A tool control optimization method and system for parts processing

Abstract

The present invention discloses a tool control optimization method and system applied to part processing, which relates to the technical field of machine tool tool control, including setting a tool processing path of a tool on a processing material, dividing the tool processing path according to a plurality of continuous functional stages; determining the tool life according to the service information of the tool, and determining the acceptable wear degree of the tool in each functional stage; selecting a plurality of proofreading points in the tool processing path of each functional stage; defining proofreading point tool control quality index, adjusting the prediction function of the processing process parameters according to the deviation and the tool control quality index; adjusting the processing control parameters by adjusting the prediction function of the processing process parameters, so as to optimize the tool control. The prediction function is accurately adjusted according to the deviation and the tool control quality index, which ensures the effectiveness of the tool control optimization, improves the accuracy and adaptability of the tool control, and thus improves the efficiency of part processing.

Description

Technical Field

[0001] The present application relates to the technical field of machine tool tool control, and more specifically, to a tool control optimization method and system for part processing. Background Art

[0002] Tool control optimization solutions for parts processing involve the field of mechanical processing, especially the selection, use and maintenance of tools. In traditional mechanical processing, tool control mainly relies on experience and operator skills. However, with the development of modern manufacturing, the requirements for processing accuracy and efficiency are getting higher and higher, and traditional tool control methods can no longer meet the needs of modern production.

[0003] In the existing technology, the processing materials and parts requirements have determined the selection of tools. The effectiveness of parts processing mainly depends on the control effect of the tool. The processing control parameters (cutting speed, feed rate, cutting depth, etc.) are often controlled in real time according to the changes in the processing parameters (cutting force, temperature, vibration, etc.). Therefore, the prediction of processing parameters is particularly important. The current prediction model or function of processing parameters is often fixed and cannot adapt to the changing processing conditions, resulting in low accuracy and adaptability of tool control.

[0004] Therefore, how to improve the accuracy and adaptability of tool control is a technical problem that needs to be solved. Summary of the invention

[0005] The present invention provides a tool control optimization method for part processing, which is used to solve the technical problems of poor accuracy and low adaptability of tool control caused by unchanged processing process parameter prediction function in the prior art. The method comprises:

[0006] According to the part drawing, basic information of the processing material and basic information of the tool, a tool processing path of the tool on the processing material is set, the tool processing path is divided into multiple continuous functional stages, the tool processing path corresponding to each functional stage is determined, and the division of the path and the functional stage is completed;

[0007] Determine the tool life according to the service information of the tool, and obtain an acceptable wear degree of the tool through tool life mapping, assign the acceptable wear degree of the tool to each functional stage, and determine the acceptable wear degree of the tool in each functional stage;

[0008] Determine a prediction function of machining process parameters, predict the change of ideal values ​​of machining process parameters in each functional stage through the prediction function, select multiple calibration points in the tool machining path of each functional stage, and compare the deviation between the ideal value of machining process parameters and the actual value of machining process parameters through the calibration points;

[0009] The tool control quality index of the calibration point is defined by the tool processing path completion time and the acceptable wear degree of the tool, and the prediction function of the processing process parameters is adjusted according to the deviation situation and the tool control quality index;

[0010] The tool control is optimized by adjusting the machining control parameters through the prediction function of the machining process parameters.

[0011] In some embodiments of the present application, a tool processing path of a tool on a processing material is set according to a part drawing, basic information of a processing material, and basic information of a tool, and the tool processing path is divided into a plurality of continuous functional stages, and a tool processing path corresponding to each functional stage is determined, including:

[0012] Generate multiple initial tool processing paths through CAM software, and determine the processing area and non-processing area, the starting point and the end point in the initial tool processing path;

[0013] Calculate the proportion of non-machining area in each initial tool processing path to determine the idle stroke, calculate the length of the straight path and the length of the curved path, and the curvature of the curved path in each initial tool processing path;

[0014] Determine the straight path processing difficulty and the curved path processing difficulty respectively according to the straight path length and the curved path length and the curvature of the curved path in the initial tool processing path, determine the weights of the straight path processing difficulty and the curved path processing difficulty based on the part drawing, basic information of the processing material and basic information of the tool, and perform weighted summation of the straight path processing difficulty and the curved path processing difficulty to obtain the total processing path difficulty;

[0015] An initial tool machining path is determined as the tool machining path according to the idle stroke and the total difficulty of the machining path. The functional stages include the cutting-in stage, the cutting stage and the over-cutting-out stage. The tool machining path is divided into three stages: the cutting-in stage, the cutting stage and the over-cutting-out stage.

[0016] In some embodiments of the present application, determining the tool life according to the service information of the tool includes:

[0017] The service information of the tool includes the number of processing times, the material of each processing, the processing control parameters, the tool wear type and the wear amount corresponding to the tool wear type;

[0018]

[0019] Among them, S is the tool life, n is the number of processing times, α i is the wear weight corresponding to the material processed for the i-th time, Q i is the average value index of the processing control parameters of the i-th processing, t iis the tool usage time of the i-th processing, m is the total number of tool wear types, β j is the wear weight of the jth tool wear type, W j is the wear amount of the jth tool wear type, S 0 is the tool wear life after mapping, The tool loss life is mapped to the average value of the two loss quantities.

