Adaptive tool changing control method and system for numerical control machine tool based on three-coordinate detection

Abstract

The present application relates to the technical field of machine tool tool life prediction, and particularly relates to a numerical control machine tool adaptive tool changing control method and system based on three-coordinate detection. When a workpiece is positioned in a numerical control machine tool, various parameter information is loaded; based on a preliminary tool number, service time sequence data is extracted from a service log, combined with workpiece coordinate information before processing, workpiece model and processing control parameters as constraints, a same-mode tool processing sample set is collected; based on workpiece size abnormality detection coordinate set after processing, selected detection coordinates with a size abnormality detection frequency greater than or equal to a detection frequency threshold value are extracted; when the area occupied by the selected detection coordinates is greater than or equal to an area threshold value, the adaptive tool changing control cycle analysis is performed after the preliminary tool is switched; when the area occupied by the selected detection coordinates is less than the area threshold value, the preliminary tool is controlled to perform a processing task. The present application solves the technical problem of difficult early prediction of tool damage.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of machine tool tool life prediction, and particularly relates to a numerical control machine tool adaptive tool changing control method and system based on three-coordinate detection. BACKGROUND

[0002] The adaptive tool changing function of the current numerical control machine tool can only switch the corresponding tool according to the workpiece model. In the case that the tool has no obvious defects, the tool will not be replaced actively, and only when the size of the processed workpiece is detected to be abnormal, the tool will be replaced. The tool replacement decision depends on the detection result of the processed workpiece, and cannot predict potential tool problems before processing, resulting in that the unqualified workpiece has been produced before the tool is replaced, and the processing opportunity of the tool problem is delayed. Moreover, due to the delayed tool replacement, a certain number of unqualified workpieces are produced, which need to be reprocessed or scrapped, increasing the cost of raw material loss, working hour consumption and the like. The production of unqualified workpieces and the subsequent tool replacement and workpiece reprocessing process will interrupt the normal processing rhythm, prolong the overall processing cycle, and reduce the processing efficiency of the numerical control machine tool. In summary, the prior art has the technical problem that it is difficult to predict tool damage in advance. SUMMARY

[0003] In view of the technical problem in the prior art that it is difficult to predict tool damage in advance, the present application provides a numerical control machine tool adaptive tool changing control method and system based on three-coordinate detection to solve the problem.

[0004] The technical solution of the present application to solve the above technical problem is as follows:

[0005] In a first aspect, the present application provides a numerical control machine tool adaptive tool changing control method based on three-coordinate detection, comprising: when the workpiece is positioned in the numerical control machine tool, loading the pre-processing workpiece coordinate information, the workpiece model, the processing control parameter and the preliminary tool number; based on the preliminary tool number, extracting the service time sequence data from the service log, and combining the pre-processing workpiece coordinate information, the workpiece model and the processing control parameter as constraints to collect the same modal tool processing sample set, wherein the same modal tool processing sample set includes a post-processing workpiece size abnormality detection coordinate set; based on the post-processing workpiece size abnormality detection coordinate set, extracting selected detection coordinates with a size abnormality detection frequency greater than or equal to a detection frequency threshold; when the selected detection coordinates occupy an area greater than or equal to an area threshold, performing adaptive tool changing control cycle analysis after switching the preliminary tool; when the selected detection coordinates occupy an area less than the area threshold, controlling the preliminary tool to perform a processing task.

[0006] Optionally, when the workpiece is positioned in the numerical control machine tool, load the pre-processing workpiece coordinate information, workpiece model, processing control parameter and preliminary tool number, including: extracting the preliminary tool model of the preliminary tool number; when the workpiece is positioned in the numerical control machine tool, collecting the workpiece coordinates through the three-coordinate detection device, and setting as the pre-processing workpiece coordinate information; based on the workpiece model, matching the associated tool number set from the machine tool tool magazine, wherein the preliminary tool number belongs to the associated tool number set; based on the workpiece model, matching the expected post-processing workpiece structure information and the expected post-processing workpiece size information; based on the expected post-processing workpiece structure information, the expected post-processing workpiece size information and the preliminary tool model, processing optimization is performed on the pre-processing workpiece coordinate information to obtain the processing control parameter.

