Direct-drive static-pressure electric spindle and control method

Abstract

The invention discloses a direct-drive static-pressure motorized spindle and a control method, and belongs to the technical field of machine tool spindles, and the control method comprises the steps that an industrial personal computer receives a first operation signal acquired by acquisition equipment, extracts a dynamic characteristic signal of the motorized spindle from the first operation signal, and performs modeling on the extracted dynamic characteristic signal; parameters in the linear conversion process are adjusted according to the load change of the main shaft; setting an instruction structure of operation parameters of the motorized spindle and outputting a control instruction; and optimizing a control strategy through a machine learning model. In the implementation process of the technical scheme, the dynamic characteristic signal of the motorized spindle is extracted, modeling is carried out on the extracted dynamic characteristic signal, more accurate parameter prediction and control can be achieved, the problems of response delay and insufficient precision caused by load changes are effectively solved, and meanwhile, the accuracy of the motorized spindle is improved. And dynamic adjustment of the real-time load condition is combined, so that the motorized spindle keeps high stability and machining precision in a complex and changeable machining environment.

Description

Technical Field

[0001] The present application relates to the technical field of machine tool spindles, and in particular to a direct-drive hydrostatic electric spindle and a control method thereof. Background Art

[0002] The electric spindle is a power component widely used in CNC machine tools and high-precision processing equipment. It is usually connected to an electric motor, which directly drives the spindle to rotate without the need for traditional mechanical transmission devices, thereby improving energy transmission efficiency and response speed.

[0003] With the development of intelligence, the electric spindle is no longer simply connected to the motor, but realizes power control, motion control, feedback and monitoring, safety protection and other functions through the control system. While achieving precise control of the electric spindle, it also ensures operational stability and safety. For example, the input frequency or current of the motor is adjusted by the control system to achieve precise control of the electric spindle speed. By collecting the speed, temperature, vibration and other parameters of the electric spindle and automatically adjusting the control signal according to the feedback data, the processing accuracy and stability are maintained.

[0004] However, the existing control system still has problems of response delay and insufficient adjustment accuracy when dealing with complex and changeable processing requirements, resulting in the control system's ability to respond to input signal changes (such as load changes, command changes, etc.) cannot meet the requirements, resulting in the machining stability of the electric spindle cannot be guaranteed. Although the existing PID algorithm can optimize the response speed, this method will have overshoot and oscillation phenomena, that is, after reaching the target value, there will still be fluctuations, causing the actual result to exceed the target value and then fall back, or there will be multiple ups and downs when approaching the target value. These instabilities will affect the machining quality.

[0005] Therefore, it is necessary to provide a direct-drive hydrostatic electric spindle and a control method to solve the above problems.

[0006] It should be noted that the above information disclosed in this background technology section is only for understanding the background technology of the present application concept, and therefore, it may contain information that does not constitute the prior art. Summary of the invention

[0007] Based on the above-mentioned problems existing in the prior art, the problem to be solved by the present application is: to provide a direct-drive hydrostatic electric spindle and a control method, by linearly converting the operation process of the electric spindle, so that it can apply the existing linear processing method and reduce overshoot, oscillation and other phenomena in the adjustment process.

[0008] The technical solution adopted by the present application to solve its technical problem is: a control method for a direct-drive hydrostatic electric spindle, the direct-drive hydrostatic electric spindle includes an industrial computer and a collection device, the industrial computer is used to receive and analyze data collected from the collection device, and output control instructions after data analysis, the collection device includes a digital signal acquisition instrument and a sensor combination, the sensor combination includes a speed sensor, a current acquisition instrument and a torque sensor, the electric spindle is connected to an actuator, the actuator is a frequency converter, and is used to adjust the speed of the electric spindle according to the received control instruction;

[0009] The control method of the direct-drive hydrostatic electric spindle comprises:

[0010] The industrial computer receives the first operation signal collected by the collection device, extracts the dynamic characteristic signal of the electric spindle from the first operation signal, and models the extracted dynamic characteristic signal;

[0011] According to the load change of the spindle, the parameters in the linear conversion process are adjusted and the corresponding control instructions are generated;

[0012] Set the command structure of the electric spindle operating parameters and output control commands according to the real-time load conditions. After receiving the control commands, the inverter adjusts the speed of the electric spindle.

[0013] Based on historical data, the machine learning model is used to predict the impact of the electric spindle load change on the operating parameters and optimize the control strategy.

