1. An error sensing compensation method for precision machining is characterized by comprising the following steps:

s1, the control unit receives the processing instruction and outputs a first control command to control the execution part to perform a first action;

s2, self-outputting a sensing variable and feeding the sensing variable back to the control unit in the action process of the executing part;

s3, the control unit outputs a second control command to control the execution part to perform a second action so as to correct the sensing variable to a set range;

s4: if processing continues, the system returns to S2; if the machining is finished, the control unit controls the execution part to stop operating.

2. The error sensing compensation method for precision machining according to claim 1, wherein the sensing variable is caused by a sensing feeding physical quantity, wherein the sensing feeding physical quantity includes any one or a combination of any plural kinds of displacement, strain, force, vibration, transmission error, temperature, abrasion, impact, noise.

3. The error sensing compensation method for precision machining according to claim 1, wherein the machining instruction includes a feed amount of the executing portion in a first direction, a feed amount in a second direction, and/or a feed amount in a third direction, wherein the first direction is perpendicular to the second direction, and the third direction is perpendicular to a plane in which the first direction and the second direction lie.

4. The error sensing compensation method for precision machining according to claim 1, wherein the detected position of the sensing variable is from a cutting edge (101) of a tool provided in the actuator.

5. The error sensing compensation method for precision machining according to claim 4, wherein the tool is any one or a combination of any plurality of piezoelectric material bodies, magnetostrictive material bodies, electromagnetic permanent magnetic material bodies, shape memory alloy material bodies, electrostatic material bodies, and phase change material bodies, which are connected in series in this order, and wherein the multi-body combination of the same material bodies is included.

6. The error sensing compensation method for precision machining according to claim 1, wherein the sensing variable is obtained by a change in a frequency parameter.

7. The error sensing compensation method for precision machining according to claim 2, wherein the execution section includes a driver unit and a machine tool (103) unit;

the frequency parameter of the driver unit after the driver unit is installed on the machine tool (103) unit is f0, and the frequency parameter of the driver unit in the contact machining process of the driver unit and the workpiece (102) is f 1; and calibrating the corresponding sensing feeding physical quantity of the f1 relative to the variation delta ft of the f0 at the time t, or carrying out real-time online identification on the delta ft in the feeding process, thereby obtaining the accurate feeding quantity of the driver unit to the workpiece (102) and the sensing feeding physical quantity of the feeding load when the variation of the frequency parameter is delta ft.

8. The error sensing compensation method for precision machining according to claim 1, wherein the sensing variable feedback and the output of the second control command are continued until the machining is completed.

9. The error sensing compensation method for precision machining according to claim 4, wherein the tool is a self-sensing self-retracting driving tool.

10. The error sensing compensation method for precision machining according to claim 9, wherein the number of driving tools is one or more.

Background

And (3) driving a cutter to move relative to the workpiece by the machine tool during machining so as to finish the surface machining of the workpiece. The certainty of the removal amount or the addition amount in the machining process, namely the machining size, corresponds to the relative displacement amount between the executing part (the space position feed position of the machine tool cutter and the 3D printing nozzle) and the executed part (the workpiece or the 3D printing workpiece) or the feed amount of the machine tool cutter. Various processing machines, whether removing material or adding material, are associated with an execution part and an executed part. The machining and manufacturing dimensional accuracy and the surface quality of the executed part depend on the real-time stability and controllability of the relative position and the relative position accuracy of the preparatory work part of the executing part.

The machining precision of the machine tool is not high, and a plurality of influence factors exist, for example, the driving error is generated due to the poor precision of the lead screw manufacturing, the uncertainty of the machining precision is caused due to the motion transmission error, and the uncertainty is finally shown in the poor machining precision of the cutter relative to the workpiece; for example, the tool is affected by the dimensional change of the tool nose due to the temperature change, the tool is affected by the dimensional change of the tool nose due to the expansion and contraction caused by heat, the vibration of the tool itself is affected by the machining accuracy due to the vibration of the machine body or the local vibration, the machining process is also a micro-vibration process, the machining accuracy is also affected, and the machining accuracy is an interference factor, the wear of the nose during the use of the nose is reflected on the force or the machining dimension, besides, the assembly problem can also cause the deformation caused by the stress of a local structural part, and the machining error between the end nose and the workpiece can be caused, and the machining accuracy is finally caused.

