Mechanism and cutting simulation fused numerical control machine tool energy consumption prediction method

Abstract

The invention relates to the technical field of numerical control machine tool energy consumption prediction, and discloses a total energy consumption prediction method based on fusion of a numerical control machine tool machining mechanism and metal cutting simulation. The total energy consumption is divided into standby energy consumption, auxiliary energy consumption, no-load energy consumption of a main shaft and a feed shaft and cutting load energy consumption by analyzing the working mechanism of the numerical control machine tool; building an energy consumption monitoring and analyzing system which comprises hardware equipment and a software system, and collecting power consumption data in a non-cutting state through actual monitoring and nonlinear regression so as to build a prediction model; a workpiece cutting process is simulated by adopting computer cutting simulation, cutting force and torque data are obtained, and a material removal power consumption model and an additional load power consumption model are deduced; and finally, building a total cutting power consumption mathematical model under actual process parameters, and designing an orthogonal experiment to verify the precision of the model. According to the method, the problems of high cost, low efficiency, poor safety and the like are solved, and the energy utilization efficiency is effectively improved.

Description

Technical Field

[0001] The invention relates to the technical field of energy consumption prediction for CNC machine tool processing, and discloses a method for predicting total energy consumption in a mechanical processing process based on the fusion of processing mechanism and metal cutting simulation. Background Art

[0002] Reducing energy consumption is a key issue for green and sustainable development of the manufacturing industry. As a typical energy-consuming equipment in the manufacturing industry, CNC machine tools play an important role. In actual production, machine tools usually show very low efficiency, and they have significant potential for energy conservation and emission reduction. Therefore, it is necessary to analyze the factors affecting the energy consumption of machine tool processing and establish an accurate energy consumption prediction model to achieve accurate evaluation and effective control of energy efficiency.

[0003] Since energy consumption is affected by the inherent uncertainty in the machining process and it is difficult to obtain energy consumption data, how to model energy consumption is a huge challenge. Existing energy consumption modeling methods mainly rely on machining theory, empirical models and intelligent algorithms. Existing machining theory and empirical models can explain the machining process, but the accuracy of the model is not enough; existing intelligent algorithms are overly dependent on data sets, and unreasonable data set division and small data samples will cause large errors in modeling. In discrete machining processes, it is difficult to obtain energy consumption data. For small sample and nonlinear energy consumption data sets, it is necessary to select a more appropriate and accurate modeling method to predict energy consumption.

[0004] Finite element simulation technology is widely used in the field of machining, such as the simulation of cutting force, cutting torque, and cutting temperature. It significantly reduces the cost of the experiment and has broad industrial application prospects. Summary of the invention

[0005] In response to the need for improvement in the prior art, the present invention provides a method for predicting the total energy consumption in the machining process based on the fusion of machining mechanism and metal cutting simulation. According to the operation complexity mechanism of the CNC machine tool machining process, the machine tool layer energy consumption data caused by power not used for cutting workpieces is actually collected, and the process layer energy consumption data caused by cutting force or cutting torque is numerically analyzed by cutting simulation. The two are combined to establish a total energy consumption model of the CNC machine tool in the metal machining process, realizing accurate and rapid prediction of the total energy consumption of the machining process.

[0006] The technical solution adopted to achieve the purpose of the present invention is as follows, that is, a total energy consumption prediction in the machining process based on the fusion of machining mechanism and metal cutting simulation, and the specific steps include the following:

[0007] Analyze the multi-component composition characteristics and cutting process mechanism of CNC machine tools, and convert the total energy consumption E total Divided into standby energy consumption E standby, auxiliary energy consumption E auxiliary , no-load energy consumption E of the spindle and feed axis idle and cutting load energy consumption E cutting ;

[0008] E total =E standby +E auxiliary +E idle +E cutting

[0009] According to the execution complexity of the machine tool, the total energy consumption is first divided into standby energy consumption Estandby, whose characteristics mainly include:

