Processing data acquisition method and system applied to CNC machine tools

Abstract

The present invention relates to the technical field of CNC machine tool operation, and specifically to a processing data acquisition method and system for CNC machine tools. The method comprises: obtaining a processing accuracy error value based on the difference between cutting parameters in different dimensions and initial cutting parameters; obtaining a tool wear characteristic value based on the change in the difference between the cutting parameters and the initial cutting parameters; obtaining a tool wear impact value based on the tool wear characteristic value and the cutting force change impact value; obtaining a processing accuracy error impact value based on the tool wear impact value and the processing accuracy error value; obtaining a current acquisition frequency adjustment factor based on the change trend of the processing accuracy error impact value in different target error historical time periods; and obtaining the current boring and milling processing data acquisition frequency based on the acquisition frequency adjustment factor. The present invention improves the boring and milling processing accuracy of CNC machine tools.

Description

Technical Field

[0001] The present invention relates to the technical field of numerical control machine tool operation, and in particular to a processing data acquisition method and system applied to numerical control machine tools. Background Art

[0002] CNC machine tools, as key automation equipment in modern manufacturing, are widely used in fields such as metalworking, mold making, and precision machining. Especially during boring and milling operations, the machining accuracy of the machine tool directly impacts the quality and performance of the parts. To ensure machining accuracy, traditional methods typically rely on preset initial cutting parameters for machining control. However, due to factors such as tool wear, workpiece material differences, machine tool vibration, and temperature fluctuations, actual machining parameters can deviate over time, leading to the accumulation of machining errors.

[0003] When performing high-precision CNC boring and milling processing, the accuracy of the boring and milling processing will deteriorate due to tool wear and vibration generated during the processing. The existing CNC machine tool data acquisition method mostly collects cutting parameters at a fixed frequency, which makes it difficult to reflect the dynamic changes of the processing status in real time and cannot effectively capture abnormal conditions of tool wear and vibration. This leads to low data acquisition efficiency and difficulty in timely correction of processing errors, making the boring and milling processing accuracy of CNC machine tools increasingly worse. Summary of the Invention

[0004] The present invention provides a processing data acquisition method and system for CNC machine tools to solve the existing problem: the existing CNC machine tool data acquisition methods mostly collect cutting parameters at a fixed frequency, which makes it difficult to reflect the dynamic changes of the processing state in real time and cannot effectively capture abnormal conditions such as tool wear and vibration. This leads to low data acquisition efficiency and difficulty in timely correction of processing errors, resulting in increasingly poor boring and milling processing accuracy of CNC machine tools.

[0005] The processing data acquisition method and system applied to CNC machine tools of the present invention adopt the following technical solutions:

[0006] The present invention proposes a processing data acquisition method applied to a CNC machine tool, the method comprising the following steps:

[0007] Obtaining the cutting parameter sequence and initial cutting parameters of the CNC machine tool during boring and milling processing;

[0008] By analyzing the differences between the cutting parameter sequence and the initial cutting parameters, several target moments are obtained; according to the fluctuations between the cutting parameters at the target moments and the initial cutting parameters, several target error history time periods are obtained; according to the differences between the cutting parameters in different dimensions and the initial cutting parameters, the machining accuracy error values ​​of the target error history time periods are obtained;

[0009] According to the change amplitude of the cutting parameters, the cutting force change influence value in the target error history period is obtained; according to the difference change between the cutting parameters and the initial cutting parameters, the tool wear characteristic value in the target error history period is obtained; according to the tool wear characteristic value and the cutting force change influence value, the tool wear influence value in the target error history period is obtained; according to the tool wear influence value and the machining accuracy error value, the machining accuracy error influence value in the target error history period is obtained;

[0010] According to the change trend of the machining accuracy error influence value in different target error historical time periods, the acquisition frequency adjustment factor at the current moment is obtained; based on the acquisition frequency adjustment factor, the boring and milling processing data acquisition frequency at the current moment is obtained.

[0011] Preferably, the specific method of obtaining several target moments by analyzing the differences between the cutting parameter sequence and the initial cutting parameters is:

[0012] All sampling moments before the current moment are recorded as historical moments;

[0013] Preset an error threshold parameter , will The initial cutting parameters of the first dimension and the The first historical moment The normalized value of the absolute value of the difference between the cutting parameters of the first dimension is recorded as The first historical moment The error factor of the cutting parameters of the first dimension; The mean error factor of all dimensions of cutting parameters at the historical moment is recorded as The error margin of the historical moment; the error margin is greater than or equal to the error threshold parameter The historical moment is recorded as the target moment.

