A servo self-adaptive control system automatically adjusting shaft force according to temperature gradient

Abstract

The application discloses a kind of servo self-adapting control systems that automatically adjust shaft force with temperature gradient, it is related to servo control technical field, including multidimensional environment perception end, thermodynamic model compensation end, precision execution drive end, operating data storage end and central adaptive controller;Multidimensional environment perception end real-time monitoring multi-point temperature gradient and axial load;Thermodynamic model compensation end calculates axial elongation based on thermodynamic model;Precision execution drive end carries out axial displacement fine adjustment by servo mechanism driving movable bearing seat;Central adaptive controller executes force-position hybrid closed-loop control.This application can physically offset shafting thermal deformation, maintain bearing pre-tightening force dynamic constant, effectively solve the thermal instability problem of precision spindle, significantly improve the rotation accuracy and dynamic stiffness of shafting under variable temperature conditions, and provide data support for equipment life cycle maintenance.

Description

Technical Field

[0001] This invention relates to the field of servo control technology, and in particular to a servo adaptive control system that automatically adjusts axial force according to temperature gradient. Background Technology

[0002] During the operation of precision shaft systems such as precision spindles and high-speed drive shafts, frictional losses and environmental changes will cause a significant temperature rise, resulting in thermal expansion of the spindle, bearings and support structures, which in turn causes fluctuations in bearing preload. Excessive preload will lead to increased bearing heating, increased power consumption and shortened lifespan; insufficient preload will lead to decreased spindle rotation accuracy, increased vibration and insufficient rigidity.

[0003] Traditional axial force control methods often employ fixed preload, passive spring preload, or single-point temperature empirical compensation, which are difficult to adapt to the nonlinear thermal deformation effects caused by complex temperature gradient changes, resulting in limited compensation accuracy and insufficient stability.

[0004] Therefore, a servo adaptive control system that automatically adjusts the axial force according to the temperature gradient is proposed to solve the above problems. Summary of the Invention

[0005] The main objective of this invention is to provide a servo adaptive control system that automatically adjusts shaft force according to temperature gradient, in order to solve the problem that during the operation of precision shaft systems, the thermal expansion of the shaft system caused by frictional heating and ambient temperature rise leads to fluctuations in bearing preload, which in turn affects the rotational accuracy, vibration characteristics and service life of the shaft system.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: it includes a multi-dimensional environment sensing end, a thermodynamic model compensation end, a precision execution drive end, a running data storage end, and a central adaptive control platform; the multi-dimensional environment sensing end, the thermodynamic model compensation end, the precision execution drive end, and the running data storage end are all electrically connected to the central adaptive control platform.

[0007] The multi-dimensional environmental sensing end is used to collect temperature gradient data inside and on the surface of the shaft system through a distributed sensor layout, and simultaneously acquire real-time axial preload electrical signals, converting physical quantities into standard digital signals for input into the system.

[0008] The thermodynamic model compensation end is used to establish a global heat conduction mapping of the shaft system based on the collected temperature gradient distribution, calculate the thermal elongation of the spindle and bearing assembly under non-uniform thermal field, and convert the thermal deformation into the axial displacement compensation command value of the servo mechanism.

[0009] The precision actuator is used to receive compensation commands and drive the transmission mechanism to generate micron-level displacement through a servo power source, thereby changing the axial spatial position of the movable bearing seat and mechanically compensating for force deviations caused by thermal expansion.

[0010] The operational data storage terminal is used to classify and store temperature field data, axial force fluctuation curves, and actuator displacement trajectories in real time throughout the entire system operation process, and to perform online assessment of bearing fatigue state based on historical load spectra.

[0011] The central adaptive control platform is used to integrate feedback signals from various ends, calculate and output control current through a force-position hybrid closed-loop control algorithm, and maintain the shaft preload within a preset stable range.

[0012] The multi-dimensional environmental sensing terminal includes a distributed temperature sensing array, a dynamic load monitoring array, and a signal conditioning and encapsulation module.

[0013] The distributed temperature sensing array includes multiple thin-film platinum resistance sensors, which are bonded to the outer surface of the bearing, the inner wall of the spindle sleeve, and the characteristic points of the bearing housing support by thermally conductive insulating adhesive, forming a temperature measuring grid covering the axial and radial directions.

