A method for optimizing servo feed parameters of a milling and turning machine tool

Abstract

This application relates to the field of CNC machine tool control technology, specifically to a method for optimizing servo feed parameters of a milling-turning machine tool. The method includes: collecting the rotational speed data of the servo motor of the milling-turning machine tool; analyzing the overall distribution of the difference between each rotational speed data point and the target rotational speed; determining the overall rotational speed deviation value for each measurement interval; performing detrending processing on the rotational speed data to determine the rotational speed fluctuation characteristic value and rotational speed characteristic value for each measurement interval; obtaining the step response curve and reference interval for each measurement interval through the transfer function of the servo motor; and determining the rotational speed control adaptation value and final rotational speed adaptation value for each measurement interval based on the difference between the corresponding rotational speed data in each measurement interval and its reference interval, combined with the shape characteristics of the step response curve, thereby optimizing various control parameters of the servo motor. This application aims to enhance the adaptability of the feed rate adjustment under different degrees of cutting chatter on a milling-turning machine tool.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of numerical control machine tool control, in particular to a servo feed parameter optimization method of a turning-milling combined machine tool. BACKGROUND

[0002] With the transformation and upgrading of manufacturing industry to high-end and intelligent direction, turning-milling combined machining technology is widely used in aerospace, automobile, precision mold and other fields due to its advantages of high efficiency, high precision and multi-process integration. The turning-milling combined machine tool is a numerical control machine tool integrating turning, milling, drilling and tapping functions, which can complete multi-surface machining of complex parts in one clamping, improving efficiency and machining precision.

[0003] Compared with single-function machine tools, when the turning-milling combined machine tool works, the workpiece will bear cutting forces in different directions, and the fixture needs to consider the load requirements of turning and milling functions, thereby causing the decrease of fixing rigidity, especially during side milling, which easily excites the natural frequency of the system, thereby causing resonance. The turning-milling combined machine tool analyzes the vibration response at different positions during machining, and selects the optimal feed amount at the corresponding position, which effectively avoids chatter during milling.

[0004] At present, the servo feed system controls the input voltage of the servo motor through the PID algorithm to realize the stable speed of the tool. The change of the feed amount causes the change of the cutting resistance of the tool, which has a great influence on the cutting speed. The servo feed system with fixed parameters has a slow response speed to the resistance change caused by the change of the feed amount, and the stability of the tool speed is poor, thereby affecting the smoothness of the workpiece surface and causing the decline of the machining quality. SUMMARY

[0005] In view of the above, it is necessary to provide a servo feed parameter optimization method of a turning-milling combined machine tool to solve the above problems.

[0006] The first aspect of the present application provides a servo feed parameter optimization method of a turning-milling combined machine tool, which comprises:

[0007] Collecting the speed data of the servo motor of the turning-milling combined machine tool, and presetting the measurement interval;

[0008] Analyzing the overall distribution of the difference between each speed data and the target speed to determine the overall deviation value of the speed of each measurement interval; based on the change of the data in the detrended sequence after eliminating the inherent change of the speed data in each measurement interval, the speed fluctuation characteristic value of each measurement interval is determined; the speed characteristic value of each measurement interval is determined by comprehensively considering the speed overall deviation value and the speed fluctuation characteristic value;

[0009] Obtaining the step response curve of each measurement interval and the reference interval through the transfer function of the servo motor; determining the speed control adaptive value of each measurement interval according to the difference between each measurement interval and the corresponding speed data in the reference interval, and combining the shape characteristics of the step response curve; analyzing the change of the overall deviation value of the speed between each measurement interval and the reference interval, and the change characteristics of the speed characteristic value, and determining the final speed adaptive value of each measurement interval in combination with the speed control adaptive value;

[0010] Optimizing various control parameters of the servo motor PID algorithm based on the final speed adaptive value.

[0011] The overall deviation value of the speed of each measurement interval is specifically the mean value of the absolute values of all speed deviations obtained in each measurement interval; and the speed deviation is specifically the difference between the target speed and each speed data.

[0012] The speed fluctuation characteristic value of each measurement interval is specifically:

[0013] Calculating the change trend of each point after curve fitting of the detrended sequence obtained in each measurement interval to determine the overall fluctuation deviation of the speed data in each measurement region.