[0010]

[0011]

[0012] In the formula, E standby is the total standby energy consumption, t p ,t q is the start time and end time of standby, P standby P is the stable operating power during the standby period. i is the power consumed by the i-th component when the machine tool is in standby mode, n represents the total energy consumption of n devices in the standby stage, P con The power consumed by the control system is used to identify the processing code, calculate data and logic processing, output electrical signals to the servo drive devices of each axis, control the operation of electrical components and monitor the working status of the system. sc The power consumed by the display is used to display the input and output of the CNC system, which is convenient for observing the machining status of the machine tool. fan The power consumed by the fan device is used to reduce the temperature of the electronic control system. con , P scr and P fan These three parts are constant power, P lub and P sp They are the power consumed by the basic lubrication and cooling device in the high-voltage circuit and the spindle forced lubrication and cooling device, respectively. The power value is related to the efficiency of the relevant oil pump, workload, energy loss in the oil circuit, and oil supply cycle, and is a non-constant power.

[0013] According to the execution complexity of the machine tool, the total energy consumption is further divided into auxiliary energy consumption E auxiliary , its main features include:

[0014]

[0015] E auxiliary is the total auxiliary energy consumption, P i is the average power consumed by the i-th auxiliary device, tp i ,t q i is the start time and end time of the action performed by the i-th auxiliary device, n represents the total auxiliary action category during machine tool processing, P auxiliary It represents the sum of the instantaneous power of a task or multiple tasks in the current time period, P i is the power consumed by the i-th auxiliary action or state, P startup It is the instantaneous power when the machine tool is started. This power is used to power the electric cabinet, control panel, display, fan, etc. light It is used to provide the power required for lighting the internal processing controls of the machine tool. This part is constant power, P toolchange is the instantaneous power of the tool changing device during tool changing, P accelerate The instantaneous power used for the spindle to accelerate to the target speed value, P spraycool In order to stabilize the power consumed by spraying cutting fluid, the power value is related to the efficiency of the relevant oil pump, workload, energy loss in the oil circuit and oil supply cycle. Assuming that the flow rate during the cutting process is a constant value, the power size is also constant, P rapid The power consumed by the feed axis to reach the maximum feed speed when achieving rapid feed or rapid retract. Its calculation and demand will vary depending on the number of axes of the machine tool. In a multi-axis machine tool, the movement of each axis consumes power, and different axes may have different acceleration, speed and load conditions. The movement directions of different axes (X-axis, Y-axis, Z-axis) may cause different loads and friction, which affects the power consumption of each axis. blowair Power consumed by the air blowing cleaning and cooling device;

[0016] According to the execution complexity of the machine tool, the total energy consumption is then divided into no-load cutting energy consumption E idle , its main features include:

[0017]

[0018] E idle Total energy consumption of the machine tool during the no-load cutting phase, P idle is the instantaneous power value at a certain no-load cutting moment, t p ,t q is the start time and end time of the no-load action, n represents the number of energy-consuming devices in the no-load stage, which mainly comes from the no-load power consumption of the spindle rotation P spindle and feed axis no-load operation power consumption P feed , where the feed axis operation power consumption depends on the number of feed axis movements m involved in the machining path;

[0019] According to the execution complexity of the machine tool, the total energy consumption is finally divided into cutting energy consumption Ecutting , its main features include:

[0020]

[0021] Total cutting power P cutting Includes the effective material removal power P caused by cutting force and cutting torque required to overcome the plastic deformation of the material remove and the additional load loss power consumption P caused by the limited transmission efficiency of the machine tool additional It consists of two parts.