[0014] The dynamic load monitoring array includes a piezoelectric force sensor, which is installed at the end face contact and pressing point between the movable bearing seat and the frame support structure by means of bolt pre-tightening, and is used to capture transient changes in axial load.

[0015] The signal conditioning and packaging module includes a charge amplifier, a low-pass filter, and a multi-channel ADC converter. The charge signal output by the piezoelectric force sensor is transmitted to the charge amplifier for level conversion through a shielded cable. After the mechanical vibration noise interference is filtered out by the low-pass filter, the signal is converted into a digital signal by the ADC converter and transmitted to the central adaptive control platform.

[0016] The thermodynamic model compensation module includes a heat conduction analysis module, a stiffness evolution analysis module, and a compensation amount calculation module.

[0017] The heat conduction analysis module is used to construct a three-dimensional unsteady temperature field model of the shaft system based on the temperature rise data of each point fed back by the distributed temperature sensing array and the finite element interpolation method.

[0018] The stiffness evolution analysis module is used to dynamically correct the physical properties of the material based on the real-time temperature gradient. The correction logic includes adjusting the Young's modulus and thermal expansion coefficient of the material according to the temperature rise curve, and calculating the structural stiffness change of the bearing assembly in different temperature zones.

[0019] The compensation calculation module is used to calculate the cumulative thermal elongation of each component of the shaft system through integration. The calculation formula is as follows: ; in, This represents the comprehensive thermal disturbance evaluation index of the shaft system. Indicates the axial temperature gradient deviation. Indicates radial temperature gradient deviation. This represents the difference between the ambient temperature and the reference temperature.

[0020] The precision actuation drive includes a servo drive control module, a precision transmission actuation module, a position feedback monitoring module, and a preload constant mechanism.

[0021] The servo drive control module controls the power driver through pulse width modulation signals to adjust the motor's current vector.

[0022] The precision transmission execution module consists of a servo motor, a planetary reducer, and a planetary ball screw. The output shaft of the servo motor is connected to the input end of the planetary reducer via a coupling. The output end of the planetary reducer drives the planetary ball screw to rotate. The screw nut seat and the movable bearing seat are fixedly connected by end face bolts, converting the rotational motion into axial linear displacement.

[0023] The position feedback monitoring module includes a high-line-count grating ruler. The reading head of the grating ruler is mounted on the frame, and the scale is mounted on the side of the movable bearing seat. Position feedback is achieved by detecting the relative displacement between the reading head and the scale.

[0024] The constant preload mechanism includes a disc spring assembly, which is stacked in opposite directions on the guide shaft at the rear end of the bearing housing and located between the movable bearing housing and the thrust bracket. The disc spring assembly provides the basic static preload through the elastic deformation of the disc spring and absorbs the high-frequency force pulsation during the servo adjustment process.

[0025] The central adaptive control platform adopts a multi-ring nested control structure, and the specific control flow is as follows: Step 1: Establish a regression correlation model between preload deviation and compensation displacement, and calculate the coefficients of the first-order term of the regression equation: ; in, The temperature-force load coupling coefficient represents the univariate linear evolution relationship between the temperature gradient change and preload fluctuation in the shaft system. Indicates the first Real-time temperature values ​​at each temperature acquisition point. This indicates the axial preload value fed back by the force sensor at the corresponding moment. and These represent the average temperature and average pressure during the sampling period, respectively.

[0026] Step 2: Calculate the coefficients of the quadratic term in the regression equation to correct for nonlinear thermal deformation. ; in, The coefficient of the quadratic term reflects the combined effect of the temperature rise rate and the nonlinear expansion of the material on the preload: ; in, The system's fundamental load constants are represented by the coefficients mentioned above, which are used to construct a preload prediction model. .

[0027] Step 3: The central adaptive control platform will transmit the detected pressure values ​​in real time. Compared with the standard preload setting value Compare and calculate the deviation value. ,like If the absolute value exceeds the preset threshold, the servo adjustment program will be activated via commands. The output is sent to the precision actuator to drive the movable bearing housing to move.