Piezoelectric materials and magnetostrictive materials are two typical solid intelligent materials, and the intelligent characteristics of the materials are that the force-electricity coupling of the piezoelectric materials and the force-magnetism coupling of the magnetostrictive materials are reversible. The piezoelectric effect is that the piezoelectric effect applies pressure to the same piezoelectric material body to generate an electric signal, and the inverse piezoelectric effect applies an electric field to generate deformation. The material has Joule effect on the same magnetostrictive material, namely deformation is generated by applying a magnetic field, and also has Villary effect, namely the magnetic field is generated by applying pressure. At present, in the design of intelligent material drivers at home and abroad, an intelligent material is basically used as a driving body, and the driver is designed by adopting an intelligent material and only has a driving function but no sensing function.

Disclosure of Invention

In view of the defects in the prior art, the invention aims to provide an error sensing compensation method for precision machining.

The invention provides an error sensing compensation method for precision machining, which comprises the following steps:

s1, the control unit receives the processing instruction and outputs a first control command to control the execution part to perform a first action;

s2, self-outputting a sensing variable and feeding the sensing variable back to the control unit in the action process of the executing part;

s3, the control unit outputs a second control command to control the execution part to perform a second action so as to correct the sensing variable to a set range;

s4: if processing continues, the system returns to S2; if the machining is finished, the control unit controls the execution part to stop operating.

Preferably, the sensed variable is caused by a sensed feed physical quantity, wherein the sensed feed physical quantity comprises any one or a combination of any more of displacement, strain, force, vibration, transmission error, temperature, wear, impact, noise.

Preferably, the machining instruction comprises a feeding amount of the execution part along a first direction, a feeding amount along a second direction and/or a feeding amount along a third direction, wherein the first direction is perpendicular to the second direction, and the third direction is perpendicular to a plane in which the first direction and the second direction are located.

Preferably, the detection position of the sensing variable is from a cutting edge of a tool provided in the actuator.

Preferably, the cutter is a multi-body combination which is formed by sequentially connecting any one or any combination of a piezoelectric material body, a magnetostrictive material body, an electromagnetic permanent magnetic material body, a shape memory alloy material body, an electrostatic material body and a phase change material body in series, wherein the multi-body combination comprises the same material body.

Preferably, the sensor variable is obtained by a change in a frequency parameter.

Preferably, the execution section includes a driver unit and a machine tool unit;

the frequency parameter of the driver unit after being installed on the machine tool unit is f0, and the frequency parameter of the driver unit in the contact machining process of the driver unit and the workpiece is f 1; calibrating the corresponding sensing feeding physical quantity of the f1 relative to the variation delta ft of the f0 at the time t, or carrying out real-time online identification on the delta ft in the feeding process, thereby obtaining the accurate feeding quantity of the driver unit to the workpiece and the sensing feeding physical quantity of the feeding load when the variation of the frequency parameter is delta ft.

Preferably, the feedback of the sensing variable and the output of the second control command are continued until the machining is completed.

Preferably, the tool is a self-sensing self-retracting driving tool.

Preferably, the number of driving tools is one or more.

Compared with the prior art, the invention has the following beneficial effects:

1. the invention combs and summarizes a plurality of complex factors influencing the processing precision, the combination of various influencing factors is finally shown on the tool point of the tool, the final processing precision is finally realized by compensating the error of the tool point of the tool, the sensing of the feeding displacement and/or force of the tool point is realized on the tool through an intelligent material, the accurate error compensation is further realized, the high-precision processing is realized, the error is offset by feeding compensation, and the continuity of the error compensation is realized by sensing and compensating in real time, thereby greatly improving the processing precision.

2. The invention designs and skillfully applies intelligent materials in the field of precision machining, realizes self-sensing self-driving of a tool nose, solves the technical problem which is difficult to solve for long time in machine tool machining, and realizes precision machining and accurate feeding.

3. The compensation method can realize the accurate feeding of the net feeding amount by various methods such as physical calibration modeling, mathematical analysis modeling and the like, simplify the complex problem and solve the big problem of the precision machining of the machine tool.

Drawings

Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:

FIG. 1 is a schematic representation of the method steps of the present invention;

FIG. 2 is a schematic view of a machine tool machining a workpiece;

FIG. 3 is a schematic view of the structure of the portion A in FIG. 2;

FIG. 4 is a schematic diagram showing the structure of the tool end cutting feed displacement;

FIG. 5 is a schematic diagram showing the cutting feed force of the tool;

FIG. 6 is a schematic view showing the structure of the cutter end superimposed vibration;

FIG. 7 is a schematic diagram showing the tool tip superimposed with machine tool system drive errors;

FIG. 8 is a schematic diagram showing the tool tip superimposed machine tool structural strain feed;

FIG. 9 is a schematic diagram showing the tool tip superimposed with the machine tool temperature stress strain feed;

FIG. 10 is a schematic diagram of a driver unit;

FIG. 11 is a schematic structural view of the driver unit, in which the tool and the workpiece are shown;

fig. 12 is a schematic view showing the variation of the elastic modulus of a magnetostrictive material body in a magnetostrictive actuator/tool feeder for a machine tool according to the state of an operating magnetic field and the stress level;

FIG. 13 is a driver mechanics model;

fig. 14 is a driver equivalent mechanical model.

