Atmospheric plasma jet machining thermal error online compensation method and system

Abstract

The application provides an atmospheric plasma jet processing thermal error online compensation method and system, a nonlinear removal function of atmospheric plasma considering thermal effect is obtained through experiment calibration; for a target removal surface type, a nominal removal function and a linear equation set method are used to solve a residence time; a feed speed is calculated according to the residence time and a motion path; data is stored in a motion control board and a machine tool motion is started, a highest temperature of a processing area is measured online through an infrared thermal imager, a target is adjusted based on an equal volume material removal amount according to a remaining motion time length of a motion cache area, dynamic adjustment of the residence time is carried out, forward-looking and interpolation motion planning are carried out in real time, and the plasma jet head covers all residence points along the planned path until the plasma jet head covers all residence points along the planned path. The application adjusts the residence time in real time through temperature change of the processing area, effectively suppresses the atmospheric plasma processing error caused by the thermal effect, and improves the processing precision.

Description

Technical Field

[0001] This invention relates to the technical field of ultra-precision machining, specifically to a method and system for online thermal error compensation in atmospheric plasma jet machining. Background Technology

[0002] Atmospheric plasma jet processing technology is a non-contact surface processing technology. Under atmospheric pressure, it uses a radio frequency high-voltage power supply to generate highly active plasma composed of ions, electrons and free radicals. This plasma acts on the material surface and undergoes a chemical reaction to produce gaseous products, thereby removing the material and completing the surface shaping of the parts. It has the advantages of high efficiency, energy saving and environmental protection.

[0003] Currently, atmospheric plasma machining faces significant thermal error issues when applied to ultra-precision machining. Atmospheric plasma jet machining is essentially chemical etching, where the material removal rate depends on the chemical etching reaction rate and is further influenced by thermodynamic temperature. During atmospheric plasma jet machining, the plasma heat source continuously transfers heat to the workpiece. Simultaneously, the workpiece's heat dissipation capacity varies at different locations, causing temperature fluctuations in the etching reaction region and time-varying nonlinear changes in the material etching rate. This significantly impacts the machining accuracy of atmospheric plasma jet machining. The paper "Ji P, Li D, Su X, et al. Optimization strategy for the velocity distribution based on tool influence function non-linearity in atmospheric pressure plasma processing[J]. Precision Engineering, 2020, 65: 269-278" proposes an optimization algorithm for residence time based on removal function selection, which to some extent suppresses the nonlinear error caused by thermal effects in atmospheric plasma processing. However, this method only establishes the relationship between removal rate and plasma nozzle velocity, simplifies the influence of thermal effects in the processing, and ignores the temperature field coupling effect of adjacent residence points and the temperature fluctuation caused by global temperature drift and different local heat dissipation conditions. This limits the further improvement of atmospheric plasma processing accuracy.

[0004] Therefore, a new technical solution is needed to improve the above-mentioned technical problems. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the purpose of this invention is to provide an online thermal error compensation method and system for atmospheric plasma jet processing.

[0006] According to the present invention, an online thermal error compensation method for atmospheric plasma jet processing is provided, the method comprising the following steps:

[0007] Step S1: Experimentally calibrate the time-varying nonlinear removal function of atmospheric plasma considering thermal effects;

[0008] Step S2: For the surface to be removed from the target material, set the nominal removal function and solve for the dwell time;

[0009] Step S3: Calculate the feed rate based on the dwell time and motion path;

[0010] Step S4: After the machine tool starts moving, the highest temperature of the processing area is measured online by an infrared thermal imager. Based on the remaining movement time of the movement buffer area and the requirement for removal of equal volume of material, the dwell time is dynamically adjusted. The forward and interpolation movement planning is performed in real time until the plasma nozzle covers all dwell points along the planned path.