[0007] Wherein, based on the expected post-processing workpiece structure information, the expected post-processing workpiece size information and the preliminary tool model, processing optimization is performed on the pre-processing workpiece coordinate information to obtain the processing control parameter, including: obtaining the processing size constraint interval and the processing angle constraint interval of the preliminary tool model; based on the expected post-processing workpiece structure information and the expected post-processing workpiece size information, randomly constructing a plurality of expected post-processing workpiece coordinate information based on the pre-processing workpiece coordinate information; based on the processing size constraint interval and the processing angle constraint interval, processing the pre-processing workpiece coordinate information to obtain a plurality of groups of initial processing control parameters satisfying the plurality of expected post-processing workpiece coordinate information; performing shortest cutting path sorting on the plurality of groups of initial processing control parameters to obtain the processing control parameter.

[0008] The method comprises the following steps: based on the preliminary tool number, extracting service time sequence data from the service log, combining the pre-machining workpiece coordinate information, the workpiece model and the machining control parameter as constraints, collecting the same modal tool machining sample set, based on the workpiece model, extracting workpiece structure information and workpiece material information, obtaining a tool machining sample to be analyzed, wherein the tool machining sample to be analyzed includes a tool record model, tool service time record data, pre-machining workpiece record coordinate information, pre-machining workpiece record structure information, workpiece record material information, machining record control parameter and post-machining workpiece record coordinate information; when the tool record model is the same as the preliminary tool model, the tool service time record data is consistent with the service time sequence data, the pre-machining workpiece coordinate information is consistent with the pre-machining workpiece record coordinate information, the pre-machining workpiece record structure information is consistent with the workpiece structure information, and the machining control parameter is consistent with the machining record control parameter, extracting the coordinates in the post-machining workpiece record coordinate information that do not meet the expected post-machining workpiece structure information and the expected post-machining workpiece size information as post-machining workpiece size anomaly detection coordinates; storing the tool machining sample to be analyzed in association with the post-machining workpiece size anomaly detection coordinates and adding it to the same modal tool machining sample.

[0009] When the tool record model is the same as the preliminary tool model, the tool service time record data is consistent with the service time sequence data, the pre-machining workpiece coordinate information is consistent with the pre-machining workpiece record coordinate information, the pre-machining workpiece record structure information is consistent with the workpiece structure information, and the machining control parameter is consistent with the machining record control parameter, the method comprises the following steps: when the tool service time record data and the service time sequence data have a tool service state similarity greater than or equal to a service state similarity threshold, the tool service time record data is considered to be consistent with the service time sequence data, otherwise, the tool service time record data is considered to be inconsistent with the service time sequence data; when the pre-machining workpiece coordinate information and the pre-machining workpiece record coordinate information have a coordinate intersection ratio greater than or equal to a coordinate intersection ratio threshold, the pre-machining workpiece coordinate information is considered to be consistent with the pre-machining workpiece record coordinate information, otherwise, the pre-machining workpiece coordinate information is considered to be inconsistent with the pre-machining workpiece record coordinate information; when the pre-machining workpiece record structure information and the workpiece structure information have a structure similarity greater than or equal to a structure similarity threshold, the pre-machining workpiece record structure information is considered to be consistent with the workpiece structure information, otherwise, the pre-machining workpiece record structure information is considered to be inconsistent with the workpiece structure information.

[0010] Optionally, based on the size abnormality detection coordinate set of the processed workpiece, the selected detection coordinates with a size abnormality detection frequency greater than or equal to a detection frequency threshold are extracted, including: grouping the size abnormality detection coordinate set of the processed workpiece at the same position, and counting the number of coordinates in the group to obtain a first position size abnormality detection frequency to an Nth position size abnormality detection frequency; extracting positions with a size abnormality detection frequency greater than or equal to the detection frequency threshold from the first position size abnormality detection frequency to the Nth position size abnormality detection frequency, and setting the positions as the selected detection coordinates.

[0011] Optionally, the area threshold obtaining process includes: loading an area threshold calibration library, wherein the area threshold calibration library is used to store a one-to-one correspondence between a workpiece model and an area threshold; inputting the workpiece model into the area threshold calibration library, and outputting the area threshold.

[0012] In a second aspect, the present application provides a numerical control machine tool adaptive tool changing control system based on three-coordinate detection, comprising:

[0013] A basic information acquisition module is configured to load workpiece coordinate information before processing, a workpiece model, processing control parameters, and a preliminary tool number when a workpiece is positioned on a numerical control machine tool.

[0014] A same-mode sample collection module is configured to extract service time sequence data from a service log based on the preliminary tool number, and collect a same-mode tool processing sample set by combining the workpiece coordinate information before processing, the workpiece model, and the processing control parameters as constraints, wherein the same-mode tool processing sample set includes a size abnormality detection coordinate set of a processed workpiece.