Giant magnetostrictive rod 1 large electromagnetic coil 6

Piezoelectric stack 2 tool nose 101

Disc spring 3 workpiece 102

Output rod 4 machine tool 103

Small electromagnetic coil 5

Detailed Description

The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that it would be obvious to those skilled in the art that various changes and modifications can be made without departing from the spirit of the invention. All falling within the scope of the present invention.

Example 1:

the invention provides an error sensing compensation method for precision machining, which comprises the following steps:

s1, the control unit receives the processing instruction and outputs a first control command to control the execution part to perform a first action;

and S2, outputting a sensing variable by self and feeding the sensing variable back to the control unit in the action process of the executing part, wherein the detection part of the sensing variable is from the knife edge 101 of the knife tool of the executing part, and the sensing variable is obtained by the change of the frequency parameter.

S3, the control unit outputs a second control command to control the execution part to perform a second action so as to correct the sensing variable to a set range, and performs feedback and command output in real time so as to correct the processing sensing variable in real time and ensure the processing precision of the workpiece 102;

s4: if processing continues, the system returns to S2; if the machining is completed, the control unit controls the execution unit to stop operating, and the feedback of the sensing variable and the output of the second control command are continued until the machining is completed.

In an actual process of machining the workpiece 102, the machining instruction includes a feeding amount of a tool in a first direction, a feeding amount in a second direction, and/or a feeding amount in a third direction, where the tool is provided by the execution portion, the first direction is perpendicular to the second direction, the third direction is perpendicular to a plane where the first direction and the second direction are located, the motions in the first direction, the second direction, and the third direction respectively correspond to motions of the tool in the X direction, the Y direction, and the Z direction, and the execution portion machines the workpiece 102 to a machining position through the feeding motions in the three directions.

Further, the actuator includes a driver unit whose frequency parameter after being mounted on the machine tool 103 unit is f0, and a machine tool 103 unit whose frequency parameter during machining in contact with the workpiece 102 is f 1; calibrating the corresponding sensing feeding physical quantity of the f1 relative to the variation delta ft of the f0 at the time t, or carrying out real-time online identification on the delta ft in the feeding process, thereby obtaining the accurate feeding quantity of the driver unit to the workpiece 102 and the sensing feeding physical quantity of the feeding load when the variation of the frequency parameter is delta ft.

The executing part is suitable for material reducing processing equipment such as a machine tool 103, the machine tool 103 is various traditional material removing processing machine tools such as a lathe, a milling machine, a grinding machine, a planer, a drilling machine, a multi-axis numerical control processing center and the like, and the tool is a turning tool, a milling cutter, a honing oilstone, a grinding wheel, a drill bit, a boring cutter, a grinding wheel, a grinding head, a polishing head, a fluid injection needle and the like; the cutter is also suitable for material increase processing equipment, such as a metal 3D printer, and the cutter at the moment can be a 3D printing nozzle.

The tool in the invention is a self-sensing self-telescopic driving tool, and the number of the driving tools can be set to be one according to the complexity of the processed workpiece, and can also be set to be a plurality of tools for processing simultaneously, so that the processing efficiency is improved.

In the actual process of processing the workpiece 102, the processing accuracy is affected by various factors of sensing feeding physical quantities, which include any one or a combination of any more of displacement, strain, force, vibration, transmission error, temperature, abrasion, impact, and noise, and the sensing feeding physical quantities bring about sensing variables, wherein the force includes an externally applied force, and also includes a stress generated by the execution part itself, and the like.

As shown in fig. 4, S in the figure is the position of the cutting edge 101 relative to the workpiece 102, where S is determined by two quantities, S ═ S₀+ Δ S, wherein S₀The control unit executes the machining instruction to control the displacement feed amount generated by the driving of the machine tool 103, and deltaS is the displacement and/or strain generated by the cutter.

