Control method and device for vertical milling head based on adaptive parameters and force feedback compensation

Abstract

The application discloses a vertical and horizontal milling head control method and device based on adaptive parameters and force feedback compensation, and relates to the technical field of vertical and horizontal milling head control.The vertical and horizontal milling head control method based on adaptive parameters and force feedback compensation comprises: force signal interference monitoring, force signal validity monitoring, and vertical and horizontal milling head parameter dynamic adjustment monitoring.The application determines whether to perform force sensor signal amplification multiple adjustment, determines whether to perform vertical and horizontal milling head parameter dynamic adjustment analysis based on the force signal validity identification result, and finally determines whether to perform adaptive vertical and horizontal milling head parameter dynamic adjustment based on the vertical and horizontal milling head parameter dynamic adjustment analysis result, so that the vertical and horizontal milling head control accuracy of adaptive parameters and force feedback compensation is improved, and the problem of low vertical and horizontal milling head control accuracy of adaptive parameters and force feedback compensation caused by force signal sampling mismatch in the prior art is solved.

Description

Technical Field

[0001] This invention relates to the field of vertical and horizontal milling head control technology, and in particular to a vertical and horizontal milling head control method and device based on adaptive parameters and force feedback compensation. Background Technology

[0002] During the machining of guideways with a vertical and horizontal milling head, the workpiece is first clamped on the worktable. A laser measuring device automatically calibrates the workpiece reference, ensuring consistent machining of the bottom and sides of the guideway. Subsequently, the C-axis rotation mechanism rotates the milling head to a specified angle according to machining requirements, and the automatic balancing center synchronously adjusts the counterweight to ensure stability and balance. Next, the vertical and horizontal spindles start simultaneously, and the vertical and horizontal milling head control center dynamically adjusts cutting parameters using an adaptive algorithm. During machining, a coolant spray system installed on the outside of the vertical and horizontal milling head tool holder, including a coolant flow sensor and intelligent flow controller, intelligently adjusts the flow rate according to the machining location and depth to effectively control the temperature of the cutting area. Spiral blades in the chip removal channel propel chips out quickly, and a filter prevents chip backflow. A force sensor monitors the cutting speed in real time. The cutting depth is determined by the force signal processor, which transmits the data to the vertical and horizontal milling head control center for dynamic cutting depth compensation. After machining, the tool exchange mechanism quickly changes tools through a quick-locking device and a tool magazine management system to prepare for the next workpiece machining. Simultaneously, the spindle online monitoring system continuously monitors the spindle status, and triggers a safety mechanism to stop machining immediately upon detecting an abnormality. In the process of machining guideways with the vertical and horizontal milling head, the existing technology first requires the operator to input machining commands into the vertical and horizontal milling head control center and select the vertical or horizontal machining mode. During machining, the vertical and horizontal milling head control center monitors the operating status of the servo motor and hydraulic system in real time, adjusts the spindle speed and feed rate based on preset parameters, and provides position information through sensors (such as displacement sensors) to ensure machining accuracy.

[0003] When machining high-hardness workpieces with vertical and horizontal milling heads, the presence of hard particles (such as carbide inclusions) or uneven grain size within the workpiece material can cause instantaneous impact loads when the cutting tool mounted on the spindle of the vertical and horizontal milling head comes into contact with these uneven areas. This results in a rapid change in the depth of cut, which in turn can cause high-frequency fluctuations in the force signal collected by the force sensor mounted on the spindle of the vertical and horizontal milling head. There may be a mismatch between the high-frequency fluctuation frequency of the force signal and the sampling frequency of the force sensor, which may lead to distortion of the collected force signal. Consequently, misjudgments may occur when force signal identification is performed based on the distorted force signal. When adaptive cutting parameters (such as cutting speed and depth of cut) are adjusted based on the distorted or misjudged force signal, the adjustment of the adaptive cutting parameters may be deviated. Ultimately, this leads to machining defects such as out-of-tolerance dimensional accuracy when the workpiece is machined based on the deviated cutting parameters. There is a problem of low accuracy in the control of vertical and horizontal milling heads due to the mismatch in force signal sampling and the resulting adaptive parameters and force feedback compensation. Summary of the Invention

[0004] To address the problem of low accuracy in adaptive parameter and force feedback compensation control of vertical and horizontal milling heads in existing technologies due to force signal sampling mismatch, this invention provides a vertical and horizontal milling head control method and apparatus based on adaptive parameters and force feedback compensation. The technical solution is as follows:

[0005] On the one hand, a control method for vertical and horizontal milling heads based on adaptive parameters and force feedback compensation is provided. This method includes: during the machining process of the vertical and horizontal milling head, force signal interference analysis is performed, and based on the results of the force signal interference analysis, it is determined whether to adjust the amplification factor of the force sensor signal. The adjustment of the amplification factor of the force sensor signal is used to reduce the excessive distortion of the first impact signal amplification and improve the recognition of the second impact signal, so as to ensure the accuracy of force signal acquisition. After the force signal interference analysis is qualified, the validity of the force signal is identified and judged, and based on the results of the validity identification and judgment, it is determined whether to perform dynamic adjustment analysis of the vertical and horizontal milling head parameters. If the dynamic adjustment analysis of the vertical and horizontal milling head parameters is not performed, an alarm for inaccurate force signal identification is sent; otherwise, based on the results of the dynamic adjustment analysis of the vertical and horizontal milling head parameters, it is determined whether to perform adaptive dynamic adjustment of the vertical and horizontal milling head parameters. The adaptive dynamic adjustment of the vertical and horizontal milling head parameters includes adaptive cutting parameter adjustment and C-axis rotation mechanism torque and angle adjustment. The adaptive cutting parameter adjustment is used to optimize cutting efficiency and machining quality, and the C-axis rotation mechanism torque and angle adjustment is used to ensure the C-axis rotation accuracy and stability.

[0006] On the other hand, a vertical and horizontal milling head control device based on adaptive parameters and force feedback compensation is provided. This device applies a vertical and horizontal milling head control method based on adaptive parameters and force feedback compensation. The device includes: a C-axis rotary mechanism, a right-angle transmission box, a dual-output spindle, sensors, encoders, and a controller. The core power component of the C-axis rotary mechanism is a C-axis motor, which also includes a main input shaft, a C-axis bearing, and a brake. It integrates a servo drive unit to drive the entire milling head to rotate around the vertical axis and has an angle locking function. The right-angle transmission box has a built-in bevel gear set, which can transmit power to the vertical spindle and the horizontal spindle respectively. The dual-output spindle includes a vertical spindle and a horizontal spindle. The axes of the vertical spindle and the horizontal spindle are spatially perpendicular and are used to process the bottom and sides of guide rails or box-type parts. Sensors are used to detect cutting reaction forces and rotational speed. Encoders include a C-axis encoder and a spindle encoder, which are used to acquire the position and speed signals of the vertical and horizontal dual-output milling head in real time. The controller is used to receive sensor signals and encoder feedback signals, and accurately control the vertical and horizontal milling head based on the analysis results.

[0007] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0008] 1. By performing force signal interference analysis and determining whether to adjust the force sensor signal amplification factor based on the analysis results, it helps to specifically address the distortion problem caused by high-frequency fluctuations in the force signal and the mismatch between the sampling frequency and the sampling frequency during the cutting process, ensuring the accuracy of force signal acquisition. After the force signal interference analysis is qualified, the validity of the force signal is identified and judged. Based on the validity identification result, it is determined whether to perform dynamic adjustment analysis of the vertical and horizontal milling head parameters. This helps to reduce misjudgments when identifying based on distorted force signals and provides valid force signals for dynamic adjustment analysis of vertical and horizontal milling head parameters. If dynamic adjustment analysis of vertical and horizontal milling head parameters is not performed, an alarm for inaccurate force signal identification is sent. Conversely, based on the dynamic adjustment analysis result, it is determined whether to perform adaptive dynamic adjustment of vertical and horizontal milling head parameters. This helps to solve the problem of adaptive cutting parameter adjustment deviation caused by distorted or misjudged force signals, reduce quality defects such as machining dimensional accuracy deviations, and improve the accuracy of machining quality data feedback and cutting status assessment.

[0009] 2. By selectively choosing the verification values ​​of force signal fluctuation amplitude and force signal mutation frequency as core data items, the fluctuation amplitude characteristics and instantaneous mutation characteristics of the force signal can be comprehensively captured. After harmonic averaging, the combined interference effects of the two types of indicators on the force signal of the vertical and horizontal milling head can be comprehensively considered, avoiding the deviation caused by single parameter evaluation. This makes the force signal interference index more objectively reflect the overall comprehensive degree of interference to the force signal during the machining process. Based on the force signal interference index, it is determined whether to activate the interference marking mechanism and trigger the adjustment of the force sensor signal amplification factor. This helps to specifically solve the problem of excessive distortion or blurring of details in the force signal caused by instantaneous impact, and achieves dynamic adaptation between the amplification factor and signal characteristics. At the same time, the adjustment effect is quantitatively evaluated by the signal-to-noise ratio of the second impact signal and the distortion rate of the first impact signal, ensuring that subsequent force signal validity identification is only performed when the adjustment meets the standards. This helps to avoid signal quality deterioration caused by ineffective adjustment, providing a more accurate and stable signal foundation for subsequent force signal validity identification, thereby reducing the deviation of vertical and horizontal milling head parameter adjustment caused by force signal interference.