[0011] Preferably, in the atmospheric plasma time-varying nonlinear removal function calibration method considering thermal effects in step S1, the removal function is a rotationally symmetric Gaussian function, that is, at the residence point (x i y i The amount of material removed from the material surface at (x, y) after a unit time of residence at point ) is:

[0012]

[0013] The peak etching rate v and the full width at half maximum (FWHM) of the removal function are exponential functions of temperature T.

[0014]

[0015]

[0016] In the formula, v1, v2, v3, f1, f2, and f3 are coefficients calibrated through experiments.

[0017] Preferably, in the atmospheric plasma time-varying nonlinear removal function calibration method considering thermal effects in step S1, multiple single-point processing experiments are used, and the variation curve of the highest temperature T in the atmospheric plasma processing area and the material removal surface shape M at each dwell point are recorded by an infrared thermal imager. k (x, y), construct the following nonlinear least squares model:

[0018]

[0019] In the formula, the optimization coefficient vector p = [v1, v2, v3, f1, f2, f3], and E is the sum of squares of the differences between the actual removal amount and the calculated removal amount:

[0020]

[0021] Where (x) j y j ) represents the coordinates of the sampling point for the j-th surface removal amount, T q Δt represents the highest temperature of the processing area recorded by the thermal imager in the qth frame, N(k) represents the total number of frames of data recorded by the infrared thermal imager corresponding to the kth single-point processing experiment, and Δt represents the sampling period of the infrared thermal imager.

[0022] Preferably, in step S4, the dwell point (x) i y i ) The dwell time t after regulation i 'for:

[0023]

[0024] Where v c and F c The nominal peak etching rate and full width at half maximum (FWHM) of the removal function used to solve for the dwell time; T i For real-time temperature measurement of the processing area; v(T) i ) and F(T i ) is the removal function at temperature T i The actual peak etching rate and full width at half maximum (FWHM) are as follows; t i The planned dwell time at the processing point.

[0025] Preferably, in the temperature measurement of the processing area in step S4, a coaxial coplanar excitation structure is used to form a long plasma jet, the processing spacing is adjusted until the processing area is fully exposed, and an infrared thermal imager is used to monitor the temperature of the processing area.

[0026] The present invention also provides an online thermal error compensation system for atmospheric plasma jet processing, the system comprising the following modules:

[0027] Module M1: Experimentally calibrates the time-varying nonlinear removal function of atmospheric plasma considering thermal effects;

[0028] Module M2: For the surface to be removed from the target material, set the nominal removal function and solve for the dwell time;

[0029] Module M3: Calculates the feed rate based on dwell time and motion path;

[0030] Module M4: After the machine tool starts moving, the highest temperature of the processing area is measured online by an infrared thermal imager. Based on the remaining movement time in the motion buffer area and the requirement for removal of equal volume of material, the dwell time is dynamically adjusted. The forward and interpolation motion planning is performed in real time until the plasma nozzle covers all dwell points along the planned path.

[0031] Preferably, in the atmospheric plasma time-varying nonlinear removal function calibration system considering thermal effects in module M1, the removal function is a rotationally symmetric Gaussian function, that is, at the residence point (x i y i The amount of material removed from the material surface at (x, y) after a unit time of residence at point ) is:

[0032]

[0033] The peak etching rate v and the full width at half maximum (FWHM) of the removal function are exponential functions of temperature T.

[0034]

[0035]

[0036] In the formula, v1, v2, v3, f1, f2, and f3 are coefficients calibrated through experiments.

[0037] Preferably, in the atmospheric plasma time-varying nonlinear removal function calibration system considering thermal effects in module M1, multiple single-point processing experiments are used, and the variation curve of the highest temperature T in the atmospheric plasma processing area and the material removal surface shape M at each dwell point are recorded by an infrared thermal imager. k (x, y), construct the following nonlinear least squares model:

[0038]

[0039] In the formula, the optimization coefficient vector p = [v1, v2, v3, f1, f2, f3], and E is the sum of squares of the differences between the actual removal amount and the calculated removal amount:

[0040]

[0041] Where (x) j y j ) represents the coordinates of the sampling point for the j-th surface removal amount, T q Δt represents the highest temperature of the processing area recorded by the thermal imager in the qth frame, N(k) represents the total number of frames of data recorded by the infrared thermal imager corresponding to the kth single-point processing experiment, and Δt represents the sampling period of the infrared thermal imager.