[0014] During the implementation of the technical solution of the present application, by extracting the dynamic characteristic signals of the electric spindle and modeling the extracted dynamic characteristic signals, more accurate parameter prediction and control can be achieved, effectively reducing the response delay and insufficient precision caused by load changes. At the same time, combined with the dynamic adjustment of real-time load conditions, the electric spindle can maintain high stability and processing accuracy in a complex and changeable processing environment; in addition, through the introduction of machine learning models, the control system can continuously learn and optimize, further reduce overshoot and oscillation phenomena, and improve processing efficiency.

[0015] Furthermore, the dynamic characteristic signal includes moment of inertia, angular velocity, input torque and friction torque.

[0016] Furthermore, the method for modeling the extracted dynamic feature signal includes:

[0017] A dynamic response model is established, and the dynamic signal is used as the input of the dynamic response model. The dynamic characteristics of the electric spindle are modeled using differential equations and linearly transformed.

[0018] According to the established differential equation, the initial angular velocity of the electric spindle is obtained to obtain the change of the angular velocity with time;

[0019] A linearized state feedback model is constructed, and the input torque corresponding to the current angular velocity of the spindle is used as the input of the linearized state feedback model to achieve linear conversion.

[0020] Furthermore, the process of dynamic characteristic modeling is implemented using the differential equation method, and the established differential equation is: J(dw / dt)=Ti-Tf, where t is the running time of the spindle, J(dw / dt) represents the angular acceleration of the spindle, and dw / dt refers to the derivative of the angular velocity with respect to time, representing the rate of change of the angular velocity. After multiplying by the moment of inertia J, the corresponding speed under the required change of the spindle torque is obtained.

[0021] Furthermore, the Ti-Tf represents torque balance, that is, the difference between the applied input torque and the friction torque determines the angular acceleration of the spindle. If Ti is greater than Tf, it means that the spindle is in an accelerating state. If Ti is less than Tf, it means that the spindle is in a decelerating state.

[0022] Furthermore, the calculation method of the change in angular velocity over time is: w(t)=w(0)+tΔT / J, wherein t represents time, ΔT represents net torque, ΔT=Ti-Tf, and ΔT / J represents the angular acceleration of the main shaft.

[0023] Furthermore, adjusting the parameters in the linear conversion process includes: first presetting a set of gain values, which are obtained through simulation; establishing a mapping relationship between gain and load, and using a transfer function for linear response; according to the distribution of the load, using an interpolation method to extract key load points; performing simulation verification, and further adjusting the gain during the verification process.

[0024] Furthermore, the interpolation method is linear interpolation or polynomial interpolation.

[0025] Furthermore, the gain and the electric spindle angular velocity are set as the instruction type of the electric spindle operation parameters.

[0026] A direct-drive static pressure electric spindle includes an industrial computer, an acquisition device and a control system, wherein the control system includes: a dynamic feature extraction module, which is used for the industrial computer to receive a first operation signal acquired by the acquisition device, extract the dynamic features of the electric spindle from the first operation signal, and model the extracted dynamic features;

[0027] The linear parameter adjustment module is used to adjust the parameters in the linear conversion process according to the load change of the spindle and generate corresponding control instructions;

[0028] The control command output module is used to set the command structure of the electric spindle operating parameters and output the control command according to the real-time load conditions;

[0029] The control strategy optimization module is used to predict the impact of the electric spindle load change on the operating parameters through a machine learning model based on historical data and optimize the control strategy.

[0030] The beneficial effects of the present application are as follows: a direct-drive hydrostatic electric spindle and control method provided by the present application can achieve more accurate parameter prediction and control by extracting the dynamic characteristic signals of the electric spindle and modeling the extracted dynamic characteristic signals, thereby effectively reducing the response delay and insufficient precision problems caused by load changes, and at the same time, combined with the dynamic adjustment of real-time load conditions, the electric spindle can maintain high stability and machining accuracy in a complex and changeable machining environment; in addition, through the introduction of machine learning models, the control system can continuously learn and optimize, further reduce overshoot and oscillation phenomena, and improve machining efficiency.

[0031] In addition to the above-described purposes, features and advantages, the present application also has other purposes, features and advantages. The present application will be further described in detail with reference to the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The drawings in the specification, which constitute a part of the present application, are used to provide further understanding of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute improper limitations on the present application.