[0015] A selected detection coordinate acquisition module is configured to extract selected detection coordinates with a size abnormality detection frequency greater than or equal to a detection frequency threshold based on the size abnormality detection coordinate set of the processed workpiece.

[0016] A tool changing strategy generation module is configured to perform adaptive tool changing control cycle analysis after switching the preliminary tool when the selected detection coordinates have an area greater than or equal to an area threshold, and control the preliminary tool to perform a processing task when the selected detection coordinates have an area less than the area threshold.

[0017] By implementing the present application, when a workpiece is positioned on a numerical control machine tool, workpiece coordinate information before processing, a workpiece model, processing control parameters, and a preliminary tool number are loaded, providing complete and accurate data support for subsequent same-mode tool processing sample set collection, tool state evaluation, and processing control, avoiding deviations in subsequent processes caused by missing or incorrect initial data, and ensuring the orderly start of the entire adaptive tool changing control process.

[0018] Through implementation of the present application, based on the preliminary tool number, service time sequence data is extracted from the service log, and the same mode tool machining sample set is collected by taking the workpiece coordinate information before machining, the workpiece model and the machining control parameter as constraints, wherein the same mode tool machining sample set includes a workpiece size abnormality detection coordinate set after machining, and by screening the same mode sample, the historical data similar to the current machining scene can be focused on, thereby providing strong data basis for subsequent analysis of size abnormality problems caused by the tool, and the potential machining risk of the preliminary tool can be more accurately judged;

[0019] Through implementation of the present application, based on the workpiece size abnormality detection coordinate set after machining, selected detection coordinates with a size abnormality detection frequency greater than or equal to a detection frequency threshold are extracted, the high-frequency abnormal position is screened out from a large amount of abnormal coordinate data, the accidental abnormal coordinate interference is excluded, the key position prone to size abnormality is accurately positioned, and a core judgment basis is provided for subsequent judgment of whether the tool needs to be replaced.

[0020] Through implementation of the present application, when the occupation area of the selected detection coordinate is greater than or equal to an area threshold, adaptive tool changing control cycle analysis is performed after switching the preliminary tool; when the occupation area of the selected detection coordinate is less than the area threshold, the preliminary tool is controlled to perform a machining task, scientific decision of whether to use the preliminary tool is realized, a large number of unqualified workpieces caused by continuous use of the tool with potential problems are avoided, and resource waste caused by excessive tool replacement is also prevented, and the machining quality and cost are effectively balanced.

[0021] In summary, through implementation of the present application, the machining risk of the preliminary tool can be accurately evaluated based on historical same mode data before machining, and whether the tool needs to be replaced can be judged in advance, thereby breaking the lag mode of replacing the tool only after the workpiece appears abnormal in the traditional mode, significantly reducing the unqualified product rate caused by tool problems, reducing the machining cost, and at the same time, ensuring the machining precision. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 A flowchart of a numerical control machine tool adaptive tool changing control method based on three-coordinate detection provided by the present application is shown in the figure.

[0023] Figure 2 A structure diagram of a numerical control machine tool adaptive tool changing control system based on three-coordinate detection provided by the present application is shown in the figure.

[0024] In the figure, the components represented by each number are as follows:

[0025] The basic information acquisition module 11, the same mode sample acquisition module 12, the selected detection coordinate acquisition module 13, and the tool changing strategy generation module 14. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0028] In the description of this invention, the term "for example" is used to mean "used as an example, illustration, or description." Any embodiment described as "for example" in this invention is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the invention. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that the invention can be made without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed herein.

[0029] Example 1, as Figure 1 As shown, this embodiment of the invention provides an adaptive tool changing control method for CNC machine tools based on three-coordinate measuring machine detection, including:

[0030] S100: When the workpiece is positioned on the CNC machine tool, load the workpiece coordinate information, workpiece model, machining control parameters and pre-processed tool number before machining.

[0031] S200: Based on the pre-tool number, extract service time sequence data from the service log, and combine the pre-processing workpiece coordinate information, the workpiece model and the processing control parameters as constraints to collect a processing sample set of the same mode tool, wherein the processing sample set of the same mode tool includes the coordinate set of workpiece size anomaly detection after processing;

[0032] S300: Based on the set of coordinates for detecting dimensional anomalies in the processed workpiece, extract selected coordinates whose dimensional anomaly detection frequency is greater than or equal to the detection frequency threshold;

[0033] S400: When the selected detected coordinate occupies an area greater than or equal to the area threshold, perform adaptive tool changing control cycle analysis after switching the preliminary tool; when the selected detected coordinate occupies an area less than the area threshold, control the preliminary tool to perform a machining task.