[0022] Build a real-time monitoring system for electric energy consumption of CNC machine tools, such as Figure 2 As shown in the diagram of the energy consumption mechanism analysis of the operation complexity of CNC machine tools, it mainly includes two parts: hardware equipment and software application;

[0023] The real-time monitoring method is used to collect various power consumption data of CNC machine tools in non-cutting state, and the corresponding energy consumption mathematical prediction model of each component is established through regression analysis method:

[0024] E accelerate =Αn 2 +Bn+C

[0025] The measurement items are mainly the average power consumption E of the CNC machine tool spindle in acceleration state. accelerate , the energy consumption of the whole process from the beginning of acceleration to reaching the stable speed state can be obtained by integrating the power over time. If the spindle speed is determined when the machine tool is started, the energy consumption of the startup process is also determined, which means that the startup energy consumption fitting function of the machine tool can be obtained by curve fitting;

[0026]

[0027] The measurement items are mainly the startup instantaneous power P of the CNC machine tool. startup , the energy consumption of the entire process from startup to reaching a stable operating state can be obtained by integrating the power over time.

[0028]

[0029] The measurement items are mainly the lighting power P of CNC machine tools. light , consuming electrical energy and generating heat. The lighting device power is a fixed value, which can be obtained by turning on the lighting device to collect m power values ​​for a period of time and taking the arithmetic average.

[0030]

[0031] The measurement items are mainly the basic power P of the tool change action of the CNC machine tool toolchangeThe average power required for automatic tool change from position i to the next position can be obtained by collecting m power values ​​multiple times and performing arithmetic averaging.

[0032]

[0033] The measurement items are mainly the power P of CNC machine tool cutting fluid in a stable spraying state. sparycool The main energy-consuming parts of the cutting fluid supply device are the motor and the pump. Since the cutting fluid flow rate and pressure are the specified values ​​during the use of the cutting fluid, the loss in the circuit is basically unchanged, so its power value is approximately a constant value. The power of the cutting fluid supply device can be obtained by starting the cutting fluid supply device to collect m power values ​​for a period of time and taking the arithmetic average.

[0034]

[0035] The measurement items are mainly the power P of the CNC machine tool during rapid feed rapid Rapid feed motion is usually used for rapid positioning in CNC machining processes. In this process, the sudden increase in feed speed usually causes the appearance of power peaks, which can be obtained by integrating the power over time.

[0036]

[0037] The measurement items are mainly the power P when the CNC machine tool blowing device is turned on. blowair The gas flow and working pressure used by the blowing device are specifically specified, so it can be regarded as a constant gas pressure and airflow. The power consumed by the blowing device is the product of the gas flow and gas pressure per unit time as a fixed value. The corresponding power can be obtained by turning on the blowing device and collecting m power values ​​within a period of time and taking the arithmetic average.

[0038]

[0039] The measurement items are mainly the inherent spindle rotation power P of the CNC machine tool in the no-load cutting state. spindle ,like Figure 4 As shown in the scatter plot of the measured spindle idling power and the smoothing process, according to the characteristics of the main transmission system of the CNC machine tool, the main transmission system includes high-speed and low-speed transmission chains. Therefore, the spindle power model of the CNC machine tool should be modeled and studied in sections.

[0040]

[0041] The measurement items are mainly the inherent feed power P of the CNC machine tool in the no-load cutting state. feed The motion of the feed axis can be divided into two categories. One is the feed motion on the horizontal plane, such as the axis feed P of CNC milling machines and machining centers. feed-X , Pfeed-Y The other type is the feed motion on the vertical plane, such as the axial feed P of the machining center. feed-Z- and downward feed P feed-Z+ .