[0014] Preferably, the specific method for obtaining several target error historical time periods according to the fluctuation of the difference between the cutting parameters at the target moment and the initial cutting parameters is:

[0015] The sequence of consecutive target moments is recorded as an error sequence. For any error sequence, if the normalized value of the variance of the error amplitudes of all target moments in the error sequence is greater than or equal to the error threshold parameter , record the time period consisting of all target moments in any error sequence as the target error history time period.

[0016] Preferably, the specific method for obtaining the machining accuracy error value of the target error historical time period according to the difference between the cutting parameters of different dimensions and the initial cutting parameters is:

[0017] In the In the target error history period, the first The ratio between the mean of the error factor of the cutting parameter in the dimension and the mean of the error amplitude of all target moments is taken as the first Weight factors of cutting parameters of different dimensions;

[0018] The first The target error in the historical period The weight factor of the cutting parameters of the first dimension is The target error history period of all target moments The product of the mean values ​​of the error factors of the cutting parameters in different dimensions is recorded as The precision error factor of the cutting parameters of the first dimension; The normalized value of the product of the number of all target moments in the target error history period and the cumulative sum of the precision error factors of the cutting parameters of all dimensions is used as the first The machining accuracy error value of the target error historical time period.

[0019] Preferably, the specific method for obtaining the cutting force change impact value in the target error historical time period according to the change amplitude of the cutting parameters is:

[0020] In the In the target error history time period, the target moment with the same cutting depth and feed amount is recorded as the comparison moment;

[0021] The first The difference between the maximum and minimum cutting forces at all target moments in the target error history period is recorded as the variation of the cutting force; The target error in the historical period The cutting force at the first comparison moment is The absolute value of the difference between the mean values ​​of the cutting forces at all comparison moments in the target error history period is recorded as The cutting force difference factor at the first comparison moment; The product of the inverse proportional normalized value of the cumulative sum of the cutting force difference factors of all comparison moments in the target error history period and the change amplitude of the cutting force is taken as the first The impact value of cutting force changes in the target error history period.

[0022] Preferably, the specific method for obtaining the tool wear characteristic value in the target error history time period according to the difference change between the cutting parameters and the initial cutting parameters is:

[0023] The first The sequence of error amplitudes of all target moments in the target error history period is recorded as target error sequence; using the STF decomposition algorithm to Decompose the target error sequence to obtain several components;

[0024] Preset a difference threshold parameter , if The first The margin of error and The difference between the error margins is greater than or equal to the difference threshold parameter , will The error amplitude is recorded as the wear error amplitude; The ratio of all wear error amplitudes to all error amplitudes in the first component is taken as the The probability that each component belongs to the wear component;

[0025] In the Among all the components after the target error sequence is decomposed, the component corresponding to the maximum value of the wear component possibility is recorded as The wear component of the target error sequence;

[0026] The first The difference between the maximum and minimum values ​​of the wear error amplitude in the wear component of the target error sequence is recorded as the wear error increment; the wear error increment is compared with the The product of the probability of the wear component of the target error sequence belonging to the wear component is taken as the Tool wear characteristic values ​​in a target error history period.

[0027] Preferably, the specific method for obtaining the tool wear influence value in the target error history time period based on the tool wear characteristic value and the cutting force change influence value is:

[0028] The first The tool wear characteristic value in the target error history period is The sum of the maximum values ​​of the wear error amplitudes in the wear components of the target error sequences is recorded as the first sum value; the first sum value is added to the The normalized value of the product of the cutting force change influence values ​​in the target error history time period is used as the first The tool wear impact value in the target error history period.

[0029] Preferably, the specific method for obtaining the machining accuracy error impact value of the target error historical time period based on the tool wear impact value and the machining accuracy error value is:

[0030] Preset a constant parameter ,Will With the The sum of the tool wear influence values ​​in the target error history time period is recorded as the second sum; the second sum is added to the The product of the machining accuracy error values ​​of the target error historical time period is used as the The impact value of machining accuracy error in a target error historical period.

[0031] Preferably, the specific method for obtaining the current acquisition frequency adjustment factor according to the change trend of the machining accuracy error influence value in different target error historical time periods is:

[0032] The first target error historical period and the The difference in the machining accuracy error impact value between the target error historical time periods is recorded as The error impact difference value of the target error historical time period; if the error impact difference value is less than or equal to the difference threshold parameter , then target error history time period, recorded as the vibration error history time period; if the error impact difference value is greater than the difference threshold parameter , then The target error history time period is recorded as , and the wear error history time period is recorded as ;

[0033] The difference between the machining accuracy error influence value of the last target error historical time period and the machining accuracy error influence value of the first target error historical time period is recorded as the first difference; the ratio between the number of wear error historical time periods and the number of vibration error historical time periods is recorded as the first ratio; the normalized value of the product of the first difference and the first ratio is recorded as the acquisition frequency adjustment factor at the current moment.

