue, and the servo dynamic characteristic matching degree is quantitatively adjusted based on the quantitative relationship.

[0098] Specifically, for the machine tool axis system of two motion directions orthogonal to each other: x-axis and y-axis, the tracking errors ex(t) and ey(t) of the two axes can be obtained from the time-domain tracking error model as follows: y

[0099]

[0100]

[0101] where w x (t) = L -1 [H x (s) / s] and w y (t) = L -1 [H y (s) / s].

[0102] Substituting the above formula into the expression of the servo dynamic characteristic matching eigenvalue ξ yx of the x-axis to the y-axis can obtain:

[0103]

[0104] where K ppx and K ppy are the x-axis position loop proportional amplification coefficient and the y-axis position loop proportional amplification coefficient, respectively.

[0105] ​The five-axis linkage CNC machine tool involved in this paper has a servo period τ of 2 ms, which can be considered to be zero. The above formula is further expanded by the Maclaurin formula of the natural exponential function:

[0106]

[0107] Neglecting the small amount of high order, the expression of ξ yx is further simplified as:

[0108]

[0109] wherein, ξ yx is the servo dynamic characteristic matching eigenvalue, K ppx is the x-axis position loop proportional amplification coefficient, K ppy is the y-axis position loop proportional amplification coefficient, and τ is the servo period.

[0110] The above formula gives the relationship between the control system parameters in the machine tool axis system and the servo dynamic characteristic matching eigenvalue.

[0111] As one of the typical servo matching debugging methods, roundness testing method is widely recognized and widely used in related fields such as machine tool manufacturing. Based on this method, taking the X-Y plane as an example, the verification experiment of the quantitative relationship between the control parameters of the servo control system and the servo dynamic characteristic matching eigenvalue shown in the above formula was carried out on a certain AC rotary table five-axis linkage machine tool equipped with Siemens 840D SL numerical control system.

[0112] First, under the condition that the servo control system control parameters of the x-axis and the y-axis are completely consistent, a roundness test is completed as a control experiment group. In this experiment, the position loop proportional gain coefficients of the x-axis and the y-axis are set as K ppx = K ppy = 10, the speed loop proportional amplification coefficients of the x-axis and the y-axis are set as K pvx = K pvy = 5.189, the speed loop integral time constants of the x-axis and the y-axis are set as T ivx = T ivy = 9, the current loop proportional amplification coefficients of the x-axis and the y-axis are set as K pix = K piy = 27.705, and the current loop integral time constants of the x-axis and the y-axis are set as T iix = T iiy = 5. The experimental parameters are set as: the roundness test track radius R = 100 mm, and the feed rate F = 5000 mm / min. The experimental results are as follows: Figure 6As shown, when the servo control system control parameters of the x-axis and the y-axis are completely consistent, the servo dynamic characteristic matching eigenvalue size should be 1 according to the quantity relationship shown by the above formula. However, the differences existing in the ball screw gap and other electrical systems and mechanical systems cause the actual servo dynamic characteristic matching eigenvalue size to be slightly less than or slightly greater than 1 at this time, and the servo dynamic characteristics of the two axes are not completely matched. At this time, the roundness test error value is 5.9 um.

[0113] Next, on the basis of the control group experiment, the y-axis servo control system control parameters were kept unchanged, the experimental group parameters were the same as the control group, and only the x-axis servo control system control parameters were changed in turn. The variation range of each servo control system control parameter was -40%, -20%, -10%, +10%, +20%, and +40%, and a roundness test was completed under each condition. A total of 30 roundness tests were completed. The roundness test error when each servo control system control parameter changed is listed in Table 2. According to the experimental results, when K pvx , K pix , T ivx , and T iix change, the roundness test error size does not change significantly and is basically the same as the control experiment group result, thereby proving that K pvx , K pix , T ivx , and T iix have no significant effect on the servo dynamic characteristic matching eigenvalue, that is, the conclusion that only the position loop proportional amplification coefficient of the two-axis servo control system has a significant effect on the servo dynamic characteristic matching eigenvalue is verified.

[0114] Table 2

[0115]

[0116] Next, a third roundness test experiment was carried out to verify the quantitative relationship between the position loop proportional amplification coefficient of the servo control system and the servo dynamic characteristic matching eigenvalue. The y-axis servo control system control parameters were kept unchanged, the parameters in the experimental group were the same as the control group, and the parameters of the x-axis servo control system other than K ppx were consistent with the y-axis. Four roundness tests were carried out under the conditions of K ppx = 11, 12, 13, and 14.4. The servo period τ of the machine tool was 2 ms, which was obtained from the numerical control system. The normal trajectory profile error ΔR and the data processing results at |k(u)| = 1 on the circular command trajectory curve were obtained from the numerical control system, wherein ΔR0 is the roundness test error measured in the control experiment group; ξ yx , and S p,xyThe size of (u, τ) is calculated according to the theoretical value of the above quantity relationship. When the trajectory tracking error ||AC(u)||2 in the two experiments is considered to be unchanged, it is known that the two experimental structures should have the following relationship

[0117]

[0118] Wherein, E1 and E2 are ΔR-ΔR0 in the two experiments.