[0033] In the attached picture:

[0034] Figure 1 It is a schematic diagram of the overall process of a control method of a direct-drive hydrostatic electric spindle in the present application;

[0035] Figure 2 It is a schematic diagram of the module structure of a control system of a direct-drive hydrostatic electric spindle in the present application. DETAILED DESCRIPTION

[0036] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0037] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0038] Embodiment 1: The present application provides a direct-drive hydrostatic electric spindle and a control method. The direct-drive hydrostatic electric spindle includes an industrial computer and a collection device. The industrial computer is used to receive and analyze data collected from the collection device, and output control instructions after data analysis. The collection device includes a digital signal acquisition instrument and a sensor combination. The sensor combination includes a speed sensor, a current acquisition instrument, and a torque sensor. The electric spindle is connected to an actuator, which is a frequency converter. The frequency converter is used to adjust the speed of the electric spindle according to the received control instructions. The specific working principle and use method of each device can refer to the prior art and will not be described in detail in this embodiment.

[0039] The control method of the direct-drive hydrostatic electric spindle is applied to the operation process of the direct-drive hydrostatic electric spindle. Through data acquisition, data analysis, signal adjustment and output, the operation process of the direct-drive hydrostatic electric spindle is adjusted, and the problems of response delay and insufficient adjustment accuracy are reduced in the process. Figure 1 As shown, the control method includes the following steps:

[0040] Step 10: The industrial computer receives the first operation signal collected by the collection device, extracts the dynamic characteristics of the electric spindle from the first operation signal, and models the extracted dynamic characteristics.

[0041] In order to control the operation process of the direct-drive hydrostatic electric spindle and reduce the amount of data, unnecessary data is eliminated. After the industrial computer receives the first operation signal collected by the acquisition device, the dynamic characteristics of the electric spindle are extracted therefrom. The first operation signal includes the electric spindle speed signal collected by the speed sensor and the torque signal collected by the torque sensor, wherein the dynamic characteristics include factors such as speed, torque, and friction. The acquisition device can be a plurality of digital signal acquisition instruments, various sensors or other acquisition systems, such as speed sensors, current acquisition instruments, and torque sensors, etc., which are not limited in this embodiment, as long as the operation signal of the electric spindle can be collected. The speed sensor is used to detect the speed information of the electric spindle in real time, thereby obtaining the speed signal. The current acquisition instrument is used for the current data of the electric spindle, and then the load change of the electric spindle is calculated according to the current data. The torque sensor is used to obtain the torque information of the electric spindle during operation, thereby obtaining the input torque, friction torque and other signals of the electric spindle.

[0042] Among them, there will be multiple characteristic signals in the first operation signal, which can be divided into dynamic characteristic signals and static characteristic signals according to the characteristic type, wherein the dynamic characteristic signals include moment of inertia, angular velocity, input torque, friction torque, etc., wherein the moment of inertia represents the resistance of the spindle to rotation, the angular velocity is the speed of the spindle rotation, the unit is radians per second, the input torque is the torque applied to the spindle, driving the spindle to rotate, the friction torque is the torque generated by the friction force, which will produce an obstructive force on the rotation of the spindle. In this embodiment, the above four dynamic signals are used as modeling parameters, and then motion modeling is performed through differential equations. Specifically, the method for modeling the extracted dynamic characteristic signals includes:

[0043] Step 101: establishing a dynamic response model, taking the dynamic signal as the input of the dynamic response model, using differential equations to model the dynamic characteristics of the electric spindle, and performing linear transformation;

[0044] In order to obtain accurate dynamic characteristics of the electric spindle, so as to facilitate subsequent analysis, dynamic characteristics modeling is required. The process of dynamic characteristics modeling is implemented by differential equation method, because differential equation method can accurately describe the motion law of the electric spindle. Specifically, taking the dynamic signals as moment of inertia J, angular velocity w, input torque Ti, and friction torque Tf as examples, the established differential equation is:

[0045] J(dw / dt)=Ti-Tf, this equation describes the dynamic behavior of the electric spindle during operation, where t is the operating time of the spindle, J(dw / dt) represents the angular acceleration of the spindle, and dw / dt refers to the derivative of the angular velocity with respect to time, representing the rate of change of the angular velocity. After multiplying it with the moment of inertia J, the corresponding speed under the required change of the spindle torque is obtained;

[0046] Ti-Tf represents torque balance, that is, the difference between the applied input torque and the friction torque determines the angular acceleration of the spindle. If Ti is greater than Tf, it means that the spindle is in an accelerating state. On the contrary, if Ti is less than Tf, it means that the spindle is in a decelerating state. By establishing a differential equation, the dynamic characteristics analysis and torque balance of the spindle can be more conveniently performed, thereby accurately controlling and optimizing the electric spindle. In addition, the model can also be used to predict the dynamic response of the spindle under different working conditions, thereby facilitating the maintenance of the electric spindle.

