Energy consumption control method and system of numerical control machine tool

Abstract

The invention relates to the technical field of numerical control machine tool energy consumption control, and discloses an energy consumption control method and system for a numerical control machine tool, and the method comprises the steps: collecting the operation parameters of a servo motor in real time, and constructing a dynamic state matrix; calculating a load proportion and total energy consumption based on the dynamic state matrix, and judging a load balance state of the servo motor; further constructing a multi-objective optimization model, and solving an energy consumption optimization value and a load proportion optimization value of the servo motor in combination with a particle swarm optimization algorithm; compared with the prior art that operation energy consumption control of a servo motor is rough, and particularly under the conditions of a complex machining path and multi-axis cooperative machining, energy consumption optimization and load balancing cannot be effectively considered, the technical problem that in the prior art, energy consumption optimization and load balancing cannot be effectively considered is solved. According to the invention, collaborative optimization of energy consumption and load among the servo motors is realized, so that the problems of energy consumption waste and uneven load distribution are avoided, and the energy efficiency of the numerical control machine tool under complex processing conditions is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of energy consumption control of numerical control machine tools, and particularly relates to an energy consumption control method and system for a numerical control machine tool. Background Art

[0002] Currently, there are still significant deficiencies in the energy consumption control of numerical control machine tools in complex machining tasks. For example, in the case of multiple-axis servo motors running simultaneously, the load distribution of the servo motors often relies on static parameter settings and cannot be dynamically adjusted according to the real-time operating state, resulting in energy consumption waste and uneven load among servo motors. In addition, the existing technologies often focus on energy consumption optimization and load synchronization performance separately, lacking a comprehensive control method that takes both into account, especially in scenarios of complex machining paths and multi-workpiece collaborative machining, where efficient energy consumption control cannot be fully satisfied. Therefore, there is an urgent need for an energy consumption control method that can still achieve energy consumption minimization and load balance under the dynamic change of the load of multiple-axis servo motors to improve the operating efficiency and machining quality of numerical control machine tools. Summary of the Invention

[0003] Aiming at the above-mentioned existing technical deficiencies, the purpose of the present invention is to propose an energy consumption control method for a numerical control machine tool, aiming to solve the technical problem that the energy consumption control of servo motor operation in the existing technology is relatively rough, especially under complex machining paths and multi-axis collaborative machining conditions, and it is impossible to effectively take into account both energy consumption optimization and load balance.

[0004] To solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides an energy consumption control method for a numerical control machine tool,

[0005] The energy consumption control method for the numerical control machine tool includes:

[0006] Step S10: Real-time collect and calculate the operating parameters of the i-th servo motor of the numerical control machine tool, including:

[0007] Torque T i : The output torque of the servo motor, used to measure the mechanical output ability of the motor; rotational speed ω i : The rotational speed of the servo motor, used to reflect the real-time motion state of the motor; real-time load L i : The working load currently borne by the servo motor, defined as the ratio of torque to rotational speed; energy consumption P i : The energy consumption of the servo motor per unit time, calculated according to current and voltage; store the collected operating parameters of the servo motor as a dynamic state matrix S at time interval Δt, where n is the number of servo motors;

[0008] Step S20: Calculate the load ratio r i and the total energy consumption Ptotal , according to the load ratio r i Determine whether the servo motor is in a load balancing state, preset a load balancing threshold ε. If the load ratio r of the servo motor i is greater than the load balancing threshold ε, then proceed to the next step for optimization; otherwise, maintain the current step state;

[0009] Step S30: Construct the first multi-objective optimization model F1 according to the energy consumption P i The formula is:

[0010]

[0011] where is the average energy consumption of all servo motors; α is the energy consumption deviation penalty coefficient; the model F1 is used to represent the energy consumption synchronization between servo motors;

[0012] Construct the second multi-objective optimization model F2 according to the load ratio r i The formula is:

[0013]