[0034] In step S100 of the embodiment of the present application, when the workpiece is positioned in the numerical control machine tool, load the pre-machining workpiece coordinate information, workpiece model, machining control parameter and preliminary tool number, including:

[0035] Extract the preliminary tool model of the preliminary tool number;

[0036] When the workpiece is positioned in the numerical control machine tool, collect the workpiece coordinates by a three-coordinate detection device, and set them as the pre-machining workpiece coordinate information;

[0037] Based on the workpiece model, match the associated tool number set from the tool magazine of the machine tool, wherein the preliminary tool number belongs to the associated tool number set;

[0038] Based on the workpiece model, match the expected post-machining workpiece structure information and the expected post-machining workpiece size information;

[0039] Based on the expected post-machining workpiece structure information, the expected post-machining workpiece size information and the preliminary tool model, perform machining optimization on the pre-machining workpiece coordinate information to obtain the machining control parameter.

[0040] In the embodiment of the present application, the purpose of step S100 is to obtain and match the logic by disassembling the key data, accurately collect the core parameters before machining, provide complete, adaptive and accurate basic data support for subsequent same modality tool sample screening, abnormal risk assessment and tool changing decision, and ensure that the entire adaptive tool changing control process has data accuracy and effectiveness from the source.

[0041] First, the preliminary tool model of the preliminary tool number needs to be extracted. Specifically, from the tool information library stored in the numerical control machine tool system, according to the input preliminary tool number such as "T0105", the unique corresponding tool model information such as "hard alloy end mill EMR-2005" is called and read to complete the extraction of the preliminary tool model.

[0042] Secondly, when the workpiece is positioned in the numerical control machine tool, the three-coordinate detection device is used to collect the workpiece coordinates, which are set as the workpiece coordinate information before machining. That is, after the workpiece is positioned and fixed on the workbench of the numerical control machine tool through the clamp, the three-coordinate detection device (such as a contact probe head) of the machine tool is started, the probe head is controlled to touch the key feature points (such as the hole center and the edge end point) of the workpiece surface according to the preset sampling path, the X, Y and Z axis coordinate data of each feature point are collected, and the coordinate data is integrated into the workpiece coordinate information before machining and is stored.

[0043] Then, based on the workpiece model, the associated tool number set is matched from the tool magazine, wherein the preliminary tool number belongs to the associated tool number set.

[0044] Specifically, a corresponding database of “workpiece model- associated tool number set” is established in the machine tool system in advance, for example, the tool number set associated with the workpiece model “WF-003 (aluminum alloy flange)” is {T0105, T0106, T0201}. After the workpiece model “WF-003” is input, the corresponding associated tool number set is called from the database, and it is checked whether the preliminary tool number is in the set to confirm its adaptability.

[0045] Next, the expected workpiece structure information after machining and the expected workpiece size information after machining need to be matched based on the workpiece model.

[0046] That is, in the machine tool system or the matching management software, the three-dimensional model and the size annotation file corresponding to each workpiece model are stored in advance. When the workpiece model such as “WF-003” is input, the system automatically calls the three-dimensional model corresponding to the model, extracts the structural feature information in the model, such as “one center hole, three evenly distributed mounting holes, and one annular groove”, as the expected workpiece structure information after machining; and reads the size tolerance data annotated in the model, such as “the center hole diameter φ10±0.002mm, the annular groove width 8±0.001mm, and the groove depth 5±0.001mm”, as the expected workpiece size information after machining.

[0047] Further, based on the expected workpiece structure information after machining, the expected workpiece size information after machining, and the preliminary tool model, machining optimization is performed on the workpiece coordinate information before machining to obtain the machining control parameter.

[0048] In step S100 of the embodiment of the present application, based on the expected workpiece structure information after machining, the expected workpiece size information after machining, and the preliminary tool model, machining optimization is performed on the workpiece coordinate information before machining to obtain the machining control parameter, including:

[0049] The machining size constraint interval and the machining angle constraint interval of the preliminary tool model are obtained.

[0050] Based on the expected post-processing workpiece structure information and the expected post-processing workpiece size information, the pre-processing workpiece coordinate information is constructed with a plurality of expected post-processing workpiece coordinate information;

[0051] Based on the machining size constraint interval and the machining angle constraint interval, the pre-processing workpiece coordinate information is machined to obtain a plurality of initial machining control parameters satisfying the plurality of expected post-processing workpiece coordinate information;

[0052] The plurality of initial machining control parameters are sorted by the shortest cutting path to obtain the machining control parameter.

