Precise grinding method, system and equipment for high-precision transmission shaft

Abstract

The invention discloses a precise grinding machining method, system and equipment for a high-precision transmission shaft, and relates to the technical field of grinding machining. The method comprises the steps that a measuring assembly is deployed to obtain grinding state characteristics in real time along with automatic grinding; a programmable impedance network is inserted into the servo driver to construct a double-closed-loop control architecture; the grinding state characteristics are input into a state ring for displacement and mechanical error analysis, and a selectable activation impedance ring determines regulation and control parameters through a resistance and capacitance parameter regulation compensation decision; and the programmable impedance network implements time window regulation and control compensation on the grinding process according to the parameters. The technical problems that in the grinding process of an existing high-precision transmission shaft, due to mechanical load fluctuation, thermal deformation and system rigidity changes, the size precision is difficult to control stably, and the machining consistency is poor are solved, and the purposes that the grinding state is sensed in real time through a double-closed-loop framework, and self-adaptive impedance regulation and control are conducted are achieved; the size precision and form and location tolerance stability of the transmission shaft are improved, the rejection rate is reduced, and the machining efficiency is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of grinding processing, in particular to a precision grinding processing method, system and equipment for high-precision transmission shafts. BACKGROUND

[0002] As a key component in mechanical transmission system, the machining precision of transmission shaft directly affects the running stability, noise level and service life of the entire equipment. With the development of high-end equipment manufacturing industry, micron-level or even higher precision requirements are put forward for the size tolerance, geometric tolerance and surface quality of transmission shaft. As the last process of transmission shaft machining, the process level of precision grinding directly determines the final quality of the workpiece.

[0003] In the existing grinding processing technology, numerical control program is usually used to preset the processing path and parameters, and online measurement technology is used for feedback control. However, the traditional control method has the following limitations: first, the grinding process is a time-varying, nonlinear complex process. Factors such as grinding wheel wear, workpiece stiffness change, cutting heat deformation and vibration interference will cause large deviation between the actual grinding state and the preset program. The traditional proportional-integral-derivative control or single size feedback control is difficult to realize real-time and high-precision comprehensive compensation for the dynamic change of displacement error and mechanical error. Second, the existing technology pays insufficient attention to the dynamic matching of electrical parameters and mechanical load. The servo drive system usually uses fixed electrical parameters, which cannot be adjusted adaptively according to the real-time grinding load change. The mismatch between electrical parameters and mechanical load often leads to system response lag, oscillation and even overshoot, thereby leaving vibration marks or size out-of-tolerance on the workpiece surface. Therefore, how to overcome the problems of insufficient dynamic error compensation and poor matching of electrical parameters and mechanical load in the existing technology to realize high-precision and high-stability automatic grinding of transmission shafts is a technical problem to be solved by those skilled in the art. SUMMARY

[0004] The present application provides a precision grinding processing method, system and equipment for high-precision transmission shafts, which solves the technical problems of unstable size precision control and poor processing consistency caused by mechanical load fluctuation, thermal deformation and system stiffness change during the grinding process of existing high-precision transmission shafts.

[0005] In a first aspect, the present application provides a precision grinding processing method for high-precision transmission shafts, which comprises:

[0006] In the grinding machine, a measurement component is deployed to obtain grinding state features in real time during the automatic grinding process of the transmission shaft workpiece; a double closed-loop control architecture is constructed by inserting a programmable impedance network into a servo driver, wherein the state loop and the impedance loop are connected through supervised training, and the measurement component and the programmable impedance network are connected to form the double closed-loop control architecture; according to the double closed-loop control architecture, the grinding state features are input into the state loop, displacement error based on diameter value and mechanical error based on mechanical load are analyzed, and the impedance loop is optionally activated to make a compensation decision based on optimal resistance and capacitance combination to determine impedance control parameters; the programmable impedance network responds to the impedance control parameters to perform process time window control and compensation superposition on the automatic grinding process of the grinding machine.

[0007] In a second aspect of the present application, a high-precision transmission shaft precision grinding processing system is provided, which comprises:

[0008] The state measurement module is deployed in the grinding machine to obtain grinding state features in real time during the automatic grinding process of the transmission shaft workpiece; the closed-loop architecture construction module constructs a double closed-loop control architecture by inserting a programmable impedance network into a servo driver, wherein the state loop and the impedance loop are connected through supervised training, and the measurement component and the programmable impedance network are connected to form the double closed-loop control architecture; the closed-loop architecture analysis module inputs the grinding state features into the state loop according to the double closed-loop control architecture, performs displacement error analysis based on diameter value and mechanical error analysis based on mechanical load, and optionally activates the impedance loop to make a compensation decision based on optimal resistance and capacitance combination to determine impedance control parameters; the grinding control module controls the programmable impedance network to respond to the impedance control parameters to perform process time window control and compensation superposition on the automatic grinding process of the grinding machine.

[0009] In a third aspect of the present application, an electronic device is provided, comprising: a memory for storing executable instructions; a processor for executing the executable instructions stored in the memory to implement the high-precision transmission shaft precision grinding processing method provided by the present application.