[0010] 3. By selectively choosing the proportion of force signal baseline drift, the proportion of force signal harmonic distortion rate, and the proportion of unqualified force signal interference index as core data items, the integrity and stability characteristics of the force signal after the force sensor signal amplification factor is adjusted can be comprehensively captured. Then, through weighted coupling calculation with the force signal feature weight parameters, the force signal feature matching result is obtained. This can comprehensively consider the impact of each indicator on the validity of the force signal, avoid the deviation caused by single parameter evaluation, and make the feature matching result more objectively reflect the overall degree of conformity between the force signal characteristics and the standard force signal characteristics. Based on the force signal feature matching result, the validity of the force signal is judged and qualified force signal data is uploaded. This helps to specifically solve the identification misjudgment problem caused by force signal feature distortion and instability, ensure the accuracy and reliability of the force signal data used for dynamic adjustment analysis of vertical and horizontal milling head parameters, and provide high-quality data support for the precise control of the vertical and horizontal milling head machining process. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a flowchart of the vertical and horizontal milling head control method based on adaptive parameters and force feedback compensation provided in the embodiments of the present invention;

[0013] Figure 2 This is a schematic diagram of the shaft gear meshing of the vertical and horizontal milling head control device based on adaptive parameters and force feedback compensation provided in an embodiment of the present invention;

[0014] Figure 3 This is a flowchart summarizing the vertical and horizontal milling head control method based on adaptive parameters and force feedback compensation provided in the embodiments of the present invention.

[0015] Figure 4 This is a logic diagram of the adaptive vertical and horizontal milling head parameter dynamic adjustment of the vertical and horizontal milling head control method based on adaptive parameters and force feedback compensation provided in the embodiments of the present invention;

[0016] Figure 5 This is a schematic diagram of the milling head structure of the vertical and horizontal milling head control device based on adaptive parameters and force feedback compensation provided in an embodiment of the present invention;

[0017] Figure 6 This is a schematic diagram demonstrating the operation system of the vertical and horizontal milling head control device based on adaptive parameters and force feedback compensation provided in an embodiment of the present invention.

[0018] In the diagram: 1. C-axis motor; 2. Main input shaft; 3. C-axis bearing; 4. Brake; 5. Vertical spindle; 6. Horizontal spindle; 7. C-axis encoder; 8. Spindle encoder; 9. Transmission gear. Detailed Implementation

[0019] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0020] like Figure 1 The diagram shown is a flowchart of a vertical and horizontal milling head control method based on adaptive parameters and force feedback compensation provided in an embodiment of the present invention. Figure 1 It can be seen that: First, force signal interference monitoring involves analyzing force signal interference during the machining of vertical and horizontal milling heads, and determining whether to adjust the force sensor signal amplification factor based on the analysis results. Adjusting the force sensor signal amplification factor is used to reduce excessive distortion of the first impact signal and improve the recognition of the second impact signal, ensuring the accuracy of force signal acquisition. Through force signal interference monitoring, it is helpful to reduce the distortion of strong impacts and the ambiguity of weak signals by adjusting the signal amplification factor in a targeted manner, thereby improving the accuracy of the original force signal acquisition.

[0021] Secondly, force signal validity monitoring involves identifying and judging the validity of force signals after the force signal interference analysis is deemed satisfactory. Based on the results of the force signal validity identification and judgment, a decision is made on whether to perform dynamic adjustment analysis of vertical and horizontal milling head parameters. Force signal validity monitoring helps to screen out real and valid force signal data and reduce deviations in the dynamic adjustment of vertical and horizontal milling head parameters caused by invalid signals.

[0022] Finally, the dynamic adjustment monitoring of the vertical and horizontal milling head parameters is performed. If the dynamic adjustment analysis of the vertical and horizontal milling head parameters is not performed, an alarm for inaccurate force signal recognition will be sent. Otherwise, based on the analysis results, it will be determined whether to perform adaptive dynamic adjustment of the vertical and horizontal milling head parameters. Adaptive dynamic adjustment of the vertical and horizontal milling head parameters includes adaptive cutting parameter adjustment and C-axis rotation mechanism torque and angle adjustment. Adaptive cutting parameter adjustment is used to optimize cutting efficiency and machining quality, while C-axis rotation mechanism torque and angle adjustment is used to ensure C-axis rotation accuracy and stability. Dynamic adjustment monitoring of the vertical and horizontal milling head parameters helps to achieve dynamic adaptation between the machining parameters of the vertical and horizontal milling head and the actual working conditions, thereby improving the accuracy, efficiency, and stability of the vertical and horizontal milling head machining.

[0023] It should be noted that before designing the vertical and horizontal milling head control method based on adaptive parameters and force feedback compensation provided in this application, a database storing various setting data is established. The database includes, but is not limited to, preset force signal mutation frequency, preset rise rate threshold, preset force signal interference threshold, preset interference mark count threshold, preset first signal threshold, and preset second signal threshold, etc., among which various preset values ​​are directly set by technical personnel.

[0024] In this embodiment, through the synergistic effect of force signal interference monitoring, force signal validity monitoring, and dynamic adjustment monitoring of vertical and horizontal milling head parameters, a coherent vertical and horizontal milling head machining control and assurance system is constructed. This system ensures the accuracy of force signal acquisition and the effectiveness of force signal identification, while also improving the precision of vertical and horizontal milling head parameter adjustment and the stability of machining quality. It effectively solves problems such as insufficient machining accuracy and low efficiency caused by force signal distortion, invalidity, or improper parameter adjustment. Among them, force signal interference monitoring provides a high-quality raw signal foundation for subsequent force signal validity monitoring. If force signal interference is not effectively processed, resulting in distorted acquired signals, then the validity identification based on this will also be biased, thereby affecting the authenticity of the influence signal feature judgment. The result of force signal validity monitoring directly affects the monitoring effect of dynamic adjustment of vertical and horizontal milling head parameters. If the valid force signal identification is inaccurate or the qualified force signal data is unreliable, it will lead to distortion of the input data for parameter adjustment analysis, causing the adaptive parameter adjustment result to be mismatched with the actual machining requirements.

[0025] like Figure 2 The diagram shown is a schematic representation of the shaft gear meshing of a vertical and horizontal milling head control method device based on adaptive parameters and force feedback compensation provided in an embodiment of the present invention. Figure 2 It can be seen that the main input shaft 2 is equipped with a transmission gear 9, which meshes with the transmission gear 9 to transmit the rotational motion of the main input shaft to the horizontal spindle 6.

[0026] like Figure 3 The diagram shown is a general overview flowchart of the vertical and horizontal milling head control method based on adaptive parameters and force feedback compensation provided in an embodiment of the present invention. Figure 3It can be seen that during the machining of vertical and horizontal milling heads, force signal interference analysis is performed, and the force signal interference index is obtained. It is then determined whether the force signal interference index is greater than a preset force signal interference threshold. If not, the validity of the force signal is assessed; otherwise, an interference marking mechanism is activated, and the value of the interference mark counter is obtained. It is then determined whether the value of the interference mark counter exceeds a preset interference marking count threshold. If not, a reset prompt for the interference mark counter is sent; otherwise, the force sensor signal amplification factor adjustment is triggered. After the force sensor signal amplification factor adjustment is completed, the effect of the adjustment is verified, and the signal amplification adjustment quality value is obtained. It is then determined whether the signal amplification adjustment quality value is greater than a preset amplification quality threshold. If so, a... If the large-scale adjustment fails, an alarm will be triggered. Conversely, multimodal interference suppression processing will be performed, followed by force signal validity identification and judgment, and the effective force signal ratio value will be obtained. It will be determined whether the effective force signal ratio value is less than the preset effective force signal ratio threshold. If so, an alarm for inaccurate force signal identification will be sent. Otherwise, dynamic adjustment analysis of vertical and horizontal milling head parameters will be performed, and the vertical and horizontal milling head parameter adjustment evaluation value will be obtained. It will be determined whether the vertical and horizontal milling head parameter adjustment evaluation value is greater than the preset horizontal milling head parameter adjustment threshold. If not, continuous monitoring of the vertical and horizontal milling head machining process will be performed. Otherwise, adaptive dynamic adjustment of vertical and horizontal milling head parameters will be performed. The adaptive dynamic adjustment of vertical and horizontal milling head parameters includes adaptive cutting parameter adjustment and C-axis rotary mechanism torque and angle adjustment and torque feedback dynamic compensation.

[0027] Furthermore, the specific process of force signal interference analysis is as follows: Force signal data reflecting force signal interference during the machining of vertical and horizontal milling heads is acquired. This force signal data includes verification values ​​for force signal fluctuation amplitude and force signal mutation frequency. The verification value for force signal fluctuation amplitude is represented by quantifying the proportion of force signal fluctuation amplitude within a preset force signal interference analysis time period and a preset force signal fluctuation amplitude, and then weighting it with a force signal fluctuation amplitude weighting coefficient. The preset force signal interference analysis time period represents the time period for force signal interference analysis, during which the maximum and minimum force signal intensity are monitored by a force signal acquisition and monitoring instrument. The force signal fluctuation amplitude is calculated by quantizing the deviation between the two values. The preset force signal fluctuation amplitude is represented by the average value of the force signal fluctuation amplitude over a historical time period. Deviation quantization represents difference calculation, proportion quantization represents ratio calculation, and weighting processing represents multiplication. The force signal mutation frequency verification value is represented by the result of quantizing the force signal mutation frequency within a preset force signal interference analysis period and the preset force signal mutation frequency, and then weighting it with a force signal mutation frequency weighting coefficient. Specifically, when the force signal monitored by the piezoelectric force sensor has a rise rate greater than a preset rise rate threshold within a preset short time window during the preset force signal acquisition period... The corresponding number of occurrences is used as the force signal abrupt change frequency. The force signal intensity value at the end of the preset short time window, monitored by the force sensor monitoring instrument, is quantized as a deviation from the force signal intensity value at the beginning of the preset short time window. The result of this deviation quantization and the ratio quantization of the preset short time window duration is used as the rise rate. The preset rise rate threshold is represented by the average rise rate of the force signal over a historical time period. The preset force signal abrupt change frequency is represented by the average force signal abrupt change frequency over a historical time period. The preset short time window is the minimum time interval used to capture instantaneous changes in the force signal. The force signal data is then harmonic-averaged to obtain a comprehensive value reflecting the interference of the force signal within the preset force signal acquisition time period. The force signal interference index measures the degree of interference. When the force signal fluctuation amplitude increases, the overall fluctuation range of the force signal expands, causing some instantaneous signals that did not originally reach the preset mutation threshold to be included in the mutation statistics, thereby increasing the force signal mutation frequency. When the force signal mutation frequency increases, frequent force signal mutation interference will be superimposed on the steady-state fluctuation, causing the force signal fluctuation amplitude to increase further. The increase in force signal fluctuation amplitude and force signal mutation frequency will cause the force signal interference index to increase. Judgment is made based on the force signal interference index: when the force signal interference index is greater than the preset force signal interference threshold, the interference marking mechanism is activated; otherwise, the validity of the force signal is identified and judged.