[0119] Table 3 is the roundness test result table when Kppx is different, which gives the actual value of the left side of the above equation and the theoretical value of the right side of the above equation calculated by experimental data analysis and the quantity relationship obtained when the experimental results of Kppx=11 are taken as the benchmark. Since the trajectory tracking error ||AC(u)||2 changes more and more obviously with the increase of Kppx, the deviation between the actual value of the left side of the equation and the theoretical value of the right side of the equation in Table 3 gradually increases, but overall the experimental results are consistent with the above equation. ppx

[0120] The above experimental results show that the size of the trajectory tracking error ||AC(u)||2 calculated according to the quantity relationship between the position loop proportional amplification coefficient of the servo control system and the matching characteristic value of the servo dynamic characteristic is correct, and further proves that the quantity relationship between the position loop proportional amplification coefficient of the servo control system and the matching characteristic value of the servo dynamic characteristic is correct.

[0121] Table 3

[0122]

[0123] So far, the quantitative adjustment of the matching degree of the servo dynamic characteristic of the machine tool shaft system has been completed, and the quantity relationship between the position loop proportional amplification coefficient of the servo control system and the matching characteristic value of the servo dynamic characteristic is determined.

[0124] ​​Therefore, the embodiment of the application establishes a typical machine tool spindle model based on a PID motor servo control system and a screw nut mechanical transmission system, and on the basis of considering that the influence of the disturbance torque on the tracking error size is reflected in roughness and waviness, the transfer function between the input position command and the tracking error in the complex frequency domain is determined; the approximate simplification method of "ignoring the relatively small amount through order of magnitude analysis, and thus extracting the main influencing factors" is applied to the transfer function simplification, and the transfer function of the tracking error in the same type and similar specification machine tool spindle system is simplified without losing generality; the accuracy of the simplified result is verified through simulation; based on the minimum time interval servo period of the numerical control machine tool position input command, the mathematical analytical expression of the tracking error in the time domain is analyzed using the delay theorem; based on the Maclaurin formula, the tracking error model in the time domain is substituted into the servo dynamic characteristic matching characteristic value expression to further expand to obtain the mathematical relationship between the servo control system parameters and the servo dynamic characteristic matching characteristic value; the relationship between the parameters in the servo control system and the servo dynamic characteristic matching characteristic value is verified through experiments.

[0125] According to the servo dynamic characteristic matching degree quantitative adjustment method proposed in the embodiment of the application, the machine tool spindle model is established according to the structure of the typical motor servo control system and the structure of the mechanical transmission system, and based on the established machine tool spindle model, the transfer function expression between the input and the tracking error in the complex frequency domain is established with the position command as the input signal, the transfer function is simplified by referring to the order of magnitude of the machine tool spindle system structure parameters, the rationality of the simplification is verified through simulation, the tracking error model in the time domain is obtained through inverse pull transformation by combining the continuous step signal with the delay theorem, and the tracking error model in the time domain is substituted into the servo dynamic characteristic matching characteristic value expression. Under the approximate condition that exists in general cases, the quantitative relationship between the position loop proportional amplification coefficient and the servo dynamic characteristic matching characteristic value is obtained through the Maclaurin formula expansion, and the quantitative adjustment of the servo dynamic characteristic matching degree is realized based on the obtained quantitative relationship. Therefore, the mathematical relationship between the parameters in the servo control system and the matching degree is solved, which solves the problems of low precision in optimizing the servo dynamic characteristic matching degree in the related art, the quantitative relationship between the position loop proportional amplification coefficient and the servo dynamic characteristic matching characteristic value is obtained, and the quantitative adjustment of the servo dynamic characteristic matching degree is realized based on the obtained quantitative relationship.

[0126] Secondly, the servo dynamic characteristic matching degree quantitative adjustment device proposed in the embodiment of the application is described with reference to the accompanying drawings.

[0127] Figure 7 The block schematic diagram of the servo dynamic characteristic matching degree quantitative adjustment device in the embodiment of the application.

[0128] As Figure 7As shown, the servo dynamic characteristic matching degree quantitative adjustment device 10 comprises a building module 100, a building module 200, an optimization module 300 and an adjustment module 400.