[0014] where is the average load ratio; the model F2 is used to represent the load synchronization between servo motors;

[0015] Integrate the first multi-objective optimization model F1 and the second multi-objective optimization model F2 to obtain the third multi-objective optimization model F3. The formula is:

[0016] F3 = w1·F1 + w2·F2

[0017] where w1 and w2 are objective weight coefficients;

[0018] Introduce the particle swarm optimization algorithm, and use the third multi-objective optimization model F3 as the objective function of the particle swarm optimization algorithm to solve and obtain the optimization results. The optimization results include the energy consumption optimization value p of the servo motor aim and the load ratio optimization value r of the servo motor aim ;

[0019] Step S40: Adjust the energy consumption P of the servo motor based on the optimization results i , including: Calculate the load correction value ΔP according to the current load ratio r i and the load ratio optimization value r aim , and adjust the energy consumption P according to the load correction value ΔP i to obtain the corrected energy consumption P i i i ; Preset the corrected energy consumption safety threshold P new safe ​​, if |P i new -p aim | > P safe , then adjust the corrected energy consumption P i new = P safe ;

[0020] Step S50: After the energy consumption is adjusted and corrected, loop through steps S10 to S50.

[0021] Preferably, in step S10, the real-time load L i is calculated by the formula

[0022] Preferably, in step S10, the energy consumption P i is calculated by the formula P i = V i ·I i ·η, where V i is the motor voltage, I i is the motor current, and η is the motor efficiency.

[0023] Preferably, in step S20, the load ratio r i is used to measure the contribution ratio of each servo motor in the total load, and the calculation formula is where is the total load of all servo motors; the total energy consumption P total is defined as the sum of the energy consumptions of all servo motors, and the calculation formula is and is used to evaluate the overall energy consumption level.

[0024] Preferably, in step S40, the load correction value ΔP i is calculated by the formula:

[0025] ΔP i = β·(r i -r aim )

[0026] where β is the load correction coefficient.

[0027] Preferably, in step S40, the load correction value ΔP i is calculated by the formula P i new = P i +ΔP i .

[0028] Preferably, in step S10, the acquisition time interval Δt of the servo motor operating parameters is dynamically set according to actual requirements.

[0029] The present invention also provides an energy consumption control system for a numerically controlled machine tool, including:

[0030] A data acquisition module for real-time acquisition and calculation of the operating parameters of the i-th servo motor of a numerically controlled machine tool, including:

[0031] Torque T i : The output torque of the servo motor, used to measure the mechanical output ability of the motor; rotational speed ω i : The rotational speed of the servo motor, used to reflect the real-time motion state of the motor; real-time load L i : The working load currently borne by the servo motor, defined as the ratio of torque to rotational speed; energy consumption P i : The energy consumption of the servo motor per unit time, calculated based on current and voltage; store the collected operating parameters of the servo motor as a dynamic state matrix S at time intervals Δt, where n is the number of servo motors;

[0032] A state analysis module for calculating the load ratio r i and total energy consumption P total based on the dynamic state matrix S, i judge whether the servo motor is in a load balancing state, preset a load balancing threshold ε, if the load ratio r i of the servo motor is greater than the load balancing threshold ε, then enter the next step for optimization, otherwise maintain the current step state;

[0033] An optimization modeling module for constructing a first multi-objective optimization model F1 according to the energy consumption P i , and the formula is:

[0034]

[0035] where, is the average energy consumption of all servo motors; α is the energy consumption deviation penalty coefficient; the model F1 is used to represent the energy consumption synchronization among servo motors;

[0036] Construct a second multi-objective optimization model F2 according to the load ratio r i , and the formula is:

[0037]

[0038] where, is the average load ratio; the model F2 is used to represent the load synchronization among servo motors;

[0039] Integrate the first multi-objective optimization model F1 and the second multi-objective optimization model F2 to obtain a third multi-objective optimization model F3, and the formula is:

[0040] F3 = w1·F1 + w2·F2

[0041] Among them, w1 and w2 are target weight coefficients;

[0042] The particle swarm optimization algorithm is introduced, and the third multi-objective optimization model F3 is used as the objective function of the particle swarm optimization algorithm to solve the optimization results. The optimization results include the energy consumption optimization value p of the servo motor. aim and the load ratio optimization value r of the servo motor aim ;

[0043] Energy consumption adjustment module, used to adjust the energy consumption P of the servo motor based on the optimization results i , including: according to the current load ratio r i and load ratio optimization value r aim Calculate the load correction value ΔP i , according to the load correction value ΔP i Adjust energy consumption P i Get the corrected energy consumption P i new ; Preset modified energy consumption safety threshold P safe , if |P i new -p aim |>P safe , then adjust the corrected energy consumption P i new =P safe ;

[0044] The loop control module is used to loop through steps S10 to S50 after the energy consumption is adjusted and corrected.

[0045] The present invention also provides an energy consumption control device for a CNC machine tool, comprising a memory, a processor, and an energy consumption control program for the CNC machine tool stored in the memory and executable on the processor. When the energy consumption control program for the CNC machine tool is executed by the processor, the energy consumption control method for the CNC machine tool is implemented.

[0046] The present invention also provides a computer program product, including an energy consumption control program for a numerically controlled machine tool, wherein the energy consumption control program for the numerically controlled machine tool implements the energy consumption control method for the numerically controlled machine tool when executed by a processor.

[0047] The beneficial effects of the present invention are as follows: compared with the prior art, the servo motor operation energy consumption control is relatively rough, especially under the conditions of complex processing paths and multi-axis collaborative processing, which cannot effectively take into account the technical problems of energy consumption optimization and load balancing;

[0048] Because the present application realizes the coordinated optimization control of energy consumption and load between servo motors by introducing multi-objective optimization modeling and feedback adjustment mechanism, it avoids the problems of energy waste and uneven load distribution and improves the energy efficiency of CNC machine tools under complex processing conditions. Brief Description of the Drawings

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0050] Figure 1 It is a schematic flowchart of the first embodiment of an energy consumption control method for a numerically controlled machine tool according to the present invention.

[0051] Figure 2 It is a schematic diagram of the equipment of an energy consumption control method for a numerically controlled machine tool according to the present invention. Detailed Embodiments

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0053] Embodiment 1: As Figure 1 shown, it is a schematic flowchart of the first embodiment of the energy consumption control method for the numerically controlled machine tool of the present invention, and the first embodiment of the energy consumption control method for the numerically controlled machine tool of the present invention is proposed.

[0054] In the first embodiment, the energy consumption control method for the numerically controlled machine tool includes:

[0055] Step S10: Real-time collect and calculate the operating parameters of the i-th servo motor of the numerically controlled machine tool, including:

[0056] Torque T i : The output torque of the servo motor, with the unit of N·m, used to measure the mechanical output ability of the motor; rotational speed ω i : The rotational speed of the servo motor, with the unit of RPM / min, used to reflect the real-time motion state of the motor; real-time load L i : The working load currently borne by the servo motor, defined as the ratio of torque to rotational speed, with the unit of N·m / RPM; energy consumption P i : The energy consumption of the servo motor per unit time, with the unit of W, calculated according to current and voltage; store the collected operating parameters of the servo motor as a dynamic state matrix S at time interval Δt, where n is the number of servo motors;

[0057] It should be understood that the relationship between torque, rotational speed, load, and energy consumption can be used to evaluate the operating efficiency of a servo motor. For example, by analyzing the changes in energy consumption and real-time load, it can be determined whether the servo motor is operating overloaded or wasting energy; the construction of the dynamic state matrix provides data support for subsequent energy consumption optimization algorithms. Through matrix S, the state changes of the servo motor can be monitored in real time, providing a basis for energy consumption control and load balancing optimization.