[0014] Calculating the absolute value of the difference between each speed data and the corresponding point in the detrended sequence, and taking the sum of the absolute values of the differences of all speed data obtained in each measurement interval as the fluctuation change amount of the speed data in each measurement interval.

[0015] The overall fluctuation deviation and the fluctuation change amount are positively fused to obtain the speed fluctuation characteristic value of each measurement interval.

[0016] The overall fluctuation deviation of the speed data in each measurement region is specifically the mean value of the slope values of all points in the detrended sequence.

[0017] The speed characteristic value of each measurement interval is specifically the product of the overall deviation value of the speed and the speed fluctuation characteristic value of each measurement interval.

[0018] The step response curve of each measurement interval and the reference interval is specifically obtained based on the transfer function of the servo motor, and the step response curve is obtained at the end of each measurement interval according to the parameters of the servo motor PID algorithm; the step response curve is sampled to obtain the reference interval of each measurement interval.

[0019] The speed control adaptive value of each measurement interval is specifically:

[0020] The vector composed of the PID control parameters of each measurement interval is taken as the parameter vector.

[0021] The time for the step response curve to enter the steady state value within the system specified error range is recorded as the adjustment time, and the time for the step response curve to rise from the initial value to the steady state value is recorded as the rise time; the sum of the rise time and the adjustment time is taken as the adaptation length of the adaptive parameter vector of each measurement interval;

[0022] The cumulative sum of the absolute value of the difference between the rotational speed data at the same sampling time in each measurement interval and the reference interval is calculated as the first difference;

[0023] The ratio of the adaptation length of the adaptive parameter vector of each measurement interval to the cumulative sum of the adaptation lengths of all measurement interval adaptive parameter vectors is taken as the time weight, and the product of the first difference and the time weight is taken as the rotational speed control adaptation value of each measurement interval.

[0024] The specific process of determining the final adaptation value of the rotational speed of each measurement interval is as follows:

[0025] The difference between the rotational speed overall deviation value of each reference interval and its corresponding measurement interval is recorded as the second difference;

[0026] The absolute value of the difference between the rotational speed characteristic value of each reference interval and its corresponding measurement interval is recorded as the third difference;

[0027] The second difference, the third difference, and the rotational speed control adaptation value are forward fused to obtain the final adaptation value of the rotational speed of each measurement interval.

[0028] The process of optimizing various control parameters of the servo motor PID algorithm is as follows:

[0029] The final adaptation value of the rotational speed is taken as the fitness function value of the corresponding measurement interval parameter vector, and an optimization algorithm is used to minimize the fitness function value to obtain the optimal parameter vector.

[0030] The present application has at least the following beneficial effects:

[0031] The application collects the servo motor speed data of the turning-milling combined machine tool, and presets a measurement interval. Through collecting the actual speed data, the real-time state of the servo motor can be reflected, ensuring that the analysis is based on real data. After dividing the data into measurement intervals, the performance of each interval can be analyzed independently, which is convenient for finding the behavior rules of the system at different time periods. By analyzing the difference between each speed data and the target speed, the speed deviation is obtained, which can identify the control error and performance problem of the servo motor; based on the overall distribution of the speed deviation in each measurement interval, the overall speed deviation value of each measurement interval is determined, which provides a quantitative scale for subsequent analysis, helping to judge whether the system has persistent error or instability; based on the change of the data in the detrended sequence after eliminating the inherent changes of the speed data in each measurement interval, the speed fluctuation characteristic value of each measurement interval is determined, which can reveal the long-term stability of the servo motor and the performance fluctuation of the system, providing a reference for analyzing the stability, accuracy and response speed of the servo motor; by integrating the speed overall deviation value and the speed fluctuation characteristic value, the speed characteristic value of each measurement interval is determined, which can more comprehensively reflect the overall effect of the motor speed control by integrating the two characteristics, and identify potential performance problems or abnormalities; by obtaining the step response curve of each measurement interval and the reference interval through the transfer function of the servo motor, the response speed and stability of the servo motor to the input signal can be reflected, which is helpful for judging the dynamic performance of the motor system, and obtaining the reference interval is helpful for comparing the response characteristics of the motor under different working conditions; according to the difference between the corresponding speed data in each measurement interval and its reference interval, combined with the shape characteristics of the step response curve, the speed control adaptation value of each measurement interval is determined, through the shape characteristics of the step response curve, the dynamic performance problems such as hysteresis, overshoot and steady-state error of the motor can be identified, and this characteristic value is helpful for optimizing the motor control system, reducing the response time and steady-state error; by analyzing the change of the speed overall deviation value and the change characteristics of the speed characteristic value between each measurement interval and its reference interval, combined with the speed control adaptation value, the final speed adaptation value of each measurement interval is determined, through comprehensive analysis of multiple characteristic values, the understanding of the motor performance is further improved, and the final speed adaptation value is obtained, which can more comprehensively reflect the stability, accuracy and dynamic response capability of the system. This characteristic value provides an effective basis for the next step of PID control parameter optimization, ensures the efficiency and stability of the motor operation, helps to find the optimal PID parameters, thereby improving the overall stability and accuracy of the system, and enhancing the adaptability of the feeding amount adjustment of the turning-milling combined machine tool under different cutting chatter degrees. BRIEF DESCRIPTION OF DRAWINGS