As shown in fig. 5, F in the figure is a feed load of the cutting edge 101 relative to the workpiece 102, where F is determined by two quantities, and F is F₀+ Δ F, wherein F₀The force generated by the machine tool 103 driving is controlled by the control unit executing the machining instruction, and the Δ F is the stress generated by the tool itself and/or the force generated by the wear of the cutting edge.

As shown in fig. 6, S in the figure_VibShows the actual feeding amount of the tool nose 101 and the workpiece 102 in the machining process, and the actual feeding amount and the feeding amount corresponding to the machining instruction have a stable stateThe fluctuation, for example, the feed amount corresponding to the machining instruction is 1 mm, and the actual feed amount is fluctuated up and down by 1 mm, such as 0.9 mm, further such as 1.1 mm, further such as 1.2 mm, such as caused by disturbance vibration including various aspects, vibration of the machine tool itself, vibration from the outside, and the like.

As shown in fig. 7, S in the figure_transfThe actual feeding amount of the driving caused by the transmission error due to the low machining precision of the transmission part of the machine tool, for example, the transmission error caused by the low machining precision of the transmission screw, has an unstable fluctuation with the feeding amount corresponding to the machining instruction, thereby affecting the machining precision.

As shown in fig. 8, S in the figure_{structure-strain}The actual feeding amount is driven under the interference of stress release factors in the structural strain and assembly of the machine tool, and the unstable fluctuation exists between the actual feeding amount and the feeding amount corresponding to a machining instruction, so that the machining precision is influenced.

As shown in fig. 9, S in the figure_temp-strainIn order to drive the actual feeding amount under the condition of the temperature change of the machine tool or the external temperature change, the actual feeding amount and the feeding amount corresponding to the machining instruction are changed, and the machining precision is further influenced.

Further, in addition to the above-described sensing feed physical quantity that affects the machining accuracy of the machine tool, various factors that affect impact, noise, and the like are included. The change of the external temperature can cause the micro deformation of each part of the machine tool 103 caused by thermal expansion and cold contraction, and finally shows that the change of the distance and the force between the tool nose 101 of the tool and the workpiece 102 can cause the influence on the machining precision, and the temperature change caused by friction in the machining process of the tool and the workpiece 102 can also cause the micro deformation of the tool, so that the machining precision can be influenced essentially. The combination of vibrations of the machine tool 103 as a whole, local vibrations, and multiple vibrations also causes uncertainty in the machining accuracy of the tool and the workpiece 102. During the tool driving and feeding process, the output control command cannot be accurately executed, which causes a transmission error, for example, due to the fact that the screw rod machining precision for transmission is not high, which causes the inaccuracy of output driving, for example, the tool is driven to advance along the first direction for 1 mm, but actually, the tool may be driven to advance for 0.98 mm due to the problem of the screw rod machining precision, and therefore, the transmission error also affects the machining precision. Meanwhile, the machining precision of the cutter is influenced by stress relief due to the difference of assembling force of each component in the assembling process. The wear of the tool is also becoming more severe as the machining frequency increases, and may also be a factor in the reduction of machining accuracy.

Further, aiming at the condition that the machining precision is influenced a lot in the machining process of the precision workpiece 102 and the change of the feeding amount caused by various factors is difficult to be listed, the final machining precision sensing compensation is implemented on the tool nose 101 of the tool, no matter how many unstable influencing factors exist, the final machining precision is implemented by implementing error compensation on the tool nose 101 of the tool, the combination of various influencing factors is finally represented on the tool nose 101 of the tool and self-sensing and self-driving are implemented, the error is offset through the feeding compensation, and the real-time sensing and compensation are implemented, so that the continuity of the error compensation is implemented, and the machining precision is greatly improved.

Example 2:

this embodiment is a preferred embodiment of embodiment 1.

The present embodiment takes a lathe as an example, and illustrates a method for realizing error sensing compensation in the machining process of the machine tool 103. In addition, the cutter in the invention is a combination of any one or more of a piezoelectric material body, a magnetostrictive material body, an electromagnetic permanent magnetic material body, a shape memory alloy material body, an electrostatic material body and a phase change material body which are connected in series in sequence, wherein the cutter comprises a multi-body combination of the same material body, and the effect of the invention can be realized through the arrangement of the structure. Specifically, the tool comprises a material which can realize signal acquisition and further self-sensing self-expansion under various conditions of magnetic field or electric field addition, cold and hot deformation, fluid pressure deformation and chemical reaction deformation.