[0020] In some embodiments of the present application, a prediction function of a processing parameter is determined, and the change of an ideal value of the processing parameter in each functional stage is predicted by the prediction function, including:

[0021] The processing parameter data and other related data of different processing paths in the past processing history are collected, the data are standardized and normalized, and a processing parameter prediction model is established to determine the prediction function of the processing parameters. The prediction model can predict the ideal values ​​of the processing parameters on different processing paths.

[0022] In some embodiments of the present application, multiple calibration points are selected in the tool processing path of each functional stage, including:

[0023] Machining process parameters include cutting forces, temperature, and vibration;

[0024] Select several points near the starting point and end point of the tool processing path in the cutting phase as calibration points;

[0025] According to the prediction function of the machining process parameters, three maximum points of the ideal maximum cutting force, the ideal maximum temperature and the ideal maximum vibration on the tool machining path in the cutting stage are predicted, and several points near each of the three maximum points are selected as calibration points;

[0026] The point of the ideal maximum vibration value and the path segment with the largest ideal vibration value change rate on the tool machining path in the overcutting stage are predicted according to the prediction function of the machining process parameters, and several points near the point and between the path segments are selected as calibration points.

[0027] In some embodiments of the present application, the deviation between the ideal value of the processing parameter and the actual value of the processing parameter is compared through the calibration point, including:

[0028] The ideal value of the machining process parameter and the actual value of the machining process parameter are projected onto a curve graph whose horizontal axis is the path length and whose vertical axis is the size of the machining process parameter, respectively, to obtain an ideal curve and an actual curve;

[0029] The ideal curve and the actual curve are split into three types of calibration curves through calibration points: between the starting point and the calibration point, between the calibration point and the calibration point, and between the calibration point and the end point. The ideal curve and the actual curve in the calibration curve are aligned on the horizontal axis scale, and the ideal value and the actual value on each horizontal axis unit scale are compared to obtain the deviation on each horizontal axis unit scale, thereby determining the average deviation value.

[0030] In some embodiments of the present application, after selecting a plurality of calibration points in the tool processing path of each functional stage, the method further includes:

[0031] The acceptable wear degree of the tool in each functional stage is allocated to each calibration point, and the acceptable wear degree of the tool corresponding to each calibration point is determined.

[0032] In some embodiments of the present application, the tool control quality index of the calibration point is defined by the tool processing path completion time and the acceptable wear degree of the tool, including:

[0033] Z a =γ 1 (t a前 -T a前 )+γ 2 (h a前 -H a前 )+γ 3 R a前 ;

[0034] Among them, Z a is the tool control quality index of the ath calibration point, γ 1 , γ 2 , γ 3 are the mass conversion coefficients corresponding to the completion time, wear degree and machining accuracy, t a前 is the time threshold for completing all paths before the ath calibration point, T a前 h is the time taken to complete all paths before the ath calibration point, a前 H is the acceptable wear degree of the tool for all paths before completing the ath calibration point. a前 The actual tool wear degree of all paths before the ath calibration point is R a前 The degree of part processing accuracy corresponding to all paths completed before the ath calibration point.

[0035] In some embodiments of the present application, the prediction function of adjusting the machining process parameters according to the deviation situation and the tool control quality index includes:

[0036] If the average deviation value does not exceed the deviation threshold, and the tool control quality index exceeds the control quality index threshold, the prediction function of the machining process parameters is not adjusted;

[0037] Otherwise, the prediction function of the machining process parameters is adjusted;

[0038]

[0039] Among them, Y' b+1 is the prediction function of the machining process parameters of the b+1th calibration point, Y b is the prediction function of the machining process parameters of the bth calibration point, ε b is the compensation coefficient corresponding to the type of calibration curve corresponding to the bth calibration point, c b is the difference between the average deviation value of the calibration curve corresponding to the bth calibration point and the deviation threshold, exp is an exponential function, k is a preset constant, x b is the average deviation value of the calibration curve corresponding to the bth calibration point, x b阈 is the deviation threshold of the calibration curve corresponding to the bth calibration point, v b is the tool control quality index of the bth calibration point, v b阈 is the control quality index threshold of the bth calibration point, is the first correction factor obtained by mapping the difference between the average deviation value of the calibration curve corresponding to the bth calibration point and the deviation threshold, d b is the difference between the tool control quality index of the bth calibration point and the control quality index threshold, is the second correction factor obtained by mapping the difference between the tool control quality index of the bth calibration point and the control quality index threshold.