[0034] The present invention also proposes a processing data acquisition system for CNC machine tools, comprising a memory and a processor, wherein the processor executes a computer program stored in the memory to implement the steps of the above-mentioned processing data acquisition method for CNC machine tools.

[0035] The beneficial effects of the technical solution of the present invention are: the present invention obtains the machining accuracy error value according to the difference between the cutting parameters in different dimensions and the initial cutting parameters; obtains the tool wear characteristic value according to the change of the difference between the cutting parameters and the initial cutting parameters; obtains the tool wear influence value according to the tool wear characteristic value and the cutting force change influence value; obtains the machining accuracy error influence value according to the tool wear influence value and the machining accuracy error value; obtains the acquisition frequency adjustment factor at the current moment according to the change trend of the machining accuracy error influence value in different target error historical time periods; obtains the boring and milling processing data acquisition frequency at the current moment based on the acquisition frequency adjustment factor; by automatically adjusting the data acquisition frequency, the CNC machine tool can adapt to the wear process and adjust the acquisition strategy in real time to ensure that the accuracy remains in the best state; thereby improving the boring and milling processing accuracy of the CNC machine tool. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0037] Figure 1 A flowchart of the steps of the processing data acquisition method applied to a CNC machine tool of the present invention;

[0038] Figure 2 The figure is a flow chart showing the characteristic relationship of the processing data acquisition method applied to a CNC machine tool according to the present invention. DETAILED DESCRIPTION

[0039] To further illustrate the technical means and effectiveness of the present invention in achieving its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of the processing data acquisition method and system for CNC machine tools proposed in accordance with the present invention. In the following description, references to different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0040] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0041] The specific scheme of the processing data acquisition method and system for CNC machine tools provided by the present invention will be described in detail below with reference to the accompanying drawings.

[0042] See also Figure 1, which shows a flowchart of a method for collecting machining data applied to a CNC machine tool provided by one embodiment of the present invention, the method comprising the following steps:

[0043] Step S001: Obtaining a cutting parameter sequence and initial cutting parameters when a CNC machine tool performs boring and milling processing.

[0044] It should be noted that this embodiment collects the cutting parameters and initial cutting parameters of the CNC machine tool during boring and milling processing in real time, analyzes the differences between them to evaluate the impact of tool wear on processing accuracy, and obtains the acquisition frequency adjustment factor at the current moment to adaptively adjust the data acquisition frequency of the CNC machine tool.

[0045] In a specific implementation of the embodiment of the present invention, a specific method for obtaining a cutting parameter sequence and initial cutting parameters when a CNC machine tool performs boring and milling processing is as follows:

[0046] Through the programming interface of the CNC machine tool system, the set cutting force, cutting depth and feed rate are directly read and recorded as the initial cutting parameters when the CNC machine tool performs boring and milling processing; every 1 second is a sampling moment, and each time a cutting force sensor is installed in the CNC machine tool to measure the magnitude of the cutting force to obtain the cutting force, a displacement sensor is used to monitor the relative position of the tool to measure the feed rate, and an optical sensor is used to measure the specific position of the tool, and the distance between the tool and the workpiece is obtained to calculate the cutting depth; a total of 10 minutes of data collection is carried out; the sequence consisting of the three dimensional data of cutting force, cutting depth and feed rate at all sampling moments is recorded as the cutting parameter sequence when the CNC machine tool performs boring and milling processing.

[0047] Among them, in the CNC boring and milling process, the initial cutting parameters are set manually and will be continuously updated and changed over time; that is, the cutting parameters at each sampling moment will correspond to an initial cutting parameter.

[0048] At this point, the cutting parameter sequence and initial cutting parameters of the CNC machine tool during boring and milling processing are obtained through the above method.

[0049] Step S002: Obtain several target moments by analyzing the differences between the cutting parameter sequence and the initial cutting parameters; obtain several target error historical time periods based on the difference fluctuations between the cutting parameters at the target moments and the initial cutting parameters; obtain the machining accuracy error value of the target error historical time period based on the differences between the cutting parameters in different dimensions and the initial cutting parameters.

[0050] It should be noted that during CNC boring and milling processing, not only will there be a certain deviation between the cutting parameters collected in real time and the initial cutting parameters set manually due to the wear of the tool and the vibration generated during the processing, but there will also be a certain deviation between the cutting parameters collected in real time and the initial cutting parameters set manually due to the errors in the system itself; however, the deviation caused by the system error is relatively small and the difference is relatively stable, while the deviation caused by tool wear and vibration is relatively large and the difference is relatively unstable; therefore, it is necessary to eliminate the influence of the system error and further analyze the errors caused by tool wear and vibration to obtain the processing accuracy error value within different target error historical time periods.