[0042] Preferably, in module M4, the dwell point (x) i y i ) The dwell time t after regulation i 'for:

[0043]

[0044] Where vc and F c The nominal peak etching rate and full width at half maximum (FWHM) of the removal function used to solve for the dwell time; T i For real-time temperature measurement of the processing area; v(T) i ) and F(T i ) is the removal function at temperature T i The actual peak etching rate and full width at half maximum (FWHM) are as follows; t i The planned dwell time at the processing point.

[0045] Preferably, in the temperature measurement of the processing area in module M4, a coaxial coplanar excitation structure is used to form a long plasma jet, the processing spacing is adjusted until the processing area is fully exposed, and an infrared thermal imager is used to monitor the temperature of the processing area.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] This invention establishes a calibration method for time-varying nonlinear removal function of atmospheric plasma that takes into account thermal effects. By using temperature detection data of the processing area, a real-time residence time control method is established based on the assumption of equal volume material removal, which effectively suppresses atmospheric plasma processing errors caused by thermal effects and improves processing accuracy. Attached Figure Description

[0048] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0049] Figure 1 This is a schematic flowchart of the method of the present invention;

[0050] Figure 2 This is a graph showing the amount of material removed during the calibration experiment of this invention;

[0051] Figure 3 This is a graph showing real-time temperature monitoring data during the calibration experiment of this invention;

[0052] Figure 4 The graph shows the time-varying nonlinear removal function of atmospheric plasma considering thermal effects, obtained by calibration in this invention.

[0053] Figure 5 This is a surface profile of the target material removed in this invention;

[0054] Figure 6 This is a diagram of the residence time matrix obtained by the present invention;

[0055] Figure 7 This is a diagram of residual processing error after online compensation of dwell time according to the present invention. Detailed Implementation

[0056] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0057] Example 1:

[0058] According to the present invention, an online thermal error compensation method for atmospheric plasma jet processing is provided, the method comprising the following steps:

[0059] Step S1: Experimentally calibrate the time-varying nonlinear removal function of atmospheric plasma considering thermal effects; in the calibration method of the time-varying nonlinear removal function of atmospheric plasma considering thermal effects, the removal function is a rotationally symmetric Gaussian function, that is, at the residence point (x i y i The amount of material removed from the material surface at (x, y) after a unit time of residence at point ) is:

[0060]

[0061] The peak etching rate v and the full width at half maximum (FWHM) of the removal function are exponential functions of temperature T.

[0062]

[0063]

[0064] In the formula, v1, v2, v3, f1, f2, and f3 are coefficients calibrated through experiments.

[0065] In the calibration method of time-varying nonlinear removal function of atmospheric plasma considering thermal effects, multiple single-point processing experiments are used. The variation curve of the highest temperature T in the atmospheric plasma processing area and the material removal surface shape M at each residence point are recorded by infrared thermal imager. k (x, y), construct the following nonlinear least squares model:

[0066]

[0067] In the formula, the optimization coefficient vector p = [v1, v2, v3, f1, f2, f3], and E is the sum of squares of the differences between the actual removal amount and the calculated removal amount:

[0068]

[0069] Where (x) j y j ) represents the coordinates of the sampling point for the j-th surface removal amount, Tq Δt represents the highest temperature of the processing area recorded by the thermal imager in the qth frame, N(k) represents the total number of frames of data recorded by the infrared thermal imager corresponding to the kth single-point processing experiment, and Δt represents the sampling period of the infrared thermal imager.