[0028] Specifically, the interference marking mechanism works as follows: Interference marking is performed when the force signal interference index is detected to be greater than the preset force signal interference threshold within a preset force signal acquisition time period. The interference mark counter is incremented by 1, where the preset force signal interference threshold is represented by the average force signal interference index over a historical time period. The interference mark counter value is continuously monitored and accumulated within the preset force signal marking time period. The interference mark counter is used to mark the number of times the force signal interference index is greater than the preset force signal interference threshold within the preset force signal marking time period. When the value of the interference mark counter exceeds the preset interference mark count threshold within the preset force signal marking time period, the force sensor signal amplification factor is adjusted; otherwise, a reset prompt for the interference mark counter is sent. The preset force signal marking time period represents the time period during which the interference marking mechanism is implemented, and the duration of the preset force signal marking time period is greater than the duration of the preset force signal acquisition time period.

[0029] It is important to note that the influence values ​​of force signal fluctuation amplitude and force signal mutation frequency are used to reflect the degree of influence of force signal data on the force signal interference index. In this embodiment, there is a mapping group obtained from the database. This mapping group contains mapping sets, which are pre-set by professional technicians. For example, this mapping group is gradually constructed through statistical analysis and influence value verification of historical vertical and horizontal milling head machining force signal interference data: First, extract a large number of specific parameter combinations of force signal fluctuation amplitude and force signal mutation frequency in actual machining scenarios, assign quantitative values ​​to each parameter based on the weight of its influence on the interference index, and simultaneously record the actual values ​​of the influence values ​​of force signal fluctuation amplitude and force signal mutation frequency in the corresponding scenarios. Then, through correlation analysis (such as Kendall rank correlation coefficient analysis), the random fluctuations caused by the machining environment are eliminated. Abnormal correlation data caused by temporary calibration of moving instruments are retained, and the correspondence between statistically significant force signal parameter combinations and the influence values ​​of force signal fluctuation amplitude and force signal mutation frequency is preserved. Finally, a mapping group containing multiple mapping sets is formed. The mapping relationship adopts a one-to-one correspondence or many-to-one form to accurately reflect the influence degree of different interference factors on the force signal interference index under different data scenarios. The mapping relationship uses the 0-1 value range to represent the weight influence value ratio. When the system receives the quantification results of the ratio of force signal fluctuation amplitude verification value and force signal mutation frequency verification value, it can quickly retrieve the corresponding force signal fluctuation amplitude influence value and force signal mutation frequency influence value from the pre-built mapping group, thereby accurately quantifying the influence degree of the two types of data items on the force signal interference index.

[0030] In this embodiment, force signal interference analysis enables the quantitative capture of force signal fluctuations and abrupt changes, as well as the accurate assessment of the overall interference level. Combined with an interference marking mechanism, dynamic monitoring and response are performed on force signal interference that continuously exceeds a preset interference marking threshold. This helps to specifically distinguish between instantaneous and occasional interference and continuous systematic interference, avoiding unnecessary adjustments or adjustment delays caused by misjudgment. It improves the timeliness and accuracy of force signal interference processing, ensuring that the quality of the force signal collected by the force sensor meets the requirements for subsequent force signal validity identification and judgment and adjustment of vertical and horizontal milling head parameters.

[0031] Furthermore, the specific process for adjusting the force sensor signal amplification factor is as follows: AA1, judging the strength of the instantaneous impact signal based on the force signal fluctuation amplitude: when the force signal fluctuation amplitude is greater than a preset first signal threshold, the corresponding force signal is determined as the first impact signal; when the force signal fluctuation amplitude is less than a preset second signal threshold, the corresponding force signal is determined as the second impact signal; when the force signal fluctuation amplitude is neither greater than the preset first signal threshold nor less than the preset second signal threshold, the corresponding force signal is determined as the third impact signal. The preset first and second signal thresholds are both preset by designated personnel, and the preset first signal threshold is greater than the preset second signal threshold. The force signal acquisition and monitoring instrument monitors the preset force signal acquisition time period. The maximum and minimum values ​​of the internal force signal intensity are quantized to reflect the magnitude of the force signal fluctuation within a preset force signal acquisition time period. AA2 involves inputting the force signal interference index and force sensor load rate into a force signal amplification factor adjustment coefficient mapping set in the database to obtain the force signal amplification factor adjustment coefficient. This coefficient is a quantized parameter determined by the mapping set based on the combination of the force signal interference index and the force sensor load rate. It is used to dynamically adjust the amplification factor to balance the need for distortion prevention in the first impact signal and improved recognition of the second impact signal. The mapping set of the force signal interference index and force sensor load rate is pre-set and stored by designated personnel. The database reflects the correspondence between the combination of force signal interference index and force sensor load rate and the force signal amplification factor adjustment coefficient. For example, this mapping set is gradually constructed through statistical analysis and parameter verification of historical vertical and horizontal milling head machining force signal adjustment scenarios: First, specific combination parameters of force signal interference index and force sensor load rate in a large number of actual machining scenarios are extracted, and each parameter is assigned a weighted influence value based on its degree of influence on amplification factor adjustment. The actual effective force signal amplification factor adjustment coefficient in the corresponding scenario is recorded simultaneously. Then, abnormal correlation data caused by temporary sensor failures or sudden machining anomalies are removed through correlation analysis (such as Spearman rank correlation coefficient analysis), and statistically significant force signal interference index and force sensor load rate adjustment coefficient are retained. The correspondence between the combination of sensor load rates and the force signal amplification factor adjustment coefficient ultimately forms a mapping set that can be directly queried; AA3, when the first impact signal is detected, the adjustment step size is used to gradually reduce the amplification factor of the signal, which helps to reduce waveform distortion caused by excessive amplification of the first impact signal and ensure that the force signal accurately reflects the impact intensity within the effective range. When the second impact signal is detected, the adjustment step size is used to gradually increase the amplification factor of the signal, which helps to enhance the amplitude intensity of the second impact signal, improve its recognition in noisy backgrounds, reduce feature loss caused by insufficient force signal recognition, and ensure the effective extraction of detailed force signal information;When a third impact signal is detected, maintaining the current amplification factor helps preserve the original waveform characteristics and amplitude ratio of the force signal, reduces signal fluctuation interference caused by frequent adjustments, ensures the continuity and stability of the force signal under moderate-intensity impacts, and improves signal processing efficiency. During the force sensor signal amplification factor adjustment process, the force signal interference index is continuously monitored. When the force signal interference index is less than the preset force signal interference threshold, the force sensor signal amplification factor adjustment effect is verified; otherwise, the force sensor signal amplification factor adjustment continues. If the number of force sensor signal amplification factor adjustments exceeds the preset maximum number of adjustments, and the force signal interference index is still not less than the preset force signal interference threshold, an invalid force signal amplification factor adjustment prompt is sent. The preset maximum number of adjustments is pre-set by a designated person, and the amplification factor does not exceed the preset maximum signal amplification factor. After the force sensor signal amplification factor adjustment is completed, the effect of the force sensor signal amplification factor adjustment is verified.

[0032] Specifically, the verification process for the force sensor signal amplification factor adjustment effect is as follows: First, obtain signal amplification verification data items reflecting the force sensor signal amplification factor adjustment effect. These data items include the signal-to-noise ratio (SNR) of the second impact signal and the distortion rate of the first impact signal. Second, after adjusting the force sensor signal amplification factor within a preset force signal acquisition time period, the ratio of the maximum amplitude of the second impact signal monitored by the force signal acquisition and monitoring instrument to a preset force signal noise threshold is used as the SNR of the second impact signal. The preset force signal noise threshold is represented by the average force signal noise value over a historical time period. Third, after adjusting the force sensor signal amplification factor within the preset force signal acquisition time period, the deviation quantization result of the amplitude of the first impact signal waveform at a preset time monitored by the force signal acquisition and monitoring instrument and the amplitude of the corresponding preset standard first impact signal waveform, along with the sum of the preset first impact signal waveform constant, is used as the reciprocal of the result. The signal intensity corresponding to the peak of the first impact signal waveform at the preset time monitored by the force signal acquisition and monitoring instrument is used as the amplitude corresponding to the first impact signal waveform. The preset standard first impact signal waveform is obtained by using a Fourier transform algorithm to select the lowest frequency and strongest signal from the force signal. The force signal, separated from the complex force signal by its frequency components, is represented by a preset time. The preset time indicates the moment for verifying the effect of adjusting the force sensor signal amplification factor. The preset first impact signal waveform constant is pre-set by designated personnel to avoid meaningless distortion rates due to the quantization result of the deviation between the amplitude of the first impact signal waveform and the preset standard first impact signal waveform being zero. The result of weighted coupling operations on the signal amplification verification data items and their corresponding weight parameters is used as the signal amplification adjustment quality value to reflect the overall effect of the force sensor signal amplification factor adjustment. The weight parameters of the signal amplification verification data items include the signal-to-noise ratio weight coefficient of the second impact signal and the distortion rate weight coefficient of the first impact signal. The weighted coupling operation represents the summation operation after multiplying each item. Based on the judgment of the signal amplification adjustment quality value: when the signal amplification adjustment quality value is greater than the preset amplification quality threshold, an amplification factor adjustment failure alarm is sent. Otherwise, the force signal after the force sensor signal amplification factor adjustment is adjusted is subjected to multimodal interference suppression processing based on the adaptive wavelet threshold denoising algorithm, and then the validity of the force signal is identified and judged. The preset amplification quality threshold is represented by the average value of the signal amplification adjustment quality value over a historical time period.