[0053] In the embodiment of the application, the purpose of the above subdivision step in step S100 is to plan the optimal machining path and parameter according to the expected workpiece structure and size, the preliminary tool model and the pre-processing workpiece coordinate, so as to ensure efficient machining process and accurately achieve the target size, and avoid low machining efficiency or size out-of-tolerance caused by unreasonable parameters.

[0054] Firstly, the machining size constraint interval and the machining angle constraint interval of the preliminary tool model need to be obtained. That is, the machining constraint interval corresponding to the preliminary tool model is retrieved from the tool parameter library, for example, the machining size constraint interval of the "hard alloy end mill EMR-2005" is "cutting depth 0.1-5mm, cutting width 1-20mm", and the machining angle constraint interval is the main deflection angle 30°-60°.

[0055] Then, based on the aforementioned expected post-processing workpiece structure information and pre-processing workpiece coordinate information, a plurality of post-processing workpiece coordinate information conforming to the expected size is generated by a random disturbance algorithm, such as the center hole post-processing coordinate (X100, Y100, Z10), the mounting hole coordinate (X120, Y117.32, Z-8) and the like.

[0056] Next, the machining size and angle constraint interval need to be combined to calculate the corresponding initial machining control parameters for each group of post-processing coordinate information, including spindle speed, feed speed, cutting path node coordinate, etc., and finally form a plurality of initial machining control parameters.

[0057] Specifically, for each group of expected post-processing workpiece coordinate information, the pre-processing workpiece coordinate is combined to calculate the cutting path of the tool from the starting point to the end point through the kinematics model. For example, for the center hole machining, the path of the tool from the initial position (X100, Y100, Z50) to the target coordinate (X100, Y100, Z-10) needs to be calculated. Then, within the machining size and angle constraint interval, the spindle speed, feed speed, cutting depth and other parameters are matched for the path to form a plurality of initial machining control parameters.

[0058] Finally, the cutting path lengths corresponding to multiple sets of initial parameters are calculated and compared, and the set of parameters with the shortest cutting path is selected as the final machining control parameter. Specifically, the length of the cutting path corresponding to each set of initial machining control parameters can be calculated. For example, the path lengths corresponding to three sets of initial machining control parameters are 150 mm, 145 mm, and 160 mm, respectively. By comparison, the set of initial machining control parameters with the shortest path (145 mm) is selected as the final machining control parameter.

[0059] In step S200 of the embodiment of the present application, based on the preliminary tool number, the service time sequence data is extracted from the service log, and the machining before workpiece coordinate information, the workpiece model, and the machining control parameter are combined as constraints to collect the same modal tool machining sample set, including:

[0060] Based on the workpiece model, the workpiece structure information and the workpiece material information are extracted;

[0061] The tool machining sample to be analyzed is obtained, wherein the tool machining sample to be analyzed includes a tool record model, tool service time sequence record data, workpiece pre-machining record coordinate information, pre-machining workpiece record structure information, workpiece record material information, machining record control parameters, and workpiece post-machining record coordinate information;

[0062] When the tool record model is the same as the preliminary tool model, the tool service time sequence record data is consistent with the service time sequence data, the pre-machining workpiece coordinate information is consistent with the workpiece pre-machining record coordinate information, the pre-machining workpiece record structure information is consistent with the workpiece structure information, and the machining control parameter is consistent with the machining record control parameter, the coordinate in the workpiece post-machining record coordinate information that does not meet the expected post-machining workpiece structure information and the expected post-machining workpiece size information is set as the post-machining workpiece size abnormality detection coordinate;

[0063] The tool machining sample to be analyzed is stored in association with the post-machining workpiece size abnormality detection coordinate and added to the same modal tool machining sample.

[0064] In the embodiment of the present application, the purpose of step S200 is to filter the historical tool machining samples that completely match the current machining scene, and to extract the post-machining size abnormality detection coordinates in the samples to construct a "same modal tool machining sample set". This sample set can accurately reflect the potential machining risk of the current preliminary tool under the same working condition, provide data support for subsequent judgment of whether to replace the tool in advance, and avoid the production of unqualified products caused by traditional lagging replacement of tools.