[0042] Formulate relevant process parameters, determine the workpiece material, select the appropriate tool and processing method, and select the appropriate cutting speed v, feed speed f, and cutting depth a according to the shape and size of the workpiece p and cutting width a e ,The orthogonal experimental design is shown in Table 1. For the actual cutting of the workpiece material, the finite element cutting simulation is used to simulate the real machining process of the workpiece. After obtaining the key cutting force and cutting torque data, the theoretical effective material removal power consumption model is further derived. On this basis, the additional load power consumption model caused by mechanical transmission loss is theoretically modeled;

[0043] Table 1 Experimental factors and levels

[0044]

[0045] Based on the process parameters proposed in Table 1, a three-dimensional cutting model of the workpiece and cutting tool is built, and the material parameters related to the workpiece, such as density, inelastic heat fraction, melting point, thermal conductivity, specific heat capacity, Young's modulus, Poisson's ratio, expansion rate, Johnson-cook model parameters and failure parameters, are searched. The relevant material coefficients are imported into ABAQUS, and the analysis steps, interactions, loads, and grid divisions are set in sequence. Finally, the dynamic thermal-mechanical coupling cutting simulation is displayed for the actual cutting stage of the machine tool, and the relevant cutting force and cutting torque are output, and the material removal power P in the cutting power is further analyzed. remove In addition, Figure 5 As shown in the figure, the three major deformation power consumption areas of metal material removal. The cutting power consumption mode has the following three parts: Plastic deformation power loss P p ; Friction power consumption P in tool-workpiece contact area f ; Chip kinetic energy, surface energy and elastic deformation power loss P e Therefore, the finite element software is used to analyze the material deformation characteristics of the workpiece:

[0046] P remove =P p +P f +P e

[0047] P remove =T·ω+F·ν f

[0048]

[0049] Padditional =αP remove

[0050]

[0051] Build a total cutting power consumption model for CNC machine tools:

[0052]

[0053] Orthogonal experiments under real working conditions are designed, and main effect analysis, variance analysis and prediction accuracy analysis of the regression model are carried out to verify the effectiveness of the model. According to the processing requirements, the processing method is determined and the machine tool and tool model are selected. On this basis, the range of processing parameters is reasonably formulated. The implementation case of the present invention application is CNC side milling finishing. The workpiece material is selected as a typical 45# steel plate (45#), without any quenching and tempering and heat treatment. The workpiece size specification is 70mm×30mm×20mm; the processing tool is a 65-degree tungsten steel material carbide four-edge flat bottom end mill, the basic size parameters are 10*25*10D*75 (mm) (edge ​​diameter*edge length*shank diameter*total length), the helix angle is 40 degrees, the cutting edge width is 1mm, and the groove angle is 40 degrees. Referring to the machine tool performance constraints and the processing range recommended by the tool manufacturer, the side milling is established with four factors and three levels of spindle speed, feed speed, milling width, and milling depth as independent variables. The L27 (313) experimental scheme that conforms to the Taguchi orthogonal array is shown in Table 2.

[0054] Table 2 Orthogonal array L 27 (3 13 ) Experimental Design

[0055]

[0056] Least squares regression prediction model for total cutting load power:

[0057]

[0058] Table 3 Variance analysis of total cutting load power prediction model

[0059]

[0060] Features and beneficial effects of the present invention:

[0061] This method effectively solves the problems of high cost, low efficiency, poor safety, and difficulty in measuring key experimental data in actual processing. Relying on the interaction between the processing mechanism of CNC machine tools and metal cutting simulation, it can calculate the power level and energy consumption status of CNC machine tools in different processing periods. Through analysis, the peak and trough periods of energy consumption can be found to optimize the energy utilization efficiency in the processing process. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 Flowchart of Energy Consumption Modeling for CNC Machine Tools

[0063] Figure 2 Analysis diagram of energy consumption mechanism of CNC machine tool operation complexity

[0064] Figure 3 Measured power curve distribution diagram of three-axis CNC machining center GX600

[0065] Figure 4 Scatter plot and smoothing of measured spindle idling power

[0066] Figure 5 Three major deformation power consumption areas during metal material removal DETAILED DESCRIPTION

[0067] The following will be combined with the drawings in the implementation cases of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Without departing from the above technical ideas of the present invention, various replacements and changes are made according to the common technical knowledge and customary means in the field, which should be included in the protection scope of the present invention.