[0058] For example, there are 3 servo motors with the following operating parameters: The first servo motor, T1 = 10 N·m, ω1 = 150 RPM / min, P1 = 500 W; the second servo motor: T2 = 15 N·m, ω2 = 200 RPM / min, P2 = 600 W; the third servo motor: T3 = 8 N·m, ω3 = 120 RPM / min, P3 = 400 W; Calculate the real-time load The dynamic state matrix is: Through this matrix, the operating state of the servo motor can be further analyzed to determine whether the load is balanced and whether the energy consumption needs to be optimized.

[0059] Step S20: Calculate the load ratio r i and the total energy consumption P total based on the dynamic state matrix S. According to the load ratio r i determine whether the servo motor is in a load-balanced state. Preset the load-balancing threshold ε. If the load ratio r i of the servo motor is greater than the load-balancing threshold ε, then proceed to the next step for optimization; otherwise, maintain the current step state.

[0060] It should be noted that the load ratio r i is used to measure the contribution ratio of each servo motor in the total load, and the calculation formula is where is the total load of all servo motors; the total energy consumption P total is defined as the sum of the energy consumption of all servo motors, and the calculation formula is with the unit of W, which is used to evaluate the overall energy consumption level.

[0061] It can be understood that when the load ratio of the servo motor is close to 1 / n, it means that the load distribution is uniform. Theoretically, if the load of all servo motors is completely balanced, the load ratio is 1 / n. However, in actual operation, due to differences in processing paths, workpiece weights, or servo motor performance, the load ratio will deviate. If the difference in the load ratio between servo motors exceeds the threshold, it indicates that the current load distribution is unbalanced and needs to be readjusted through optimization steps.

[0062] For example, there are 3 servo motors, and their real-time loads are L1 = 0.067 N·m / RPM, L2 = 0.075 N·m / RPM, and L3 = 0.060 N·m / RPM; calculate the total load: Calculate the load ratio: Calculate the difference in load ratios: max(r i ) - min(r i ) = 0.371 - 0.297 = 0.074; if the preset load balancing threshold ε = 0.05, then 0.074 > 0.05, indicating that the load is unbalanced and the next step of optimization is required, otherwise maintain the current state.

[0063] Step S30: According to the energy consumption P i Construct the first multi-objective optimization model F1, and the formula is:

[0064]

[0065] where, is the average energy consumption of all servo motors; α is the energy consumption deviation penalty coefficient; the model F1 is used to represent the energy consumption synchronization between servo motors;

[0066] According to the load ratio r i Construct the second multi-objective optimization model F2, and the formula is:

[0067]

[0068] where, is the average load ratio; the model F2 is used to represent the load synchronization between servo motors;

[0069] Combine the first multi-objective optimization model F1 and the second multi-objective optimization model F2 to obtain the third multi-objective optimization model F3, and the formula is:

[0070] F3 = w1·F1 + w2·F2

[0071] where, w1 and w2 are the objective weight coefficients;

[0072] Introduce the particle swarm optimization algorithm, and use the third multi-objective optimization model F3 as the objective function of the particle swarm optimization algorithm to solve and obtain the optimization results. The optimization results include the energy consumption optimization value p aim of the servo motor and the load ratio optimization value r aim of the servo motor;

[0073] It should be noted that the first multi-objective optimization model minimizes the difference in energy consumption between servo motors while ensuring the minimum total energy consumption, thereby reducing energy waste; the second multi-objective optimization model emphasizes the load synchronization between servo motors to avoid the situation where some servo motors are overloaded while other servo motors are idle; particle swarm optimization is an iterative optimization algorithm that finds the optimal solution by simulating the movement of particles in the search space, and is suitable for complex multi-objective optimization problems.

[0074] It can be understood that the priorities of total energy consumption optimization and load synchronization optimization are balanced by weights w1 and w2, and the weights can be dynamically adjusted according to the application scenario. For example, if more attention is paid to energy saving, w1 can be increased, and if more attention is paid to load balancing, w2 can be increased.