[0129] The building module 100 is configured to build a machine tool shaft model according to a preset motor servo control system structure and a preset mechanical transmission system structure; the building module 200 is configured to build a transfer function between an input and a tracking error in a complex frequency domain based on the machine tool shaft model and taking a position instruction as an input signal; the optimization module 300 is configured to optimize the transfer function, combine a continuous step signal with a delay theorem based on the optimized transfer function, and obtain a tracking error model in a time domain through an inverse Laplace transform; and the adjustment module 400 is configured to obtain a quantitative relationship between a position loop proportional amplification coefficient and a servo dynamic characteristic matching characteristic value by substituting the tracking error model in the time domain into a servo dynamic characteristic matching characteristic value expression, and quantitatively adjust a servo dynamic characteristic matching degree based on the quantitative relationship.

[0130] Optionally, in some embodiments, the optimization module is further configured to: obtain a quantity order of a machine tool shaft system structure parameter in the machine tool shaft model; and optimize the transfer function according to the quantity order of the machine tool shaft system structure parameter.

[0131] Optionally, in some embodiments, the optimized transfer function is:

[0132]

[0133] wherein H(s) is the optimized transfer function, K pp is the position loop proportional amplification coefficient.

[0134] Optionally, in some embodiments, the preset motor servo control system adopts a PID control structure; and the preset mechanical transmission system adopts a screw nut or a worm and gear structure.

[0135] Optionally, in some embodiments, the quantitative relationship is:

[0136]

[0137] wherein ξ yx is the servo dynamic characteristic matching characteristic value, K ppx is an x-axis position loop proportional amplification coefficient, K ppy is a y-axis position loop proportional amplification coefficient, and τ is a servo period.

[0138] It should be noted that the foregoing explanation and description of the servo dynamic characteristic matching degree quantitative adjustment method embodiment are also applicable to the servo dynamic characteristic matching degree quantitative adjustment device of this embodiment, which will not be described here again.

[0139] The servo dynamic characteristic matching degree quantitative adjustment device provided by the embodiment of the application is built according to a preset motor servo control system structure and a preset mechanical transmission system structure, a machine tool shaft model is built based on the machine tool shaft model, a transfer function between an input and a tracking error in a complex frequency domain is established based on the machine tool shaft model and the position instruction as an input signal, the transfer function is optimized, a continuous step signal is combined with a delay theorem based on the optimized transfer function, a tracking error model in a time domain is obtained through inverse pull type transformation, and a quantitative relationship between a position loop proportional amplification coefficient and a servo dynamic characteristic matching characteristic value is obtained by substituting the tracking error model in the time domain into a servo dynamic characteristic matching characteristic value expression, and the servo dynamic characteristic matching degree is quantitatively adjusted based on the quantitative relationship. Thus, the mathematical relationship between the parameters in the servo control system and the matching degree is solved, the problem of low precision when optimizing the servo dynamic characteristic matching degree is solved, the quantitative relationship between the position loop proportional amplification coefficient and the servo dynamic characteristic matching characteristic value is obtained, and the quantitative adjustment of the servo dynamic characteristic matching degree is realized based on the obtained quantitative relationship.

[0140] Figure 8 The structure schematic diagram of the electronic device provided by the embodiment of the application is provided. The electronic device can include:

[0141] The memory 801, the processor 802 and the computer program stored in the memory 801 and executable on the processor 802.

[0142] The processor 802 implements the servo dynamic characteristic matching degree quantitative adjustment method provided in the above embodiment when executing the program.

[0143] Further, the electronic device further includes:

[0144] The communication interface 803 is used for communication between the memory 801 and the processor 802.

[0145] The memory 801 is used to store the computer program executable on the processor 802.

[0146] The memory 801 can include a high-speed RAM (Random Access Memory, random access memory) memory, and can also include a non-volatile memory, for example, at least one disk memory.

[0147] If the memory 801, the processor 802 and the communication interface 803 are implemented independently, the communication interface 803, the memory 801 and the processor 802 can be connected with each other through a bus and complete communication between each other. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, Figure 8 Only one thick line is used to represent the bus in the figure, but it does not mean that there is only one bus or only one type of bus.

[0148] Optionally, in a specific implementation, if the memory 801, the processor 802 and the communication interface 803 are integrated on a chip, the memory 801, the processor 802 and the communication interface 803 can complete communication between each other through an internal interface.

[0149] The processor 802 can be a CPU (Central Processing Unit), or an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application.

[0150] The embodiments of the present application also provide a computer readable storage medium, which stores a computer program, and the program is executed by a processor to implement the servo dynamic characteristic matching degree quantitative adjustment method as above.

[0151] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example" or "some examples" means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms is not necessarily for the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the present specification and the features of the different embodiments or examples without contradiction.