[0068] The present invention discloses a method for predicting the total energy consumption of CNC machine tools in a machining process based on the fusion of machining mechanism and metal cutting simulation. Figure 1 As shown, the following steps are included:

[0069] Analyze the multi-component composition characteristics and cutting process mechanism of CNC machine tools, and convert the total energy consumption E total Divided into standby energy consumption E standby , auxiliary energy consumption E auxiliary , no-load energy consumption E of the spindle and feed axis idle and cutting load energy consumption E cutting .

[0070] Build a real-time monitoring system for electric energy consumption of CNC machine tools, such as Figure 2 As shown in the diagram of the energy consumption mechanism analysis of the operation complexity of CNC machine tools, it mainly includes two parts: hardware equipment and software application. The main hardware equipment of this system uses a three-phase electric power meter YP9830 produced by Shenzhen Yongpeng Instrument Co., Ltd., and the PC uses ASUS laptop Flying Fortress 6, the operating system is WINDOWS11, and the software part uses the manufacturer's supporting test software Yongpeng Electric Three-Phase Tester V3.0. Take the 810D / GX600 three-axis vertical machining center produced by Hardinge Company of the United States as an example to demonstrate the construction of this test system, and deploy the power tester at the power bus of the machine tool equipment to collect the total power to obtain the energy consumption data of the machine tool.

[0071] like Figure 3 , Figure 4 As shown, a real-time monitoring method is used to collect various power consumption data of CNC machine tools in non-cutting state, and a mathematical prediction model for energy consumption corresponding to each component is established through regression analysis.

[0072]

[0073]

[0074]

[0075]

[0076] E accelerate =0.0024n 2 +1.824n+68.2

[0077]

[0078]

[0079]

[0080]

[0081] P blowair =102.468W

[0082]

[0083] P feed-X =5.2328+0.012022ν fX +1.5419×10 -6 ν fX 2 (R 2 =0.99818)

[0084] P feed-Y =2.6892+0.011787ν fY +1.1014×10 -6 ν fY 2 (R 2 =0.99814)

[0085] P feed-Z+ =-4.1785-0.020092ν fZ+ +1.9957×10 -6 ν fZ+ 2 (R 2 =0.99243)

[0086] P feed-Z- =5.3862+0.09527ν fZ- +1.9981×10 -6 ν fZ- 2 (R 2 =0.99542)

[0087] like Figure 5 The three major deformation power consumption areas during metal material removal are shown in the figure. Finite element cutting simulation is used to explain the real deformation power consumption of the workpiece. The key cutting force and cutting torque data obtained through 3D milling simulation are used to derive the dynamic power formula. The derivation process is as follows:

[0088]

[0089] Where T is the torque acting on the outer circumference of the tool axial cross section, n is the corresponding spindle speed, and F f is the magnitude of the force in the feed direction, v f is the feed speed.

[0090] Check the machine tool manual, inverter and motor nameplate in detail, and consult the motor manufacturer to perform theoretical calculations on the load energy loss coefficient of the machine tool's main power system to obtain the load loss power model P caused by the cutting load. additional , this load loss coefficient is a constant, generally between 0.15 and 0.25:

[0091] Table 4 Basic data of CNC machining center Siemens810D / GX600 machine tool

[0092]

[0093]

[0094]

[0095] Where, t 1 , t 2 , t 3 , t 4 , t 5 , t 6 , t 7 , t 8 , t 9 are the working time or energy consumption time of each component during the processing, and N is the number of tool changes.