[0051] Preferably, in some implementations of the embodiments of the present invention, a specific method for obtaining a plurality of target moments by analyzing the difference between the cutting parameter sequence and the initial cutting parameters is as follows:

[0052] All sampling moments before the current moment are recorded as historical moments;

[0053] Preset an error threshold parameter , wherein this embodiment is based on This example is described as an example, and this embodiment is not specifically limited. Depends on the specific implementation situation;

[0054] The first The initial cutting parameters of the first dimension and the The first historical moment The normalized value of the absolute value of the difference between the cutting parameters of the first dimension is recorded as The first historical moment The error factor of the cutting parameters of the first dimension; The mean error factor of all dimensions of cutting parameters at the historical moment is recorded as The error margin of the historical moment; the error margin is greater than or equal to the error threshold parameter The historical moment is recorded as the target moment;

[0055] Preferably, in some implementations of the embodiments of the present invention, due to certain errors in the CNC machine tool's own system, there may be certain deviations between the cutting parameters collected in real time and the manually set initial cutting parameters. However, the deviation caused by the system error is relatively small and the difference is relatively stable, while the deviation caused by tool wear and vibration is relatively large and the difference is relatively unstable. Therefore, based on the difference fluctuation between the cutting parameters at the target time in the cutting parameter sequence and the initial cutting parameters, a specific method for obtaining several target error historical time periods is as follows:

[0056] The sequence of consecutive target moments is recorded as an error sequence. For any error sequence, if the normalized value of the variance of the error amplitudes of all target moments in the error sequence is greater than or equal to the error threshold parameter , record the time period consisting of all target moments in any error sequence as the target error history time period;

[0057] Among them, all target error historical time periods are sorted from large to small according to the time interval between them and the current moment.

[0058] Preferably, in some implementations of the embodiments of the present invention, in In the target error history period, the greater the deviation between the real-time collected cutting parameters and the manually set initial cutting parameters caused by tool wear and vibration, and the longer the duration, the greater the deviation between the real-time collected cutting parameters and the manually set initial cutting parameters, and the longer the deviation lasts, the greater the deviation between the real-time collected cutting parameters and the manually set initial cutting parameters. The more obvious the precision error of boring and milling processing is in the target error history time period, and the deviation degree corresponding to the cutting parameters of different dimensions is different; therefore, according to the difference between the cutting parameters of different dimensions in the target error history time period and the initial cutting parameters, the specific method for obtaining the machining precision error value of each target error history time period is as follows:

[0059] In the In the target error history period, the first The ratio between the mean of the error factor of the cutting parameter in the dimension and the mean of the error amplitude of all target moments is taken as the first Weight factors of cutting parameters of different dimensions;

[0060] The first The target error in the historical period The weight factor of the cutting parameters of the first dimension is The target error history period of all target moments The product of the mean values ​​of the error factors of the cutting parameters in different dimensions is recorded as The precision error factor of the cutting parameters of the first dimension; The normalized value of the product of the number of all target moments in the target error history period and the cumulative sum of the precision error factors of the cutting parameters of all dimensions is used as the first The machining accuracy error value of the target error historical period;

[0061] The specific formula is:

[0062]

[0063] Where, Indicates the The machining accuracy error value of the target error historical period; Indicates the The number of all target moments in the target error history period; The number of types of cutting parameters representing all dimensions; Indicates the The target error in the historical period Weight factors of cutting parameters of different dimensions; Indicates the The target error history period of all target moments The mean of the error factors of the cutting parameters in different dimensions; represents the linear normalization function.

[0064] At this point, the machining accuracy error value within each target error historical time period is obtained through the above method.

[0065] Step S003: According to the change amplitude of the cutting parameters, obtain the cutting force change influence value in the target error historical time period; according to the difference change between the cutting parameters and the initial cutting parameters, obtain the tool wear characteristic value in the target error historical time period; according to the tool wear characteristic value and the cutting force change influence value, obtain the tool wear influence value in the target error historical time period; according to the tool wear influence value and the machining accuracy error value, obtain the machining accuracy error influence value of the target error historical time period.