[0010] One or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0011] In the grinding machine deployment measurement component, the grinding state characteristics are obtained in real time during the automatic grinding process of the transmission shaft workpiece. Then, a double closed-loop control architecture is constructed by inserting a programmable impedance network in the servo driver, in which the state loop and the impedance loop are connected through the supervised training, and the measurement component and the programmable impedance network are connected to form the double closed-loop control architecture. Subsequently, according to the double closed-loop control architecture, the grinding state characteristics are input into the state loop, the displacement error based on the diameter value and the mechanical error based on the mechanical load are analyzed, and the impedance loop is optionally activated to make the compensation decision based on the optimal resistance and capacitance combination to determine the impedance regulation parameters. Finally, the programmable impedance network responds to the impedance regulation parameters to regulate and compensate the process time window of the automatic grinding process of the grinding machine. The technical problems of unstable size precision control and poor machining consistency caused by mechanical load fluctuation, thermal deformation and system stiffness change in the existing high-precision transmission shaft grinding process are solved, and the technical effects of real-time sensing of grinding state and adaptive impedance regulation through the double closed-loop architecture, improving the size precision and shape tolerance stability of the transmission shaft, reducing the scrap rate and improving the machining efficiency are achieved. BRIEF DESCRIPTION OF DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0013] Figure 1 The high-precision transmission shaft precision grinding machining method flowchart provided by the embodiment of the present application.

[0014] Figure 2 The high-precision transmission shaft precision grinding machining system structure schematic diagram provided by the embodiment of the present application.

[0015] Figure 3 The structure schematic diagram of the exemplary electronic device of the present application.

[0016] Explanation of reference signs: state measurement module 11, closed-loop architecture construction module 12, closed-loop architecture analysis module 13, grinding regulation module 14, processor 21, memory 22, input device 23, output device 24. DETAILED DESCRIPTION

[0017] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the specific embodiments, structures, features and effects according to the present application are described in detail as follows.

[0018] Embodiment one, as Figure 1As shown, the embodiment of the present application provides a precision grinding processing method of high-precision transmission shaft, wherein the method comprises:

[0019] In the grinding machine, a measurement component is deployed to acquire the grinding state features in real time during the automatic grinding process of the transmission shaft workpiece.

[0020] In one embodiment, the online detection unit is arranged at the key stress and displacement position of the grinding machine, so as to synchronously operate during the automatic grinding of the transmission shaft and realize continuous monitoring of the processing state. Specifically, a non-contact displacement sensor can be arranged near the grinding wheel frame to detect the slight change of the workpiece outer circle radius or diameter in real time, and a force sensor can be installed at the headstock, tailstock or support position to collect normal grinding force, tangential grinding force and axial force and other load data. After high-speed acquisition and filtering processing, various sensing signals form multi-dimensional grinding state parameters, including size change amount, size change rate, force fluctuation amplitude and its change trend, etc. The above state features are continuously updated during the grinding process, providing real-time data basis for subsequent error analysis and closed-loop control adjustment.

[0021] Further, the real-time acquisition of the grinding state features comprises:

[0022] A measurement component is deployed on the grinding machine to acquire the grinding state features of the transmission shaft processing process; wherein the deployment of the measurement component comprises: symmetrically installing at least two high-frequency eddy current displacement sensors on both sides of the grinding wheel frame, wherein the sensing probe is aligned with the surface of the transmission shaft workpiece, wherein the high-frequency eddy current displacement sensor measures the workpiece radius change; installing three-way piezoelectric force sensors on the headstock and tailstock of the grinding machine, wherein the three-way piezoelectric force sensor measures the normal grinding force, tangential grinding force and axial force.

[0023] Preferably, first according to the structure layout of the grinding machine, the installation position is selected on both sides of the grinding wheel frame, which is rigid and stable and has less vibration interference. At least two high-frequency eddy current displacement sensors are symmetrically fixed. During installation, the sensors are accurately calibrated to make the sensor probe axis perpendicular to the outer surface of the transmission shaft and maintain a predetermined initial gap distance. By calibrating the sensor zero point, the corresponding relationship between the voltage signal and the workpiece radius is established. During grinding, the high-frequency eddy current displacement sensor collects the radial displacement change data of the workpiece surface in real time at a high sampling frequency. After signal amplification, filtering and analog-digital conversion processing, the workpiece radius change and its rate of change are obtained, thereby reflecting the dynamic change characteristics of the machining size. In addition, a three-way piezoelectric force sensor is installed on the force transmission path of the headstock and tailstock of the grinding machine. During installation, the pre-tightening force is controlled to be in the linear working interval, and a standard loading device is used to apply known force values in the normal, tangential and axial directions to complete independent calibration of the three axes and establish the force-electric conversion relationship model in the normal, tangential and axial directions. During actual grinding, the force generated by the grinding contact is transmitted to the force sensor through the spindle and support structure. The three-way piezoelectric force sensor synchronously outputs the corresponding charge signal. After the signal is converted to a voltage signal by a charge amplifier, it is filtered and decoupled to obtain the real-time values and fluctuation trends of the normal grinding force, tangential grinding force and axial force. Finally, the displacement data and three-way force data are time-synchronized and data-fused to form a multi-dimensional grinding state feature dataset containing size change characteristics and mechanical load characteristics, providing real-time input parameters for subsequent error analysis and closed-loop control adjustment.

[0024] By inserting a programmable impedance network in the servo driver, a double closed-loop control architecture is constructed, wherein the cascaded state loop and impedance loop are supervised trained and connected with the measurement components and the programmable impedance network to form the double closed-loop control architecture.

[0025] In one embodiment, first structural modification is made in the control link of the servo driver, a programmable impedance network is inserted in the forward channel of the current loop or the power drive pre-stage, the programmable impedance network communicates with the control unit through a digital interface, so that the resistance value and capacitance value can be adjusted in real time during operation, thereby changing the equivalent electrical impedance characteristics of the drive system. After the hardware is embedded, the drive system is recalibrated to establish the mapping relationship between the impedance parameters and the system response characteristics. Subsequently, a double closed-loop control architecture is constructed at the control architecture level. During the construction process, based on historical grinding data and calibration experimental data, the state loop and the impedance loop are supervised and trained to determine the mapping model between the state error characteristics and the impedance parameter adjustment, so that the two form a cascaded control relationship. The outer layer of the double closed-loop control architecture is the state loop, which is used to receive the grinding state characteristics collected by the measurement assembly to form displacement error and mechanical error signals. The inner layer is the impedance loop, which is used to calculate the optimal resistance and capacitance combination of the current drive system. Then, the state loop and the measurement assembly are connected by data, the impedance loop and the programmable impedance network are connected by parameter control, and the two loops are cascaded to form a closed control link of measurement-analysis-impedance adjustment-drive response, which is the final complete double closed-loop control architecture, realizing real-time optimization and precision improvement of the grinding process.