[0033] It is important to note that the weighting coefficients of the second impact signal signal-to-noise ratio and the first impact signal distortion rate are used to reflect the influence of the signal amplification verification data item on the signal amplification adjustment quality value. In this embodiment, there is a mapping group obtained from the database. This mapping group contains a mapping set, which is pre-set by professional technicians. For example, this mapping group is gradually constructed through statistical analysis and influence value verification of historical force sensor signal amplification adjustment effect verification data: First, extract the specific parameter combinations of the second impact signal signal-to-noise ratio and the first impact signal distortion rate in a large number of actual processing scenarios, assign each parameter a quantified value based on the influence weight on the signal amplification adjustment quality value, and simultaneously record the actual values ​​of the weighting coefficients of the second impact signal signal-to-noise ratio and the first impact signal distortion rate in the corresponding scenarios. Then, through correlation analysis (such as Kendall rank correlation coefficient analysis), the results are further analyzed. (Analysis, etc.) Remove abnormal correlation data caused by accidental fluctuations in the processing environment and temporary instrument calibration, retain the statistically significant signal amplification verification data item combination and the correspondence between the second impact signal signal-to-noise ratio weight coefficient and the first impact signal distortion rate weight coefficient, and finally form a mapping group containing multiple mapping sets. The mapping relationship adopts a one-to-one correspondence or many-to-one form to accurately reflect the degree of influence of different verification indicators on the signal amplification adjustment quality value under different data scenarios. The mapping relationship uses the 0-1 value range to represent the weight coefficient ratio. When the system receives the quantification result of the signal amplification verification data item, it can quickly retrieve the corresponding second impact signal signal-to-noise ratio weight coefficient and first impact signal distortion rate weight coefficient from the pre-built mapping group, and then accurately quantify the degree of influence of the two types of data items on the signal amplification adjustment quality value.

[0034] In this embodiment, by adjusting the amplification factor of the force sensor signal, the amplification factor is dynamically adapted according to impact signals of different intensities. Combined with the verification of the amplification factor adjustment effect of the force sensor signal, the quantitative evaluation and feedback of signal quality is achieved. This helps to balance the need for anti-distortion of the first impact signal and improved recognition of the second impact signal, reduces the loss or distortion of force signal features caused by improper force signal processing, improves the accuracy and reliability of force signal acquisition, and ensures that the processed force signal can provide a high-accuracy force signal data foundation for subsequent multimodal interference suppression and force signal validity identification, thereby ensuring the scientific nature of the vertical and horizontal milling head parameter adjustment and the stability of the machining process.

[0035] Furthermore, the specific process for force signal validity identification and judgment is as follows: Force signal feature data items are acquired to reflect the integrity and stability of the force signal characteristics after the force sensor signal amplification factor adjustment. These force signal feature data items include the proportion of force signal baseline drift, the proportion of force signal harmonic distortion rate, and the proportion of unqualified force signal interference index. The proportion of force signal baseline drift is represented by the result of quantizing the force signal baseline drift with a preset force signal baseline drift. Specifically, the Euclidean distance of the force signal baseline from its initial position within the preset signal identification time period is used as the force signal baseline drift. The preset force signal baseline drift is obtained by comparing the force signal baseline drift over historical time periods. The average value represents the time period for force signal validity identification and judgment. The force signal harmonic distortion rate ratio is represented by the result of quantizing the force signal harmonic distortion rate and the standard force signal harmonic distortion rate. The ratio of the total effective value of each harmonic in the force signal to the effective value of the fundamental wave within the preset signal identification time period is used as the force signal harmonic distortion rate. The force signal separated from the complex force signal based on the Fourier transform algorithm, which identifies the lowest and strongest signal frequency component, is used as the fundamental wave. Signal components in the force signal that are integer multiples of the fundamental wave are used as harmonics. The signal strength of each separated harmonic is calculated based on the root mean square. The algorithm calculates the effective values ​​of each harmonic signal intensity, and the result of the sum of squares and square root operations is taken as the total effective value of each harmonic. The result of the separation of the fundamental signal calculated using the root mean square algorithm is taken as the effective value of the fundamental signal. The proportion of the unqualified force signal interference index is represented by the result of quantifying the proportion of the unqualified force signal interference index with the preset unqualified force signal interference index. The force signal interference index greater than the preset force signal interference threshold is taken as the unqualified force signal interference index. The preset unqualified force signal interference index is represented by the average value of the unqualified force signal interference index over a historical period. The force signal feature data items and force signal feature weight parameters are weighted. The result of the coupling operation is used as the force signal feature matching result to reflect the overall degree of conformity between the force signal characteristics and the standard force signal characteristics. The force signal feature weight parameters include the force signal baseline drift weight coefficient, the force signal harmonic distortion rate weight coefficient, and the unqualified force signal interference index weight coefficient. Effective instantaneous impact load signal marking is performed: it is determined whether the force signal feature matching result is less than the preset force signal deviation threshold. If so, the corresponding force signal data is marked as an effective instantaneous impact load signal; otherwise, the corresponding force signal data is marked as an interfering instantaneous impact load signal. The preset force signal deviation threshold is represented by the average value of the force signal feature matching results over a historical time period.The system determines whether the effective force signal ratio is less than a preset effective force signal ratio threshold. If so, an alarm for inaccurate force signal recognition is sent; otherwise, the force signal recognition is deemed valid, and the corresponding force signal data is marked as qualified and synchronously uploaded to the vertical milling head control center for dynamic adjustment and analysis of the vertical milling head parameters. The preset effective force signal ratio threshold is represented by the average effective force signal ratio over a historical time period. The effective force signal ratio is calculated by quantifying the ratio of the effective instantaneous impact load signal data to the total instantaneous impact load signal data within the preset recognition time period. The total instantaneous impact load signal data represents the sum of the effective instantaneous impact load signal data monitored by the piezoelectric dynamic force sensor and the interfering instantaneous impact load signal data. The effective instantaneous impact load signal data represents the total amount of force signal data marked as effective instantaneous impact load signals within the preset recognition time period.

[0036] It is important to note that the weighting coefficients for force signal baseline drift, force signal harmonic distortion rate, and non-conforming force signal interference index are used to reflect the influence of force signal feature data items on the force signal feature matching results. In this embodiment, there is a mapping group obtained from the database. This mapping group contains mapping sets, which are pre-set by professional technicians. For example, this mapping group is gradually constructed through statistical analysis and influence value verification of historical force signal validity identification data: First, specific parameter combinations of force signal baseline drift, force signal harmonic distortion rate, and non-conforming force signal interference index are extracted from a large number of actual processing scenarios. Each parameter is assigned a quantified value based on its influence on the feature matching results. The actual values ​​of the above three types of weights in the corresponding scenarios are recorded simultaneously. Then, through the phase... Correlation analysis (such as Kendall rank correlation coefficient analysis) removes abnormal correlation data caused by fluctuations in the processing environment and temporary instrument calibration, retaining the correspondence between statistically significant feature data item combinations and the three types of weights. Finally, a mapping group containing multiple mapping sets is formed, in which the mapping relationship adopts a one-to-one correspondence or many-to-one form, so as to accurately reflect the degree of influence of different feature indicators on the force signal feature matching results under different data scenarios. The mapping relationship uses the 0-1 numerical range to represent the weight parameter proportion. When the system receives the proportion quantification result of the force signal feature data item, it can quickly retrieve the corresponding three types of weight parameters from the pre-built mapping group, thereby accurately quantifying the degree of influence of each feature data item on the force signal feature matching result.

[0037] In this embodiment, by identifying and judging the validity of force signals, the integrity and stability of force signal characteristics are quantitatively evaluated from multiple dimensions, including force signal baseline drift, force signal harmonic distortion rate, and interference index of unqualified force signals. By combining the force signal feature matching results with the effective force signal ratio, qualified force signal data that meets the standards is accurately screened out. This helps to filter out invalid data caused by force signal distortion or interference, reduces the need for adaptive dynamic adjustment of vertical and horizontal milling head parameters based on unreliable force signals, improves the reliability of force signal data and the accuracy of subsequent dynamic adjustment analysis of vertical and horizontal milling head parameters, and ensures that the force data uploaded to the vertical and horizontal milling head control center can truly reflect the instantaneous impact load state during the machining process.

[0038] like Figure 3 The diagram shown is a general overview flowchart of the vertical and horizontal milling head control method based on adaptive parameters and force feedback compensation provided in an embodiment of the present invention. Figure 3 It is known that the adaptive vertical and horizontal milling head parameter dynamic adjustment includes adaptive cutting parameter adjustment and C-axis rotation mechanism torque and angle adjustment. During the adaptive cutting parameter adjustment process, the cutting speed is adjusted first. When the force signal fluctuation amplitude is less than the preset impact smoothing threshold, the cutting depth is adjusted. After the adaptive cutting parameter adjustment is completed, if the vertical and horizontal milling head parameter adjustment evaluation value is not greater than the preset horizontal milling head parameter adjustment threshold, the corresponding cutting parameters are marked as qualified cutting parameters and synchronously uploaded to the vertical and horizontal milling head control center; otherwise, a cutting parameter adjustment failure alarm is sent. If the workpiece is in a horizontal position... During machining, the torque and angle of the C-axis rotary mechanism are adjusted. First, the torque of the C-axis rotary mechanism is adjusted. After the torque adjustment is completed, it is determined whether the C-axis torque deviation index is less than the preset torque deviation threshold. If not, an invalid torque adjustment prompt is sent. Otherwise, the C-axis rotation angle is adjusted. After the C-axis rotation angle is adjusted, it is determined whether the C-axis rotation angle deviation index is less than the preset C-axis rotation angle threshold. If yes, dynamic torque feedback compensation is performed. Otherwise, an invalid angle adjustment prompt is sent.