[0040] Correspondingly, the present application also provides a tool control optimization system for part processing, comprising:

[0041] A setting module is used to set a tool processing path of a tool on a processing material according to a part drawing, basic information of processing materials and basic information of a tool, divide the tool processing path into a plurality of continuous functional stages, determine the tool processing path corresponding to each functional stage, and complete the division of the path and the functional stage;

[0042] A wear module is used to determine the tool life according to the service information of the tool, and obtain an acceptable wear degree of the tool through tool life mapping, assign the acceptable wear degree of the tool to each functional stage, and determine the acceptable wear degree of the tool in each functional stage;

[0043] A calibration module is used to determine a prediction function of a machining process parameter, predict the change of the ideal value of the machining process parameter at each functional stage through the prediction function, select multiple calibration points in the tool machining path at each functional stage, and compare the deviation between the ideal value of the machining process parameter and the actual value of the machining process parameter through the calibration points;

[0044] An adjustment module is used to define the tool control quality index of the calibration point by the tool processing path completion time and the acceptable wear degree of the tool, and adjust the prediction function of the processing process parameters according to the deviation situation and the tool control quality index;

[0045] The control module is used to adjust the machining control parameters by adjusting the prediction function of the machining process parameters to optimize the tool control.

[0046] By applying the above technical solutions, a tool processing path of the tool on the processing material is set according to the part drawing, basic information of the processing material and basic information of the tool, and the tool processing path is divided into multiple continuous functional stages, and the tool processing path corresponding to each functional stage is determined to complete the division of the path and the functional stage; the tool life is determined according to the service information of the tool, and an acceptable wear degree of the tool is obtained through tool life mapping, and the acceptable wear degree of the tool is assigned to each functional stage to determine the acceptable wear degree of the tool in each functional stage; the prediction function of the processing process parameters is determined, and the change of the ideal value of the processing process parameters in each functional stage is predicted through the prediction function, and multiple proofreading points are selected in the tool processing path of each functional stage, and the deviation between the ideal value of the processing process parameters and the actual value of the processing process parameters is compared through the proofreading points; the tool control quality index of the proofreading point is defined by the completion time of the tool processing path and the acceptable wear degree of the tool, and the prediction function of the processing process parameters is adjusted according to the deviation and the tool control quality index; the processing control parameters are adjusted through the prediction function of the adjusted processing process parameters to achieve optimization of tool control. This application sets a tool processing path for the tool on the processing material based on the part drawing, basic information of the processing material and basic information of the tool, and divides the tool processing path into multiple continuous functional stages, so as to select the appropriate tool processing path and divide the processing functional stages, providing a solid foundation for subsequent control. The tool life is determined according to the service information of the tool, the remaining life of the tool is accurately evaluated, and the degree of wear is allocated to each proofreading point in each stage, thereby ensuring that the wear can be effectively monitored. The prediction function of the processing process parameters is adjusted according to the deviation and the tool control quality index, and the prediction function is accurately adjusted according to the deviation and the tool control quality index, ensuring the effectiveness of the tool control optimization, improving the accuracy and adaptability of the tool control, and thus improving the efficiency of part processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0048] Figure 1 A schematic flow chart of a tool control optimization method for part machining proposed in an embodiment of the present invention is shown;

[0049] Figure 2 A schematic structural diagram of a tool control optimization system for part machining proposed in an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0051] The present application embodiment provides a tool control optimization method for part processing, such as Figure 1 As shown, the method comprises the following steps:

[0052] Step S101, according to the part drawing, basic information of the processing material and basic information of the tool, a tool processing path of the tool on the processing material is set, the tool processing path is divided into multiple continuous functional stages, the tool processing path corresponding to each functional stage is determined, and the division of the path and the functional stage is completed.

[0053] In this embodiment, selecting a reasonable tool processing path can effectively ensure the effectiveness of tool processing. The process of tool processing the material can be divided into the following stages:

[0054] 1. Entry stage:

[0055] -The tool starts moving from the non-machining area of ​​the workpiece and gradually enters the machining area.

[0056] -High cutting forces may occur during this stage as the tool needs to overcome the initial resistance of the workpiece material.

[0057] 2. Cutting stage:

[0058] -The tool cuts on the workpiece to remove excess material.

[0059] -Cutting forces, temperature and tool wear reach their peak in this stage.

[0060] -The quality of the cutting stage directly affects the final accuracy, surface quality and tool life of the workpiece.

[0061] 3. Transition phase:

[0062] -The tool gradually withdraws from the machining area and no longer cuts.

[0063] - This stage may generate large vibrations and shocks because the tool stops cutting suddenly, resulting in a sudden reduction in cutting forces.

[0064] 4. Cut-out stage:

[0065] -The tool completely exits the non-machining area of ​​the workpiece.

[0066] - Cutting forces are usually not generated during this stage, but vibrations and shocks may occur.

[0067] In order to save computing resources, the cut-out and transition stages are combined into a new stage.