Claims

1. A method for predicting the total energy consumption of CNC machine tools by integrating mechanism and cutting simulation. It is characterized in that The following steps are involved: S1, analyze the multi-component composition characteristics and cutting process mechanism of CNC machine tools, and convert the total energy consumption E total Divided into standby energy consumption E standby , auxiliary energy consumption E auxiliary , no-load energy consumption E of the spindle and feed axis idle and the total energy consumption of cutting load E cutting ; S2, build a real-time monitoring system for electric energy consumption of CNC machine tools, which mainly includes hardware equipment and software applications; S3, using a real-time monitoring method to collect various power consumption data of the CNC machine tool in a non-cutting state, and establishing a mathematical prediction model of fixed power or energy consumption corresponding to each component through a nonlinear regression analysis method; S4, for the actual cutting of workpiece materials, finite element cutting simulation is used to simulate the real machining process of the workpiece. After obtaining the key cutting force and cutting torque data, the theoretical material removal power consumption model is further derived in combination with the kinetic energy theorem in cutting processing; S5, combining the machine tool manual, inverter and motor nameplate, and consulting the motor manufacturer, theoretically calculate the load energy loss coefficient of the main power system of the machine tool, and on this basis, theoretically model the additional load power consumption model caused by mechanical transmission loss; S6, based on S4 and S5, models the total energy consumption of the most complex cutting load in the CNC machine tool processing process, establishes a nonlinear regression model of the total power of the cutting load in detail, and performs variance analysis to verify the accuracy and effectiveness of the model; S7, build a total power consumption model for the entire machining process of CNC machine tools.

2. The method for predicting the total energy consumption of a CNC machine tool according to claim 1, It is characterized in that In step S1, the energy consumption mechanism of the operation complexity in the CNC machine tool processing process is analyzed, as shown in Figure 2: S101, according to the execution complexity of the machine tool, the total energy consumption is first divided into standby energy consumption E standby , its main features include: S102, the total energy consumption is further divided into auxiliary energy consumption E according to the execution complexity of the machine tool auxiliary , its main features include: S103, according to the execution complexity of the machine tool, the total energy consumption is then divided into no-load cutting energy consumption E idle , its main features include: S104, according to the execution complexity of the machine tool, the total energy consumption is finally divided into cutting energy consumption E cutting , its main features include:

3. The method for predicting the total energy consumption of a CNC machine tool according to claim 1, It is characterized in that In step S2, a real-time monitoring system for electric energy consumption of CNC machine tools is built, which mainly includes two parts: hardware equipment and software application.