As shown in fig. 10 and 11, the driver unit is mainly composed of a giant magnetostrictive (GMM/Terfenol-D) rod 1 made of a magnetostrictive material and a piezoelectric stack block 2(PZT) made of a piezoelectric material. The disc spring 3 extrudes the output rod 4, the piezoelectric stack block 2 and the giant magnetostrictive rod 1 which are connected in series in sequence. The drive sensing mechanism can be described as:

initially, a high frequency (-n 10 kHz) micro amplitude (-mA) electrical signal is applied to the GMM rod by a small electromagnetic coil 5 to excite Va2, producing a piezoelectric signal Vps2 corresponding to the magnetostrictive drive response applied to the PZT. At this time, since the driver unit is in the asserted state, a stable harmonic response peak frequency fvps2 can be obtained from the Vps2 signal. The peak frequency signal may be used as a "self-tuning" parameter for the driver unit's own initial state or as a consistency parameter indicator for the driver unit's own initial (base) state of operation.

Secondly, a large-amplitude low-frequency electric signal is applied to the GMM rod by a large electromagnetic coil 6 to excite Va1 (the frequency is 0-n 100 Hz, and the amplitude nA-n 10A), and the GMM rod is excited to extend to generate a driving output delta s. Since the smart material has the Δ E effect of young's modulus, the GMM elongation or external applied load will cause a change in its own stiffness, i.e. a corresponding change in the natural frequency of the driver unit, which corresponds to a change in the deflection δ f that produces fvps 2.

In summary, by identifying and accurately quantifying δ f, the corresponding magnitude of the driving displacement and/or driving force of the driver unit can be obtained, and therefore, self-sensing driving feeding based on magnetostrictive composite piezoelectric material driving can be realized. The end of the driving output rod 4 is fixedly connected with a machining tool, and the device can be a self-sensing self-telescopic driving tool. The tool is arranged on a machine tool 103 and can be used for feeding or positioning the tail end of a feeding mechanism of the machine tool 103 relative to the position of a workpiece 102 to be machined, and finally controllable precision machining is realized.

Furthermore, the sensing signal can acquire the change of displacement and/or force by identifying a phase signal and a time-frequency signal in addition to the electric signal acquisition of the piezoelectric material in the embodiment, and in practical application, the parts corresponding to the signal acquisition in the cutter have the conditions of the same frequency and different phases or the same frequency and different time, so that the invention is not limited to the structure driven by the magnetostrictive composite piezoelectric material.

In addition, in the design of a specific product, the tool nose can be a sensing point, one or more self-sensing drivers or corresponding sensors are assisted in the feeding direction of the tool, the self-sensing drivers or the corresponding sensors are used for assisting in the final sensing monitoring of the tool nose or in the detection of segmentation and sub-functions (such as through heat, vibration and the like), and finally, the sensing of the tool nose is combined for verifying the accuracy of the self-sensing self-driving.

Further, the ambient temperature, the state of the work object of the carrier machine tool 103 where the drive is located, changes, resulting in uncertain changes such as the degree of pressing or actual cutting of the driving tool, feed mechanism and tool against the workpiece 102 — corresponding to single or compound errors occurring between the tool tip of the machine tool 103 and the workpiece 102: interference factors such as a transmission accumulated error (figure 7) of a machine tool 103 system, a temperature rise error (figure 9) or a stress strain deformation error (figure 8) of a bed body structure, environmental vibration (figure 6) and the like can be normalized to the strain and stress change of the output end of the self-sensing driver, namely the change of the stress and the strain of the tool nose. These strain and stress variations resulting from the motion of the end of the transducer driver relative to the workpiece 102 can be traced to the magnitude of the offset variation frequency δ f or signal frequency/spectral signature after the initial "self-tuning" frequency fvps2, and the corresponding magnitude obtained. Thus, the feed disturbance error amount can be compensated for by sensing and drive output control from the sensing actuator to achieve accurate feed of the desired net feed amount.

Although the interference of the driving process is traced based on the frequency normalization, the compensation is carried out, and the accurate control method is simple, convenient and clear, in the actual working condition, a plurality of physical quantities are parallel to generate δ f, and the difficulty is caused in correspondingly identifying the related physical quantities. The invention thus addresses multiple drive disturbances self-sensing and compensates for accurate drive in three respects.

The method comprises the following steps: physical calibration modeling

Since the self-sensing driver adopted by the machine tool 103 has the initial state self-tuning characteristic, a certain single interference for determining the variation can be continuously applied by adopting a control variable method based on the initial state calibrated by the driverAnd (3) correspondingly measuring delta F by using physical quantities (such as the magnetic field intensity of the magnetostrictive drive, the ambient temperature, the ambient vibration and the like) delta w, so that a corresponding relation F (delta F-delta w) is established. And 2 or more than 2 variable quantities can be simultaneously applied to the main physical quantity for carrying out coupling input loading to obtain delta w₁,δw₂… … to δ f. And finally, fitting the test data to obtain a corresponding relation model.