[0028] The running data storage terminal includes a local storage unit, a communication unit, and a fatigue assessment module.

[0029] The local storage unit records synchronous time-series data of temperature, force, and displacement in real time through a high-speed cache.

[0030] The communication unit uploads data to the host computer via an industrial Ethernet interface and sets an over-limit threshold. When the preload or temperature gradient exceeds the safety boundary, the central adaptive control platform is triggered to output an emergency stop signal.

[0031] The fatigue assessment module is used to perform statistical analysis on the stored axial force load spectrum, as follows: Step 1: Use the rainflow counting method to perform cyclic counting on the axial preload fluctuation curve and extract the load amplitude and mean.

[0032] Step 2: Calculate the damage factor based on the linear damage accumulation theory and the SN curve of the bearing material: ; in, For cumulative damage value, This refers to the actual number of cycles at a specific load level. This represents the theoretical total number of cycles required for the bearing to reach its fatigue limit under this load level.

[0033] Step 3: When When the value approaches the critical value, the system outputs a maintenance warning signal to the outside through the communication unit.

[0034] The present invention has the following beneficial effects: 1. In this invention, by setting up a multi-dimensional environmental sensing end and utilizing the combined layout of a distributed temperature sensing array and a piezoelectric force sensor, the limitations of traditional single-point temperature measurement are changed. Through the direct contact installation of a thin-film platinum resistance sensor with the outer ring of the bearing, the real-time capture of the actual temperature gradient inside the shaft system is realized, providing a high-precision data source for subsequent thermal deformation compensation and reducing the adjustment error caused by the fuzziness of the temperature field perception.

[0035] 2. In this invention, by setting up a thermodynamic model compensation end and a central adaptive control platform, and using regression equations to calculate the coefficients of the first and second terms, a dynamic mapping model of temperature gradient and axial displacement is constructed. The output angle of the servo motor is corrected in real time through a PID algorithm, enabling the system to actively pre-compensate for nonlinear thermal expansion. This solves the problem of response lag in traditional passive pre-tightening methods under complex temperature rise conditions and maintains the stability of shaft rotation accuracy in hot environments.

[0036] 3. In this invention, by setting a precision actuator drive end and adopting a mechanical structure of servo motor combined with planetary ball screw and disc spring assembly, rigid-flexible composite control of force and displacement is realized. The micrometer unit of grating ruler is used for full closed-loop position feedback, which ensures the positioning accuracy of the actuator. At the same time, the disc spring assembly absorbs the impact during the mechanical adjustment process through its own elastic characteristics, extends the mechanical fatigue life of bearings and transmission components, and improves the reliability of precision shaft system in long-term continuous operation. Attached Figure Description

[0037] Figure 1 This is a schematic diagram of the overall system architecture of a servo adaptive control system that automatically adjusts axial force according to temperature gradient according to the present invention. Figure 2 This is a schematic diagram of the architecture of the multi-dimensional environmental sensing end in a servo adaptive control system that automatically adjusts axial force according to temperature gradient according to the present invention. Figure 3 This is a schematic diagram of the thermodynamic model compensation end in a servo adaptive control system that automatically adjusts axial force according to temperature gradient according to the present invention. Figure 4 This is a schematic diagram of the architecture of the precision execution drive end in a servo adaptive control system that automatically adjusts axial force according to temperature gradient according to the present invention. Figure 5 This is a schematic diagram of the health diagnosis storage terminal in a servo adaptive control system that automatically adjusts axial force according to temperature gradient according to the present invention.

[0038] The attached figures are labeled as follows: 1. Multi-dimensional environmental sensing end; 11. Distributed temperature sensing array; 111. Temperature measurement unit; 12. Dynamic load monitoring array; 121. Piezoelectric force sensor; 13. Signal conditioning and packaging module; 2. Thermodynamic model compensation end; 21. Heat conduction analysis module; 22. Stiffness evolution analysis module; 23. Compensation amount calculation module; 3. Precision execution drive end; 31. Servo drive control module; 32. Precision transmission execution module; 33. Position feedback monitoring module; 331. Grating ruler micrometer unit; 34. Preload constant mechanism; 341. Elastic compensation element; 4. Running data storage end; 41. Fatigue assessment module; 42. Storage module; 421. Local storage unit; 422. Communication unit; 5. Central adaptive control platform. Detailed Implementation