[0032] Figure 1 Figure 1 shows a step flow chart of a servo feed parameter optimization method of a turning-milling combined machine tool according to an embodiment of the present application.

[0033] Figure 2 Figure 2 shows a diagram for obtaining a final adaptive value of a rotating speed according to an embodiment of the present application. DETAILED DESCRIPTION

[0034] In the description of the embodiments of the present application, the words "exemplary", "or", "for example", etc. are used to mean serving as an example, instance, or illustration. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being preferred or superior to other embodiments or design solutions. Rather, the use of the words "exemplary", "or", "for example", etc. is intended to present concepts in a particular manner.

[0035] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.

[0036] In addition, it should be pointed out that the terms "first", "second" in the present application and the drawings are used to distinguish similar objects, and are not intended to describe a specific order or sequence. The method disclosed in the embodiments of the present application or the method shown in the flow chart includes one or more steps for implementing the method, and the execution order of the steps can be interchanged with each other without departing from the scope of the present application, and some steps can also be deleted.

[0037] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0038] The specific scheme of the servo feed parameter optimization method of the turning-milling combined machine tool provided by the present application will be described in detail below in combination with the drawings.

[0039] Please refer to Figure 1 Figure 1 shows a step flow chart of a servo feed parameter optimization method of a turning-milling combined machine tool according to an embodiment of the present application. The method comprises the following steps:

[0040] The first step: collecting the rotating speed data of the servo motor of the turning-milling combined machine tool, and presetting the measurement interval.

[0041] In the present application, the rotating speed of the milling cutter tool of the turning-milling combined machine tool is controlled by the servo motor.

[0042] The application collects the rotating speed data of the servo motor through the photoelectric encoder installed on the servo motor, and the collection rate is set to 20 Hz in the embodiment, and the implementer can set it according to the actual situation.

[0043] Further, the preset number of continuously collected rotating speed data is divided into a measurement interval in the embodiment, and the preset number is 60.

[0044] The second step is to analyze the overall distribution of the deviation between the rotating speed data in each measurement interval and the target rotating speed data, determine the rotating speed overall deviation value of each measurement interval, determine the rotating speed fluctuation characteristic value of each measurement interval based on the change of the data in the detrended sequence after the inherent change of the rotating speed data in each measurement interval, and determine the rotating speed characteristic value of each measurement interval by comprehensively considering the rotating speed overall deviation value and the rotating speed fluctuation characteristic value.

[0045] In the process of milling a workpiece on a turning-milling combined machine tool, the servo motor provides cutting force for the tool. Stable rotating speed data output by the servo motor can ensure the consistency of the workpiece surface finish and the consistency of the workpiece quality, and can also avoid tool damage caused by rotating speed data fluctuation.

[0046] To reduce machining chatter, the cutting feed rate of the turning-milling combined machine tool changes constantly during the milling process. The larger the cutting feed rate, the greater the resistance that the tool needs to overcome during milling, resulting in an increase in the torque of the servo motor. When the servo motor is driven by input voltage, the rotating speed of the servo motor decreases as the torque increases. Therefore, the input voltage of the servo motor needs to be controlled in real time to ensure the stability of the rotating speed data during cutting.