[0066] It should be noted that the error caused by tool wear is irreversible, while the error caused by vibration will be corrected by the CNC machine tool itself over time. Therefore, the error caused by tool wear is used to further correct the machining accuracy error value to obtain the machining accuracy error influence value; in the cutting process of CNC boring and milling, the cutting force usually changes with the different stages of the machining process, and the cutting force is related to the cutting depth and feed rate; when the cutting depth and feed rate are the same during the machining process, the cutting force should be similar; but when the tool wears, the sharpness of the blade decreases and becomes more blunt, which increases the contact area between the tool and the workpiece material during the cutting process, requiring greater force to overcome the deformation resistance of the material; and after the tool wears, the surface roughness increases, and the friction coefficient between the tool and the workpiece material also increases, which leads to greater friction during the cutting process, thereby increasing the cutting force, that is, when the feed rate and cutting depth are the same, the cutting force becomes greater and greater, indicating that the tool is more likely to wear.

[0067] Preferably, in some implementations of the embodiments of the present invention, a specific method for obtaining the cutting force change impact value in each target error historical time period according to the change amplitude of the cutting force in the target error historical time period is:

[0068] In the In the target error history time period, the target moment with the same cutting depth and feed amount is recorded as the comparison moment;

[0069] The first The difference between the maximum and minimum cutting forces at all target moments in the target error history period is recorded as the variation of the cutting force; The target error in the historical period The cutting force at the first comparison moment is The absolute value of the difference between the mean values ​​of the cutting forces at all comparison moments in the target error history period is recorded as The cutting force difference factor at the first comparison moment; The product of the inverse proportional normalized value of the cumulative sum of the cutting force difference factors of all comparison moments in the target error history period and the change amplitude of the cutting force is taken as the first The impact value of cutting force changes in the target error history period;

[0070] The specific formula is:

[0071]

[0072] Where, Indicates the The impact value of cutting force changes in the target error history period; Indicates the The maximum value of the cutting force at all target moments in the target error history period; Indicates the The minimum value of the cutting force at all target moments in the target error history period; Indicates the The number of all comparison moments in the target error history period; Indicates the The target error in the historical period Cutting force at the comparison moment; Indicates the The mean value of the cutting force at all comparison moments in the target error history period; Represents an exponential function with a natural constant as the base, and the embodiment adopts Model to present inverse proportional relationship and normalization processing, As the input of the model, the implementer can choose the inverse proportional function and normalization function according to the actual situation;

[0073] Among them, if The greater the change in cutting force in the target error history period, and the lower the similarity of cutting force at the comparison moment, the lower the change in cutting force in the target error history period, The errors in the target error history period are caused by tool wear.

[0074] Preferably, in some implementations of the embodiments of the present invention, since both tool wear and vibration generated during the machining process can cause precision errors in boring and milling machining, and the error caused by tool wear is irreversible, it is necessary to identify the error caused by tool wear; based on the change in the difference between the cutting parameters and the initial cutting parameters within the target error historical time period, the specific method for obtaining the tool wear characteristic value in each target error historical time period is as follows:

[0075] The first The sequence of error amplitudes of all target moments in the target error history period is recorded as target error sequence; using the STF decomposition algorithm to Decompose the target error sequence to obtain several components;

[0076] It should be noted that, for any component, the error caused by wear is irreversible and gradually increases, which means that the difference between adjacent error amplitudes in the component is gradually increasing, that is, the more negative the first-order difference value is, the more likely the component is a wear component; the STF decomposition algorithm is an existing technology, and this embodiment will not be described in detail here.

[0077] Preset a difference threshold parameter , wherein this embodiment is based on This example is described as an example, and this embodiment is not specifically limited. Depends on the specific implementation situation;

[0078] Jordi The first The margin of error and The difference between the error margins is greater than or equal to the difference threshold parameter , will The error amplitude is recorded as the wear error amplitude; The ratio of all wear error amplitudes to all error amplitudes in the first component is taken as the The probability that each component belongs to the wear component;

[0079] In the Among all the components after the target error sequence is decomposed, the component corresponding to the maximum value of the wear component possibility is recorded as The wear component of the target error sequence;

[0080] Among them, if The greater the difference between the maximum and minimum values ​​of the wear error amplitude in the wear component of a target error sequence, the greater the error increment caused by tool wear.

[0081] The first The difference between the maximum and minimum values ​​of the wear error amplitude in the wear component of the target error sequence is recorded as the wear error increment; the wear error increment is compared with the The product of the probability of the wear component of the target error sequence belonging to the wear component is taken as the Tool wear characteristic values ​​in target error history time periods;

[0082] The specific formula is:

[0083]

[0084] Where, Indicates the Tool wear characteristic values ​​in target error history time periods; Indicates the wear error increment and the The wear component of the target error sequence belongs to the wear component possibility; Indicates the The maximum value of the wear error amplitude in the wear component of the target error sequence; Indicates the The minimum value of the wear error amplitude in the wear component of the target error sequence.