[0026] Further, the double closed-loop control architecture is constructed, comprising:

[0027] A programmable impedance network is inserted in the forward channel of the current loop of the servo driver, wherein the programmable impedance network is composed of a digital potentiometer and a programmable capacitance array; according to the measurement assembly and the programmable impedance network, a double closed-loop control architecture is constructed, wherein the double closed-loop control architecture includes a state loop and an impedance loop.

[0028] Preferably, the control structure of the servo driver is first analyzed to determine the forward control channel of the current loop or the power amplifier front-end node. Without changing the original position loop and speed loop structure, a programmable impedance network is connected in series between the current command output and the power drive module, which is in the modulation path of the drive control signal. The programmable impedance network is composed of a digital potentiometer and a programmable capacitor array. The digital potentiometer is used to realize discrete or continuous adjustment of the equivalent resistance value, and the programmable capacitor array is used to realize the combination switching of the equivalent capacitance value. The two are connected with the upper control unit through the control bus, such as SPI or I2C interface, so that the resistance and capacitance parameters can be written and updated in real time by the control algorithm. After the hardware is embedded, the servo driver is tested, that is, under different impedance combinations, the dynamic performance indicators of the servo driver such as step response, overshoot, response time and steady-state error are collected, and the corresponding relationship between the impedance parameters and the system response characteristics is established, providing a basic model for subsequent impedance loop calculation. Subsequently, according to the functional division of the measurement assembly and the programmable impedance network, a double closed-loop control architecture is constructed. Specifically, the workpiece diameter change data and three-way grinding force data collected by the measurement assembly are input into the control unit as the input of the outer state loop. The state loop compares the real-time measurement value with the target diameter and target load range, calculates the displacement error, error rate and mechanical error, forms a comprehensive state error signal, and outputs the adjustment demand. On this basis, the inner impedance loop is constructed, which takes the error characteristics output by the state loop as the input, combines the pre-established impedance parameter-response characteristic model, calculates the optimal resistance and capacitance combination under the current condition, and generates impedance regulation parameters. The parameter is sent to the programmable impedance network through the digital interface to realize the real-time adjustment of the equivalent impedance of the servo driver. Finally, the state loop is responsible for error identification and control target generation, and the impedance loop is responsible for drive characteristic optimization and dynamic matching. The two are cascaded through the control unit and connected with the measurement assembly and the programmable impedance network for data and control, forming a complete double closed-loop control architecture to realize the closed control process of state sensing, error analysis, impedance adjustment and drive response.

[0029] Further, according to the measurement assembly and the programmable impedance network, a double closed-loop control architecture is constructed, comprising:

[0030] The grinding process of the transmission shaft workpiece is obtained, the grinding state is taken as the input, the displacement error amount and the rate based on the diameter value are taken as the first decision target, and the mechanical error size and the rate based on the mechanical load are taken as the second decision target. The state loop is constructed. The optimal resistance and capacitance combination calculated based on impedance matching is taken as the optimization regulation target, and the impedance loop is constructed. The state loop and the impedance loop are cascaded, and the connection between the state loop and the measurement assembly and the impedance loop and the programmable impedance network is established, to constitute the double closed-loop control architecture.

[0031] Optionally, first, the grinding process parameters of the transmission shaft workpiece are acquired, including the feed speed, cutting depth, target diameter, tolerance range, and allowable load range of each stage of rough grinding, semi-fine grinding, and fine grinding. At the same time, historical grinding data and calibration test data are collected, wherein the historical grinding data includes the diameter change amount, change rate, three-direction grinding force and its fluctuation characteristics recorded under different materials, different grinding stages, and different load conditions, and the corresponding processing quality results, such as size error and roundness error; the calibration test data is obtained by performing step response and disturbance response tests under different impedance parameter combinations, including system response time, overshoot, steady-state error, and vibration amplitude. On this basis, for the state ring, a mapping model of grinding state characteristics-processing error results is constructed, which takes the displacement error amount and change rate of the real-time diameter as the first decision target, and takes the mechanical error and change rate of the normal force, tangential force, and axial force of the mechanical load as the second decision target. A double-target error evaluation model is established by a supervised training method, such as a regression model or a weighted neural network model, to output a comprehensive error evaluation value, a corresponding adjustment demand amount, and a weight distribution coefficient. This model is used to weight and fuse the displacement error and the mechanical error in the running process to form the control decision result of the state ring.

[0032] In the training phase, the historical grinding data and the calibration test data are first taken as sample bases, and each sample data contains diameter error amount, diameter error change rate, normal grinding force error amount, tangential grinding force error amount, axial force error amount, and its change rate, and the corresponding control results, including comprehensive error evaluation value, adjustment demand amount, and weight distribution coefficient. The control results are used as supervision labels to evaluate the influence degree of the current grinding state on the processing result. In the feature processing stage, all input variables are normalized, and a double-target feature vector is constructed. In terms of model construction, a multivariate weighted regression model or a lightweight feedforward neural network model can be used. For example, in the weighted neural network model, the input layer, the hidden layer, and the output layer are set, and the sample data is iteratively trained by using the Adam or gradient descent algorithm. When the mean square error of the validation set converges to a preset threshold, such as less than 0.01, the training is stopped. After the training is completed, the stable model parameter matrix and the bias term are obtained to form a fixed double-target error evaluation model.