[0039] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0040] Please refer to Figures 1 to 5 As shown: In a servo adaptive control system that automatically adjusts axial force according to temperature gradient, the overall system architecture is as follows. Figure 1 As shown, its core lies in solving the problem of axial preload failure caused by temperature rise in precision shaft systems during high-speed operation through a closed-loop feedback mechanism. The system uses a central adaptive control platform 5 as the logic processing hub, and its peripheral collaborative structure includes a multi-dimensional environmental sensing terminal 1, a thermodynamic model compensation terminal 2, a precision execution drive terminal 3, and a running data storage terminal 4. The central adaptive control platform 5 interacts bidirectionally with each endpoint through an industrial bus to ensure the real-time issuance of control commands and the accurate transmission of feedback signals.

[0041] The specific structure and layout of the multi-dimensional environmental sensing terminal 1 are as follows: Figure 2As shown; in the physical structure of the precision shaft system, a high-precision bearing is installed inside the spindle sleeve, and the outer ring of the bearing fits tightly with the inner wall of the spindle sleeve; in order to achieve omnidirectional capture of temperature gradient, the distributed temperature sensing array 11 consists of multiple thin-film platinum resistance sensors. These sensors are bonded to the circumferential surface of the bearing outer ring, the inner wall of the spindle sleeve, and the characteristic heat source points of the bearing housing support by insulating adhesive with high thermal conductivity; this layout forms a temperature measurement grid covering the axial and radial directions, which can monitor the heat conduction process of the heat generated by the spindle rotation friction in the structural components in real time; at the same time, the piezoelectric force sensor 121 in the dynamic load monitoring array 12 is installed at the end of the movable bearing housing and the frame support structure. The piezoelectric force sensor 121 is pre-tightened using high-strength bolts to maintain a constant initial clamping state, thus enabling it to sensitively detect minute transient changes in axial load. The signal conditioning and packaging module 13 is housed in a shielded box near the sensor, which integrates a charge amplifier, a low-pass filter, and a multi-channel ADC converter. The weak charge signal output by the piezoelectric force sensor 121 is first transmitted to the charge amplifier for level conversion via a low-noise shielded cable. Then, it is filtered by a low-pass filter to remove various high-frequency vibration noises generated during machining. Finally, the analog voltage signal is converted into a high-resolution digital signal by the ADC converter and input to the central adaptive control platform 5.

[0042] The structure of the compensation end 2 in the thermodynamic model is as follows: Figure 3 As shown, its main task is to convert the sensed temperature data into mechanically compensated displacement. The heat conduction analysis module 21 receives temperature rise data from the distributed temperature sensor array 11 and uses the finite element interpolation algorithm to construct a three-dimensional unsteady temperature field model of the shaft system inside the central adaptive control platform 5. The stiffness evolution analysis module 22 dynamically corrects the physical properties of the main shaft material based on the real-time temperature gradient. Specifically, the Young's modulus and thermal expansion coefficient of the material are not constant values, but functions that change with temperature. The system calculates the structural stiffness of the bearing assembly in the current temperature range through the built-in material property library. The compensation calculation module 23 executes the core calculation logic and obtains the compensation displacement reference value by integrating the cumulative thermal elongation of each component of the shaft system. The calculation process introduces a comprehensive thermal disturbance evaluation index for the shaft system, which comprehensively considers the combined effects of axial temperature gradient deviation, radial temperature gradient deviation, and ambient temperature fluctuations on the system stability.