[0047] The PID algorithm is the most commonly used method for controlling servo motors in the industry. Because the workpiece milling process has high requirements for the stability of the rotating speed data, the fixed parameters of the traditional PID algorithm cannot respond to the change of the rotating speed data caused by the change of the cutting resistance, resulting in large fluctuations in the rotating speed data. According to the change of the rotating speed data, the application optimizes the parameters of the PID algorithm in real time to reduce the fluctuation of the rotating speed data caused by the change of the feed rate.

[0048] For the rotating speed data of the servo motor in each measurement interval, the degree of influence of the feed rate adjustment on the rotating speed of the servo motor in the period is obtained. The application gives an implementation process as follows:

[0049] The target rotating speed of the milling tool is set as 3000 r / min; the target rotating speed is subtracted from each rotating speed data in the measurement interval to obtain the rotating speed deviation of each rotating speed data, the mean value of the absolute values of all the rotating speed deviations obtained in the measurement interval is calculated, and the mean value is recorded as the rotating speed overall deviation value of the measurement interval, which reflects the deviation of the rotating speed data in the measurement interval from the target rotating speed. It should be understood that the greater the variation of the feed amount in the workpiece milling process, the greater the torque variation of the servo motor, the greater the deviation of the rotating speed data in the measurement interval from the target rotating speed, and the greater the calculated rotating speed overall deviation value.

[0050] Since the variation of the cutting chatter degree has strong randomness, the randomness of the feed amount adjustment is strong, and the rotating speed deviation in the measurement interval has strong fluctuation characteristics. According to the fluctuation characteristics of the rotating speed deviation, the influence degree of the current feed amount variation on the rotating speed of the servo motor is obtained.

[0051] Generally, the milling process can be divided into three stages of cutting in, stable and cutting out. When cutting in or cutting out in each stage, the tool just contacts the workpiece or gradually separates from the workpiece, and the feed amount needs to be controlled in stages according to the milling stage. Therefore, it is also necessary to analyze the fluctuation characteristics in combination with the milling stage in which each measurement interval is located.

[0052] Specifically, from K times of historical milling processes of the same type of workpiece as the current workpiece, the machining time of each stage in each milling process is determined, and the average value of the machining time of each stage in the K times of milling processes is taken as the machining period of each stage.

[0053] Further, the machining period to which each measurement interval belongs is determined according to the starting time of each measurement interval. For any machining period, the tool will automatically slow down when cutting in or gradually separating from the workpiece, for example, the tool will generally slow down by 20%-30% when cutting in or cutting out in each stage, in order to reduce the impact load and avoid causing vibration or blade collapse. Therefore, if the measurement interval contains the time period of cutting in or cutting out in the machining period, the data in the measurement interval will have significant rotating speed variation, and this data fluctuation caused by cutting in or cutting out should be eliminated. Therefore, for each measurement interval, the rotating speed data in the measurement interval is arranged in time sequence and input into the detrend algorithm to filter out the trend component inherent in the milling process in each machining stage, and the remaining detrend sequence mainly corresponds to the fluctuation component caused by cutting chatter.

[0054] The detrend analysis is a known technology in the field of data processing, and the specific process will not be described again. Preferably, the detrend algorithm used in the embodiment is DFA (Detrended fluctuation analysis) algorithm.

[0055] Further, curve fitting is performed on the detrended sequence of each measurement interval, and the slope value corresponding to each point of the detrended sequence is calculated, and the average of the slope values of all points in the detrended sequence is taken as the overall fluctuation deviation of the rotational speed data in each measurement interval; then, the absolute value of the difference between each rotational speed data and the corresponding point in the detrended sequence is calculated, and the sum of the absolute values of the difference values calculated for all the rotational speed data in each measurement interval is taken as the fluctuation variation of the rotational speed data in each measurement interval, and the overall fluctuation deviation and the fluctuation variation are positively fused, and the fusion result is taken as the rotational speed fluctuation characteristic value of each measurement interval, which is used to represent the data fluctuation degree caused by cutting chatter due to the change of the feed rate in each measurement interval.