[0068] In some embodiments of the present application, a tool processing path of a tool on a processing material is set according to a part drawing, basic information of a processing material, and basic information of a tool, and the tool processing path is divided into a plurality of continuous functional stages, and a tool processing path corresponding to each functional stage is determined, including:

[0069] Generate multiple initial tool processing paths through CAM software, and determine the processing area and non-processing area, the starting point and the end point in the initial tool processing path;

[0070] Calculate the proportion of non-machining area in each initial tool processing path to determine the idle stroke, calculate the length of the straight path and the length of the curved path, and the curvature of the curved path in each initial tool processing path;

[0071] Determine the straight path processing difficulty and the curved path processing difficulty respectively according to the straight path length and the curved path length and the curvature of the curved path in the initial tool processing path, determine the weights of the straight path processing difficulty and the curved path processing difficulty based on the part drawing, basic information of the processing material and basic information of the tool, and perform weighted summation of the straight path processing difficulty and the curved path processing difficulty to obtain the total processing path difficulty;

[0072] An initial tool machining path is determined as the tool machining path according to the idle stroke and the total difficulty of the machining path. The functional stages include the cutting-in stage, the cutting stage and the over-cutting-out stage. The tool machining path is divided into three stages: the cutting-in stage, the cutting stage and the over-cutting-out stage.

[0073] In this embodiment, the straight path processing difficulty and the curved path processing difficulty are determined according to the straight path length and the curved path length and the curvature of the curved path in the initial tool processing path. The longer the straight path length, the lower the processing difficulty is usually, because the movement of the tool on the straight path is relatively simple. The longer the curved path length, the higher the processing difficulty is usually, because the tool needs to adjust its direction frequently. The greater the curvature, the more complex the movement of the tool on the curved path, and the higher the processing difficulty is usually. The smaller the curvature, the simpler the movement of the tool on the curved path, and the lower the processing difficulty is usually. An initial tool processing path is determined as the tool processing path based on the idle stroke and the total difficulty of the processing path, and a path with relatively few idle strokes and low total difficulty of the processing path is selected.

[0074] It should be noted that the idle stroke refers to the movement path of the tool in the non-machining area, which does not participate in material removal.

[0075] Step S102, determining the tool life according to the service information of the tool, and obtaining an acceptable wear degree of the tool through tool life mapping, allocating the acceptable wear degree of the tool to each functional stage, and determining the acceptable wear degree of the tool in each functional stage.

[0076] In this embodiment, the remaining life of the tool is determined based on the service information (usage) of the tool, and the processing difficulty of each functional stage is estimated, and the acceptable wear degree of the tool is allocated accordingly.

[0077] In some embodiments of the present application, determining the tool life according to the service information of the tool includes:

[0078] The service information of the tool includes the number of processing times, the material of each processing, the processing control parameters, the tool wear type and the wear amount corresponding to the tool wear type;

[0079]

[0080] Among them, S is the tool life, n is the number of processing times, α i is the wear weight corresponding to the material processed for the i-th time, Q i is the average value index of the processing control parameters of the i-th processing, t i is the tool usage time of the i-th processing, m is the total number of tool wear types, β j is the wear weight of the jth tool wear type, W j is the wear amount of the jth tool wear type, S 0 is the tool wear life after mapping, The tool loss life is mapped to the average value of the two loss quantities.

[0081] In this embodiment, the degree of wear in the past is estimated by the number of processing times, the material of each processing, and the processing control parameters. The tool wear type and the wear amount corresponding to the tool wear type, such as cutting edge wear, back tool face wear, front tool face wear, etc., are the wear reflected on the surface. The average value of the two types of wear is taken and mapped to obtain the tool loss life.

[0082] Step S103, determine the prediction function of the machining process parameters, predict the change of the ideal value of the machining process parameters in each functional stage through the prediction function, select multiple calibration points in the tool machining path of each functional stage, and compare the deviation between the ideal value of the machining process parameters and the actual value of the machining process parameters through the calibration points.

[0083] In this embodiment, the processing parameters are parameters generated during the processing, such as cutting force, temperature, vibration, etc. The cutting process itself is a dynamically changing system, in which parameters such as cutting force, temperature, vibration, etc. will continue to change as the processing progresses. Here, the prediction function of the processing parameters is determined based on the processing parameter data and other related data through machine learning or statistics. And select several points with special significance (maximum cutting force, maximum temperature, maximum vibration) on the path of each stage as calibration points to compare the deviation between the actual processing parameters and the ideal processing parameters.

[0084] In some embodiments of the present application, a prediction function of a processing parameter is determined, and the change of an ideal value of the processing parameter in each functional stage is predicted by the prediction function, including:

[0085] The processing parameter data and other related data of different processing paths in the past processing history are collected, the data are standardized and normalized, and a processing parameter prediction model is established to determine the prediction function of the processing parameters. The prediction model can predict the ideal values ​​of the processing parameters on different processing paths.

[0086] It should be noted that how to establish the prediction model or prediction function here is not the protection point of this application. As long as the above requirements are met, it falls within the protection scope of this application.