[0039] Furthermore, the specific process of dynamic adjustment analysis of vertical and horizontal milling head parameters is as follows: Obtain force signal adjustment parameters that reflect the stability of the force signal after the force sensor signal amplification factor adjustment and its adaptability to machining requirements. These parameters include the force signal interference index and the effective force signal proportion coefficient. The effective force signal proportion value is added to a preset effective force signal proportion constant, and the result of the reciprocal operation is used as the effective force signal proportion coefficient. The preset effective force signal proportion constant is a fixed value greater than 0, pre-set by the operator to avoid an effective force signal proportion value of zero. The coefficients are meaningless; the result of the weighted coupling operation of the force signal adjustment parameters and the force signal adjustment weight parameters is used as the evaluation value of the vertical and horizontal milling head parameter adjustment to reflect the degree of adaptation between the current parameters of the vertical and horizontal milling head and the machining state. The force signal adjustment weight parameters include the force signal interference index weight coefficient and the effective force signal proportion coefficient weight coefficient; the vertical and horizontal milling head parameter dynamic adjustment judgment is performed based on the evaluation value of the vertical and horizontal milling head parameter adjustment: if the evaluation value of the vertical and horizontal milling head parameter adjustment is greater than the preset horizontal milling head parameter adjustment threshold, then adaptive vertical and horizontal milling head parameter dynamic adjustment is performed; otherwise, the vertical and horizontal milling head machining process is continuously monitored.

[0040] It is important to note that the force signal interference index weighting coefficient and the effective force signal proportion coefficient weighting coefficient are used to reflect the degree of influence of the force signal adjustment parameters on the evaluation value of the vertical and horizontal milling head parameter adjustment. In this embodiment, there is a mapping group obtained from the database. This mapping group contains mapping sets, which are pre-set by professional technicians. For example, this mapping group is gradually constructed through statistical analysis and influence value verification of historical vertical and horizontal milling head parameter adjustment analysis data: First, extract the specific parameter combinations of the force signal interference index and the effective force signal proportion coefficient in a large number of actual machining scenarios, assign each parameter a quantitative value based on the weight of its influence on the parameter adjustment evaluation value, and simultaneously record the actual values ​​of the two types of weighting coefficients in the corresponding scenarios. Then, through correlation analysis (such as Kendall rank), the results are analyzed. (Correlation coefficient analysis, etc.) Removes abnormal correlation data caused by sudden changes in processing conditions or temporary equipment debugging, retains the statistically significant force signal adjustment parameter combinations and the correspondence between the two types of weight coefficients, and finally forms a mapping group containing multiple mapping sets. The mapping relationship adopts a one-to-one correspondence or many-to-one form to accurately reflect the degree of influence of different force signal parameters on the evaluation value of vertical and horizontal milling head parameter adjustment under different data scenarios. The mapping relationship uses the 0-1 value range to represent the weight parameter ratio. When the system receives the quantification result of the force signal adjustment parameters, it can quickly retrieve the corresponding two types of weight coefficients from the pre-built mapping group, and then accurately quantify the degree of influence of each force signal parameter on the evaluation value of vertical and horizontal milling head parameter adjustment.

[0041] In this embodiment, dynamic adjustment analysis of vertical and horizontal milling head parameters enables a comprehensive evaluation based on the stability and adaptability of force signals to determine the need for adaptive dynamic adjustment of vertical and horizontal milling head parameters. Combined with weighted parameters that differentiate between different force signal parameters, this helps to accurately identify the adaptation deviation between the current parameters of the vertical and horizontal milling head and the machining state, reducing unnecessary adjustments or lag in the vertical and horizontal milling head parameters. This improves the targeting and timeliness of adapting to dynamic adjustments of vertical and horizontal milling head parameters, ensuring that the vertical and horizontal milling head can flexibly adapt its parameters according to the actual machining force signal state, thereby optimizing the machining efficiency and quality of the vertical and horizontal milling head and ensuring the stability and reliability of the machining process.

[0042] Furthermore, the adaptive dynamic adjustment of vertical and horizontal milling head parameters includes adaptive cutting parameter adjustment and C-axis rotation mechanism torque and angle adjustment. The specific process of adaptive cutting parameter adjustment is as follows: The qualified force signal data and the vertical and horizontal milling head parameter adjustment evaluation value are input into a mapping table that establishes a mapping relationship between the combination of qualified force signal data and the vertical and horizontal milling head parameter adjustment evaluation value and the corresponding cutting parameter adjustment ratio. The cutting parameter adjustment ratio includes the cutting speed adjustment ratio and the cutting depth adjustment ratio. The cutting parameter adjustment ratio is a quantitative parameter determined by the mapping table based on the combination of qualified force signal data and the vertical and horizontal milling head parameter adjustment evaluation value. It is used to dynamically adjust the cutting speed and cutting depth to balance machining efficiency and quality. The mapping table, which establishes the mapping relationship between qualified force signal data and the vertical and horizontal milling head parameter adjustment evaluation value, is pre-set by designated personnel and stored in a database to reflect the qualified force... The mapping table is constructed by gradually building upon statistical analysis and parameter verification of historical vertical and horizontal milling head machining cutting parameter adjustment scenarios. First, specific combinations of qualified force signal data and vertical and horizontal milling head parameter adjustment evaluation values ​​from a large number of actual machining scenarios are extracted. Each parameter is assigned a weighted influence value based on its impact on cutting parameter adjustment. Simultaneously, the actual effective cutting parameter adjustment ratios in the corresponding scenarios are recorded. Then, through correlation analysis (such as Spearman rank correlation coefficient analysis), abnormal correlation data caused by temporary equipment failures or abnormal machining materials are eliminated. The statistically significant mapping table between the combination of qualified force signal data and vertical and horizontal milling head parameter adjustment evaluation values ​​and the cutting parameter adjustment ratios is retained, ultimately forming a directly queryable mapping table. The cutting parameter adjustment ratios include the cutting speed adjustment ratio and the cutting depth adjustment ratio.Adjusting cutting parameters: The cutting speed adjustment command is input from the vertical / horizontal milling head control center to the spindle drive system. The adjustment step size is the magnitude corresponding to the cutting speed adjustment ratio, gradually increasing the cutting speed. This helps reduce the increased impact load caused by sudden changes in cutting speed. When the force signal fluctuation amplitude is detected to be less than the preset impact smoothing threshold, the cutting depth adjustment command is input from the vertical / horizontal milling head control center to the feed drive system. The adjustment step size is the magnitude corresponding to the cutting depth adjustment ratio, gradually increasing the cutting depth. This helps prevent drastic fluctuations in the force signal caused by sudden changes in cutting depth. The vertical / horizontal milling head parameter adjustment evaluation value is continuously monitored. When the vertical / horizontal milling head parameter adjustment evaluation value is not greater than the preset horizontal milling head parameter adjustment threshold, the corresponding cutting parameters are marked as qualified cutting parameters and synchronously uploaded to the vertical / horizontal milling head control center; otherwise, the cutting parameters are sent. Adjusting the failure alarm: If the workpiece is being machined horizontally, the torque and angle of the C-axis rotary mechanism are adjusted. The maximum and minimum force signal intensity within a preset adjustment time period are monitored by a force sensor. The difference between these values ​​is used as the force signal fluctuation amplitude to reflect the intensity of the force signal impact during adaptive cutting parameter adjustment. The preset impact smoothing threshold is represented by the average force signal fluctuation amplitude over a historical time period. The preset adjustment time period indicates the time period for adaptive cutting parameter adjustment. The cutting speed does not exceed the preset maximum cutting speed threshold, and the cutting depth does not exceed the preset maximum cutting depth threshold. Cutting parameters include cutting speed and cutting depth. Qualified cutting parameters include qualified cutting speed and qualified cutting depth. The preset maximum cutting speed threshold and preset maximum cutting depth threshold are both preset by the operator.

[0043] In this embodiment, increasing the cutting speed first helps to shorten the contact time between the tool and hard points during workpiece machining, reduce instantaneous vibration and tool wear caused by hard point impact, and reduce the violent fluctuation of force signal caused by impact. This creates a relatively stable machining environment for subsequent depth of cut adjustment. Adjusting the depth of cut later helps to increase the cutting force when the impact is gentle by taking advantage of the stable force signal environment after the initial cutting speed adjustment. This reduces workpiece surface damage caused by forcibly deepening the cut when the impact is not stable, and reduces the risk of machining dimensional deviation. Through adaptive cutting parameter adjustment, it helps to achieve dynamic adaptation between cutting parameters and machining conditions, ensuring machining stability while taking into account cutting efficiency and surface quality, and improving the adaptability of vertical and horizontal milling heads to machining workpieces with complex materials.