[0065] To achieve the above object, first, the workpiece structure information and workpiece material information need to be extracted based on the workpiece model. That is, from the "workpiece attribute database" preset by the machine tool, the corresponding information is retrieved according to the input workpiece model. For example, input the workpiece model "WF-003", extract the workpiece structure information as "disc structure containing 1 φ10mm center hole, 3 φ8mm mounting hole", and the workpiece material information as "6061 aluminum alloy (hardness HB95)", complete the determination of the core attributes of the workpiece.

[0066] Then, the workpiece size abnormality detection coordinates after processing need to be extracted through multi-condition matching screening. That is, the tool record model is the same as the prepared tool model, and the tool service time sequence record data is consistent with the service time sequence data, and the workpiece coordinate information before processing is consistent with the workpiece coordinate information before processing record, and the workpiece record structure information before processing is consistent with the workpiece structure information, and the machining control parameters are consistent with the machining record control parameters, and the workpiece coordinate information after processing is not consistent with the expected workpiece structure information after processing and the expected workpiece size information after processing. Set the coordinate as the workpiece size abnormality detection coordinate after processing.

[0067] Then, the workpiece size abnormality detection coordinates after processing need to be extracted through multi-condition matching screening. That is, the tool record model is the same as the prepared tool model, and the tool service time sequence record data is consistent with the service time sequence data, and the workpiece coordinate information before processing is consistent with the workpiece coordinate information before processing record, and the workpiece record structure information before processing is consistent with the workpiece structure information, and the machining control parameters are consistent with the machining record control parameters, and the workpiece coordinate information after processing is not consistent with the expected workpiece structure information after processing and the expected workpiece size information after processing. Set the coordinate as the workpiece size abnormality detection coordinate after processing.

[0068] Wherein, when the tool record model is the same as the prepared tool model, and the tool service time sequence record data is consistent with the service time sequence data, and the workpiece coordinate information before processing is consistent with the workpiece coordinate information before processing record, and the workpiece record structure information before processing is consistent with the workpiece structure information, and the machining control parameters are consistent with the machining record control parameters, including:

[0069] When the tool service time record data and the tool service state of the service time data are greater than or equal to the service state similarity threshold, the tool service time record data is considered to be consistent with the service time data, otherwise, the tool service time record data is considered to be inconsistent with the service time data;

[0070] When the pre-machining workpiece coordinate information and the coordinate intersection ratio of the workpiece pre-machining record coordinate information are greater than or equal to the coordinate intersection ratio threshold, the pre-machining workpiece coordinate information is considered to be consistent with the workpiece pre-machining record coordinate information, otherwise, the pre-machining workpiece coordinate information is considered to be inconsistent with the workpiece pre-machining record coordinate information;

[0071] When the pre-machining workpiece record structure information and the structure similarity of the workpiece structure information are greater than or equal to the structure similarity threshold, the pre-machining workpiece record structure information is considered to be consistent with the workpiece structure information, otherwise, the pre-machining workpiece record structure information is considered to be inconsistent with the workpiece structure information.

[0072] First, the consistency of the tool service time record data and the service time data needs to be determined.

[0073] The service state evaluation index is a core index extracted from the service time data, including "cumulative machining time", "machining workpiece quantity" and "tool edge wear record", for example, the current standby tool service time data is "cumulative machining time of 8 hours, machining workpiece quantity of 30 pieces, edge wear of 0.002mm", and the machining sample of a certain to-be-analyzed tool is "cumulative machining time of 7.5 hours, machining workpiece quantity of 28 pieces, edge wear of 0.0018mm".

[0074] Then, the weighted fusion algorithm is used to calculate the similarity of the two groups of data, for example, the similarity of the two groups of data=(1-|preparation tool data-to-be analyzed tool machining sample data| / preparation tool data), and the "cumulative machining time weight is 40%, workpiece quantity weight is 30%, and wear weight is 30%", and the calculation can be obtained: cumulative machining time similarity=(1-|8-7.5| / 8)×40%=37.5%; machining workpiece quantity similarity=(1-|30-28| / 30)×30%≈28%; edge wear similarity=(1-|0.002-0.0018| / 0.002)×30%=27%; service state similarity=37.5%+28%+27%=92.5%.

[0075] Then, according to the screening accuracy requirement, the service state similarity threshold is preset, for example, 85%, and since 92.5%≥85%, it is determined that the service time data of the to-be-analyzed tool machining sample is consistent with the current standby tool; if the total similarity of a certain to-be-analyzed tool machining sample is 78%, it is determined that it is inconsistent.

[0076] Second, the consistency of the pre-processing workpiece coordinate information and the pre-processing workpiece record coordinate information needs to be determined.