[0085] Preferably, in some implementations of the embodiments of the present invention, a specific method for obtaining the tool wear impact value in each target error history time period according to the tool wear characteristic value and the cutting force change impact value is:

[0086] The first The tool wear characteristic value in the target error history period is The sum of the maximum values ​​of the wear error amplitudes in the wear components of the target error sequences is recorded as the first sum value; the first sum value is added to the The normalized value of the product of the cutting force change influence values ​​in the target error history time period is used as the first Tool wear impact value in target error history time period;

[0087] The specific formula is:

[0088]

[0089] Where, Indicates the Tool wear impact value in target error history time period; Indicates the The impact value of cutting force changes in the target error history period; Indicates the Tool wear characteristic values ​​in target error history time periods; Indicates the The maximum value of the wear error amplitude in the wear component of the target error sequence; Linear normalization value.

[0090] Preferably, in some implementations of the embodiments of the present invention, since the error caused by tool wear is irreversible, the impact on the boring and milling machining accuracy error is greater than the impact caused by vibration. The specific method for obtaining the machining accuracy error impact value for each target error historical time period based on the tool wear impact value and the machining accuracy error value is as follows:

[0091] Preset a constant parameter , wherein this embodiment is based on This example is described as an example, and this embodiment is not specifically limited. Depends on the specific implementation situation;

[0092] Will With the The sum of the tool wear influence values ​​in the target error history time period is recorded as the second sum; the second sum is added to the The product of the machining accuracy error values ​​of the target error historical time period is used as the The machining accuracy error impact value of the target error historical time period;

[0093] The specific formula is:

[0094]

[0095] Where, Indicates the The machining accuracy error impact value of the target error historical time period; Indicates the Tool wear impact value in target error history time period; Indicates the The machining accuracy error value of the target error historical period; Indicates a preset constant parameter.

[0096] At this point, the machining accuracy error impact value of each target error historical time period is obtained through the above method.

[0097] Step S004: obtaining an acquisition frequency adjustment factor at the current moment according to a change trend of the machining accuracy error influence value in different target error historical time periods; and obtaining a boring and milling machining data acquisition frequency at the current moment based on the acquisition frequency adjustment factor.

[0098] It should be noted that both tool wear and vibration generated during machining will lead to deterioration in the accuracy of boring and milling machining, and the error caused by vibration will be corrected by the CNC machine tool itself over time, but the error caused by tool wear will gradually increase over time; therefore, it is necessary to adjust the frequency of collecting cutting parameter data in time according to the tool wear situation for the self-adjustment of the CNC machine tool; it is necessary to analyze the changing trend of the machining accuracy error influence value in different target error historical time periods to obtain the boring and milling machining data collection frequency adjustment factor at the current moment.

[0099] Preferably, in some implementations of the embodiments of the present invention, in the target error historical time period, if the machining accuracy error influence value first increases and then decreases to the initial state, it means that the larger proportion of the boring and milling machining accuracy error influence is caused by the vibration generated during the machining process; on the contrary, if the machining accuracy error influence value continues to rise, so that the final machining accuracy error influence value is too large compared with the initial state, it means that the larger proportion of the boring and milling machining accuracy error influence is caused by tool wear, and in this case, more frequent collection of cutting parameters is required for self-adjustment of the CNC machine tool; according to the changing trend of the machining accuracy error influence value in different target error historical time periods, the specific method for obtaining the collection frequency adjustment factor at the current moment is:

[0100] The first target error historical period and the The difference in the machining accuracy error impact value between the target error historical time periods is recorded as The error impact difference value of the target error historical time period; if the error impact difference value is less than or equal to the difference threshold parameter , then target error history time period, recorded as the vibration error history time period; if the error impact difference value is greater than the difference threshold parameter , then The target error history time period is recorded as , and the wear error history time period is recorded as ;

[0101] The difference between the machining accuracy error influence value of the last target error historical time period and the machining accuracy error influence value of the first target error historical time period is recorded as the first difference; the ratio between the number of wear error historical time periods and the number of vibration error historical time periods is recorded as the first ratio; the normalized value of the product of the first difference and the first ratio is recorded as the acquisition frequency adjustment factor at the current moment;

[0102] The specific formula is:

[0103] Where, Indicates the current acquisition frequency adjustment factor; Indicates the machining accuracy error impact value of the last target error historical period; Indicates the machining accuracy error impact value of the first target error historical period; Indicates the number of wear error history time periods; Indicates the number of vibration error history time periods; Linear normalization value.