[0043] The mechanical structure and positional relationship of the precision actuator drive end 3 are as follows: Figure 4As shown; this end is the main actuator for physical compensation, installed at the rear of the frame; the servo motor serves as the power source, and its output shaft is connected to the input end of the planetary reducer via a high-rigidity diaphragm coupling; the planetary reducer provides high torque and reduces speed, and its output end drives the planetary ball screw to rotate; the screw nut seat of the planetary ball screw and the movable bearing seat are fixedly connected by multiple high-strength end face bolts; this connection method ensures that the rotational motion of the screw can be accurately converted into the axial linear displacement of the movable bearing seat; in order to achieve absolute closed-loop position control, the system is equipped with a high-line-count grating ruler reading head on the frame, and the scale of the high-line-count grating ruler... It is installed on the side of the movable bearing housing; the relative displacement between the reading head and the scale can reflect the real axial position of the movable bearing housing in real time, and the positioning accuracy can reach the nanometer level; in addition, the preload constant mechanism 34 is the key to rigid-flexible composite control, and its core component is a disc spring assembly; the disc spring assembly is sleeved on the guide shaft at the rear end of the bearing housing in an opposing stacking manner, and its physical position is between the movable bearing housing and the thrust bracket; the disc spring assembly not only provides the basic static preload through initial compression, but more importantly, it plays a buffering role in the servo adjustment process, absorbing the high-frequency force pulsation caused by the micro-feed of the lead screw or mechanical vibration, and ensuring smooth bearing force.

[0044] The central adaptive control platform 5 adopts a multi-ring nested control structure, deeply integrating force feedback, position feedback, and temperature compensation models. At the initial system startup, the platform first establishes a regression correlation model between preload deviation and compensation displacement. Through real-time acquired temperature and force value sequences, it calculates the coefficient of the first term in the regression equation, i.e., the temperature-force load coupling coefficient. This coefficient characterizes the univariate linear evolution relationship between shaft temperature gradient changes and preload fluctuations. To further improve compensation accuracy, the system also calculates the coefficient of the second term to correct complex deformations caused by nonlinear material expansion or uneven temperature rise rates. Based on these coefficients, the central adaptive control platform 5 constructs a preload prediction model, comparing the real-time detected pressure value with the preset standard preload value. When the deviation exceeds the set safety threshold, the platform initiates a PID adaptive adjustment program. Control commands are output to the servo drive module via pulse width modulation signals, adjusting the current vector of the servo motor to drive the planetary ball screw to perform micron-level axial compensation movement of the movable bearing seat, thereby offsetting the reduction in preload caused by thermal expansion or the excessive preload caused by thermal expansion.

[0045] like Figure 5As shown, the data storage terminal 4 plays a crucial role in the entire lifecycle management; the local storage unit 421 uses a high-speed cache to synchronously record time-series data such as temperature, force load, and displacement trajectory; the communication unit 422 uploads this data to a remote server in real time via industrial Ethernet and monitors whether the data exceeds the safety boundary in real time; the fatigue assessment module 41 performs in-depth analysis based on the stored axial force load spectrum; the system uses the rainflow counting method to cyclically count the fluctuation curve of the axial preload, accurately extracting the amplitude and mean of each load fluctuation; combined with the linear damage accumulation theory and the SN curve of the bearing material, the system can calculate the cumulative damage value of the bearing; when this value approaches the failure critical point, the central adaptive control platform 5 will send a maintenance warning signal to the operator through the communication unit 422, thereby avoiding sudden failures caused by bearing fatigue.

[0046] In practical applications, such as in the spindle system of a precision CNC machine tool, when the spindle starts from a cold state and gradually accelerates to its rated speed, a large amount of heat is generated inside the bearing due to high-speed rolling friction. At this time, the distributed temperature sensing array 11 detects that the temperature between the outer ring of the bearing and the spindle sleeve rises rapidly and forms a significant axial temperature gradient. Since the thermal expansion rate of the spindle is usually faster than the expansion rate of the frame, this causes significant fluctuations in the originally set bearing preload. The central adaptive control platform 5 receives the force value decrease signal from the piezoelectric force sensor 121 and, combined with the calculation results from the thermodynamic model compensation end 2, immediately commands the servo motor to rotate. The planetary ball screw pushes the movable bearing seat to move slightly closer to the spindle, accurately compensating for the thermal expansion of the spindle. During the entire adjustment process, the grating ruler monitors the displacement accuracy in real time, while the disc spring group ensures a smooth transition of the force value. As the running time increases, the running data storage end 4 continuously accumulates data, and the fatigue assessment module 41 dynamically updates the remaining life prediction of the bearing, ensuring that the entire shaft system is always in the best working condition.