The method 2 comprises the following steps: mathematical analysis modeling

Still based on a method of normalizing frequency response, a self-sensing driver unit is regarded as a dynamic system, a driving electromagnetic field and each interference physical quantity are used as input of the system, and δ f or a plurality of δ f corresponding to physical characteristics are used as output to construct a multi-input single-output and multi-input multi-output dynamic response mathematical model. Because the signal spectrum characteristics generated by loading drivers with different physical quantities such as electromagnetic field excitation, temperature, load and the like have differences, the analysis and calculation relation model of the input physical quantity corresponding to the delta f under single excitation or multiple excitations can be carried out. The model can be simultaneously based on physical calibration modeling and data in the physical calibration modeling to carry out parameter correction and model validity verification.

The method 3 comprises the following steps: the accurate feed is obtained by frequency parameter

The driver unit on the machine tool 103 is a self-sensing driver, which is a device with self-adjustable state. The method of the invention aims to consider the self-sensing driver and the carrier of the machine tool 103 as two independent units which are fixedly connected and integrated into a system for analysis. The driver unit initial setting state parameter (single or multiple parameters) delta f0 is an initial frequency parameter, after the driver unit initial setting state parameter and the machine tool 103 unit are installed, the frequency delta f1 obtained by the driver unit secondary setting is a system initial state reference parameter, and the deviation of the two parameters can be used as a criterion for the stability/consistency of the machine tool 103 initial state. Then, the driver/tool of the machine tool 103 and the workpiece 102 are reset in the tool contact state (having the comprehensive state of machine tool 103 such as systematic error, temperature deviation, and vibration disturbance), and the frequency δ f2 is obtained. And finally, taking the frequency as a reference, obtaining the real-time feeding state detection frequency delta ft in the machining process by the active feeding of the self-sensing driver/cutter, and realizing the accurate micro-feeding in the machining process by tracking the optimal delta ft driving control. The method can realize the parametrization of the machine tool 103 state and the target of the consistency control of the driving device/cutter feeding state.

Further, the magnetostrictive constitutive model and the variable stiffness (Δ E) effect method in the driver unit are as follows:

the magnetostrictive material body generates strain under the action of an external excitation magnetic field, so that the magnetostrictive actuator outputs displacement or force. The magnetostrictive material body satisfies the following relationship:

B＝dσ+μ^σH (1)

wherein B is magnetic induction intensity, H is magnetic field intensity,d is a magnetomechanical coupling coefficient, σ is a stress inside the magnetostrictive material body, ε is a strain inside the magnetostrictive material body, μ^σPermeability under constant stress.

In formula (1)It is considered as a constant, i.e. the elastic modulus of the magnetostrictive material body corresponds to a constant stress and a constant magnetic field. However, when the magnetostrictive actuator/tool configured with the machine tool 103 is in an operating state excited by an external magnetic field, the stress and the magnetic field environment are changed rather than kept constant, resulting in a change in the elastic modulus of the magnetostrictive material body. The change in elastic modulus with the change in the external magnetic field and stress state is represented by Δ E and is defined as the elastic modulus at magnetic field strength H and stress σReducing the elastic modulus E in a zero magnetic field and no stress state₀Divided by E₀：

The constitutive relation of the magnetostrictive material bodies can be established by considering Taylor series expansion high-order terms of the Gibbs free energy function, and the model can effectively reflect the characteristics of the magnetostrictive material. The Δ E effect of the magnetostrictive material can be predicted by the model and the definition of the elastic modulus of the material:

wherein ε is the strain inside the magnetostrictive material, σ is the stress inside the magnetostrictive material, E_sTo saturation modulus of elasticity, λ_sFor saturated magnetostrictive strain, M is the magnetization, H_eEffective magnetic field strength, mu₀For vacuum permeability, σ_sIs saturation stress, M_SIs saturation magnetization, k is relaxation factor, B is magnetic induction,d is the modulus of elasticity under constant stress and constant magnetic field, d is the coefficient of magnetomechanical coupling, mu^σThe elastic modulus of the magnetostrictive material body in the magnetostrictive actuator/tool feeder for machine tool 103 corresponding to the above parameters is calculated as a graph of the change in the operating magnetic field state and the stress level for the permeability under constant stress, as shown in fig. 12.