[0047] Step 102: According to the established differential equation, the initial angular velocity of the electric spindle is obtained to obtain the variation of the angular velocity with time;

[0048] After the differential equation is established, since the differential equation contains the time component t, it is only necessary to solve the differential equation. Combined with the initial angular velocity w(0) of the electric spindle, the change w(t) of the angular velocity of the spindle over time can be obtained. Specifically, w(t)=w(0)+tΔT / J, where t represents time, ΔT represents net torque, i.e. Ti-Tf, and ΔT / J represents the angular acceleration of the spindle. After integrating the time, the change law of the angular velocity of the spindle over time can be obtained, and then the change of the angular velocity of the spindle at different times can be accurately obtained, providing a basis for subsequent speed regulation.

[0049] Step 103: construct a linearized state feedback model, and use the input torque corresponding to the current angular velocity of the main shaft as the input of the linearized state feedback model to achieve linear conversion;

[0050] In practical applications, the dynamic data of the spindle and the dynamic response model established by it are nonlinear. The nonlinear dynamic response model will increase the complexity and uncertainty of the system when controlling. Therefore, it is very important to convert the nonlinear system to a linear system based on known conditions. After converting to a linear model, the common linear control technology in the existing technology can be applied to improve the control accuracy and reduce the control overshoot, oscillation and other problems.

[0051] In this embodiment, a linearized state feedback model is constructed, and the input torque corresponding to the current angular velocity of the spindle is used as the input of the linearized state feedback model. Since the variation law of the spindle angular velocity with time, and the relationship between the variation of the spindle angular velocity and the input torque and the friction torque have been obtained in the above steps, when the spindle is operating normally, the input torque corresponding to the current angular velocity of the spindle can be obtained by conversion between formulas, and it is input into the linearized state feedback model, so that the input torque can make the dynamic behavior of the entire spindle control system linearly processed according to the input torque. In this way, through linear processing, not only the control algorithm is simplified, but also the calculation burden in the control process is reduced, the response speed and stability of the control system are improved, and high-precision control of the spindle is achieved, and the linear control technology in the prior art can be applied;

[0052] In addition, the model also takes into account various disturbances that may occur in actual work, and effectively compensates for the impact of these disturbances by adjusting the input torque in real time. This process can enhance the robustness of the control system, ensure that the electric spindle can maintain excellent performance under different working conditions, and improve processing accuracy and production efficiency.

[0053] Among them, the selection of the linearization model can refer to the existing technology, such as selecting state feedback, and by setting the corresponding feedback gain, the spindle control system can be converted into a standard linear system form, so as to facilitate the optimization and adjustment of the linearization model, and further realize the fine control of the spindle speed, thereby ensuring the high precision and high stability required in the processing process.

[0054] Step 20: According to the load change of the spindle, the parameters in the linear conversion process are adjusted and corresponding control instructions are generated;

[0055] During the operation of the spindle, it will have different operating states, resulting in different load changes. For example, in the idling state, the spindle load is small, while in heavy-load processing, the load increases significantly. When the load changes, the linear conversion in the above process will also be affected, because the linear conversion process needs to obtain the input torque at the current spindle speed and combine the corresponding feedback gain to achieve linear conversion. When the load changes, the input torque will also change at the same time. Therefore, it is necessary to dynamically adjust the input torque and feedback gain according to the change of the spindle load to ensure the accuracy of the linear conversion to meet the control requirements under different working conditions.

[0056] In this embodiment, the electric spindle is connected to an actuator, which is a frequency converter for adjusting the speed of the electric spindle according to the received control command;

[0057] When adjusting the parameters in the linear conversion process, it is first necessary to collect the real-time load data of the spindle. Through real-time data analysis, the input torque and feedback gain are accurately adjusted to maintain the accuracy of the linear conversion, forming a continuous optimization of the control system to ensure efficient and stable control performance under various working conditions, so that the control system can adapt to the load changes of the spindle in real time and maintain the accuracy of the linear conversion. Specifically, the adjustment of the parameters in the linear conversion process includes:

[0058] First, a set of gain values ​​is preset, and the gain values ​​are obtained through simulation; in the aforementioned linear conversion process, a set of gain values ​​needs to be set first, and the set of gain values ​​is used as preset values, and is adjusted according to load changes in the subsequent process;