[0056] It should be understood that, in the machining cycle to which each measurement interval belongs, the faster the feed rate changes, the faster the cutting resistance changes, the more intense the data changes in the detrended sequence of the rotational speed data in the measurement interval after eliminating the inherent changes caused by cutting in or cutting out, the larger the value of the fluctuation variation, and the more obvious the data fluctuation degree caused by cutting chatter due to the change of the feed rate, and the larger the slope value at each point in the detrended sequence; that is, the larger the rotational speed fluctuation characteristic value of each measurement interval, and the larger the data fluctuation degree of the rotational speed data in the measurement interval caused by the change of the feed rate.

[0057] The rotational speed overall deviation value and the rotational speed fluctuation characteristic value of each measurement interval are multiplied to obtain the rotational speed characteristic value of each measurement interval, which reflects the influence degree of the rotational speed of the servo motor in the measurement interval caused by the adjustment of the feed rate. It should be noted that the larger the rotational speed overall deviation value and the rotational speed fluctuation characteristic value, the larger the deviation degree of the rotational speed data from the target rotational speed, and the larger the fluctuation degree of the rotational speed deviation in the measurement interval, and the larger the calculated rotational speed characteristic value, and the greater the influence on the rotational speed in the measurement interval.

[0058] The third step is to obtain a reference interval of each measurement interval through the transfer function of the servo motor, to determine a rotational speed control adaptation value of each measurement interval according to the difference between the distribution trend of the rotational speed deviation in each measurement interval and the reference interval, and in combination with the change of the rotational speed characteristic value, and to determine a rotational speed final adaptation value of each measurement interval by comprehensively considering the rotational speed deviation and the rotational speed control adaptation value of the reference interval of each measurement interval.

[0059] The present application uses the Ziegler-Nichols method to set the initial parameters of the PID algorithm of the servo motor, obtains the initial proportional parameter, the initial integral parameter and the initial differential parameter, and takes the three values as three components to form an initial parameter vector. The Ziegler-Nichols method is a known technology, and will not be described herein.

[0060] The transfer function of the servo motor is obtained by querying the servo motor manual, and the step response curve of the parameter vector is further obtained at the end of each measurement interval, reflecting the change of the speed data under the control of the parameter vector, and the step response curve of the speed data is sampled, and the sampling frequency is set to 20Hz in the embodiment. Wherein, the step response curve obtained according to the transfer function is a known technology, and the present application will not be repeated.

[0061] For each measurement interval, the first 60 speed data of the step response curve form an interval, which is recorded as the reference interval of each measurement interval, which is used to optimize the servo motor parameters in the measurement interval.

[0062] The severity of cutting chatter in the milling process of the turning-milling combined machine tool is different in different stages, and the duration of the optimization and adjustment of the cutting feed rate is different. In different machining periods, the workpiece parts processed by milling are also different, which will also lead to the optimization and adjustment of the feed rate, further increasing the complexity of the change of the servo motor torque. For example, when processing the profile corner on the workpiece, the feed rate needs to be actively reduced to avoid inertia "overtravel" or "undertravel", and then the normal feed rate is restored after processing the corner. Therefore, it is difficult for fixed control parameters to adapt to the milling process of the turning-milling combined machine tool, and the control parameters need to be optimized and adjusted.

[0063] The present application optimizes the PID algorithm parameters of the servo motor according to the stability of the speed data control by different servo motor parameters. For each measurement interval, the speed control adaptation value of each measurement interval is calculated according to the change of the speed data in the reference interval. Specifically, an implementation process is as follows:

[0064] Firstly, the abscissa of the step response curve represents time, and the ordinate represents the response value of the system. The adjustment time is the time when the step response curve enters the steady state value within the system specified error range. The rising time is the time when the step response curve rises from the initial value to the steady state value, reflecting the time required for the parameter vector to control the speed data to be stable in the milling process. The longer the rising time, the less suitable the parameter vector is for the milling process, and the worse the control effect of the servo motor parameters. The adjustment time reflects the ability of the parameter vector to control the speed of the servo motor to be stable within a certain range when the speed data is affected at different times in different measurement intervals in the milling process. The longer the adjustment time, the worse the control ability of the parameter vector to keep the speed stable in the milling process of the turning-milling combined machine tool.