From fig. 12, the values of the elastic modulus of the magnetostrictive material bodies in the magnetostrictive actuator/tool feeder for machine tool 103 in the designed states of the pre-stress and the bias magnetic field can be obtained, and the law E (H, σ) of the change of the elastic modulus with the magnetic field and the stress can be obtained, whereby the magnetostrictive actuator/tool feeder for machine tool 103 can be determinedCorresponding rigidity k of magnetostrictive material body in telescopic driver/cutter feeding device under external magnetic field and load action₀And further for the obtained harmonic response frequency value under the state:

K₀＝E(H,σ)A/L (4)

wherein k is₀The corresponding rigidity of the magnetostrictive material body under the action of an external magnetic field and a load is shown, E (H, sigma) is the Young modulus under the given magnetic field strength H and the given compressive stress sigma, A is the sectional area, and L is the length.

The relationship between the frequency signals corresponding to the output stress and strain at the end of the machine tool 103 is shown in fig. 13 and 14, which are applied to the drive current I of the magnetostrictive actuator/tool feeding device for the machine tool 103₀(the current of the driving electromagnetic field for the displacement of the magnetostrictive body is I₀) And I under the action of high-frequency sensing exciting current₁(the magnetostrictors initially used in the self-sensing high frequency driving electromagnetic field have a current I₁) The equivalent mechanical model takes the sum of the load mass and the equivalent mass of the magnetostrictive piezoelectric composite material as the main mass M_LAnd assuming that during motion, the bottom of the body of magnetostrictive material in the magnetostrictive driver/tool against the machine end is displaced to zero, the driver/tool end is always not separated from the workpiece 102 (load), with the same displacement u.

The formula (1) shows that the displacement u of the magnetostrictive material body is composed of two parts, one part being an elastic displacement u corresponding to the elastic strain_σThe other part corresponding to the displacement u of the magnetostrictive strain_HI.e. the change in displacement generated with respect to the bias magnetic field. The rigidity and the equivalent damping coefficient of the load are respectively K_L、C_LThe equivalent stiffness and the equivalent damping of the magnetostrictive-piezoelectric composite material are respectively K_D、C_DThe damping coefficient of the system is C ═ C_D+C_LWhen no other external force acts, the motion equation of the main mass is as follows:

u＝u_σ+u_H (6)

the following can be obtained:

K＝K_L+K_D (8)

K_D＝K_DTK_DP/(K_DT+K_DP) (9)

wherein the equivalent stiffness of the magnetostrictive phase is: k_DTThe equivalent stiffness of the piezoelectric phase is: k_DP. Their stiffness is calculated by the following expressions:

K_DT＝E_T(H,σ)A_T/L_T (10)

K_DP＝E_PA_P/L_P (11)

wherein M is_LIs the sum of the load mass and the equivalent mass of the magnetostrictive piezoelectric composite material u_σElastic displacement of a body of magnetostrictive material corresponding to an elastic strain u_HIs the displacement of the magnetostrictive strain of a body of magnetostrictive material, K_LFor the stiffness of the load, C is the damping coefficient of the system, K_DIs the equivalent stiffness of the magnetostrictive-piezoelectric composite material, E_T(H, σ) Young's modulus of magnetostrictive phase (volume) given magnetic field strength H and compressive stress σ, A_TIs the cross-sectional area of the magnetostrictive phase (body), L_TIs the length of the magnetostrictive phase (body), E_pYoung's modulus of piezoelectric phase (bulk), A_PThe cross-sectional area of the piezoelectric phase (body), L_PIs the length of the piezoelectric phase (body) and u is the tool tip displacement.

Equation (5) is the magnetomechanical coupling equation for the drive. When the driver applies exciting current, the rigidity K of the system will change due to the change of the elastic modulus of the magnetostrictive material body. The right end of equation (7) is the stimulus term that causes the driver to produce an output. The natural frequency of the system can be simply estimated from the system dynamics equation and neglecting the effect of damping:

the load force and the output displacement acting on the magnetostrictive actuator can be obtained by obtaining the real natural frequency of the system according to the input magnetic field of the system and the voltage signal output by the piezoelectric phase:

F_ext＝σA (13)

wherein, F_extIs the load force acting on the magnetostrictive actuator, u is the output displacement acting on the magnetostrictive actuator, ε is the strain inside the magnetostrictive material, σ is the stress inside the magnetostrictive material, E_sTo saturation modulus of elasticity, λ_sFor saturated magnetostrictive strain, A is the driver output end area, L_DIs the equivalent length of the magnetostrictive part, u_sFor saturation stress, M is the magnetization, M_SThe saturation magnetization.