[0077] First, the area surrounded by the coordinates of the key feature points of the workpiece processing needs to be taken as the comparison object, for example, the rectangular area surrounded by the center hole coordinates (X100, Y100, Z0) and the positioning hole coordinates (X120, Y100, Z0) in the current pre-processing coordinate information of the workpiece is A; the area surrounded by the corresponding feature point coordinates in the to-be-analyzed tool processing sample is B.

[0078] Then, the coordinate intersection ratio of area A and area B is calculated. The coordinate intersection ratio (IoU) = the overlapping area of area A and area B / the total area of area A and area B. At the same time, according to the filtering accuracy requirement, the coordinate intersection ratio threshold is set, such as 95%, if IoU = 100% ≥ 95%, it is determined that the coordinates are consistent; if IoU = 80% < 95%, it is determined that the coordinates are inconsistent.

[0079] Third, the consistency of the pre-processing workpiece record structure information and the workpiece structure information needs to be determined.

[0080] First, the workpiece structure information needs to be converted into quantitative parameters, for example, the current workpiece structure information is "1 φ10mm center hole (deep 10mm), 3 φ8mm mounting hole (deep 8mm), 1 5mm wide annular groove (deep 3mm)"; the structure information of the to-be-analyzed tool processing sample is "1 φ10mm center hole (deep 10mm), 3 φ8mm mounting hole (deep 8mm), 1 5mm wide annular groove (deep 3mm)".

[0081] Then, the "feature matching rate" algorithm is used to calculate the proportion of the number of completely consistent structure features to the total number of structure features. For example, there are 3 types of structure features in total, such as 1 center hole + 3 mounting holes + 1 annular groove, and all feature parameters are completely consistent, the structure similarity = 5 / 5 × 100% = 100%; if the to-be-analyzed tool processing sample is short of 1 mounting hole, the structure similarity = 4 / 5 × 100% = 80%.

[0082] Next, according to the filtering accuracy requirement, the structure similarity threshold is preset, such as 98%, if the structure similarity = 100% ≥ 98%, it is determined that the structure is consistent; if the structure similarity = 80% < 98%, such as fewer holes or different groove depths, it is determined that the structure is inconsistent.

[0083] Further, the coordinates in the post-processing workpiece record coordinate information that do not meet the expected post-processing workpiece structure information and the expected post-processing workpiece size information are extracted and set as the post-processing workpiece size abnormality detection coordinates.

[0084] Specifically, the desired machined workpiece structure information and the desired machined workpiece size information of the current machining are called as the judgment standard, such as "containing one φ10mm center hole and three φ8mm mounting holes"; "the center hole coordinate tolerance is ±0.002mm, and the mounting hole depth tolerance is ±0.001mm".

[0085] Then, the workpiece machined record coordinate information of the same mode tool machining sample to be analyzed is called, such as the actual center hole coordinates X100.003, Y99.997, Z-10.002, and the actual mounting hole 1 coordinates X120.001, Y117.321, Z-8.002.

[0086] Then, whether each coordinate meets the desired machined workpiece size requirement is compared one by one, and the coordinate that does not meet the desired machined workpiece size requirement is determined as an abnormal coordinate, and after being summarized, it is set as the machined workpiece size abnormal detection coordinate.

[0087] Further, the tool machining sample to be analyzed needs to be associated with the machined workpiece size abnormal detection coordinate and stored, and added to the same mode tool machining sample.

[0088] That is, a special data entry is created for the tool machining sample to be analyzed in the database, including all the complete information of the tool record model, service time record data, machined record coordinates, etc.

[0089] Then, the extracted machined workpiece size abnormal detection coordinate is associated and bound with the tool machining sample entry, and the specific deviation value and the corresponding structure feature of each abnormal coordinate are recorded.

[0090] Finally, the complete data unit after binding is added to the same mode tool machining sample set.

[0091] In step S300 of the embodiment of the present application, based on the machined workpiece size abnormal detection coordinate set, a selected detection coordinate with a size abnormal detection frequency greater than or equal to a detection frequency threshold is extracted, including:

[0092] The machined workpiece size abnormal detection coordinate set is grouped at the same position, and the number of coordinates in the group is counted to obtain a first position size abnormal detection frequency to an Nth position size abnormal detection frequency;

[0093] The positions with a size abnormal detection frequency greater than or equal to the detection frequency threshold in the first position size abnormal detection frequency to the Nth position size abnormal detection frequency are extracted and set as the selected detection coordinate.