[0087] Select multiple calibration points in the tool path at each functional stage, including:

[0088] Machining process parameters include cutting forces, temperature, and vibration;

[0089] Select several points near the starting point and end point of the tool processing path in the cutting phase as calibration points;

[0090] According to the prediction function of the machining process parameters, three maximum points of the ideal maximum cutting force, the ideal maximum temperature and the ideal maximum vibration on the tool machining path in the cutting stage are predicted, and several points near each of the three maximum points are selected as calibration points;

[0091] The point of the ideal maximum vibration value and the path segment with the largest ideal vibration value change rate on the tool machining path in the overcutting stage are predicted according to the prediction function of the machining process parameters, and several points near the point and between the path segments are selected as calibration points.

[0092] In this embodiment, several points are selected near the starting point and the end point of the tool processing path in the cutting-in phase as proofreading points. A large cutting force may be generated in this phase because the tool needs to overcome the initial resistance of the workpiece material. Through multiple points near the starting point and the end point, the orderly change of the cutting force can be obtained. According to the prediction function of the processing parameters, the three maximum points of the ideal maximum cutting force, the ideal maximum temperature and the ideal maximum vibration on the tool processing path in the cutting phase are predicted, and the maximum processing parameters can be reasonably monitored. According to the prediction function of the processing parameters, the point of the ideal maximum vibration and the path segment with the largest ideal vibration value change rate on the tool processing path in the over-cut-out phase are predicted, and the area where the tool may generate vibration and impact when exiting the cutting area is selected as the proofreading point. The maximum ideal vibration value change rate can set a preset path length, and the ideal vibration value change rate is calculated.

[0093] In some embodiments of the present application, the deviation between the ideal value of the processing parameter and the actual value of the processing parameter is compared through the calibration point, including:

[0094] The ideal value of the machining process parameter and the actual value of the machining process parameter are projected onto a curve graph whose horizontal axis is the path length and whose vertical axis is the size of the machining process parameter, respectively, to obtain an ideal curve and an actual curve;

[0095] The ideal curve and the actual curve are split into three types of calibration curves through calibration points: between the starting point and the calibration point, between the calibration point and the calibration point, and between the calibration point and the end point. The ideal curve and the actual curve in the calibration curve are aligned on the horizontal axis scale, and the ideal value and the actual value on each horizontal axis unit scale are compared to obtain the deviation on each horizontal axis unit scale, thereby determining the average deviation value.

[0096] In this embodiment, the ideal curve and the actual curve are split into three types of calibration curves: between the starting point and the calibration point, between the calibration point and the calibration point, and between the calibration point and the end point through the calibration points. The starting point is the starting point of each stage, and the end point is the end point of each stage. A complete ideal curve and actual curve are composed of the starting point and the calibration point, multiple calibration points and calibration points, and the calibration point and the end point, which is convenient for comparing the ideal parameters with the actual parameters in a smaller range.

[0097] In some embodiments of the present application, after selecting a plurality of calibration points in the tool processing path of each functional stage, the method further includes:

[0098] The acceptable wear degree of the tool in each functional stage is allocated to each calibration point, and the acceptable wear degree of the tool corresponding to each calibration point is determined.

[0099] Step S104, defining the tool control quality index of the calibration point by the tool machining path completion time and the acceptable tool wear degree, and adjusting the prediction function of the machining process parameters according to the deviation and the tool control quality index.

[0100] In this embodiment, the tool control quality index of the calibration point is defined by the tool processing path completion time, the acceptable wear degree of the tool, and the processing accuracy. It is determined whether to adjust the prediction function of the processing process parameters according to the deviation situation and the tool control quality index.

[0101] In some embodiments of the present application, the tool control quality index of the calibration point is defined by the tool processing path completion time and the acceptable wear degree of the tool, including:

[0102]

[0103] Among them, Z a is the tool control quality index of the ath calibration point, γ 1 , γ 2 , γ 3 are the mass conversion coefficients corresponding to the completion time, wear degree and machining accuracy, t a前 is the time threshold for completing all paths before the ath calibration point, T a前 h is the time taken to complete all paths before the ath calibration point, a前 H is the acceptable wear degree of the tool for all paths before completing the ath calibration point. a前 The actual tool wear degree of all paths before the ath calibration point is R a前 The degree of part processing accuracy corresponding to all paths completed before the ath calibration point.

[0104] In some embodiments of the present application, the prediction function of adjusting the machining process parameters according to the deviation situation and the tool control quality index includes:

[0105] If the average deviation value does not exceed the deviation threshold, and the tool control quality index exceeds the control quality index threshold, the prediction function of the machining process parameters is not adjusted;

[0106] Otherwise, the prediction function of the machining process parameters is adjusted;

[0107]

[0108] Among them, Y' b+1 is the prediction function of the machining process parameters of the b+1th calibration point, Y b is the prediction function of the machining process parameters of the bth calibration point, ε b is the compensation coefficient corresponding to the type of calibration curve corresponding to the bth calibration point, c b is the difference between the average deviation value of the calibration curve corresponding to the bth calibration point and the deviation threshold, exp is an exponential function, k is a preset constant, x b is the average deviation value of the calibration curve corresponding to the bth calibration point, x b阈 is the deviation threshold of the calibration curve corresponding to the bth calibration point, v b is the tool control quality index of the bth calibration point, v b阈 is the control quality index threshold of the bth calibration point, is the first correction factor obtained by mapping the difference between the average deviation value of the calibration curve corresponding to the bth calibration point and the deviation threshold, d b is the difference between the tool control quality index of the bth calibration point and the control quality index threshold, is the second correction factor obtained by mapping the difference between the tool control quality index of the bth calibration point and the control quality index threshold.