When alternating current is input to the magnetostrictive actuator/tool of the machine tool 103, the kinetic equation of the system becomes a parametric vibration equation with time-varying stiffness, the system stiffness K changes due to the change in the elastic modulus E of the magnetostrictive material body, and the change in E is caused by the change in the magnetic field inside the actuator due to the input alternating current. Magnetic field strength inside magnetostrictive actuator:

in the formula: h₀A constant bias magnetic field strength; n is the number of turns of the coil; l is_DIs the length of the body of magnetostrictive material; i is₀To drive an alternating current.

The above formula shows that when the current is I₀When alternating with time, the magnetic field strength also changes with time, and it is this change that causes the magnetostrictive actuator to produce a displacement output, which also causes the magnetostrictive actuator to produce a displacement outputThe elastic modulus of the telescopic material body is changed, so that the dynamic characteristics of the system are influenced; at this time, if the young's modulus/stiffness converted into the magnetostrictive material body further changes due to other input or disturbance input, the corresponding detection frequency will change accordingly, so that the state of the machine tool 103 or the disturbance physical quantity is also detected according to the frequency signal change characteristic. It can be known from the dynamic equation of the system that when the driver applies the driving current or bears the external load force (the various quantities causing the stress change can be equal/equivalent to the load), the rigidity K of the system will change due to the change of the elastic modulus of the magnetostrictive material body, thereby causing the natural frequency of the system to change.

Simulation analysis is performed on the method, for example, the magnetostrictive piezoelectric composite material with the radius of 5 mm and the length of 50 mm is taken, the material parameter is taken to be in the formula (12), and the system natural frequency fs and the load force F can be respectively obtained by combining the formulas (13), (14) and (15)_extAnd outputting the relationship between the displacements u.

Based on the above simulation calculation results, it can be seen that, since the elastic modulus of the magnetostrictive material body changes with the load and the driving current when the driver/cutter of the machine tool 103 operates, such a characteristic of the magnetostrictive material body causes the driver/cutter system to exhibit a parametric vibration characteristic with time-varying stiffness: changes in the amplitude of the drive current and changes in the load force both result in changes in the main resonant frequency of the system. Therefore, the system output displacement and the load acting force can be obtained through the voltage output signal of the piezoelectric phase in the magnetostrictive piezoelectric composite material; or various physical quantities or interference feed errors which can be equivalent to stress and strain parameters between the magnetostrictive self-sensing driver/tool at the end of the machine tool 103 and the workpiece 102 are obtained according to the frequency signal characteristics, so as to detect and control the correction in real time.

Therefore, when the driver/tool cooperates with the machine tool 103, the unstable deviation of the feeding end, which may be caused by the machine tool 103 itself, the initial contact degree with the workpiece 102, or environmental interference, can be identified and characterized by the corresponding system harmonic response frequency and piezoelectric detection output frequency, which is equivalent to the strain or stress deviation of the driver/tool end.

Macro motion feed of the machine tool 103, micro feed of a driver/tool of the machine tool 103, superposition of the macro motion feed and the micro motion feed of the machine tool 103, vibration of the tool relative to the workpiece 102, transmission gap transmission error of the machine tool 103, stress and strain transmission feed error of a bed of the machine tool 103, feed error of temperature change of the machine tool 103 and the like can be represented as stress and strain variation of a self-sensing driver/device/tool corresponding to a reference calibration value of the tail end of the tool of the machine tool 103 relative to the workpiece 102. The variable is a stress strain with different error cause characteristic frequencies/frequency spectrums, and is further extracted by an intelligent material and a signal identification method. The driving frequency characteristic signals of feeding, cutting force, vibration, temperature, bed body stress strain, transmission clearance error and the like cannot be completely the same in practical engineering, so that the driving feeding and driving feeding states and driving feeding interference can be detected in real time and active driving control or feeding compensation control can be implemented, and the feeding intelligent processing mode of the machine tool 103, in which the tool is accurate and stable relative to the workpiece 102 and compensation correction is implemented through control, is realized. The manufacturing difficulty of the precision machine tool 103 is reduced, and the production and the manufacturing of the precision machine tool 103 are easy to realize.

Therefore, the interference compensation driving control of the self-sensing driver/cutter and the machine tool 103 realized by the method can innovatively realize the intelligent precision feeding motion machine tool 103 which can drive feeding and self-compensate feeding errors in real time.

In the description of the present application, it is to be understood that the terms "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience in describing the present application and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present application.

The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.