[0075] Step S40: Adjust the energy consumption P of the servo motor based on the optimization result i , including: according to the current load ratio r i and load ratio optimization value r aim Calculate the load correction value ΔP i , according to the load correction value ΔP i Adjust energy consumption P i Get the corrected energy consumption P i new ; Preset corrected energy consumption safety threshold P safe , if |P i new -p aim |>P safe , then adjust the corrected energy consumption P i new =P safe ;

[0076] For example, the current parameters are as follows: Current load ratio r i =0.35, target load ratio r aim =0.30, current energy consumption P i =600W, target energy consumption P aim =550W, energy consumption safety threshold P safe =50W; Correction calculation: load correction value ΔP i =β·(r i -r aim ), let β = 1000, then ΔP i =1000·(0.35-0.30)=50W, corrected energy consumption P i new =P i -ΔP i =600-50=550W, check energy consumption deviation |P i new -Paim |=|550 - 550| = 0W, because the deviation is less than P safe , no further adjustment is required, and the finally adjusted energy consumption P i ncw = 550W, meeting the optimization goal and safety requirements.

[0077] It should be understood that the energy consumption correction is an iterative process. As the load ratio is adjusted, the energy consumption correction value will gradually tend to zero, and finally the optimal energy consumption distribution of the servo motor is achieved; the setting of the safety threshold needs to comprehensively consider the rated power of the servo motor, the actual operating state and the fault protection requirements, and usually can be set according to 80%-90% of the rated power of the servo motor; during the energy consumption correction process, too large a correction value may cause the operating state of the servo motor to be unstable, and too small a correction value may cause the optimization to converge slowly. Therefore, the setting of the correction coefficient and the safety threshold needs to balance efficiency and stability.

[0078] Step S50: After the energy consumption adjustment is corrected, steps S10 to S50 are repeatedly executed in a loop.

[0079] It should be noted that the core of step S50 is to form a closed-loop optimization control process by repeatedly executing steps S10 to S50, so that the energy consumption and load state of the servo motor can be continuously and dynamically adjusted to achieve real-time optimization; after each round of energy consumption adjustment, the new servo motor operating parameters including energy consumption, load ratio, etc. will re-enter the acquisition and calculation steps to ensure that the system can respond in a timely manner to changes in processing conditions.

[0080] In addition, an energy consumption control system for a numerically controlled machine tool provided by the present invention adopts an energy consumption control method for a numerically controlled machine tool in the above embodiment, and can solve the technical problem of energy consumption control of a numerically controlled machine tool. Compared with the prior art, the beneficial effects of the energy consumption control system for a numerically controlled machine tool provided by the present invention are the same as those of the energy consumption control method for a numerically controlled machine tool provided in the above embodiment, and other technical features in the energy consumption control system for a numerically controlled machine tool are the same as the features disclosed in the above embodiment method, and will not be elaborated here.

[0081] The present invention provides an energy consumption control device for a numerically controlled machine tool. Please refer to Figure 2, An energy consumption control device for a numerically controlled machine tool includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute an energy consumption control method for a numerically controlled machine tool in Embodiment 1 above. An energy consumption control device for a numerically controlled machine tool in an embodiment of the present invention may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. An energy consumption control device for a numerically controlled machine tool is merely an example and should not impose any limitations on the functions and scope of use of embodiments of the present invention. An energy consumption control device for a numerically controlled machine tool may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which may execute various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM: Random Access Memory) 1004. In the RAM 1004, various programs and data required for the operation of an energy consumption control device for a numerically controlled machine tool are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems may be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 may allow an energy consumption control device for a numerically controlled machine tool to communicate with other devices wirelessly or wiredly to exchange data. Although an energy consumption control device for a numerically controlled machine tool with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be alternatively implemented or had.