[0033] For the impedance loop, impedance parameter-response characteristic model is established based on calibration experimental data. Specifically, taking the digital potentiometer resistance R and the equivalent capacitance C of the capacitance array as input variables, taking the system response time, overshoot, vibration amplitude and steady-state error as output variables, the response characteristic model is constructed by multivariate regression or table lookup interpolation method, and then combined with mechanical load characteristic parameters such as the current normal force and its change rate, the mapping relationship of load characteristic-optimal RC combination is established, so as to form the optimal response characteristic model that can be used for online calculation. After completing the model training, the state loop is constructed, the state loop takes the grinding state characteristics as the input, compares the real-time diameter value with the target diameter to obtain the displacement error and its change rate, and at the same time calculates the mechanical error size and its change rate, and outputs the comprehensive error evaluation value and the corresponding adjustment demand through the trained double-target error evaluation model, as the output of the outer loop control. Then, the impedance loop is constructed, the impedance loop takes the comprehensive error output by the state loop and the current load characteristics as the input, calls the established impedance parameter-response characteristic model for calculation, and solves the optimal resistance and capacitance combination under the current condition on the premise of meeting the phase constraint condition, and generates impedance control parameters. Finally, the state loop and the impedance loop are cascaded, the state loop outputs the error decision result as the outer loop, and the impedance loop optimizes the driving side dynamic characteristics according to the result as the inner loop, and at the same time, the data interface connection between the state loop and the measurement component is established, so that it can continuously receive real-time diameter and mechanical data, and the control interface connection between the impedance loop and the programmable impedance network is established, so that it can write resistance and capacitance parameters in real time. Through the above connection of measurement input, state decision, impedance optimization, driving response and measurement feedback, a complete double closed-loop control architecture is realized, and adaptive optimization control of the grinding process is realized.

[0034] According to the double closed-loop control architecture, the grinding state characteristics are input into the state loop, displacement error based on diameter value and mechanical error based on mechanical load are analyzed, and the impedance loop is optionally activated to make compensation decision based on optimal resistance and capacitance combination, and impedance control parameters are determined.

[0035] In one embodiment, after the double closed-loop control architecture is established, the grinding state feature data collected by the measurement component in real time is input to the state loop. The state loop first compares the real-time diameter value with the target diameter, calculates the displacement error and its rate of change, and analyzes the normal force, tangential force and axial force, and calculates the mechanical error of the current mechanical load relative to the set load interval and its trend. Through the double target error evaluation model, the displacement error and the mechanical error are comprehensively evaluated to obtain the comprehensive error evaluation value of the current grinding state, the corresponding adjustment requirement and the weight distribution coefficient. Under normal processing conditions, when the comprehensive error evaluation value is within the preset allowable interval, only the adjustment requirement is output by the state loop, and the feed speed or the driving instruction is fine-tuned to maintain stable processing. At this time, the impedance loop is not started to ensure the simplicity of the control structure and reduce system disturbance. When it is detected that the comprehensive error evaluation value exceeds the preset threshold, that is, the error exceeds the limit or the error rate abnormally increases, the impedance loop activation mechanism is triggered. The impedance loop takes the current comprehensive error value, the error rate and the grinding stage label as input, calls the established impedance parameter-response characteristic model, and calculates the optimal resistance and capacitance combination that can optimize the dynamic response under the current mechanical load condition. Under the premise of meeting the parameter boundary constraint, impedance control parameters are generated and written to the programmable impedance network through a digital interface. The impedance network adjusts the equivalent resistance and capacitance values in real time according to the received control parameters, thereby changing the electrical time constant and dynamic response characteristics of the servo driver. In this way, the impedance adjustment amount is superimposed on the original automatic grinding control process to quickly suppress and compensate for abnormal errors. When the error returns to the normal range, the impedance reinforcement adjustment mode can be selected to exit and return to the conventional control state dominated by the state loop, thereby ensuring system stability while improving grinding size accuracy and processing consistency.

[0036] Further, before activating the impedance loop, comprising:

[0037] With the processing of the workpiece by the transmission shaft, the first constraint condition is determined according to the grinding stage, wherein the preset impedance parameter boundary is defined by labeling the rough grinding label or the fine grinding label for each grinding stage; the parameter space of the impedance loop is constrained by the preset impedance parameter boundary, wherein the boundary of the parameter space is updated according to the label of the real-time grinding stage.

[0038] Optionally, before the transmission shaft workpiece enters the grinding process, the entire machining process is first divided into different stages according to the established grinding process, for example, a rough grinding stage, a semi-fine grinding stage and a fine grinding stage, and corresponding stage labels are set for each stage. At the initialization or process import, the feed amount, cutting depth, target size allowance and allowable vibration range of each stage are written into the control unit as stage identification basis. Subsequently, based on historical grinding data and calibration test results, the corresponding impedance parameter reasonable interval is determined for different grinding stages. Specifically, in the rough grinding stage, in order to improve the material removal efficiency and response speed, a lower equivalent resistance range and a smaller capacitor combination range can be preset; in the fine grinding stage, in order to enhance the system stiffness and suppress vibration, a higher resistance range is preset, and the capacitor combination range is appropriately expanded. The above impedance parameter interval constitutes the preset impedance parameter boundary of each stage, including the upper limit of resistance, the lower limit of resistance and the allowable interval of capacitor combination. In the actual machining process, the control unit determines the grinding stage according to the current machining progress or real-time grinding state, and automatically loads the corresponding stage label. When the impedance ring calculates the optimal resistance and capacitor combination, it first reads the impedance parameter boundary corresponding to the current stage, limits the calculation process within the parameter interval, forms a constrained parameter search space, and avoids generating impedance adjustment results that do not meet the characteristics of the current process stage. When the machining process transitions from rough grinding to fine grinding, the stage label is updated according to the stage conversion signal, and the upper limit and lower limit of the impedance parameter are automatically adjusted to complete the dynamic contraction or expansion of the parameter space. In this way, the impedance ring parameter space is updated in real time with the grinding stage, so that the impedance adjustment has both adaptive optimization capability and process constraint control, thereby meeting the requirements of machining efficiency and machining accuracy in different stages.