[0152] In addition, the terms "first", "second", etc. are used only for descriptive purposes and do not connote or imply relative importance or a quantity of the indicated technical features. Thus, a feature defined with "first", "second", etc. can include at least one of the feature explicitly or implicitly. In the description of the present application, the meaning of "N" is at least two, such as two, three, etc., unless otherwise explicitly and specifically limited.

[0153] Any process or method descriptions or descriptions of the flow diagrams described herein can be understood as representing code modules, segments, or portions of code which include one or more executable instructions for implementing specific logic functions (or steps) of the application, and that the various systems described herein can be implemented with software, firmware, hardware, or a combination thereof. In this context, the term "software" can be understood to encompass code segments or portions of code, whether referred to as software, firmware, middleware, microcode, or the like.

[0154] It should be understood that various parts of the present application can be implemented in hardware, software, firmware or a combination thereof. In the above embodiments, the N steps or methods can be implemented with software or firmware stored in a memory and executed by a suitable instruction execution system. As in another embodiment, if implemented in hardware, any of the following technologies or their combinations known in the art can be used: discrete logic circuit with logic gates for implementing logical functions on data signals, application specific integrated circuit with suitable combination logic gates, programmable gate array, field programmable gate array, etc.

[0155] Those skilled in the art of the present technology can understand that all or part of the steps carried out by the above-mentioned embodiment methods can be completed by programs instructing related hardware, and the programs can be stored in a computer readable storage medium, and the programs include one or a combination of steps of the method embodiments when executed.

[0156] Although the embodiments of the present application have been shown and described above, it should be understood that the above-mentioned embodiments are exemplary and cannot be understood as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above-mentioned embodiments within the scope of the present application.

Claims

1. A method of quantitatively adjusting the degree of servo dynamic characteristic matching, characterized by, The method comprises the following steps: building a machine tool shaft model according to a preset motor servo control system structure and a preset mechanical transmission system structure; based on the machine tool shaft model, establishing a transfer function between an input and a tracking error in a complex frequency domain with a position instruction as an input signal; optimizing the transfer function, and based on the optimized transfer function, combining a continuous step signal with a delay theorem to obtain a tracking error model in a time domain through inverse Laplace transform; and substituting the tracking error model in the time domain into a servo dynamic characteristic matching characteristic value expression to obtain a quantitative relationship between a position loop proportional amplification coefficient and the servo dynamic characteristic matching characteristic value, and quantitatively adjusting the servo dynamic characteristic matching degree based on the quantitative relationship; the optimization of the transfer function comprises: obtaining a machine tool shaft system structure parameter order of magnitude in the machine tool shaft model; and optimizing the transfer function according to the machine tool shaft system structure parameter order of magnitude; the optimized transfer function is: ； wherein, is the optimized transfer function, is the position loop proportional gain factor; the quantitative relationship is: . wherein, is a characteristic value for matching the servo dynamic characteristics, is is a proportional amplification coefficient of the shaft position loop, is a proportional amplification coefficient of the y-shaft position loop, is a servo period.

2. The method according to claim 1, characterized in that, the preset motor servo control system adopts a PID control structure; the preset mechanical transmission system adopts a screw nut or a worm and gear structure.

3. A device for quantitative adjustment of the degree of servo dynamic characteristic matching, characterized in that comprise: a building module configured to build a machine tool shaft model according to a preset motor servo control system structure and a preset mechanical transmission system structure; an establishing module configured to, based on the machine tool shaft model, establish a transfer function between an input and a tracking error in a complex frequency domain with a position instruction as an input signal; an optimization module configured to optimize the transfer function, and based on the optimized transfer function, combine a continuous step signal with a delay theorem to obtain a tracking error model in a time domain through inverse Laplace transform; and an adjusting module configured to substitute the tracking error model in the time domain into a servo dynamic characteristic matching characteristic value expression to obtain a quantitative relationship between a position loop proportional amplification coefficient and the servo dynamic characteristic matching characteristic value, and quantitatively adjust the servo dynamic characteristic matching degree based on the quantitative relationship; the optimization module is further configured to: obtain a machine tool shaft system structure parameter order of magnitude in the machine tool shaft model; and optimize the transfer function according to the machine tool shaft system structure parameter order of magnitude; the optimized transfer function is: ； wherein, is the optimized transfer function, is the position loop proportional gain factor; the quantitative relationship is: . wherein, is a servo dynamic characteristic matching eigenvalue, is is an axis position loop proportional amplification coefficient, is a y-axis position loop proportional amplification coefficient, is a servo period.

4. An electronic device, comprising: comprise: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the servo dynamic characteristic matching degree quantitative adjustment method according to any one of claims 1-2.

5. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the servo dynamic characteristic matching degree quantitative adjustment method according to any one of claims 1-2.

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