[0044] Furthermore, the specific process for adjusting the torque and angle of the C-axis rotary mechanism is as follows: BB1, Obtain the C-axis torque deviation index, which reflects the degree of adaptation between the C-axis driving torque and the current cutting requirements; Quantify the deviation between the C-axis rotary mechanism torque value within the preset adjustment period and the preset C-axis rotary mechanism torque value as the C-axis torque deviation index, which reflects the degree of deviation between the actual output torque of the C-axis rotary mechanism and the preset C-axis rotary mechanism torque, as well as the torque adaptability. The preset C-axis rotary mechanism torque value is represented by the average value of the C-axis rotary mechanism torque values ​​over historical periods; BB2, Adjust the C-axis rotary mechanism torque: Input the qualified cutting parameters, qualified force signal data, and C-axis torque deviation index into the C-axis driving torque database. The torque adjustment value is obtained by querying the adjustment coefficient mapping set. This torque adjustment value is a quantitative parameter determined by the mapping set, based on a combination of qualified cutting parameters, qualified force signal data, and the C-axis torque deviation index. It is used to dynamically adjust the C-axis drive torque to balance the adaptability of the C-axis torque output to cutting requirements. The C-axis drive torque adjustment coefficient mapping set is pre-set by designated personnel and stored in a database. It reflects the correspondence between the combination of qualified cutting parameters, qualified force signal data, and the C-axis torque deviation index and the torque adjustment value. For example, it is gradually constructed through statistical analysis and parameter verification of historical C-axis torque adjustment scenarios: first, specific combinations of three types of parameters from a large number of actual machining scenarios are extracted, and each parameter is assigned a parameter based on the... The weighted impact value of torque adjustment is recorded synchronously, along with the actual effective torque adjustment value in the corresponding scenario. Correlation analysis (such as Spearman rank correlation coefficient analysis) is then used to eliminate abnormal data caused by equipment failure or sudden changes in operating conditions. The relationship between statistically significant combinations of qualified cutting parameters, qualified force signal data, and C-axis torque deviation index and torque adjustment values ​​is retained, ultimately forming a directly queryable mapping set. Based on the torque adjustment step size corresponding to the torque adjustment value, the C-axis drive torque is gradually increased. This helps reduce rigid impact or overload caused by sudden increases in C-axis torque, ensuring that the C-axis accurately matches cutting requirements while maintaining stable torque output. This reduces rotational jamming or positioning lag caused by insufficient torque, ensuring continuous... Monitor the C-axis torque deviation index. When the C-axis torque deviation index is less than the preset torque deviation threshold, adjust the C-axis rotation angle; otherwise, continue adjusting the C-axis rotary mechanism torque. If the number of C-axis rotary mechanism torque adjustments exceeds the preset maximum number of torque adjustments, and the C-axis torque deviation index is still not less than the preset torque deviation threshold, send an invalid C-axis rotary mechanism torque adjustment prompt. The preset maximum number of torque adjustments is set in advance by a preset operator, and the C-axis drive torque does not exceed the preset maximum C-axis drive torque. BB3. After the C-axis rotary mechanism torque adjustment is completed, the specific process for adjusting the C-axis rotation angle is as follows: BB4. Obtain the C-axis rotation angle deviation index, which reflects the accuracy of the C-axis rotation angle.The deviation quantification result between the C-axis rotation angle value within the preset adjustment time period and the preset C-axis rotation angle value is used as the C-axis rotation angle deviation index to reflect the degree of deviation between the C-axis rotation angle and the preset C-axis rotation angle and the positioning accuracy. The preset C-axis rotation angle value is represented by the average value of the C-axis rotation angle values ​​over a historical time period. BB5, C-axis rotation angle adjustment: Qualified cutting parameters, qualified force signal data, C-axis rotation angle deviation index, and force signal fluctuation period are input into the C-axis rotation angle adjustment coefficient mapping set in the database for querying to obtain the C-axis rotation angle correction value. The C-axis rotation angle correction value is a quantized parameter determined by the combination of qualified cutting parameters, qualified force signal data, C-axis rotation angle deviation index, and force signal fluctuation period through the mapping set. It is used to dynamically correct the C-axis rotation angle to improve angle positioning accuracy. The C-axis rotation angle adjustment coefficient mapping set is preset by the personnel and stored in the database to reflect the correspondence between the above parameter combinations and the angle correction value. For example, it is gradually constructed through statistical analysis and parameter verification of historical C-axis angle adjustment scenarios: First, extract the specific combinations of four types of parameters from a large number of actual machining scenarios, and assign each parameter based on its influence on angle adjustment. The weighted influence value of the degree is recorded synchronously, and the actual effective angle correction value in the corresponding scenario is recorded. Then, through correlation analysis (such as Kendall rank correlation coefficient analysis), abnormal data caused by sensor error and mechanical backlash are eliminated, and the correspondence between statistically significant parameter combinations and angle correction values ​​is retained, finally forming a mapping set that can be directly queried. Based on the angle adjustment step size corresponding to the C-axis rotation angle correction value, the rotation angle is adjusted step by step, which helps to accurately compensate for angle deviation on the basis of stable torque, reduce positioning overshoot or milling head vibration caused by sudden angle adjustment, and improve the accuracy of machining position. Continuous monitoring of C The C-axis rotation angle deviation index is used. When the C-axis rotation angle deviation index is less than the preset C-axis rotation angle threshold, dynamic torque feedback compensation is performed; otherwise, C-axis rotation angle adjustment continues. If the number of C-axis rotation angle adjustments exceeds the preset maximum number of angle adjustments, and the C-axis rotation angle deviation index is still not less than the preset C-axis rotation angle threshold, an invalid angle adjustment prompt is sent. The preset maximum number of angle adjustments is set in advance by a designated person. After the C-axis rotation mechanism torque and angle adjustments are completed, dynamic torque feedback compensation is performed based on the newly acquired C-axis torque deviation and C-axis rotation angle deviation.

[0045] In this embodiment, the torque adjustment of the C-axis rotation mechanism is first used to ensure that the C-axis has a driving force that matches the cutting load, providing a stable power foundation for the C-axis rotation angle adjustment. This avoids jamming or positioning failure during angle adjustment due to insufficient torque. Then, the C-axis rotation angle adjustment is used to accurately correct the position deviation under the support of stable torque, improving the rotation positioning accuracy. This helps to reduce machining errors caused by insufficient coordination between the torque and angle of the C-axis rotation mechanism, improves the operational stability and positioning accuracy of the C-axis rotation mechanism, and ensures the workpiece posture accuracy and cutting consistency during horizontal machining.

[0046] Furthermore, the specific process of torque feedback dynamic compensation is as follows: Torque feedback parameters are obtained to reflect the dynamic coordination and stability of the C-axis rotary mechanism after torque and angle adjustment. These parameters include the verification value of the C-axis torque deviation change rate and the verification value of the C-axis rotation angle deviation change rate. The verification value of the C-axis torque deviation change rate is represented by the quantified result of the ratio of the C-axis torque deviation change rate to a preset torque deviation change rate threshold, weighted by a torque deviation change rate weighting coefficient. The change in C-axis torque deviation within a preset compensation period monitored by the C-axis torque sensor is used as the C-axis torque deviation change rate. The preset compensation period represents the time period for torque feedback dynamic compensation. The preset torque deviation change rate threshold is represented by the average value of the C-axis torque deviation change rate over historical time periods. The verification value of the C-axis rotation angle deviation change rate is represented by the quantified result of the ratio of the C-axis rotation angle deviation change rate to a preset angle deviation change rate threshold, weighted by a weighting coefficient. The verification value of the C-axis rotation angle deviation change rate is represented by the preset compensation period monitored by the C-axis angle encoder. The change in C-axis rotation angle deviation within a time period is taken as the C-axis rotation angle deviation change rate. The preset angle deviation change rate threshold is represented by the average value of the C-axis rotation angle deviation change rate over historical time periods. The result of harmonic averaging of the torque feedback parameters is used as the torque feedback compensation evaluation index to reflect the coordinated stability and compensation effectiveness of the dynamic compensation process of torque and angle of the C-axis rotary mechanism. When the C-axis torque deviation change rate increases, the dynamic stability of the C-axis torque decreases, causing some angle deviations that were originally in the stable range to be triggered to fluctuate, which in turn increases the C-axis rotation angle deviation change rate. When the C-axis rotation angle deviation change rate increases, the frequent angle fluctuations will have a counter-effect on the C-axis torque output, causing the C-axis torque deviation change rate to increase further. The two together increase the torque feedback compensation evaluation index. The C-axis torque deviation index and the C-axis rotation angle deviation index are input into a mapping table that establishes a correspondence between the combination of C-axis torque deviation index and C-axis rotation angle deviation index and the torque compensation coefficient for querying to obtain the torque compensation coefficient.The torque compensation coefficient is a quantitative parameter determined by a mapping table based on the combination of the C-axis torque deviation index and the C-axis rotation angle deviation index. It is used to dynamically adjust the torque compensation amplitude to balance the synergistic requirements of torque stability and angular accuracy. The mapping table, which shows the correspondence between the combination of the C-axis torque deviation index and the C-axis rotation angle deviation index and the torque compensation coefficient, is pre-set by designated personnel and stored in a database. This table reflects the correspondence between the two types of deviation index combinations and the torque compensation coefficient. For example, it is gradually constructed through statistical analysis and parameter verification of historical C-axis dynamic compensation scenarios: first, extracting a large number of specific combination parameters of the two types of deviation indices from actual machining, assigning weight values ​​based on the degree of influence on the compensation effect, and simultaneously recording the effective torque compensation coefficients in the corresponding scenarios; then, through correlation analysis (such as Spearman rank correlation coefficient analysis)... (etc.) Abnormal data caused by mechanical vibration and sensor drift are removed, and statistically significant combinations are retained to form a directly queryable mapping table. Dynamic torque compensation is performed based on the torque feedback compensation evaluation index: Based on the compensation amplitude corresponding to the torque compensation coefficient, the torque compensation amount is gradually increased on the basis of the current C-axis driving torque. This helps to correct the dynamic deviation between the C-axis driving torque and the C-axis angle in real time, enhances the timeliness of their coordinated response, avoids the cumulative error caused by compensation lag, and ensures the dynamic stability of C-axis operation. The torque feedback compensation evaluation index is continuously monitored. When the torque feedback compensation evaluation index is less than the preset compensation evaluation threshold, the current C-axis driving torque and C-axis rotation angle are marked as qualified C-axis operating parameters and uploaded to the vertical and horizontal milling head control center for continuous monitoring. Otherwise, a C-axis adjustment failure alarm is sent.