[0109] In this embodiment, if the average deviation value does not exceed the deviation threshold, and the tool control quality index exceeds the control quality index threshold, it means that the prediction function is relatively accurate and does not need to be adjusted. The average deviation value does not exceed the deviation threshold, and the tool control quality index does not exceed the control quality index threshold. Generally speaking, if the machining process parameters do not exceed the threshold, the tool control quality index is often qualified, so there is no need to consider such a situation. The proofreading curve corresponding to the proofreading point is the proofreading curve corresponding to the previous proofreading point or the starting point or the end point. For example, the starting point-s1 proofreading point, s1 proofreading point-s2 proofreading point, s2 proofreading point-s3 proofreading point, and s3 proofreading point-end point each correspond to a proofreading curve, where the proofreading curve corresponding to the s1 proofreading point is the curve of the starting point-s1 proofreading point, the proofreading curve corresponding to the s2 proofreading point is the curve of the s1 proofreading point-s2 proofreading point, and the proofreading curve corresponding to the s3 proofreading point is the curve of the s2 proofreading point-s3 proofreading point.

[0110] In this embodiment, if the average deviation value exceeds the deviation threshold and the control quality index exceeds the control quality index threshold, a compensation amount (ε b c b ), and multiply by a correction If the average deviation value exceeds the deviation threshold and the control quality index does not exceed the control quality index threshold, it is necessary to map the two difference values ​​and take the average value under the same dimension to complete the correction.

[0111] Step S105, adjusting the machining control parameters by adjusting the prediction function of the machining process parameters to optimize the tool control.

[0112] In this embodiment, the machining control parameters are cutting parameters, cutting speed (Vc): the linear speed of the tool relative to the workpiece surface per unit time. Feed rate (f): the distance the tool moves along the cutting direction or the angle the workpiece rotates in each cutting stroke. Cutting depth (ap): the depth of the tool's penetration into the workpiece surface. Here, the relationship between the prediction function of the machining process parameters and the machining control parameters can be determined by machine learning or statistics, so as to adjust the machining control parameters according to the adjusted prediction function.

[0113] It should be noted that how to determine the relationship between the prediction function and the processing control parameters is not the protection point of this application. As long as the above requirements are met, it falls within the protection scope of this application.

[0114] Through the description of the above implementation methods, those skilled in the art can clearly understand that the present invention can be implemented by hardware, or by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each implementation scenario of the present invention.

[0115] In order to further explain the technical idea of ​​the present invention, the technical solution of the present invention is now described in combination with specific application scenarios.

[0116] Correspondingly, the present application also provides a tool control optimization system for part processing, such as Figure 2 As shown, including:

[0117] A setting module is used to set a tool processing path of a tool on a processing material according to a part drawing, basic information of processing materials and basic information of a tool, divide the tool processing path into a plurality of continuous functional stages, determine the tool processing path corresponding to each functional stage, and complete the division of the path and the functional stage;

[0118] A wear module is used to determine the tool life according to the service information of the tool, and obtain an acceptable wear degree of the tool through tool life mapping, assign the acceptable wear degree of the tool to each functional stage, and determine the acceptable wear degree of the tool in each functional stage;

[0119] A calibration module is used to determine a prediction function of a machining process parameter, predict the change of the ideal value of the machining process parameter at each functional stage through the prediction function, select multiple calibration points in the tool machining path at each functional stage, and compare the deviation between the ideal value of the machining process parameter and the actual value of the machining process parameter through the calibration points;

[0120] An adjustment module is used to define the tool control quality index of the calibration point by the tool processing path completion time and the acceptable wear degree of the tool, and adjust the prediction function of the processing process parameters according to the deviation situation and the tool control quality index;

[0121] The control module is used to adjust the machining control parameters by adjusting the prediction function of the machining process parameters to optimize the tool control.