[0047] The physical connections between the components of this system are extremely tight. The frame, as the basic support platform of the entire system, bears all static and dynamic loads. The spindle sleeve is fixed at the front end of the frame, while the precision actuator drive end 3 is located at the rear end of the frame. The movable bearing seat slides axially on the frame through high-precision guide rails or bushings. The housings of the servo motor and planetary reducer are fixed to the rear support of the frame through flanges, ensuring the stability of the transmission system. The bearing end of the planetary ball screw is supported on the frame, while its nut end is rigidly connected to the movable bearing seat. This chain connection structure from the power source to the actuator, combined with the feedback loop of the grating ruler and the piezoelectric force sensor 121, constitutes a high-rigidity, high-response closed-loop control system.

[0048] From the perspective of signal flow, the raw physical signals collected by the multi-dimensional environmental sensing terminal 1 are converged to the signal conditioning and encapsulation module 13 through a shielded cable. The pre-processed digital signals enter the central adaptive control platform 5. The high-speed processor inside the platform runs thermodynamic model compensation logic and adaptive control algorithm in parallel. The processed control signal drives the precision execution drive terminal 3 to change the physical position of the mechanical structure. The position feedback monitoring module 33 and the dynamic load monitoring array 12 form a closed loop, continuously correcting the output of the actuator. The running data storage terminal 4 records these dynamic interaction processes throughout, providing data support for system optimization and fault diagnosis. This design concept of multi-field coupling of mechanics, electricity, hydraulics and heat enables the present invention to maintain a constant axial preload under extreme working conditions, greatly improving the processing consistency of precision manufacturing equipment.

[0049] During the long-term operation of precision shaft systems, the fatigue characteristics of materials evolve with the load history. In this embodiment, the fatigue assessment module 41 not only considers the steady-state preload but also incorporates the dynamic load fluctuations during the servo adjustment process into the calculation. By processing the high-frequency sampling data fed back by the piezoelectric force sensor 121, the system can identify abnormal vibration loads caused by poor spindle dynamic balance or bearing defects. These abnormal loads are accurately captured by the rainflow counting method and accumulated in the total damage factor. When the damage factor reaches the preset threshold, the central adaptive control platform 5 will automatically adjust the control strategy, extend the service life of the bearing by appropriately reducing the preload setting value, and display specific maintenance suggestions on the human-machine interface. This intelligent self-healing and early warning mechanism makes the servo adaptive control system different from the simple force value adjustment category and has the function of equipment health management.

[0050] The stacking method of the disc spring assembly in this invention can be flexibly adjusted for different shaft system structures. For example, in applications requiring high stiffness preload, the spring stiffness can be increased by stacking in the same direction; while in applications requiring large stroke compensation, the deformation can be increased by stacking in opposite directions. This combination of mechanical flexibility and servo rigidity allows the system to adapt to a variety of application requirements, from micro-precision spindles to large heavy-duty machine tool spindles. The selection of the planetary ball screw is also optimized according to the load capacity, and its high cycle life and high transmission efficiency ensure the long-term stability of the system under frequent adjustments. The introduction of a high-line-count grating ruler eliminates the influence of backlash and thermal deformation in the transmission chain on positioning accuracy, allowing the compensation action to be precisely applied to the movable bearing housing.

[0051] In terms of specific algorithm implementation, the central adaptive control platform 5 adopts multi-sampling rate control technology; the sampling period for temperature signals is set to the second level because the heat conduction process has significant inertia; while the sampling periods for force and displacement signals are set to the millisecond level to cope with mechanical vibration and transient load changes. Through this asymmetric sampling strategy, the system effectively reduces the processor's computational load while ensuring control accuracy; the coefficient update frequency in the regression correlation model is also dynamically adjusted according to the temperature rise rate, increasing the update frequency during the rapid temperature rise startup phase and decreasing the update frequency to enter maintenance mode during the thermal equilibrium phase; this strategy ensures the robustness and reliability of the system throughout its entire life cycle.

[0052] To enable those skilled in the art to fully understand and implement this invention, the specific implementation principles of this invention are further supplemented below with a specific application scenario.