[0039] Further, determining the impedance control parameter comprises:

[0040] inputting the grinding state feature into the state ring, and performing calculation based on the first decision target and the second decision target in parallel to determine double-pass error data identified with a weight value; and for the double-pass error data, taking any error data as a greedy target to locate the impedance control parameter in the determined parameter upper limit and parameter lower limit.

[0041] Optionally, first, the grinding state features collected by the measurement assembly in real time are input into the state ring, and the grinding state features include the real-time diameter value, the diameter change rate, and the three-way grinding force and the corresponding change rate. Two parallel computing channels are arranged inside the state ring. The first channel takes the target diameter as the reference to calculate the current diameter deviation and its change rate, forming displacement error data based on the diameter value. The second channel takes the preset mechanical load reference interval as the reference to calculate the deviation of the current normal force, tangential force or axial force and its change rate, forming mechanical error data based on the mechanical load. Subsequently, the displacement error data and the mechanical error data are normalized, and analyzed according to the double-target error evaluation model to generate a weight distribution coefficient, which is multiplied by the corresponding deviation data and change rate to obtain double-trip error data with weight identification. In the impedance ring calculation stage, the upper and lower boundaries of the resistance and capacitance parameters are determined according to the current stage constraint condition. The greedy strategy is adopted to select the error item with the highest current weight in the double-trip error data as the optimization target, and perform local search in the parameter space composed of the defined upper and lower boundaries of the parameters. By calling the impedance parameter-response characteristic model, the improvement degree of the current target error under different combinations of resistance R and capacitance C is evaluated, and the impedance parameter combination that can most effectively reduce the greedy target error is gradually approached. Finally, the impedance control parameter that satisfies the current constraint condition and has the optimal improvement effect on the selected error target is determined and output to the programmable impedance network for real-time adjustment. Through the above parallel measurement and greedy positioning process, the dominant error is quickly suppressed, and the stable control of the other error item is also considered.

[0042] Further, taking any one of the error data as the greedy target, the impedance control parameter is positioned in the determined parameter upper boundary and parameter lower boundary, including:

[0043] For the first error data in the double-trip error data, the weight value is taken as the constraint to make the parameter adjustment decision based on the optimal resistance and capacitance combination to determine the first parameter group; for the second error data, the second parameter group is determined; by mapping the first parameter group and the second parameter group, the parameter upper boundary and the parameter lower boundary are determined; the parameter upper boundary and the parameter lower boundary are taken as the parameter adjustment range, and the impedance control parameter is determined by performing balanced game.

[0044] Optionally, first, for the first error data in the double-trip error data, the weight value of the error is introduced into the parameter adjustment target function as a constraint condition in the impedance ring. Specifically, the weight value of the first error is multiplied by the deviation of the first error to form a new error value, which is taken as the constraint condition of the parameter adjustment target function. The parameter adjustment is focused on when the weight value of the first error data is greater than the weight value of the second error data. When the weight value of the first error data is greater than the weight value of the second error data, the parameter adjustment search is more inclined to improve the system response speed to quickly reduce the diameter deviation. When the size is small, more attention is paid to stability. The impedance ring calls the established impedance parameter-response characteristic model, and searches or locally searches the combination of resistance R and capacitance C within the preset boundary at the current stage, calculates the suppression effect of different combinations on the first error, selects the resistance-capacitance combination that optimizes the first error evaluation value to form the first parameter group . Subsequently, for the second error data, the same model calculation process is adopted, but the optimization target is switched to suppressing the grinding force fluctuation and load anomaly. At this time, the parameter adjustment tends to increase damping and stiffness and reduce vibration sensitivity. By searching within the stage constraint boundary, the resistance-capacitance combination that optimizes the second error evaluation value is determined as the second parameter group . Then, the parameter adjustment range is determined by mapping the first parameter group and the second parameter group. This mapping is to align the two groups of parameters in the same parameter coordinate system, respectively compare the value intervals of resistance and capacitance, and take the smaller value as the lower limit of resistance and the larger value as the upper limit of resistance and . Take the smaller value as the lower limit of capacitance and the larger value as the upper limit of capacitance and . In this way, the upper and lower limits of the parameters are obtained, forming a feasible parameter adjustment interval that covers both displacement error requirements and mechanical error requirements, avoiding the deterioration of one target due to the optimization of a single target. Then, the upper and lower limits of the parameters are taken as the unified parameter adjustment range, and the balanced game is performed in this range to determine the final impedance control parameters. Specifically, the first error target and the second error target are regarded as two game participants, and the reduction of their own errors is taken as the profit function, and the impedance parameters (R, C) are taken as the common strategy variable. The impedance ring iteratively searches within the parameter adjustment range, so that under the current parameters, any target cannot individually benefit from the improvement without significantly harming the other target, i.e., reaching the equilibrium point of error suppression and system stability. After reaching the equilibrium, the corresponding is output as the impedance control parameter and is sent to the programmable impedance network for dynamic adjustment, thereby achieving the optimal compromise between response speed and processing stability.