[0047] like Figure 5The diagram shows a milling head structure of the vertical and horizontal milling head control method device based on adaptive parameters and force feedback compensation provided in an embodiment of the present invention. It includes: a C-axis rotation mechanism, a right-angle transmission box, a dual-output spindle, sensors, encoders, and a controller. The core power component of the C-axis rotation mechanism is a C-axis motor 1, and it also includes a main input shaft 2, a C-axis bearing 3, and a brake 4. It integrates a servo drive unit to drive the entire milling head to rotate around the vertical axis and has an angle locking function. The transmission gear 9 includes a first bevel gear mounted on the vertical spindle, a second bevel gear meshing with the first bevel gear, the second bevel gear driving a first spur gear coaxial with it to rotate, and the first spur gear driving a... The rotation of the second spur gear on the horizontal spindle enables power transmission between the vertical and horizontal spindles; the right-angle transmission box contains a bevel gear set, which can transmit power to the vertical spindle 5 and the horizontal spindle 6 respectively; the dual-output spindle includes the vertical spindle 5 and the horizontal spindle 6, whose axes are spatially perpendicular, and is used to machine the bottom and sides of guide rails or box-type parts; sensors are used to detect cutting reaction forces and rotational speeds; encoders, including a C-axis encoder 7 and a spindle encoder 8, are used to acquire the position and speed signals of the vertical and horizontal dual-output milling heads in real time; the controller is used to receive sensor signals and encoder feedback signals, and to precisely control the vertical and horizontal milling heads based on the analysis results.

[0048] like Figure 6 The figure shows a schematic diagram of the operating system of the vertical and horizontal milling head control method device based on adaptive parameters and force feedback compensation provided in an embodiment of the present invention. As can be seen from the figure, this process is the console interface for horizontal spindle operation. The view switching function can also be used to switch to the vertical spindle operation process, as well as the vertical and horizontal spindle selection and working time, etc.

[0049] In summary, by performing force signal interference analysis and determining whether to adjust the force sensor signal amplification factor based on the analysis results, it helps to specifically address the distortion problem caused by high-frequency fluctuations in the force signal and the mismatch between the sampling frequency and the sampling frequency during the cutting process, ensuring the accuracy of force signal acquisition. After the force signal interference analysis is qualified, the validity of the force signal is identified and judged. Based on the validity identification result, it is determined whether to perform dynamic adjustment analysis of the vertical and horizontal milling head parameters. This helps to reduce misjudgments when identifying based on distorted force signals and provides valid force signals for dynamic adjustment analysis of vertical and horizontal milling head parameters. If dynamic adjustment analysis of vertical and horizontal milling head parameters is not performed, an alarm for inaccurate force signal identification is sent. Conversely, based on the dynamic adjustment analysis results, it is determined whether to perform adaptive dynamic adjustment of vertical and horizontal milling head parameters. This helps to solve the problem of adaptive cutting parameter adjustment deviation caused by distorted or misjudged force signals, reduce quality defects such as machining dimensional accuracy deviations, and improve the accuracy of machining quality data feedback and cutting status assessment.

[0050] The vertical and horizontal milling head control method and device based on adaptive parameters and force feedback compensation provided by this invention can also achieve the following functions: by integrating the optimized design of the right-angle transmission box bevel gear set, the closed-loop control and automatic balancing of the C-axis rotation mechanism, the temperature compensation of the dual-output spindle, the preload and vibration reduction design of the X-axis feed mechanism, and systems such as coolant injection, chip removal and cutting force monitoring, it can achieve the synergistic effects of improved transmission efficiency, reduced noise, precise angle control, thermal deformation suppression, stable feed, load balance, effective temperature and chip control and dynamic cutting force compensation during the machining process, thus comprehensively ensuring the milling head machining accuracy, stability and efficiency.

Claims

1. A control method for vertical and horizontal milling heads based on adaptive parameters and force feedback compensation, characterized in that, The method includes: During the machining of vertical and horizontal milling heads, force signal interference analysis is performed, and based on the results of the force signal interference analysis, it is determined whether to adjust the force sensor signal amplification factor. The force sensor signal amplification factor adjustment is used to reduce excessive distortion of the first impact signal and improve the identification of the second impact signal, so as to ensure the accuracy of force signal acquisition. After the force signal interference analysis is qualified, the validity of the force signal is identified and judged. Based on the result of the validity identification and judgment of the force signal, it is decided whether to perform dynamic adjustment analysis of the vertical and horizontal milling head parameters. If dynamic adjustment analysis of vertical and horizontal milling head parameters is not performed, an alarm will be triggered for inaccurate force signal identification. Conversely, if the analysis is performed, it will be determined whether to perform adaptive dynamic adjustment of vertical and horizontal milling head parameters based on the results of the dynamic adjustment analysis. The adaptive dynamic adjustment of vertical and horizontal milling head parameters includes adaptive cutting parameter adjustment and C-axis rotation mechanism torque and angle adjustment. The adaptive cutting parameter adjustment is used to optimize cutting efficiency and machining quality, and the C-axis rotation mechanism torque and angle adjustment is used to ensure C-axis rotation accuracy and stability. The specific process of force signal interference analysis is as follows: Acquire force signal data to reflect force signal interference during the machining process of vertical and horizontal milling heads. The force signal data includes force signal fluctuation amplitude verification value and force signal mutation frequency verification value. The force signal fluctuation amplitude verification value is represented by the result after weighting the force signal fluctuation amplitude and the preset force signal fluctuation amplitude within a preset force signal interference analysis period, and then weighting them with the force signal fluctuation amplitude weighting coefficient. The force signal mutation frequency verification value is represented by the result after weighting the force signal mutation frequency and the preset force signal mutation frequency within a preset force signal interference analysis time period and the force signal mutation frequency weighting coefficient. The force signal data is harmonic averaged to obtain a force signal interference index, which reflects the overall degree of interference to the force signal within a preset force signal acquisition time period. When the force signal interference index is greater than the preset force signal interference threshold, the interference marking mechanism is activated; otherwise, the validity of the force signal is identified and judged. The specific process of the interference marking mechanism is as follows: When the force signal interference index is detected to be greater than the preset force signal interference threshold within the preset force signal acquisition time period, the value of the interference mark counter is incremented by 1, and the interference mark counter value within the preset force signal mark time period is continuously monitored and accumulated. When the value of the interference mark counter exceeds the preset interference mark count threshold within the preset force signal mark time period, the force sensor signal amplification factor adjustment is triggered; otherwise, an interference mark counter reset prompt is sent. The specific process for identifying and judging the validity of the force signal is as follows: Obtain force signal characteristic data items that reflect the integrity and stability of the force signal characteristics after the force sensor signal amplification factor is adjusted, including the force signal baseline drift ratio, the force signal harmonic distortion rate ratio, and the non-conforming force signal interference index ratio. The force signal baseline drift ratio is represented by the result of proportional quantization between the force signal baseline drift and a preset force signal baseline drift. The ratio of the harmonic distortion rate of the force signal is represented by the result of quantifying the ratio of the harmonic distortion rate of the force signal to the harmonic distortion rate of the standard force signal. The percentage of the interference index of the unqualified force signal is represented by the result of quantifying the percentage of the interference index of the unqualified force signal with the preset percentage of the interference index of the unqualified force signal. The result of weighted coupling operation between force signal feature data items and force signal feature weight parameters is used as the force signal feature matching result to reflect the overall degree of fit between the force signal features and the standard force signal features. If the force signal feature matching result is less than the preset force signal deviation threshold, the corresponding force signal data is marked as a valid instantaneous impact load signal; otherwise, the corresponding force signal data is marked as an interfering instantaneous impact load signal. If the effective force signal ratio is less than the preset effective force signal ratio threshold, an alarm for inaccurate force signal recognition is sent; otherwise, the force signal recognition is deemed valid, and the corresponding force signal data is marked as qualified force signal data and uploaded synchronously to the vertical and horizontal milling head control center for dynamic adjustment and analysis of vertical and horizontal milling head parameters. The effective force signal ratio is represented by the ratio of the effective instantaneous impact load signal data to the total instantaneous impact load signal data within a preset identification time period.

2. The control method of a vertical / horizontal milling head based on adaptive parameter and force feedback compensation according to claim 1, characterized in that, The specific process for adjusting the amplification factor of the force sensor signal is as follows: When the amplitude of the force signal fluctuation is greater than the preset first signal threshold, the corresponding force signal is determined to be the first impact signal. When the amplitude of the force signal fluctuation is less than the preset second signal threshold, the corresponding force signal is determined to be the second impact signal. When the amplitude of the force signal fluctuation is neither greater than the preset first signal threshold nor less than the preset second signal threshold, the corresponding force signal is determined to be the third impact signal. The force signal interference index and the force sensor load rate are input into the force signal amplification factor adjustment coefficient mapping set to obtain the force signal amplification factor adjustment coefficient; When the first impact signal is detected, the amplification factor is gradually reduced using the adjustment step size corresponding to the force signal amplification factor adjustment coefficient. When the second impact signal is detected, the amplification factor is gradually increased using the adjustment step size corresponding to the force signal amplification factor adjustment coefficient. When the third impact signal is detected, the current amplification factor remains unchanged. During the adjustment of the force sensor signal amplification factor, the force signal interference index is continuously monitored. When the force signal interference index is less than the preset force signal interference threshold, the effect of the force sensor signal amplification factor adjustment is verified. Otherwise, the force sensor signal amplification factor adjustment continues. If the number of force sensor signal amplification factor adjustments exceeds the preset maximum number of adjustments, and the force signal interference index is still not less than the preset force signal interference threshold, an invalid force signal amplification factor adjustment prompt is sent. After the force sensor signal amplification factor adjustment is completed, the effect of the force sensor signal amplification factor adjustment is verified.