[0070] Step S2: For the surface to be removed from the target material, set the nominal removal function and solve for the dwell time;

[0071] Step S3: Calculate the feed rate based on the dwell time and motion path;

[0072] Step S4: After the machine tool starts moving, the highest temperature of the processing area is measured online by an infrared thermal imager. Based on the remaining movement time of the movement buffer area and the requirement for removal of equal volume of material, the dwell time is dynamically adjusted. The forward and interpolation movement planning is performed in real time until the plasma nozzle covers all dwell points along the planned path.

[0073] Detention point (x) i y i ) The dwell time t after regulation i 'for:

[0074]

[0075] Where v c and F c The nominal peak etching rate and full width at half maximum (FWHM) of the removal function used to solve for the dwell time; T i For real-time temperature measurement of the processing area; v(T) i ) and F(T i ) is the removal function at temperature T i The actual peak etching rate and full width at half maximum (FWHM) are as follows; t i The planned dwell time at the processing point.

[0076] In the temperature measurement of the processing area, a coaxial coplanar excitation structure is used to form a long plasma jet. The processing spacing is adjusted until the processing area is fully exposed, and an infrared thermal imager is used to monitor the temperature of the processing area.

[0077] The present invention also provides an online thermal error compensation system for atmospheric plasma jet processing. The online thermal error compensation system for atmospheric plasma jet processing can be implemented by executing the process steps of the online thermal error compensation method for atmospheric plasma jet processing. That is, those skilled in the art can understand the online thermal error compensation method for atmospheric plasma jet processing as a preferred embodiment of the online thermal error compensation system for atmospheric plasma jet processing.

[0078] Example 2:

[0079] The present invention also provides an online thermal error compensation system for atmospheric plasma jet processing, the system comprising the following modules:

[0080] Module M1: Experimentally calibrates the time-varying nonlinear removal function of atmospheric plasma considering thermal effects; in the calibration system of the time-varying nonlinear removal function of atmospheric plasma considering thermal effects, the removal function is a rotationally symmetric Gaussian function, that is, at the residence point (x i y i The amount of material removed from the material surface at (x, y) after a unit time of residence at point ) is:

[0081]

[0082] The peak etching rate v and the full width at half maximum (FWHM) of the removal function are exponential functions of temperature T.

[0083]

[0084]

[0085] In the formula, v1, v2, v3, f1, f2, and f3 are coefficients calibrated through experiments.

[0086] In the atmospheric plasma time-varying nonlinear removal function calibration system considering thermal effects in module M1, multiple single-point processing experiments are used to record the variation curve of the highest temperature T in the atmospheric plasma processing area and the material removal surface shape M at each dwelling point using an infrared thermal imager. k (x, y), construct the following nonlinear least squares model:

[0087]

[0088] In the formula, the optimization coefficient vector p = [v1, v2, v3, f1, f2, f3], and E is the sum of squares of the differences between the actual removal amount and the calculated removal amount:

[0089]

[0090] Where (x) j y j ) represents the coordinates of the sampling point for the j-th surface removal amount, T q Δt represents the highest temperature of the processing area recorded by the thermal imager in the qth frame, N(k) represents the total number of frames of data recorded by the infrared thermal imager corresponding to the kth single-point processing experiment, and Δt represents the sampling period of the infrared thermal imager.

[0091] Module M2: For the surface to be removed from the target material, set the nominal removal function and solve for the dwell time;

[0092] Module M3: Calculates the feed rate based on dwell time and motion path;

[0093] Module M4: After the machine tool starts moving, the highest temperature of the processing area is measured online by an infrared thermal imager. Based on the remaining movement time in the motion buffer area and the requirement for removal of equal volume of material, the dwell time is dynamically adjusted. The forward and interpolation motion planning is performed in real time until the plasma nozzle covers all dwell points along the planned path.

[0094] Detention point (x) i y i ) The dwell time t after regulation i 'for:

[0095]

[0096] Where v c and F c The nominal peak etching rate and full width at half maximum (FWHM) of the removal function used to solve for the dwell time; T i For real-time temperature measurement of the processing area; v(T) i ) and F(T i ) is the removal function at temperature T i The actual peak etching rate and full width at half maximum (FWHM) are as follows; t i The planned dwell time at the processing point.