[0065] Secondly, the absolute value of the difference between the speed data at the same sampling time in each measurement interval and the reference interval is calculated as a first difference; the sum of the rising time and the adjustment time is taken as the adaptation length of the adaptation parameter vector of each measurement interval, and the ratio of the adaptation length of the adaptation parameter vector of each measurement interval to the sum of the adaptation lengths of all the adaptation parameter vectors of the measurement intervals is taken as a time weight, and the product of the first difference and the time weight is taken as the speed control adaptation value of each measurement interval, which is used to represent the control ability of the parameter vector to the speed data, and the greater the speed control adaptation value, the weaker the control adaptation ability of the parameter vector to the speed data in the measurement interval; the smaller the speed control adaptation value, the stronger the control ability of the parameter vector to the speed data in the measurement interval.

[0066] It should be understood that under the adjustment of the PID algorithm, the abnormality degree of the speed data in the reference interval will be relatively reduced. On the one hand, the smaller the overall deviation value of the speed in the reference interval is than the overall deviation value of the speed in the measurement interval, on the other hand, under the control of the PID algorithm, when the speed data in the measurement interval is abnormal, the trend of the speed data in the reference interval will be opposite to that in the measurement interval, and the greater the difference between the speed characteristic values of the reference interval and the measurement interval. The calculation process of the overall deviation value of the speed in the reference interval and the speed characteristic value is consistent with the calculation process of the overall deviation value of the speed in the measurement interval and the speed characteristic value.

[0067] In summary, the speed final adaptation value of the measurement interval is determined based on the overall deviation value of the speed in the measurement interval and the reference interval, the speed characteristic value, and the speed control adaptation value of the measurement interval, and the speed final adaptation value of the i-th measurement interval is represented as :

[0068]

[0069] In the formula, the speed control adaptation value of the reference interval is represented as , the speed characteristic values of the reference interval and the measurement interval are represented as , the overall deviation values of the speed in the reference interval and the measurement interval are represented as respectively; and is recorded as a second difference; and is recorded as a third difference.

[0070] The speed final adaptation value of each measurement interval is used to reflect the adaptation degree of the PID algorithm to the speed data control in the next measurement interval under the control of the parameter variable in the current measurement interval. The acquisition diagram of the speed final adaptation value is shown in Figure 2 .

[0071] In one aspect, the greater the optimization degree of the PID algorithm to the stable control of the rotation speed data, the smaller the rotation speed control adaptive value, the greater the adaptive degree of the rotation speed data fluctuation caused by the adjustment of the servo motor parameters to the current cutting feed rate, and the smaller the obtained rotation speed final adaptive value.

[0072] On the other hand, the smaller the rotation speed deviation in the reference interval, the smaller the overshoot and oscillation existing in the control of the rotation speed data by the PID algorithm, the greater the control adaptive degree of the corresponding servo motor parameters, and the smaller the obtained rotation speed final adaptive value.

[0073] The fourth step is to optimize various control parameters of the servo motor PID algorithm based on the rotation speed final adaptive value.

[0074] The present application uses a particle swarm optimization algorithm to optimize the servo motor parameters, and a specific embodiment is as follows:

[0075] For the proportional parameter of the measurement interval, the proportional parameter kp of the previous measurement interval is taken as a reference, [0.9kp, 1.1kp] is set as the proportional parameter interval, a value is randomly selected in the proportional parameter interval as a proportional parameter of the next measurement interval.

[0076] An integral parameter and a differential parameter of the next measurement interval are obtained by using the above method, and a parameter vector of the next measurement interval is formed by using the same formation method as the initial parameter vector.

[0077] Further, 30 parameter vectors are obtained by using the same method as the initial population of the particle swarm algorithm, the rotation speed final adaptive value is taken as the fitness function value of the parameter vector, the maximum number of iterations is set to 30, the optimal parameter vector is obtained, and the corresponding proportional parameter, integral parameter and differential parameter are taken as the PID algorithm parameters of the servo motor for controlling the rotation speed of the tool servo system, thereby realizing the optimization of the parameters.