[0082] The present invention also provides a computer program product, including a computer program which, when executed by a processor, implements the steps of an energy consumption control method for a numerical control machine tool as described above. The computer program product provided by the present invention can solve the technical problem of energy consumption control for a numerical control machine tool. Compared with the prior art, the beneficial effects of the computer program product provided by the present invention are the same as those of the energy consumption control method for a numerical control machine tool provided in the above embodiments, and will not be elaborated herein.

[0083] Specifically, according to the embodiments disclosed by the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, an embodiment disclosed by the present invention includes a computer program product which includes a computer program carried on a computer-readable medium, and the computer program includes program codes for executing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by a processing device 1001, it executes the above functions defined in the methods of the embodiments disclosed by the present invention.

[0084] It should be understood that the various parts disclosed by the present invention can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in a suitable manner in any one or more embodiments or examples.

[0085] Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these modifications and variations.

Claims

1. A method for controlling energy consumption of a CNC machine tool, characterized in that: Methods include: Step S10: real-time acquisition and calculation of the operating parameters of the ith servo motor of the CNC machine tool, including: Torque T i : The output torque of the servo motor is used to measure the mechanical output capacity of the motor; the speed ω i : The speed of the servo motor, used to reflect the real-time motion state of the motor; real-time load L i : The current workload of the servo motor, defined as the ratio of torque to speed; energy consumption P i : The energy consumption of the servo motor per unit time is calculated based on the current and voltage; the collected servo motor operating parameters are stored as a dynamic state matrix S at time intervals Δt, Where n is the number of servo motors; Step S20: Calculate the load ratio r based on the dynamic state matrix S i and total energy consumption P total , according to the load ratio r i Determine whether the servo motor is in a load balancing state, preset a load balancing threshold ε, if the load ratio of the servo motor is r i If it is greater than the load balancing threshold ε, it will enter the next step for optimization, otherwise it will keep the current step state; Step S30: According to the energy consumption P i Construct the first multi-objective optimization model F1, the formula is: in, is the average energy consumption of all servo motors; α is the energy consumption deviation penalty coefficient; Model F1 is used to represent the energy consumption synchronization between servo motors; According to the load ratio r i Construct the second multi-objective optimization model F2, the formula is: in, is the average load ratio; Model F2 is used to represent the load synchronization between servo motors; The third multi-objective optimization model F3 is obtained by integrating the first multi-objective optimization model F1 and the second multi-objective optimization model F2. The formula is: F3=w1·F1+w2·F2 Among them, w1 and w2 are target weight coefficients; The particle swarm optimization algorithm is introduced, and the third multi-objective optimization model F3 is used as the objective function of the particle swarm optimization algorithm to solve the optimization results. The optimization results include the energy consumption optimization value p of the servo motor. aim and the load ratio optimization value r of the servo motor aim ; Step S40: Adjust the energy consumption P of the servo motor based on the optimization result i , including: according to the current load ratio r i and load ratio optimization value r aim Calculate the load correction value ΔP i , according to the load correction value ΔP i Adjust energy consumption P i Get the corrected energy consumption P i new ; Preset modified energy consumption safety threshold P safe , if |P i new -p aim |>P safe , then adjust the corrected energy consumption P i new =P safe ; Step S50: After the energy consumption is adjusted and corrected, steps S10 to S50 are executed in a loop.

2. The energy consumption control method of a CNC machine tool according to claim 1, characterized in that: In step S10, the real-time load L i The calculation formula is 3. The energy consumption control method of a CNC machine tool according to claim 1, characterized in that: In step S10, the energy consumption P i The calculation formula is P i =V i I i ·η, where V i is the motor voltage, I i is the motor current and η is the motor efficiency.

4. The energy consumption control method of a CNC machine tool according to claim 1, characterized in that: In step S20, the load ratio r i It is used to measure the contribution ratio of each servo motor in the total load. The calculation formula is: in is the total load of all servo motors; the total energy consumption P total Defined as the sum of the energy consumption of all servo motors, the calculation formula is Used to assess overall energy consumption levels.