[0059] A mapping relationship between gain and load is established, and a transfer function is used for linear response. After a set of gain values ​​are preset, since the load will change continuously, the gain in the process of establishing the linear relationship will change accordingly, otherwise the control system may deviate from the preset linear model. Therefore, it is necessary to establish a mapping relationship between gain and load, and use a transfer function for linear response. The transfer function is a method used in linear power systems. The mapping relationship is obtained by performing Laplace transform on the input and output. In this embodiment, the load is the input and the gain is the output, so as to ensure that the control system can quickly and accurately adjust the parameters when facing the diversity of the spindle load. The use principle and calculation formula of the transfer function can refer to the existing technology and will not be described in detail in this embodiment.

[0060] According to the distribution of the load, the interpolation method is used to extract the key load points; by extracting these key load points, the linear conversion parameters are optimized, because in actual applications, the distribution of load values ​​is not necessarily uniform. In the case of uneven distribution, the calculated gain will fluctuate greatly, and after being converted into a control signal, oscillation is likely to occur. Therefore, the interpolation method is used to extract the key load points, thereby calculating the gain under the key load points and reducing the generation of oscillations. The interpolation method can be implemented by linear interpolation or polynomial interpolation. For details, please refer to the prior art;

[0061] Perform simulation verification and further adjust the gain during the verification process; after obtaining the gain value, simulation verification is still required to observe the impact of the gain value on the subsequent linear change process, and determine whether overshoot, oscillation and other problems occur. If so, fine-tune the gain to meet the requirements and ensure that the system can maintain good performance under various working conditions.

[0062] Step 30: Set the command structure of the electric spindle operating parameters and output control commands according to the real-time load conditions;

[0063] After completing the above steps, it is also necessary to set the instruction structure of the electric spindle operating parameters. The instruction structure is a structure of control instructions for machine recognition. The instruction structure usually includes parameters such as instruction type, parameter name, parameter value, check value, and terminator. After setting the instruction structure, the computer or industrial computer can directly recognize it without conversion, thereby improving data processing efficiency. In this embodiment, the gain and the electric spindle angular velocity are set as the instruction types of the electric spindle operating parameters. Because the speed of the electric spindle is ultimately controlled, there is no need to consider other operating parameters, and the gain and angular velocity are dynamically adjusted according to real-time load feedback, and the corresponding control instructions are output, so as to accurately control the speed of the electric spindle. In addition, since linear conversion has been done, as well as the gain selection in the linear conversion process, the probability of oscillation, overshoot, etc. will be reduced, further improving the operating stability of the electric spindle.

[0064] Step 40: Based on historical data, the influence of the load change of the electric spindle on the operating parameters is predicted by the machine learning model, and the control strategy is optimized. Through in-depth analysis of historical data, the machine learning model can learn the connection between load changes and operating parameters, and realize intelligent control of the spindle. Under the guidance of prediction, the control system will be able to adapt to complex and changeable working conditions more intelligently, and ensure the efficiency and stability of the operation of the electric spindle. Specifically, the use of machine learning models to predict the influence of data changes can refer to the existing technology, and will not be described in detail in this embodiment.

[0065] Embodiment 2: Figure 2 As shown, the present application proposes a direct-drive hydrostatic electric spindle, including an industrial computer, an acquisition device, and a control system. The control system is used to implement the control method in the first embodiment. The control system includes:

[0066] The control system includes:

[0067] A dynamic feature extraction module is used for the industrial computer to receive the first operation signal collected by the collection device, extract the dynamic features of the electric spindle from the first operation signal, and model the extracted dynamic features;

[0068] The linear parameter adjustment module is used to adjust the parameters in the linear conversion process according to the load change of the spindle and generate corresponding control instructions;

[0069] The control command output module is used to set the command structure of the electric spindle operating parameters and output the control command according to the real-time load conditions;

[0070] The control strategy optimization module is used to predict the impact of the electric spindle load change on the operating parameters through a machine learning model based on historical data and optimize the control strategy.