[0078] The computer program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0079] It is apparent that a person skilled in the art can make modifications to the present application without departing from the scope of the application, and the application is not limited to the details of the above-described exemplary embodiments. Therefore, the above-described embodiments of the present application should be considered as exemplary and non-limiting; any modification to the technical solutions described in the above-described embodiments, or equivalent replacement of some of the technical features, do not cause the nature of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A method for optimizing servo feed parameters of a turning-milling hybrid machine tool, characterized in that, The method comprises the following steps: Collecting the rotation speed data of the servo motor of the turning-milling combined machine tool, and presetting a measurement interval; Analyzing the overall distribution of the difference between each rotation speed data and the target rotation speed to determine the overall rotation speed deviation value of each measurement interval; determining the rotation speed fluctuation characteristic value of each measurement interval based on the change of the data in the detrended sequence after eliminating the inherent changes of the rotation speed data in each measurement interval; and comprehensively determining the rotation speed characteristic value of each measurement interval based on the rotation speed overall deviation value and the rotation speed fluctuation characteristic value. Based on the transfer function of the servo motor, the step response curve is obtained at the end time of each measurement interval according to the parameters of the servo motor PID algorithm; the step response curve is sampled to obtain the reference interval of each measurement interval. The vector composed of the PID control parameters of each measurement interval is taken as the parameter vector; the time for the step response curve to enter the steady state value within the system specified error range is recorded as the adjustment time, and the time for the step response curve to rise from the initial value to the steady state value is recorded as the rise time; the sum of the rise time and the adjustment time is taken as the adaptation length of the adaptive parameter vector of each measurement interval; the absolute value of the difference between the rotation speed data at the same sampling time in each measurement interval and the reference interval is calculated as the first difference; the ratio of the adaptation length of the adaptive parameter vector of each measurement interval to the sum of the adaptation lengths of the adaptive parameter vectors of all measurement intervals is taken as the time weight, and the product of the first difference and the time weight is taken as the rotation speed control adaptation value of each measurement interval. The difference between the rotation speed overall deviation value of each reference interval and its corresponding measurement interval is recorded as the second difference; the absolute value of the difference between the rotation speed characteristic value of each reference interval and its corresponding measurement interval is recorded as the third difference; the second difference, the third difference, and the rotation speed control adaptation value are positively fused to obtain the final rotation speed adaptation value of each measurement interval. Based on the final rotation speed adaptation value, the various control parameters of the servo motor PID algorithm are optimized.

2. The method of claim 1, wherein the servo feed parameters are optimized by, The determination of the rotation speed overall deviation value of each measurement interval is specifically the mean value of the absolute values of all rotation speed deviations obtained in each measurement interval; the rotation speed deviation is specifically the difference between the target rotation speed and each rotation speed data.

3. The method of claim 1, wherein the method is characterized by, The determination of the rotation speed fluctuation characteristic value of each measurement interval is specifically: The change trend of each point after curve fitting of the detrended sequence obtained in each measurement interval is calculated to determine the overall fluctuation deviation of the rotation speed data in each measurement region; The absolute value of the difference between each rotation speed data and the corresponding point in the detrended sequence is calculated, and the sum of the absolute values of the differences obtained by all rotation speed data in each measurement interval is taken as the fluctuation change amount of the rotation speed data in each measurement interval; The overall fluctuation deviation and the fluctuation change amount are positively fused to obtain the rotation speed fluctuation characteristic value of each measurement interval.

4. The method of claim 3, wherein the servo feed parameters are optimized by, The overall fluctuation deviation of the rotation speed data in each measurement region is specifically the mean value of the slope values of all points in the detrended sequence.

5. The method of claim 1, wherein the servo feed parameters are optimized by using a feed rate optimization algorithm. The rotation speed characteristic value of each measurement interval is specifically the product of the rotation speed overall deviation value and the rotation speed fluctuation characteristic value of each measurement interval.

6. The method of optimizing the servo feed parameters of a turn-milling machine tool according to claim 1, characterized in that, The process of optimizing the various control parameters of the servo motor PID algorithm is specifically as follows: The final adaptive value of the rotating speed is taken as the fitness function value of the corresponding measurement interval parameter vector, and an optimization algorithm is used to minimize the fitness function value, so as to obtain an optimal parameter vector.

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