[0104] Preferably, in some implementations of the embodiments of the present invention, if the current acquisition frequency adjustment factor is larger, it indicates that the boring and milling processing accuracy has deteriorated due to tool wear as the main reason, and it is necessary to increase the acquisition frequency of the boring and milling processing data of the CNC machine tool for self-adjustment of the CNC machine tool; based on the acquisition frequency adjustment factor, the specific method for obtaining the current boring and milling processing data acquisition frequency is:

[0105] Will The sum of the sum and the initial boring and milling processing data acquisition frequency is recorded as the third sum; the product of the third sum and the acquisition frequency adjustment factor at the current moment is used as the boring and milling processing data acquisition frequency at the current moment;

[0106] The specific formula is:

[0107]

[0108] Where, Indicates the frequency of boring and milling processing data collection at the current moment; Indicates the initial boring and milling processing data acquisition frequency; Indicates the frequency adjustment factor of boring and milling processing data acquisition at the current moment; Indicates a preset constant parameter.

[0109] It should be noted that As the collection frequency for the next ten minutes; then collect the cutting parameters for the next 10 minutes, and use the above method to obtain the boring and milling processing data collection frequency at the future moment, and then according to the boring and milling processing data collection frequency at the future moment, obtain the next collection frequency for the next 10 minutes, and so on, and continuously iterate; through higher frequency data collection, the changing trend of boring and milling processing errors can be captured more quickly; when the influence of wear gradually increases, the CNC machine tool needs to make adjustments quickly; through more frequent data collection, the current processing accuracy can be fed back more timely, and the system can adjust the processing parameters more quickly to avoid accuracy deviation caused by wear.

[0110] See also Figure 2 , which shows a characteristic relationship flow chart of a processing data acquisition method applied to CNC machine tools;

[0111] Through the above steps, the processing data acquisition method applied to CNC machine tools is completed.

[0112] Another embodiment of the present invention provides a processing data acquisition system for a CNC machine tool. The system includes a memory and a processor. When the processor executes a computer program stored in the memory, the processor performs steps S001 to S004 of the above method.

[0113] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A processing data acquisition method applied to a CNC machine tool, characterized in that: The method comprises the following steps: Obtaining the cutting parameter sequence and initial cutting parameters of the CNC machine tool during boring and milling processing; the initial cutting parameters include cutting force, cutting depth and feed rate; By analyzing the differences between the cutting parameter sequence and the initial cutting parameters, several target moments are obtained; according to the fluctuations between the cutting parameters at the target moments and the initial cutting parameters, several target error history time periods are obtained; according to the differences between the cutting parameters in different dimensions and the initial cutting parameters, the machining accuracy error values ​​of the target error history time periods are obtained; According to the change amplitude of the cutting parameters, the cutting force change influence value in the target error history period is obtained; according to the difference change between the cutting parameters and the initial cutting parameters, the tool wear characteristic value in the target error history period is obtained; according to the tool wear characteristic value and the cutting force change influence value, the tool wear influence value in the target error history period is obtained; according to the tool wear influence value and the machining accuracy error value, the machining accuracy error influence value in the target error history period is obtained; According to the change trend of the machining accuracy error influence value in different target error historical time periods, the acquisition frequency adjustment factor at the current moment is obtained; based on the acquisition frequency adjustment factor, the boring and milling processing data acquisition frequency at the current moment is obtained; The specific method for obtaining the current acquisition frequency adjustment factor based on the change trend of the machining accuracy error impact value in different target error historical time periods is: The first target error historical period and the The difference in the machining accuracy error impact value between the target error historical time periods is recorded as The error impact difference value of the target error historical time period; if the error impact difference value is less than or equal to the difference threshold parameter , then target error history time period, recorded as the vibration error history time period; if the error impact difference value is greater than the difference threshold parameter , then The target error history time period is recorded as , and the wear error history time period is recorded as ; The difference between the machining accuracy error influence value of the last target error historical time period and the machining accuracy error influence value of the first target error historical time period is recorded as the first difference; the ratio between the number of wear error historical time periods and the number of vibration error historical time periods is recorded as the first ratio; the normalized value of the product of the first difference and the first ratio is recorded as the acquisition frequency adjustment factor at the current moment.

2. The processing data acquisition method for a CNC machine tool according to claim 1, characterized in that: The specific method of obtaining several target moments by analyzing the differences between the cutting parameter sequence and the initial cutting parameters is as follows: All sampling moments before the current moment are recorded as historical moments; Preset an error threshold parameter , will The initial cutting parameters of the first dimension and the The first historical moment The normalized value of the absolute value of the difference between the cutting parameters of the first dimension is recorded as The first historical moment The error factor of the cutting parameters of the first dimension; The mean error factor of all dimensions of cutting parameters at the historical moment is recorded as The error margin of the historical moment; the error margin is greater than or equal to the error threshold parameter The historical moment is recorded as the target moment.