5. The energy consumption control method of a CNC machine tool according to claim 1, characterized in that: In step S40, the load correction value ΔP i The calculation formula is: ΔP i =β·(r i -r aim ) Where β is the load correction factor.

6. The energy consumption control method of a CNC machine tool according to claim 1, characterized in that: In step S40, the load correction value ΔP i The calculation formula is P i new =P i +ΔP i .

7. The energy consumption control method of a CNC machine tool according to claim 1, characterized in that: In step S10, the collection time interval Δt of the servo motor operating parameters is dynamically set according to actual needs.

8. An energy consumption control system for a CNC machine tool, characterized in that: The energy consumption control system of the CNC machine tool comprises: The data acquisition module is used to collect and calculate the operating parameters of the ith servo motor of the CNC machine tool in real time, including: Torque T i : The output torque of the servo motor is used to measure the mechanical output capacity of the motor; the speed ω i : The speed of the servo motor, used to reflect the real-time motion state of the motor; real-time load L i : The current workload of the servo motor, defined as the ratio of torque to speed; energy consumption P i : The energy consumption of the servo motor per unit time is calculated based on the current and voltage; the collected servo motor operating parameters are stored as a dynamic state matrix S at time intervals Δt, Where n is the number of servo motors; State analysis module, used to calculate the load ratio r based on the dynamic state matrix S i and total energy consumption P total , according to the load ratio r i Determine whether the servo motor is in a load balancing state, preset a load balancing threshold ε, if the load ratio of the servo motor is r i If it is greater than the load balancing threshold ε, it will enter the next step for optimization, otherwise it will keep the current step state; Optimization modeling module is used to optimize the energy consumption P i Construct the first multi-objective optimization model F1, the formula is: in, is the average energy consumption of all servo motors; α is the energy consumption deviation penalty coefficient; Model F1 is used to represent the energy consumption synchronization between servo motors; According to the load ratio r i Construct the second multi-objective optimization model F2, the formula is: in, is the average load ratio; Model F2 is used to represent the load synchronization between servo motors; The third multi-objective optimization model F3 is obtained by integrating the first multi-objective optimization model F1 and the second multi-objective optimization model F2. The formula is: F3=w1·F1+w2·F2 Among them, w1 and w2 are target weight coefficients; The particle swarm optimization algorithm is introduced, and the third multi-objective optimization model F3 is used as the objective function of the particle swarm optimization algorithm to solve the optimization results. The optimization results include the energy consumption optimization value p of the servo motor. aim and the load ratio optimization value r of the servo motor aim ; Energy consumption adjustment module, used to adjust the energy consumption P of the servo motor based on the optimization results i , including: according to the current load ratio r i and load ratio optimization value r aim Calculate the load correction value ΔP i , according to the load correction value ΔP i Adjust energy consumption P i Get the corrected energy consumption P i new ; Preset corrected energy consumption safety threshold P safe , if |P i new -p aim |>P safe , then adjust the corrected energy consumption P i new =P safe ; The loop control module is used to loop through steps S10 to S50 after the energy consumption is adjusted and corrected.

9. An energy consumption control device for a CNC machine tool, characterized in that: The energy consumption control device of the CNC machine tool comprises: a memory, a processor and an energy consumption control program of the CNC machine tool stored in the memory and executable on the processor. When the energy consumption control program of the CNC machine tool is executed by the processor, the energy consumption control method of the CNC machine tool described in any one of claims 1 to 7 is implemented.

10. A computer program product, characterized in that The computer program product comprises an energy consumption control program for a numerically controlled machine tool, and when the energy consumption control program for a numerically controlled machine tool is executed by a processor, the energy consumption control method for a numerically controlled machine tool described in any one of claims 1 to 7 is implemented.

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