[0097] In the temperature measurement of the processing area, a coaxial coplanar excitation structure is used to form a long plasma jet. The processing spacing is adjusted until the processing area is fully exposed, and an infrared thermal imager is used to monitor the temperature of the processing area.

[0098] Example 3:

[0099] This invention provides an online thermal error compensation method for atmospheric plasma jet machining. It experimentally calibrates a time-varying nonlinear removal function for atmospheric plasma that considers thermal effects. For the target removal surface, the dwell time is calculated using a nominal removal function. The feed rate is calculated based on the dwell time and the motion path. After the machine tool starts moving, the highest temperature of the machining area is measured online using an infrared thermal imager. Based on the remaining motion time in the motion buffer zone and the required removal volume of material, the dwell time is dynamically adjusted. Real-time look-ahead and interpolation motion planning is performed until the plasma nozzle covers all dwell points along the planned path. This invention establishes a calibration method for the time-varying nonlinear removal function of atmospheric plasma that considers thermal effects. By adjusting the dwell time in real time according to the temperature changes in the machining area, it effectively suppresses atmospheric plasma machining errors caused by thermal effects and improves machining accuracy.

[0100] This implementation case provides an online thermal error compensation method for atmospheric plasma jet processing, such as... Figure 1 As shown.

[0101] This embodiment specifically includes the following steps:

[0102] Step 1: Experimentally calibrate the time-varying nonlinear removal function of atmospheric plasma considering thermal effects. The removal function is preferably a rotationally symmetric Gaussian function, i.e., at the residence point (x... i y i The amount of material removed from the material surface at (x, y) after a unit time of residence at point ) is:

[0103]

[0104] The peak etching rate v and the full width at half maximum (FWHM) of the removal function are preferably exponential functions of temperature T.

[0105]

[0106]

[0107] Multiple single-point processing experiments were conducted, and the variation curve of the highest temperature T in the atmospheric plasma processing area and the material removal surface shape M at each dwell point were recorded using an infrared thermal imager. k (x, y), construct the following nonlinear least squares model:

[0108]

[0109] In the formula, the optimization coefficient vector p = [v1, v2, v3, f1, f2, f3], and E is the sum of squares of the differences between the actual removal amount and the calculated removal amount:

[0110]

[0111] Where (x) j y j ) represents the coordinates of the sampling point for the j-th surface removal amount, T q Let N(k) be the highest temperature of the processing area recorded in the q-th frame by the thermal imager, N(k) be the total number of frames of data recorded by the infrared thermal imager corresponding to the k-th single-point processing experiment, and Δt be the sampling period of the infrared thermal imager. The temperature coefficient is calibrated by solving the nonlinear least squares problem using the Levenberg-Marquardt algorithm.

[0112] Step 2: Based on the nominal removal function model, establish the residence time and solve the linear equation system:

[0113] h = Rt

[0114] In the formula,

[0115]

[0116] Where r ijt represents the removal rate at sampling point i during etching at residence point j. j h is the length of stay at point j. i Let be the target material removal amount at sampling point i, and m and n be the number of sampling points and the number of residence points, respectively. The optimization problem is constructed using Tikhonov regularization for the linear equation system:

[0117]

[0118] Where I is the identity matrix, the optimization problem is solved to calculate the dwell time.

[0119] Step 3: Calculate the feed rate based on the dwell time and motion path;

[0120] Step 4: After starting the machine tool movement, measure the highest temperature of the processing area online using an infrared thermal imager. Based on the remaining movement time in the motion buffer zone and the required removal volume of material, adjust the dwell point (x). i y i The stay time at location ) is t i ′:

[0121]

[0122] Where v c and F c The nominal peak etching rate and full width at half maximum (FWHM) of the removal function used to solve for the dwell time; T i For real-time temperature measurement of the processing area; v(T) i ) and F(T i ) is the removal function at temperature T i The actual peak etching rate and full width at half maximum (FWHM) are as follows; t i The planned dwell time at the processing point.