3. The processing data acquisition method applied to a CNC machine tool according to claim 2, characterized in that: The specific method for obtaining several target error historical time periods based on the difference fluctuation between the cutting parameters at the target moment and the initial cutting parameters is as follows: The sequence of consecutive target moments is recorded as an error sequence. For any error sequence, if the normalized value of the variance of the error amplitudes of all target moments in the error sequence is greater than or equal to the error threshold parameter , record the time period consisting of all target moments in any error sequence as the target error history time period.

4. The processing data acquisition method for a CNC machine tool according to claim 2, characterized in that: The specific method for obtaining the machining accuracy error value of the target error historical time period based on the difference between the cutting parameters of different dimensions and the initial cutting parameters is: In the In the target error history period, the first The ratio between the mean of the error factor of the cutting parameter in the dimension and the mean of the error amplitude of all target moments is taken as the first Weight factors of cutting parameters of different dimensions; The first The target error in the historical period The weight factor of the cutting parameters of the first dimension is The target error history period of all target moments The product of the mean values ​​of the error factors of the cutting parameters in different dimensions is recorded as The precision error factors of cutting parameters in different dimensions; The first The normalized value of the product of the number of all target moments in the target error history period and the cumulative sum of the precision error factors of the cutting parameters of all dimensions is used as the first The machining accuracy error value of the target error historical time period.

5. The processing data acquisition method for a CNC machine tool according to claim 1, characterized in that: The specific method for obtaining the cutting force change impact value in the target error history time period according to the change amplitude of the cutting parameters is: In the In the target error history time period, the target moment with the same cutting depth and feed amount is recorded as the comparison moment; The first The difference between the maximum and minimum cutting forces at all target moments in the target error history period is recorded as the variation of the cutting force; The target error in the historical period The cutting force at the first comparison moment is The absolute value of the difference between the mean values ​​of the cutting forces at all comparison moments in the target error history period is recorded as The cutting force difference factor at the first comparison moment; The product of the inverse proportional normalized value of the cumulative sum of the cutting force difference factors of all comparison moments in the target error history period and the change amplitude of the cutting force is taken as the first The impact value of cutting force changes in the target error history period.

6. The processing data acquisition method for a CNC machine tool according to claim 2, characterized in that: The specific method for obtaining the tool wear characteristic value in the target error history time period according to the difference between the cutting parameters and the initial cutting parameters is: The first The sequence of error amplitudes of all target moments in the target error history period is recorded as target error sequence; using the STF decomposition algorithm to Decompose the target error sequence to obtain several components; Preset a difference threshold parameter , if The first The margin of error and The difference between the error margins is greater than or equal to the difference threshold parameter , will The error amplitude is recorded as the wear error amplitude; The ratio of all wear error amplitudes to all error amplitudes in the first component is taken as the The probability that the components belong to the wear component; In the Among all the components after the target error sequence is decomposed, the component corresponding to the maximum value of the wear component possibility is recorded as The wear component of the target error sequence; The first The difference between the maximum and minimum values ​​of the wear error amplitude in the wear component of the target error sequence is recorded as the wear error increment; The wear error increment is compared with the The product of the probability of the wear component of the target error sequence belonging to the wear component is taken as the Tool wear characteristic values ​​in a target error history period.

7. The processing data acquisition method for a CNC machine tool according to claim 6, characterized in that: The specific method for obtaining the tool wear influence value in the target error history time period based on the tool wear characteristic value and the cutting force change influence value is: The first The tool wear characteristic value in the target error history period is The sum of the maximum values ​​of the wear error amplitudes in the wear components of the target error sequences is recorded as the first sum value; the first sum value is added to the The normalized value of the product of the cutting force change influence values ​​in the target error history time period is used as the first The tool wear impact value in the target error history period.

8. The processing data acquisition method for a CNC machine tool according to claim 1, characterized in that: The specific method for obtaining the machining accuracy error impact value of the target error historical time period based on the tool wear impact value and the machining accuracy error value is: Preset a constant parameter ,Will With the The sum of the tool wear influence values ​​in the target error history time period is recorded as the second sum; the second sum is added to the The product of the machining accuracy error values ​​of the target error historical time period is used as the The impact value of machining accuracy error in a target error historical period.

9. A processing data acquisition system for a numerically controlled machine tool, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the computer program is executed by a processor, the steps of the processing data acquisition method applied to a CNC machine tool as described in any one of claims 1 to 8 are implemented.

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