[0045] The programmable impedance network responds to the impedance control parameter to perform process time window adjustment compensation superposition on the automatic grinding process of the grinding machine tool.

[0046] In one embodiment, when the impedance regulation parameter is calculated, the corresponding resistance value and capacitance combination instruction are sent to the programmable impedance network through a digital communication interface. The digital potentiometer and the capacitance array inside the programmable impedance network complete resistance value switching and capacitance combination reconstruction according to the instruction, thereby changing the equivalent electrical impedance characteristics of the servo drive system in real time, causing the electrical time constant, damping coefficient and dynamic response characteristics of the driver to be adjusted accordingly. In the automated grinding process, the grinding machine runs according to the preset process program, for example, completes rough grinding, semi-fine grinding or fine grinding according to the set feed speed, cutting depth curve and dwell time. This impedance regulation does not change the logical flow of the original process program, but dynamically superimposes adjustment on the drive response characteristics within a specific process time window. For example, during the feed acceleration stage, the response speed is improved by reducing the equivalent resistance value; during the size approaching target stage, the system stiffness and damping are enhanced by increasing the equivalent resistance or optimizing the capacitance combination to suppress vibration and overshoot; during the spark grinding or pressure maintaining stage, the system stability is maintained by optimizing the impedance matching. The process time window can be determined by the processing stage label, error trigger signal or time period determination logic. The impedance regulation parameter only takes effect within the corresponding time window, and after exceeding the window, it can be restored to the default impedance configuration or enter the next stage parameter setting. In this way, the impedance adjustment amount is superimposed in the form of dynamic compensation into the automated grinding control process, realizing targeted reinforcement control of key processing stages, and improving size stability and processing precision without changing the overall process rhythm.

[0047] Further, the programmable impedance network responds to the impedance regulation parameter, comprising:

[0048] The grinding machine performs automated grinding drive according to the preconfigured process grinding program, the measurement component performs real-time grinding state measurement synchronously, and the dynamic impedance regulation parameter is obtained based on the state loop and the impedance loop; the impedance regulation parameter is sent to the programmable impedance network to perform regulation compensation superposition of the automated grinding process.

[0049] Preferably, before the processing starts, a pre-configured process grinding program is imported into the system, which includes the feed speed curve, cutting depth parameters, spindle speed, dwell time and stage switching conditions of each grinding stage. The grinding machine automatically executes the grinding drive control according to the process program to realize the continuous processing of the transmission shaft. During the automatic grinding drive process, the measurement components deployed on the machine tool work synchronously, the high-frequency eddy current displacement sensor collects the workpiece diameter change data in real time, the three-direction piezoelectric force sensor collects the normal force, tangential force and axial force data in real time, and various signals are input into the control unit after filtering, amplification and analog-digital conversion processing to form a continuously updated grinding state characteristic data stream. Subsequently, the system inputs the grinding state characteristic data into the state ring for error analysis, calculates the displacement error and mechanical error, and obtains the comprehensive error evaluation value and the corresponding adjustment requirement amount combined with the error change rate. When the error is within the allowable range, the adjustment requirement amount output by the state ring is used as the impedance regulation parameter; when the error exceeds the boundary, the impedance ring calculates the corresponding optimal resistance and capacitance combination according to the comprehensive error characteristics and the current grinding stage label, and generates the dynamic impedance regulation parameter. Then, the system sends the impedance regulation parameter to the programmable impedance network through the digital communication interface. The digital potentiometer and capacitor array inside the programmable impedance network complete the switching of resistance and capacitance values according to the received parameters, so that the equivalent electrical impedance of the servo driver is adjusted, and the adjustment result is superimposed on the original automatic grinding control instruction to optimize the dynamic response characteristics of the driver without changing the overall process flow. Through the above process, the closed compensation process of automatic grinding drive, real-time state measurement, double-ring error analysis, impedance parameter generation and drive characteristic adjustment is realized, so that the grinding process can obtain higher size control precision and processing stability while maintaining stable process rhythm.

[0050] In summary, the embodiments of the present application have at least the following technical effects:

[0051] The state measurement module 11 is used to acquire the grinding state features in real time during the automatic grinding process of the transmission shaft workpiece by deploying a measurement component in the grinding machine tool; the closed-loop architecture construction module 12 is used to construct a double closed-loop control architecture by inserting a programmable impedance network in the servo driver, wherein the double closed-loop control architecture is constructed by connecting the measurement component and the programmable impedance network through the state loop and the impedance loop which are trained in a cascaded manner by supervised training; the closed-loop architecture analysis module 13 is used to input the grinding state features into the state loop according to the double closed-loop control architecture, perform the displacement error analysis based on the diameter value and the mechanical error analysis based on the mechanical load, and optionally activate the impedance loop to perform the parameter compensation decision based on the optimal resistance and capacitance combination to determine the impedance regulation parameters; and the grinding regulation module 14 is used to perform the process time window regulation compensation superposition on the automatic grinding process of the grinding machine tool in response to the impedance regulation parameters.

[0052] In the embodiment two, based on the same inventive concept as the precision grinding machining method of the high-precision transmission shaft in the foregoing embodiments, as shown in the embodiment two, the application provides a precision grinding machining system of a high-precision transmission shaft, wherein the system comprises: Figure 2

[0053] The state measurement module 11 is used to acquire the grinding state features in real time during the automatic grinding process of the transmission shaft workpiece by deploying a measurement component in the grinding machine tool; the closed-loop architecture construction module 12 is used to construct a double closed-loop control architecture by inserting a programmable impedance network in the servo driver, wherein the double closed-loop control architecture is constructed by connecting the measurement component and the programmable impedance network through the state loop and the impedance loop which are trained in a cascaded manner by supervised training; the closed-loop architecture analysis module 13 is used to input the grinding state features into the state loop according to the double closed-loop control architecture, perform the displacement error analysis based on the diameter value and the mechanical error analysis based on the mechanical load, and optionally activate the impedance loop to perform the parameter compensation decision based on the optimal resistance and capacitance combination to determine the impedance regulation parameters; and the grinding regulation module 14 is used to perform the process time window regulation compensation superposition on the automatic grinding process of the grinding machine tool in response to the impedance regulation parameters.