[0123] While adjusting the dwell time, forward and interpolation motion planning is carried out until the plasma nozzle covers all dwell points along the planned path.

[0124] The following case study illustrates the process of removing sinusoidal surfaces from fused silica using atmospheric plasma jets. Similar methods can be applied to different atmospheric plasma jet processing scenarios.

[0125] Step 1: Conduct a single-point material removal experiment using an atmospheric plasma jet, such as... Figure 2 As shown, temperature data during the processing is recorded, such as... Figure 3 As shown;

[0126] Step 2, assuming the removal function is a rotationally symmetric Gaussian function: The peak etching rate v and the full width at half maximum (FWHM) of the removal function are preferably exponential functions of temperature T. like Figure 4 As shown, the coefficients are calibrated by solving the following nonlinear least squares model using the Levenberg-Marquardt algorithm:

[0127]

[0128] In the formula, the optimization coefficient vector p = [v1, v2, v3, f1, f2, f3], and E is the sum of squares of the differences between the actual removal amount and the calculated removal amount:

[0129]

[0130] Step 3, based on the target material removal amount, such as Figure 5 As shown, a linear equation system is established based on the nominal removal function model to solve for the residence time: h = Rt, where Where r ij t represents the removal rate at sampling point i during etching at residence point j. j h is the length of stay at point j. i Let be the target material removal amount at sampling point i, and m and n be the number of sampling points and the number of residence points, respectively. The optimization problem is constructed using Tikhonov regularization for the linear equation system:

[0131]

[0132] Where I is the identity matrix, the optimization problem is solved to determine the dwell time, such as Figure 6 As shown.

[0133] Step 4: After starting the machine tool movement, measure the highest temperature of the processing area online using an infrared thermal imager. Based on the remaining movement time in the motion buffer zone and the required amount of material to be removed in equal volumes, adjust the processing point (x). i y i The stay time at location ) is t i ′:

[0134]

[0135] Where v c and F c The nominal peak etching rate and full width at half maximum (FWHM) of the removal function used to solve for the dwell time; T i For real-time temperature measurement of the processing area; v(T) i ) and F(T i ) is the removal function at temperature T i The actual peak etching rate and full width at half maximum (FWHM) are as follows; t iThe planned dwell time at the processing point.

[0136] While adjusting the residence time, look-ahead and interpolation motion planning are performed until the plasma nozzle covers all residence points along the planned path. After online compensation of the residence time, residual processing errors are considered. Figure 7 As shown.

[0137] Those skilled in the art can understand this embodiment as a more specific description of Embodiment 1 and Embodiment 2.

[0138] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0139] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A method for online thermal error compensation in atmospheric plasma jet processing, characterized in that, The method includes the following steps: Step S1: Experimentally calibrate the time-varying nonlinear removal function of atmospheric plasma considering thermal effects; Step S2: For the surface to be removed from the target material, set the nominal removal function and solve for the dwell time; Step S3: Calculate the feed rate based on the dwell time and motion path; Step S4: After the machine tool starts moving, the highest temperature of the processing area is measured online by an infrared thermal imager. Based on the remaining movement time of the movement buffer area and the requirement for removal of equal volume of material, the dwell time is dynamically adjusted. Real-time look-ahead and interpolation movement planning is carried out until the plasma nozzle covers all dwell points along the planned path. In the atmospheric plasma time-varying nonlinear removal function calibration method considering thermal effects in step S1, the removal function is a rotationally symmetric Gaussian function, that is, at the dwell point ( After a unit of time, the material surface ( The amount of material removed at point ) is: (1) The peak etching rate v and the full width at half maximum (FWHM) of the removal function are exponential functions of temperature T. (2) (3) In the formula These are coefficients calibrated through experiments; In step S1, the atmospheric plasma time-varying nonlinear removal function calibration method considering thermal effects uses multiple single-point processing experiments. An infrared thermal imager is used to record the variation curve of the highest temperature T in the atmospheric plasma processing area and the material removal surface shape at each dwelling point. Construct the following nonlinear least squares model: (4) In the formula, the optimization coefficient vector , E This is the sum of squares of the differences between the actual removal amount and the calculated removal amount: (5) in( () represents the coordinates of the sampling point for the removal amount of the j-th surface. This represents the highest temperature in the processing area recorded by the thermal imager in the q-th frame. N ( k ) is the first k The total number of frames of data recorded by the infrared thermal imager for each single-point processing experiment. This represents the sampling period of the infrared thermal imager.