[0122] By applying the above technical solutions, a tool processing path of the tool on the processing material is set according to the part drawing, basic information of the processing material and basic information of the tool, and the tool processing path is divided into multiple continuous functional stages, and the tool processing path corresponding to each functional stage is determined to complete the division of the path and the functional stage; the tool life is determined according to the service information of the tool, and an acceptable wear degree of the tool is obtained through tool life mapping, and the acceptable wear degree of the tool is assigned to each functional stage to determine the acceptable wear degree of the tool in each functional stage; the prediction function of the processing process parameters is determined, and the change of the ideal value of the processing process parameters in each functional stage is predicted through the prediction function, and multiple proofreading points are selected in the tool processing path of each functional stage, and the deviation between the ideal value of the processing process parameters and the actual value of the processing process parameters is compared through the proofreading points; the tool control quality index of the proofreading point is defined by the completion time of the tool processing path and the acceptable wear degree of the tool, and the prediction function of the processing process parameters is adjusted according to the deviation and the tool control quality index; the processing control parameters are adjusted through the prediction function of the adjusted processing process parameters to achieve optimization of tool control. This application sets a tool processing path for the tool on the processing material based on the part drawing, basic information of the processing material and basic information of the tool, and divides the tool processing path into multiple continuous functional stages, so as to select the appropriate tool processing path and divide the processing functional stages, providing a solid foundation for subsequent control. The tool life is determined according to the service information of the tool, the remaining life of the tool is accurately evaluated, and the degree of wear is allocated to each proofreading point in each stage, thereby ensuring that the wear can be effectively monitored. The prediction function of the processing process parameters is adjusted according to the deviation and the tool control quality index, and the prediction function is accurately adjusted according to the deviation and the tool control quality index, ensuring the effectiveness of the tool control optimization, improving the accuracy and adaptability of the tool control, and thus improving the efficiency of part processing.

[0123] Those skilled in the art will appreciate that the modules in the system in the implementation scenario can be distributed in the system of the implementation scenario according to the implementation scenario description, or can be changed accordingly and located in one or more systems different from the implementation scenario. The modules in the above implementation scenario can be combined into one module, or can be further split into multiple sub-modules.

[0124] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A tool control optimization method for part processing, characterized in that: include: According to the part drawing, basic information of the processing material and basic information of the tool, a tool processing path of the tool on the processing material is set, the tool processing path is divided into multiple continuous functional stages, the tool processing path corresponding to each functional stage is determined, and the division of the path and the functional stage is completed; Determine the tool life according to the service information of the tool, and obtain an acceptable wear degree of the tool through tool life mapping, assign the acceptable wear degree of the tool to each functional stage, and determine the acceptable wear degree of the tool in each functional stage; Determine a prediction function of machining process parameters, predict the change of ideal values ​​of machining process parameters in each functional stage through the prediction function, select multiple calibration points in the tool machining path of each functional stage, and compare the deviation between the ideal value of machining process parameters and the actual value of machining process parameters through the calibration points; The tool control quality index of the calibration point is defined by the tool processing path completion time and the acceptable wear degree of the tool, and the prediction function of the processing process parameters is adjusted according to the deviation situation and the tool control quality index; The tool control is optimized by adjusting the machining control parameters through the prediction function of the machining process parameters; in, According to the part drawing, basic information of the processing material and basic information of the tool, a tool processing path of the tool on the processing material is set, and the tool processing path is divided into multiple continuous functional stages, and the tool processing path corresponding to each functional stage is determined, including: Generate multiple initial tool processing paths through CAM software, and determine the processing area and non-processing area, the starting point and the end point in the initial tool processing path; Calculate the proportion of non-machining area in each initial tool processing path to determine the idle stroke, calculate the length of the straight path and the length of the curved path, and the curvature of the curved path in each initial tool processing path; Determine the straight path processing difficulty and the curved path processing difficulty respectively according to the straight path length and the curved path length and the curvature of the curved path in the initial tool processing path, determine the weights of the straight path processing difficulty and the curved path processing difficulty based on the part drawing, basic information of the processing material and basic information of the tool, and perform weighted summation of the straight path processing difficulty and the curved path processing difficulty to obtain the total processing path difficulty; An initial tool processing path is determined as the tool processing path according to the idle stroke and the total difficulty of the processing path, and the functional stages include the cutting-in stage, the cutting stage and the over-cutting-out stage, and the tool processing path is divided into three stages: the cutting-in stage, the cutting stage and the over-cutting-out stage; Select multiple calibration points in the tool path at each functional stage, including: Machining process parameters include cutting forces, temperature, and vibration; Select several points near the starting point and end point of the tool processing path in the cutting phase as calibration points; According to the prediction function of the machining process parameters, three maximum points of the ideal maximum cutting force, the ideal maximum temperature and the ideal maximum vibration on the tool machining path in the cutting stage are predicted, and several points near each of the three maximum points are selected as calibration points; According to the prediction function of the machining process parameters, the point of the ideal maximum vibration value and the path segment with the largest change rate of the ideal vibration value on the tool machining path in the overcutting stage are predicted, and several points near the point and between the path segment are selected as calibration points; Compare the deviation between the ideal value of the machining process parameters and the actual value of the machining process parameters through the calibration points, including: The ideal value of the machining process parameter and the actual value of the machining process parameter are projected onto a curve graph whose horizontal axis is the path length and whose vertical axis is the size of the machining process parameter, respectively, to obtain an ideal curve and an actual curve; The ideal curve and the actual curve are split into three types of calibration curves: between the starting point and the calibration point, between the calibration point and the calibration point, and between the calibration point and the end point through the calibration points. The ideal curve and the actual curve in the calibration curve are aligned on the horizontal axis scale, and the ideal value and the actual value on each horizontal axis unit scale are compared to obtain the deviation on each horizontal axis unit scale, thereby determining the average deviation value; The tool control quality indicators for the proof point are defined by the tool path completion time and the acceptable wear of the tool, including: Z a =γ1(t a前 -T a前 )+γ2(h a前 -H a前 )+γ3R a前 ; Among them, Z a is the tool control quality index of the ath calibration point, γ1, γ2, and γ3 are the quality conversion coefficients corresponding to the completion time, wear degree, and machining accuracy, respectively, t a前 is the time threshold for completing all paths before the ath calibration point, T a前 is the time taken to complete all paths before the ath calibration point, h a前 H is the acceptable wear degree of the tool for all paths before completing the ath calibration point. a前 The actual tool wear degree of all paths before the ath calibration point is R a前 The degree of part processing accuracy corresponding to all paths completed before the ath calibration point.