[0054] Further, the state measurement module 11 is used to perform the following method:

[0055] ​The measurement assembly is deployed on the grinding machine tool to obtain the grinding state characteristics of the transmission shaft machining process; wherein, the deployment of the measurement assembly comprises: symmetrically installing at least two high-frequency eddy current displacement sensors on both sides of the grinding wheel frame, wherein the sensor probe is aligned with the transmission shaft workpiece surface, and the high-frequency eddy current displacement sensor measures the workpiece radius change; installing a three-way piezoelectric force sensor on the headstock and tailstock of the grinding machine, wherein the three-way piezoelectric force sensor measures the normal grinding force, tangential grinding force and axial force.

[0056] Further, the closed-loop architecture construction module 12 is used to execute the following method:

[0057] A programmable impedance network is inserted in the current loop forward channel of the servo driver, wherein the programmable impedance network is composed of a digital potentiometer and a programmable capacitance array; a double closed-loop control architecture is constructed according to the measurement assembly and the programmable impedance network, wherein the double closed-loop control architecture includes a state loop and an impedance loop.

[0058] Further, the consistency analysis module 13 is used to execute the following method:

[0059] The grinding process of the transmission shaft workpiece is obtained, the grinding state is taken as the input, the displacement error amount and the change rate based on the diameter value are taken as the first decision target, the mechanical error size and the change rate based on the mechanical load are taken as the second decision target, the state loop is constructed; the optimal resistance and capacitance combination calculated based on impedance matching is taken as the optimization control target, the impedance loop is constructed; the state loop and the impedance loop are cascaded, and the connection between the state loop and the measurement assembly and the impedance loop and the programmable impedance network is established, to constitute the double closed-loop control architecture.

[0060] Further, the continuity analysis module 14 is used to execute the following method:

[0061] According to the grinding stage, the first constraint condition is determined along with the machining of the transmission shaft workpiece, wherein the preset impedance parameter boundary is defined by labeling the rough grinding label or the fine grinding label for each grinding stage; the parameter space of the impedance loop is constrained by the preset impedance parameter boundary, wherein the parameter space is updated in boundary according to the label of the real-time grinding stage.

[0062] Further, the continuity analysis module 14 is used to execute the following method:

[0063] The grinding state characteristics are input into the state loop, and the measurement based on the first decision target and the second decision target is executed in parallel to determine the double-path error data with weight values; for the double-path error data, any error data is taken as the greedy target, and the impedance control parameter is located in the determined upper parameter boundary and lower parameter boundary.

[0064] Further, the continuity analysis module 14 is configured to perform the following method:

[0065] For the first error data in the double-trip error data, the optimal resistance and capacitance combination-based parameter adjustment decision is made with the weight value as a constraint to determine a first parameter group; for the second error data, a second parameter group is determined; by mapping the first parameter group and the second parameter group, a parameter upper limit and a parameter lower limit are determined; the parameter upper limit and the parameter lower limit are taken as a parameter adjustment range, and by performing a balanced game, the impedance control parameter is determined.

[0066] Further, the image labeling module 15 is configured to perform the following method:

[0067] The grinding machine is automatically driven according to the preconfigured process grinding program, the measurement assembly synchronously performs real-time grinding state measurement, and the dynamic impedance control parameter is obtained based on the state ring and the impedance ring; the impedance control parameter is sent to the programmable impedance network, and the control compensation superposition of the automatic grinding process is performed.

[0068] Embodiment three, Figure 3 The structure schematic diagram of the electronic device provided in the embodiment three of the present application shows a block diagram of an exemplary electronic device suitable for implementing the embodiments of the present application. Figure 3 The electronic device shown is only an example, and should not impose any limitation on the functions and use range of the embodiments of the present application. As Figure 3 As shown, the electronic device includes a processor 21, a memory 22, an input device 23, and an output device 24; the number of processors 21 in the electronic device can be one or more, Figure 3 In the example, the processor 21 in the electronic device, the memory 22, the input device 23, and the output device 24 can be connected through a bus or other means, Figure 3 In the example, the connection through the bus is taken as an example.

[0069] The memory 22 is a kind of computer readable storage medium, which can be used to store software programs, computer executable programs and modules, such as program instructions / modules of the high-precision transmission shaft precision grinding method in the embodiments of the present application. The processor 21 performs various functional applications and data processing of the electronic device by running the software programs, instructions and modules stored in the memory 22, i.e. implements the high-precision transmission shaft precision grinding method described above.

[0070] The above merely describes the preferred embodiments of the present application, and is not intended to limit the present application in any form. Although the present application has been disclosed with the preferred embodiments as above, it is not intended to limit the present application. Any person skilled in the art can make some changes or modifications to the above disclosed technical content to obtain equivalent embodiments with equivalent changes, as long as the changes or modifications do not deviate from the technical solutions of the present application. Any modification, equivalent change and modification made to the above embodiments based on the technical essence of the present application still falls within the scope of the technical solutions of the present application.