[0053] Step 1: During the initial static preload and reference establishment of the system, the bearing assembly is first installed in the spindle sleeve by manual or automated assembly, and the outer ring of the bearing is brought into contact with the inner stepped surface of the movable bearing housing. The central adaptive control platform 5 issues an initialization command to control the precision execution drive end 3 to drive the servo motor to rotate the planetary reducer, which in turn pushes the movable bearing housing axially towards the front end of the spindle through the planetary ball screw. During this process, the movable bearing housing compresses the disc spring assembly, which undergoes elastic deformation under pressure and generates a reverse elastic force. This elastic force acts on the outer ring of the bearing through the movable bearing housing, thereby establishing the initial axial preload. The piezoelectric force sensor 121 installed between the contact surfaces captures the static pressure signal in real time and converts it into a digital signal through the signal conditioning and packaging module 13, which is then fed back to the central adaptive control platform 5. When the feedback force value reaches the preset static reference value, the platform stops driving the servo motor and simultaneously records the reading of the grating ruler at this time as the zero displacement reference, thus completing the initial coupling of the mechanical structure and control logic.

[0054] Step 2, Dynamic Thermal Gradient Sensing and Model Calculation: When the precision shaft system begins high-speed rotation, frictional losses between the spindle and bearings cause a significant temperature rise in the axial core area. At this time, the distributed temperature sensor array 11, attached to different positions on the bearing outer ring and spindle sleeve, begins to cyclically collect the real-time temperature of each measurement point. Due to the time lag and spatial non-uniformity of heat conduction in metal structural components, the difference in the temperature rise rate at different points forms a complex axial and radial temperature gradient. The central adaptive control platform 5 calls the algorithm of the thermodynamic model compensation end 2, substitutes the collected multi-point temperatures into the three-dimensional unsteady temperature field model, and calculates the thermal elongation of the spindle and support structure under the current temperature distribution. This step predicts the trend of increased bearing clearance or a surge in preload caused by thermal deformation through theoretical model, realizing the transformation from passive response to active prediction, and solving the technical defects of traditional temperature control methods in adjusting lag under complex working conditions.

[0055] Step 3: During the execution of servo adaptive axial force adjustment, the central adaptive control platform 5 calculates the compensation displacement based on the thermodynamic model and combines it with the real-time load fluctuation deviation fed back by the piezoelectric force sensor 121. It then generates execution commands through an adaptive PID control algorithm. The servo motor precisely rotates a specific angle according to the command. After torque amplification and deceleration by the planetary reducer, the planetary ball screw converts the rotational motion into a micrometer-level linear displacement of the movable bearing seat. If the model predicts that the preload will loosen due to thermal elongation of the spindle, the planetary ball screw pushes the movable bearing seat further forward, using the further compression of the disc spring assembly to compensate for the spindle elongation. Conversely, if the temperature rise causes excessive preload, the screw drives the bearing seat to retreat slightly. During the movement, a high-line-count grating ruler continuously detects the displacement of the movable bearing seat and feeds back the position signal to the central adaptive control platform 5 in real time. Through dual closed-loop control of the position loop and force loop, the backlash error in the mechanical transmission chain is offset, ensuring the absolute accuracy of axial force adjustment.

[0056] In step four, during closed-loop accuracy verification and operational health assessment, after the axial force adjustment is completed, the system continuously monitors the stability of the preload through the piezoelectric force sensor 121 to verify whether the adjustment effect has reached the constant state expected by the thermodynamic model. At the same time, the operational data storage terminal 4 stores the collected full-cycle data in a structured manner. The fatigue assessment module 41 inside the central adaptive control platform 5 uses the rainflow counting method to conduct real-time analysis of these dynamic loads and calculate the cumulative damage of the bearing under the combined action of alternating stress and thermal stress. By comparing the SN curve of the material, the system can calculate the remaining fatigue life of the bearing in real time. This assessment method based on actual operating load rather than simply operating time can more accurately reflect the true health status of the precision shaft system. When the assessment results show an abnormal damage rate, the system will automatically fine-tune the preload control strategy to optimize the bearing's stress environment while ensuring machining accuracy, thus achieving synergistic optimization of machining performance and equipment life.