2. A tool control optimization method for part processing as claimed in claim 1, characterized in that: Determine tool life based on tool service information, including: The service information of the tool includes the number of processing times, the material of each processing, the processing control parameters, the tool wear type and the wear amount corresponding to the tool wear type; Among them, S is the tool life, n is the number of processing times, α i is the wear weight corresponding to the material processed for the i-th time, Q i is the average value index of the processing control parameters of the i-th processing, t i is the tool usage time of the i-th processing, m is the total number of tool wear types, β j is the wear weight of the jth tool wear type, W j is the wear amount of the jth tool wear type, S0 is the tool loss life after mapping, The tool loss life is mapped to the average value of the two loss quantities.

3. A tool control optimization method for part processing as claimed in claim 1, characterized in that: Determine the prediction function of the machining process parameters, and use the prediction function to predict the changes in the ideal values ​​of the machining process parameters at each functional stage, including: The processing parameter data and other related data of different processing paths in the past processing history are collected, the data are standardized and normalized, and a processing parameter prediction model is established to determine the prediction function of the processing parameters. The prediction model can predict the ideal values ​​of the processing parameters on different processing paths.

4. A tool control optimization method for part processing as claimed in claim 1, characterized in that: After selecting a plurality of calibration points in the tool processing path of each functional stage, the method further comprises: The acceptable wear degree of the tool in each functional stage is allocated to each calibration point, and the acceptable wear degree of the tool corresponding to each calibration point is determined.

5. A tool control optimization method for part processing as claimed in claim 1, characterized in that: Predictive functions for adjusting machining process parameters based on deviations and tool control quality indicators, including: If the average deviation value does not exceed the deviation threshold, and the tool control quality index exceeds the control quality index threshold, the prediction function of the machining process parameters is not adjusted; Otherwise, the prediction function of the machining process parameters is adjusted; Among them, Y ’ b+1 is the prediction function of the machining process parameters of the b+1th calibration point, Y b is the prediction function of the machining process parameters of the bth calibration point, ε b is the compensation coefficient corresponding to the type of calibration curve corresponding to the bth calibration point, c b is the difference between the average deviation value of the calibration curve corresponding to the bth calibration point and the deviation threshold, exp is an exponential function, k is a preset constant, x b is the average deviation value of the calibration curve corresponding to the bth calibration point, x b阈 is the deviation threshold of the calibration curve corresponding to the bth calibration point, v b is the tool control quality index of the bth calibration point, v b阈 is the control quality index threshold of the bth calibration point, is the first correction factor obtained by mapping the difference between the average deviation value of the calibration curve corresponding to the bth calibration point and the deviation threshold, d b is the difference between the tool control quality index of the bth calibration point and the control quality index threshold, is the second correction factor obtained by mapping the difference between the tool control quality index of the bth calibration point and the control quality index threshold.

6. A tool control optimization system for parts processing, characterized in that: A system for implementing a tool control optimization method for part machining as claimed in any one of claims 1 to 5, the system comprising: A setting module is used to set a tool processing path of a tool on a processing material according to a part drawing, basic information of processing materials and basic information of a tool, divide the tool processing path into a plurality of continuous functional stages, determine the tool processing path corresponding to each functional stage, and complete the division of the path and the functional stage; A wear module is used to determine the tool life according to the service information of the tool, and obtain an acceptable wear degree of the tool through tool life mapping, assign the acceptable wear degree of the tool to each functional stage, and determine the acceptable wear degree of the tool in each functional stage; A calibration module is used to determine a prediction function of a machining process parameter, predict the change of the ideal value of the machining process parameter at each functional stage through the prediction function, select multiple calibration points in the tool machining path at each functional stage, and compare the deviation between the ideal value of the machining process parameter and the actual value of the machining process parameter through the calibration points; An adjustment module is used to define the tool control quality index of the calibration point by the tool processing path completion time and the acceptable wear degree of the tool, and adjust the prediction function of the processing process parameters according to the deviation situation and the tool control quality index; The control module is used to adjust the machining control parameters by adjusting the prediction function of the machining process parameters to optimize the tool control.

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