3. The vertical and horizontal milling head control method based on adaptive parameters and force feedback compensation according to claim 2, characterized in that, The specific process for verifying the effect of adjusting the amplification factor of the force sensor signal is as follows: Acquire signal amplification verification data items used to reflect the effect of force sensor signal amplification factor adjustment, including the signal-to-noise ratio of the second impact signal and the distortion rate of the first impact signal; The result of weighted coupling operation of the signal amplification verification data item and the corresponding signal amplification verification data item weight parameter is used as the signal amplification adjustment quality value to reflect the overall effect of the force sensor signal amplification factor adjustment. The signal amplification verification data item weight parameter includes the second impact signal-to-noise ratio weight coefficient and the first impact signal distortion rate weight coefficient. Based on the judgment of signal amplification adjustment quality value: when the signal amplification adjustment quality value is greater than the preset amplification quality threshold, an amplification factor adjustment failure alarm is sent; otherwise, the force signal after the force sensor signal amplification factor adjustment is adjusted is processed for multimodal interference suppression based on the adaptive wavelet threshold denoising algorithm, and then the validity of the force signal is identified and judged.

4. The vertical and horizontal milling head control method based on adaptive parameters and force feedback compensation according to claim 1, characterized in that, The specific process of dynamic adjustment and analysis of vertical and horizontal milling head parameters is as follows: Obtain force signal adjustment parameters that reflect the stability of the force signal after the force sensor signal amplification factor is adjusted and its adaptability to processing requirements, including the force signal interference index and the effective force signal ratio coefficient; The result of weighted coupling operation of force signal adjustment parameters and force signal adjustment weight parameters is used as the evaluation value of vertical and horizontal milling head parameter adjustment to reflect the degree of fit between the current parameters of the vertical and horizontal milling head and the machining state. If the evaluation value of the vertical and horizontal milling head parameter adjustment is greater than the preset horizontal milling head parameter adjustment threshold, then adaptive dynamic adjustment of the vertical and horizontal milling head parameters will be performed; otherwise, continuous monitoring of the vertical and horizontal milling head machining process will be performed.

5. The vertical and horizontal milling head control method based on adaptive parameters and force feedback compensation according to claim 1, characterized in that, The adaptive dynamic adjustment of vertical and horizontal milling head parameters includes adaptive cutting parameter adjustment and C-axis rotation mechanism torque and angle adjustment; The specific process of adjusting the adaptive cutting parameters is as follows: The qualified force signal data and the evaluation value of the vertical and horizontal milling head parameter adjustment are input into a mapping table that establishes a mapping relationship between the combination of qualified force signal data and the evaluation value of the vertical and horizontal milling head parameter adjustment and the corresponding cutting parameter adjustment ratio, and the cutting parameter adjustment ratio is obtained. The cutting parameter adjustment ratio includes the cutting speed adjustment ratio and the cutting depth adjustment ratio. The cutting speed adjustment command is input from the vertical and horizontal milling head control center to the spindle drive system, and the cutting speed is gradually increased by stepping the adjustment step size corresponding to the cutting speed adjustment ratio. When the force signal fluctuation amplitude is detected to be less than the preset impact smoothing threshold, the cutting depth adjustment command is input from the vertical and horizontal milling head control center to the feed drive system. The cutting depth is gradually increased step by step with the amplitude corresponding to the cutting depth adjustment ratio as the adjustment step size. The vertical and horizontal milling head parameter adjustment evaluation value is continuously monitored. When the vertical and horizontal milling head parameter adjustment evaluation value is not greater than the preset horizontal milling head parameter adjustment threshold, the corresponding cutting parameter is marked as qualified cutting parameter and uploaded to the vertical and horizontal milling head control center. Otherwise, a cutting parameter adjustment failure alarm is sent. If the workpiece is being machined horizontally, the torque and angle of the C-axis rotary mechanism are adjusted. The cutting parameters include cutting speed and depth of cut, and the qualified cutting parameters include qualified cutting speed and qualified depth of cut.

6. The vertical and horizontal milling head control method based on adaptive parameters and force feedback compensation according to claim 5, characterized in that, The specific process for adjusting the torque and angle of the C-axis rotary mechanism is as follows: Obtain the C-axis torque deviation index, which reflects the degree of fit between the C-axis drive torque and the current cutting requirements; The result of quantifying the deviation between the C-axis rotary mechanism torque value and the preset C-axis rotary mechanism torque value within the preset adjustment time period is used as the C-axis torque deviation index to reflect the degree of deviation between the actual output torque of the C-axis rotary mechanism and the preset C-axis rotary mechanism torque, as well as the torque adaptability. Input the qualified cutting parameters, qualified force signal data and C-axis torque deviation index into the C-axis drive torque adjustment coefficient mapping set for querying to obtain the torque adjustment value; Based on the torque adjustment step size corresponding to the torque adjustment value, the C-axis driving torque is gradually increased, and the C-axis torque deviation index is continuously monitored. When the C-axis torque deviation index is less than the preset torque deviation threshold, the C-axis rotation angle is adjusted; otherwise, the C-axis rotary mechanism torque adjustment continues. If the number of C-axis rotary mechanism torque adjustments is greater than the preset maximum number of torque adjustments, and the C-axis torque deviation index is still not less than the preset torque deviation threshold, an invalid C-axis rotary mechanism torque adjustment prompt is sent. After the torque adjustment of the C-axis rotary mechanism is completed, the specific process for adjusting the C-axis rotation angle is as follows: The result of quantifying the deviation between the C-axis rotation angle value within the preset adjustment time period and the preset C-axis rotation angle value is used as the C-axis rotation angle deviation index to reflect the degree of deviation between the C-axis rotation angle and the preset C-axis rotation angle and the positioning accuracy. Input the qualified cutting parameters, qualified force signal data, C-axis rotation angle deviation index and force signal fluctuation period into the C-axis rotation angle adjustment coefficient mapping set for querying, and obtain the C-axis rotation angle correction value; Based on the angle adjustment step size corresponding to the C-axis rotation angle correction value, the rotation angle is adjusted step by step, and the C-axis rotation angle deviation index is continuously monitored. When the C-axis rotation angle deviation index is less than the preset C-axis rotation angle threshold, torque feedback dynamic compensation is performed; otherwise, the C-axis rotation angle adjustment continues. If the number of C-axis rotation angle adjustments is greater than the preset maximum number of angle adjustments, and the C-axis rotation angle deviation index is still not less than the preset C-axis rotation angle threshold, an invalid angle adjustment prompt is sent. After the torque and angle of the C-axis rotary mechanism are adjusted, dynamic torque feedback compensation is performed based on the newly acquired C-axis torque deviation and C-axis rotation angle deviation.

7. The control method of a vertical / horizontal milling head based on adaptive parameter and force feedback compensation according to claim 6, characterized in that, The specific process of the torque feedback dynamic compensation is as follows: To obtain torque feedback parameters that reflect the dynamic coordination and stability of the C-axis rotary mechanism after torque and angle adjustment, the torque feedback parameters include the verification value of the C-axis torque deviation change rate and the verification value of the C-axis rotation angle deviation change rate; The verification value of the C-axis torque deviation change rate is represented by the quantified result of the ratio of the C-axis torque deviation change rate to the preset torque deviation change rate threshold, and the result after weighting the torque deviation change rate weighting coefficient. The verification value of the C-axis rotation angle deviation change rate is represented by the quantified result of the ratio of the C-axis rotation angle deviation change rate to the preset angle deviation change rate threshold, and the result after weighting the angle deviation change rate weighting coefficient. The result of harmonic averaging of the torque feedback parameters is used as a torque feedback compensation evaluation index to reflect the coordinated stability and compensation effectiveness of the torque and angle dynamic compensation process of the C-axis rotary mechanism. Input the C-axis torque deviation index and the C-axis rotation angle deviation index into a mapping table that establishes a correspondence between the combination of the C-axis torque deviation index and the C-axis rotation angle deviation index and the torque compensation coefficient, and then query the table to obtain the torque compensation coefficient. Based on the compensation range corresponding to the torque compensation coefficient, the torque compensation amount is gradually increased on the basis of the current C-axis driving torque. The torque feedback compensation evaluation index is continuously monitored. When the torque feedback compensation evaluation index is less than the preset compensation evaluation threshold, the current C-axis driving torque and C-axis rotation angle are marked as qualified C-axis operating parameters and uploaded to the vertical and horizontal milling head control center for continuous monitoring. Otherwise, a C-axis adjustment failure alarm is sent.

8. A vertical and horizontal milling head control device based on adaptive parameters and force feedback compensation, employing the vertical and horizontal milling head control method based on adaptive parameters and force feedback compensation as described in any one of claims 1-7, characterized in that, include: C-axis rotary mechanism, right-angle transmission box, dual-output spindle, sensor, encoder and controller: The core power component of the C-axis rotary mechanism is the C-axis motor (1), and it also includes a main input shaft (2), a C-axis bearing (3) and a brake (4). It integrates a servo drive unit to drive the entire milling head to rotate around the vertical axis and has an angle locking function. The right-angle transmission box has a built-in bevel gear set, which can transmit power to the vertical spindle (5) and the horizontal spindle (6) respectively. The dual-output spindle includes a vertical spindle (5) and a horizontal spindle (6). The vertical spindle (5) and the horizontal spindle (6) are perpendicular in space and are used to process the bottom and sides of guide rails or box-type parts. The sensor is used to detect cutting reaction force and rotational speed; The encoders include a C-axis encoder (7) and a spindle encoder (8), which are used to acquire the position and speed signals of the vertical and horizontal dual-output milling head in real time; The controller is used to receive feedback signals from sensors and encoders, and to precisely control the vertical and horizontal milling heads based on the analysis results.

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