[0057] All contents not described in detail in the specification are existing technologies known to those skilled in the art, and the model parameters of each electrical appliance are not specifically limited; conventional equipment can be used. Electrical control components not mentioned in this technical solution are not shown in the figures because they are existing technologies, and will not be described here.

[0058] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A servo adaptive control system that automatically adjusts axial force according to temperature gradient, characterized in that, It includes a multi-dimensional environmental sensing terminal (1), a thermodynamic model compensation terminal (2), a precision execution drive terminal (3), an operation data storage terminal (4), and a central adaptive control platform (5); the multi-dimensional environmental sensing terminal (1), the thermodynamic model compensation terminal (2), the precision execution drive terminal (3), and the operation data storage terminal (4) are all connected to the central adaptive control platform (5); the multi-dimensional environmental sensing terminal (1) is used to collect the distributed temperature gradient of the shaft system and the real-time axial preload signal; the thermodynamic model compensation terminal (2) is used to calculate the thermal elongation of the shaft system according to the temperature gradient and generate the displacement compensation value; the precision execution drive terminal (3) is used to fine-tune the axial position of the movable bearing seat according to the compensation command; the operation data storage terminal (4) is used to store temperature, axial force, and displacement operation data; the central adaptive control platform (5) is used to realize force-position hybrid closed-loop control.

2. The system according to claim 1, characterized in that, The multi-dimensional environmental sensing terminal (1) includes a distributed temperature sensing array (11), a dynamic load monitoring array (12), and a signal conditioning and packaging module (13). The distributed temperature sensing array (11) includes multiple temperature measuring units (111) arranged along the axial and radial directions of the main shaft. The temperature measuring units (111) are fixed to the outer ring of the bearing, the main shaft sleeve, and the surface of the support. The dynamic load monitoring array (12) includes a piezoelectric force sensor (121) installed between the bearing housing and the frame. The signal conditioning and packaging module (13) is used to amplify, filter, and convert the temperature and force signals to analog-to-digital.

3. The system according to claim 2, characterized in that, The temperature measuring unit (111) adopts a thin-film platinum resistance sensor and is installed by thermal bonding or thread fastening.

4. The system according to claim 1, characterized in that, The thermodynamic model compensation end (2) includes a heat conduction analysis module (21), a stiffness evolution analysis module (22), and a compensation amount calculation module (23); the heat conduction analysis module (21) is used to calculate the shaft temperature distribution based on temperature data; the stiffness evolution analysis module (22) is used to correct the material elastic modulus and thermal expansion coefficient based on temperature; the compensation amount calculation module (23) is used to convert the thermal deformation into an axial displacement compensation value.

5. The system according to claim 1, characterized in that, The precision drive end (3) includes a servo drive control module (31), a precision transmission execution module (32), and a position feedback monitoring module (33); the servo drive control module (31) is used to output drive signals; the precision transmission execution module (32) is composed of a servo motor, a reduction mechanism, and a planetary ball screw; the position feedback monitoring module (33) uses a grating ruler micrometer unit (331) to realize full closed-loop displacement feedback.

6. The system according to claim 5, characterized in that, The precision actuator drive end (3) also includes a preload constant mechanism (34), which includes an elastic compensation element (341) disposed between the movable bearing seat and the thrust bracket. The elastic compensation element (341) adopts a disc spring structure.

7. The system according to claim 1, characterized in that, The central adaptive control platform (5) adopts a three-loop servo control structure, consisting of a current loop, a speed loop, and a position loop from the inside out, with axial preload as the outer loop for correction.

8. The system according to claim 1, characterized in that, The central adaptive control platform (5) adjusts the output in real time using a PID algorithm based on the measured displacement of the grating ruler and the feedback axial force from the piezoelectric force sensor (121) to maintain a constant axial preload.

9. The system according to claim 4, characterized in that, The running data storage terminal (4) includes a storage module (42), which includes a local storage unit (421) and a communication unit (422) for recording historical temperature, axial force, and displacement data, and supporting data uploading, querying, and over-limit alarms.

10. The system according to claim 9, characterized in that, The running data storage terminal (4) also includes a fatigue assessment module (41) for statistical analysis of the axial force load spectrum and calculation of the remaining bearing life based on the linear damage accumulation theory.

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