Claims

1. A precision grinding method for high-precision drive shafts, characterized in that, The method includes: Deploy measurement components on grinding machines to acquire grinding status characteristics in real time during the automated grinding process of the workpiece along the drive shaft; A dual-closed-loop control architecture is constructed by inserting a programmable impedance network into the servo driver. The dual-closed-loop control architecture is formed by supervising the training of the cascaded state loop and impedance loop, and establishing connections with the measurement component and the programmable impedance network. Based on the dual closed-loop control architecture, the grinding state characteristics are input into the state loop to perform displacement error based on diameter value and mechanical error based on mechanical load. Optionally, the impedance loop can be activated to make parameter adjustment compensation decisions based on the optimal resistance and capacitance combination to determine the impedance control parameters. The programmable impedance network responds to the impedance control parameters to adjust and compensate for the process time window of the automated grinding process of the grinding machine tool.

2. The precision grinding method for high-precision drive shafts as described in claim 1, characterized in that, Real-time acquisition of grinding status characteristics, including: Deploy measurement components on a grinding machine to acquire grinding state characteristics of the drive shaft machining process; The deployment of the measurement component includes: At least two high-frequency eddy current displacement sensors are symmetrically installed on both sides of the grinding wheel frame, wherein the sensing probe is aligned with the workpiece surface of the drive shaft, and the high-frequency eddy current displacement sensor measures the change in workpiece radius. A triaxial piezoelectric force sensor is installed on the headstock and tailstock of the grinding machine. The triaxial piezoelectric force sensor measures the normal grinding force, the tangential grinding force and the axial force.

3. The precision grinding method for high-precision drive shafts as described in claim 1, characterized in that, Constructing a dual closed-loop control architecture includes: A programmable impedance network is inserted into the forward current loop of the servo driver, wherein the programmable impedance network consists of a digital potentiometer and a programmable capacitor array; Based on the measurement component and the programmable impedance network, a dual-loop control architecture is constructed, wherein the dual-loop control architecture includes a state loop and an impedance loop.

4. The precision grinding method for high-precision drive shafts as described in claim 3, characterized in that, Based on the measurement component and the programmable impedance network, a dual closed-loop control architecture is constructed, including: The grinding process of the drive shaft workpiece is obtained. The grinding state is used as input, and the displacement error and rate of change based on the diameter value are used as the first decision objective. The mechanical error and rate of change based on the mechanical load are used as the second decision objective to construct the state loop. The impedance loop is constructed with the optimal resistance and capacitance combination calculated based on impedance matching as the optimization control objective. The state loop and impedance loop are cascaded, and connections are established between the state loop and the measurement components, and between the impedance loop and the programmable impedance network, to form the dual closed-loop control architecture.

5. The precision grinding method for high-precision drive shafts as described in claim 4, characterized in that, Before activating the impedance loop, the following steps are included: As the transmission shaft workpiece is processed, the first constraint condition is determined according to the grinding stage. In this process, the preset impedance parameter boundary is defined by calibrating the rough grinding label or fine grinding label for each grinding stage. The impedance loop is constrained in terms of parameter space by the preset impedance parameter boundary, wherein the parameter space is updated with the label of the real-time grinding stage.

6. The precision grinding method for high-precision drive shafts as described in claim 5, characterized in that, Determine the impedance control parameters, including: The grinding state characteristics are input into the state loop, and the calculations based on the first decision objective and the second decision objective are performed in parallel to determine the two-way error data with weighted values. For the two-way error data, taking any one of the error data as the greedy target, the impedance control parameter is located within the determined upper and lower bounds of the parameters.

7. The precision grinding method for high-precision drive shafts as described in claim 6, characterized in that, Using any error data point as the greedy target, locate the impedance control parameters within the defined upper and lower bounds of the parameters, including: For the first error data in the two-way error data, a parameter adjustment decision based on the optimal combination of resistor and capacitor is made with the weight value as a constraint to determine the first parameter group; For the second error data, determine the second set of parameters; The upper and lower bounds of the parameters are determined by mapping the first parameter group and the second parameter group. The upper and lower bounds of the parameters are used as the parameter tuning range, and the impedance control parameters are determined by performing an equilibrium game.

8. The precision grinding method for high-precision drive shafts as described in claim 1, characterized in that, The programmable impedance network responds to the impedance modulation parameters, including: The grinding machine tool performs automated grinding according to the pre-configured process grinding program, and the measuring component synchronously performs real-time grinding status measurement, and obtains dynamic impedance control parameters based on the status loop and impedance loop. By sending the impedance control parameters to the programmable impedance network, the control and compensation superposition of the automated grinding process is performed.

9. A precision grinding system for high-precision drive shafts, characterized in that, A precision grinding method for implementing the high-precision drive shaft according to any one of claims 1-8, the system comprising: Status measurement module: Deploy measurement components on the grinding machine tool to acquire grinding status characteristics in real time during the automated grinding process of the workpiece along the drive shaft; Closed-loop architecture building module: By inserting a programmable impedance network into the servo driver, a dual closed-loop control architecture is constructed. The dual closed-loop control architecture is formed by supervising the training of the cascaded state loop and impedance loop, and establishing connections with the measurement component and the programmable impedance network. Closed-loop architecture analysis module: Based on the dual closed-loop control architecture, the grinding state characteristics are input into the state loop, and displacement error based on diameter value and mechanical error based on mechanical load are analyzed. Optionally, the impedance loop is activated to make parameter adjustment compensation decisions based on the optimal resistance and capacitance combination to determine the impedance control parameters. Grinding control module: The programmable impedance network responds to the impedance control parameters to control and compensate the process time window of the automated grinding process of the grinding machine tool.

10. An electronic device, characterized in that, The electronic device includes: Memory, used to store executable instructions; The processor, when executing executable instructions stored in the memory, implements the precision grinding method for the high-precision drive shaft as described in any one of claims 1-8.

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