4. The method for predicting the total energy consumption of a CNC machine tool according to claim 1, It is characterized in that In step S3, a real-time monitoring method is used to collect various power consumption data of the CNC machine tool in the non-cutting state, and a mathematical prediction model of energy consumption corresponding to each component is established by regression analysis: S301, the measurement items are mainly the power P of the CNC machine tool in the stable standby state standby The power of the machine tool in standby mode is related to its own characteristics and is generally fixed. For a specific model of CNC machine tool, its standby power is a fixed value and will not change with changes in processing conditions: S302, the measurement items are mainly the startup instantaneous power P of the CNC machine tool startup , the energy consumption of the entire process from startup to reaching a stable operating state can be obtained by integrating the power over time: S303, the measurement items are mainly the lighting power P of CNC machine tools light , consuming electricity and generating heat. The power of the lighting device is a fixed value, which can be obtained by turning on the lighting device to collect m power values ​​for a period of time and taking the arithmetic average: S304, the measurement items are mainly the basic power P of the tool change action of the CNC machine tool toolchange , the average power required for automatic tool change from position i to the next position, it is necessary to collect m power values ​​multiple times and perform arithmetic averaging to obtain: S305, the measurement item is mainly the instantaneous power P of the CNC machine tool spindle acceleration state accelerate , the energy consumption of the whole process from the beginning of acceleration to reaching the stable speed state can be obtained by integrating the power over time. If the spindle speed is determined when the machine tool is started, the energy consumption of the startup process is also determined, which means that the startup energy consumption fitting function of the machine tool can be obtained by curve fitting: E accelerate =A 2 +Bn+C S306, the measurement items are mainly the power P of CNC machine tool cutting fluid in a stable spraying state sparycool The main energy-consuming parts of the cutting fluid supply device are the motor and the pump. Since the cutting fluid flow and pressure are the specified values ​​during the use of the cutting fluid, the loss in the circuit is basically unchanged, so its power value is approximately a constant value. The power of the cutting fluid supply device can be collected by turning on the cutting fluid supply device and averaging the m power values ​​for a period of time to obtain: S307, the measurement item is mainly the power P of the CNC machine tool during rapid feed rapid Rapid feed motion is usually used for rapid positioning in CNC machining. In this process, the sudden increase in feed speed usually causes the appearance of power peaks, which can be obtained by integrating the power over time: S308, the measurement item is mainly the power P when the blowing device of the CNC machine tool is turned on blow air The gas flow and working pressure used by the blowing device are specifically specified, so it can be regarded as a constant gas pressure and airflow. The power consumed by the blowing device is the product of the gas flow and gas pressure per unit time as a fixed value. By turning on the blowing device to collect m power values ​​within a period of time and taking the arithmetic average, the corresponding power can be obtained: In the formula, p a is the working pressure of the air gun, q a is the gas flow rate; S309, the measurement items are mainly the inherent spindle rotation power P of the CNC machine tool in the no-load cutting state spindle As shown in Figure 4, the measured spindle idling power scatter plot and smoothing process, according to the characteristics of the main transmission system of the CNC machine tool, the main transmission system includes high-speed and low-speed transmission chains. Therefore, the spindle power model of the CNC machine tool should be modeled and studied in sections: Where A, B and C are the coefficients of the model, which can be obtained from the experimental results of power; n 1 , n 2 ,……,n n-1 and n max The spindle speed is set according to the machine tool manual and actual processing requirements; S310, the measurement items are mainly the inherent feed power P of the CNC machine tool in the no-load cutting state feed The motion of the feed axis can be divided into two categories. One is the feed motion on the horizontal plane, such as the axis feed P of CNC milling machines and machining centers. feed-X , P feed-Y The other type is the feed motion on the vertical plane, such as the axial feed P of the machining center. feed-Z- and downward feed P feed-Z+ : P feed =P feed-X +P feed-Y +P feed-Z- +P feed-Z+。 5. The method for predicting the total energy consumption of a CNC machine tool according to claim 1, It is characterized in that Before step S4, the experimental factors and levels are formulated as shown in Table 1 to determine the appropriate tool and processing method for the workpiece material, and to select the appropriate cutting speed n, feed speed f, and cutting depth a according to the shape and size of the workpiece. p and cutting width a e Table 1 Experimental factors and levels 6. The method for predicting the total energy consumption of a CNC machine tool according to claim 1, It is characterized in that In step S4, based on the process parameters proposed in claim 5, a three-dimensional cutting model of the workpiece and the cutting tool is constructed, and a dynamic thermal coupling cutting simulation is performed on the actual cutting stage of the machine tool to calculate the material removal power P in the cutting power. remove In addition, the finite element software is used to analyze the material deformation characteristics of the workpiece:

7. Perform theoretical calculation on the load energy loss coefficient of the main power system of the machine tool to obtain the load loss power model P caused by the cutting load of the machine tool additional : P additional =αP remove 8. The method for predicting total energy consumption of a CNC machine tool according to claim 1, It is characterized in that In step S6, the accuracy and effectiveness of the model are verified by designing an orthogonal experiment under real working conditions, where the metal cutting total load power model adopts the least squares regression prediction method: Q remove =C 1 +a 1 n+a 2 f+a 3 a e +a 4 a p +a 5 nf+a 6 na e +a 7 na p + a 8 fa e +a 9 fa p +a 10 a e a p +a 11 n 2 +a 12 f 2 +a 13 a e 2 +a 14 a p 2 AND cutting =And remove +E additional 9. The method for predicting the total energy consumption of a CNC machine tool according to claim 1, It is characterized in that In step S7, a total power consumption model E of the CNC machine tool is constructed. total : AND total =And standby +E auxiliary +E idle +E cutting。

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