[0071] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A control method for a direct-drive hydrostatic electric spindle, characterized in that: The direct-drive static pressure electric spindle includes an industrial computer and a collection device, the industrial computer is used to receive and analyze data collected from the collection device, and output control instructions after data analysis, the collection device includes a digital signal acquisition instrument and a sensor combination, the sensor combination includes a speed sensor, a current acquisition instrument and a torque sensor, the electric spindle is connected to an actuator, the actuator is a frequency converter, and the frequency converter is used to adjust the speed of the electric spindle according to the received control instructions; The control method of the direct-drive hydrostatic electric spindle comprises: The industrial computer receives a first operation signal collected by the collection device, wherein the first operation signal includes a spindle speed signal collected by a speed sensor and a torque signal collected by a torque sensor, extracts a dynamic characteristic signal of the spindle from the first operation signal, and models the extracted dynamic characteristic signal; The current acquisition instrument generates a load change signal of the main shaft, and the industrial computer adjusts the parameters in the linear conversion process according to the load change signal of the main shaft, and generates corresponding control instructions; The industrial computer sets the instruction structure of the electric spindle operating parameters and outputs control instructions according to the real-time load conditions. After receiving the control instructions, the frequency converter adjusts the speed of the electric spindle. Based on historical data, the industrial computer uses a machine learning model to predict the impact of the electric spindle load changes on the operating parameters and optimize the control strategy.

2. The control method of a direct-drive hydrostatic electric spindle according to claim 1, characterized in that: The dynamic characteristic signals include moment of inertia, angular velocity, input torque and friction torque.

3. The control method of a direct-drive hydrostatic electric spindle according to claim 2, characterized in that: Methods for modeling the extracted dynamic feature signals include: A dynamic response model is established, and the dynamic signal is used as the input of the dynamic response model. The dynamic characteristics of the electric spindle are modeled using differential equations and linearly transformed. According to the established differential equation, the initial angular velocity of the electric spindle is obtained to obtain the change of the angular velocity with time; A linearized state feedback model is constructed, and the input torque corresponding to the current angular velocity of the spindle is used as the input of the linearized state feedback model to achieve linear conversion.

4. The control method of a direct-drive hydrostatic electric spindle according to claim 3, characterized in that: The process of dynamic characteristic modeling is implemented using the differential equation method. The established differential equation is: J(dw / dt)=Ti-Tf, where t is the running time of the spindle, J(dw / dt) represents the angular acceleration of the spindle, and dw / dt refers to the derivative of the angular velocity with respect to time, representing the rate of change of the angular velocity. After multiplying it by the moment of inertia J, the corresponding speed under the required change of the spindle torque is obtained.

5. The control method of a direct-drive hydrostatic electric spindle according to claim 4, characterized in that: The Ti-Tf represents torque balance, that is, the difference between the applied input torque and the friction torque determines the angular acceleration of the spindle. If Ti is greater than Tf, it means that the spindle is in an accelerating state. If Ti is less than Tf, it means that the spindle is in a decelerating state.

6. The control method of a direct-drive hydrostatic electric spindle according to claim 4, characterized in that: The calculation method of the change of the angular velocity over time is: w(t)=w(0)+tΔT / J, wherein t represents time, ΔT represents net torque, ΔT=Ti-Tf, and ΔT / J represents the angular acceleration of the main shaft.

7. The control method of a direct-drive hydrostatic electric spindle according to claim 1, characterized in that: Adjusting the parameters in the linear conversion process includes: first presetting a set of gain values, which are obtained through simulation; establishing a mapping relationship between gain and load, and using transfer function for linear response; according to the distribution of load, using interpolation method to extract key load points; performing simulation verification, and further adjusting the gain during the verification process.

8. The control method of a direct-drive hydrostatic electric spindle according to claim 7, characterized in that: The interpolation method is linear interpolation or polynomial interpolation.

9. The control method of a direct-drive hydrostatic electric spindle according to claim 1, characterized in that: The command type for setting the gain and the angular velocity of the electric spindle as the operating parameters of the electric spindle.

10. A direct drive hydrostatic electric spindle, characterized in that: It includes an industrial computer, a collection device and a control system, the control system is used to implement the control method according to any one of claims 1 to 9, and the control system includes: A dynamic feature extraction module is used for the industrial computer to receive the first operation signal collected by the collection device, extract the dynamic features of the electric spindle from the first operation signal, and model the extracted dynamic features; The linear parameter adjustment module is used to adjust the parameters in the linear conversion process according to the load change of the spindle and generate corresponding control instructions; The control command output module is used to set the command structure of the electric spindle operating parameters and output the control command according to the real-time load conditions; The control strategy optimization module is used to predict the impact of the electric spindle load change on the operating parameters through a machine learning model based on historical data and optimize the control strategy.

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