2. The online thermal error compensation method for atmospheric plasma jet processing according to claim 1, characterized in that, In step S4, the dwell point Length of stay after adjustment for: (8) in and The nominal peak etching rate and full width at half maximum (FWHM) of the removal function used to solve for the dwell time; For real-time temperature measurement of the processing area; and To remove the function at temperature The actual peak etching rate and full width at half maximum (FWHM) are as follows; The planned dwell time at the processing point.

3. The online thermal error compensation method for atmospheric plasma jet processing according to claim 1, characterized in that, In step S4, the temperature measurement of the processing area is performed by using a coaxial coplanar excitation structure to form a plasma jet, adjusting the processing spacing until the processing area is fully exposed, and using an infrared thermal imager to monitor the temperature of the processing area.

4. An online thermal error compensation system for atmospheric plasma jet processing, characterized in that, The system includes the following modules: Module M1: Experimentally calibrates the time-varying nonlinear removal function of atmospheric plasma considering thermal effects; Module M2: For the surface to be removed from the target material, set the nominal removal function and solve for the dwell time; Module M3: Calculates the feed rate based on dwell time and motion path; Module M4: After the machine tool starts moving, the highest temperature of the processing area is measured online by an infrared thermal imager. Based on the remaining movement time in the movement buffer area and the requirement for removal of equal volume of material, the dwell time is dynamically adjusted. The forward and interpolation movement planning is performed in real time until the plasma nozzle covers all dwell points along the planned path. In the atmospheric plasma time-varying nonlinear removal function calibration system considering thermal effects in module M1, the removal function is a rotationally symmetric Gaussian function, i.e., at the dwell point ( After a unit of time, the material surface ( The amount of material removed at point ) is: (1) The peak etching rate v and the full width at half maximum (FWHM) of the removal function are exponential functions of temperature T. (2) (3) In the formula These are coefficients calibrated through experiments; In the atmospheric plasma time-varying nonlinear removal function calibration system considering thermal effects in module M1, multiple single-point processing experiments are used to record the variation curve of the highest temperature T in the atmospheric plasma processing area and the material removal surface shape at each dwelling point using an infrared thermal imager. Construct the following nonlinear least squares model: (4) In the formula, the optimization coefficient vector , E This is the sum of squares of the differences between the actual removal amount and the calculated removal amount: (5) in( () represents the coordinates of the sampling point for the removal amount of the j-th surface. This represents the highest temperature in the processing area recorded by the thermal imager in the q-th frame. N ( k ) is the first k The total number of frames of data recorded by the infrared thermal imager for each single-point processing experiment. This represents the sampling period of the infrared thermal imager.

5. The online thermal error compensation system for atmospheric plasma jet processing according to claim 4, characterized in that, In module M4, the dwell point Length of stay after adjustment for: (8) in and The nominal peak etching rate and full width at half maximum (FWHM) of the removal function used to solve for the dwell time; For real-time temperature measurement of the processing area; and To remove the function at temperature The actual peak etching rate and full width at half maximum (FWHM) are as follows; The planned dwell time at the processing point.

6. The online thermal error compensation system for atmospheric plasma jet processing according to claim 4, characterized in that, In the temperature measurement of the processing area in module M4, a coaxial coplanar excitation structure is used to form a plasma jet, the processing spacing is adjusted until the processing area is fully exposed, and an infrared thermal imager is used to monitor the temperature of the processing area.

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