[0094] In the embodiment of the present application, the purpose of step S300 is to screen out high-frequency abnormal positions from a large number of size anomaly detection coordinates of the same modal tool machining sample, exclude accidental single abnormal coordinate interference, accurately locate the key area of the current prepared tool that is most likely to cause size out-of-tolerance under the same working condition, provide a core focusing object for subsequent abnormal area judgment to determine whether to change the tool, and avoid the mistake of changing the tool due to focusing on non-key abnormal positions.

[0095] Firstly, the same position grouping needs to be performed on the size anomaly detection coordinate set of the machined workpiece, and the number of coordinates in the group is counted to obtain the size anomaly detection frequency of the first position to the size anomaly detection frequency of the Nth position.

[0096] Specifically, a position error threshold value, such as ±0.001 mm, needs to be set. If the X, Y, and Z axis deviations of two abnormal coordinates are within the threshold value, it is determined that they are in the same position. For example, coordinate A (X100.002, Y99.998, Z-10.001) and coordinate B (X100.001, Y99.999, Z-10.002) have an axis deviation of ≤0.001 mm, which are considered to be in the same position.

[0097] Then, the size anomaly detection coordinate set of the machined workpiece is traversed. It is assumed that it contains 20 abnormal coordinates. The coordinates are grouped according to the above standard to obtain: the center hole area, 12 abnormal coordinates, the number of coordinates in the group = 12; the mounting hole 1 area, 5 abnormal coordinates, the number of coordinates in the group = 5; the mounting hole 2 area, 2 abnormal coordinates, the number of coordinates in the group = 2; and the mounting hole 3 area, 1 abnormal coordinate, the number of coordinates in the group = 1.

[0098] Next, the abnormal detection frequency is calculated. The abnormal detection frequency = the number of coordinates in a certain position group / the total number of the same modal tool machining samples. The center hole area abnormal detection frequency = 12 / 15 = 80% (the first position size anomaly detection frequency); the mounting hole 1 area abnormal detection frequency = 5 / 15 ≈ 33% (the second position size anomaly detection frequency); the mounting hole 2 area abnormal detection frequency = 2 / 15 ≈ 13% (the third position size anomaly detection frequency); and the mounting hole 3 area abnormal detection frequency = 1 / 15 ≈ 7% (the fourth position size anomaly detection frequency). Similarly, the Nth position abnormal detection frequency is obtained.

[0099] Finally, a detection frequency threshold value needs to be preset according to the machining precision requirement and historical experience. It is assumed that the machining precision requirement of the current workpiece is ±0.002 mm, and the detection frequency threshold value is set to 50%. The size anomaly detection frequency of each position is compared with the detection frequency threshold value. All the same position abnormal coordinates corresponding to the “center hole area” that meet the detection frequency threshold value requirement, i.e., the above-mentioned 12 center hole abnormal coordinates, are summarized and set as the selected detection coordinates.

[0100] In step S400 of the embodiment, when the area of the selected detected coordinates is greater than or equal to the area threshold, the adaptive tool changing control cycle analysis is performed after the switching of the standby tool; and when the area of the selected detected coordinates is less than the area threshold, the standby tool is controlled to perform the machining task.

[0101] In step S400 of the embodiment, the area threshold obtaining process comprises:

[0102] The area threshold calibration library is loaded, wherein the area threshold calibration library is used to store the one-to-one correspondence between the workpiece model and the area threshold.

[0103] The workpiece model is input into the area threshold calibration library, and the area threshold is output.

[0104] In the embodiment, the purpose of step S400 is to make a final tool use decision based on the comparison between the area of the selected detected coordinates and the area threshold: when the abnormal area is large, it is determined that the current standby tool has significant machining risk, and the tool needs to be replaced and the cycle analysis is entered; and when the abnormal area is small, it is determined that the risk is controllable, and the tool is allowed to continue to be used. Through this quantitative judgment, the precision control of tool replacement is realized, and the machining quality and efficiency are balanced.

[0105] Firstly, the area of the selected detected coordinates needs to be calculated. For the selected detected coordinates determined in step S300, such as 12 abnormal coordinates of the center hole area, a three-dimensional space area calculation algorithm is used to fit the coordinate points as a continuous area, such as a circular area with a diameter of φ10.005mm for the center hole abnormal area, and the actual occupied area of the area is calculated, such as 0.08mm 2 .

[0106] Further, the area needs to be compared with the area threshold and a decision is made.

[0107] Firstly, the area threshold needs to be determined. The area threshold can be obtained from the area threshold calibration library.

[0108] The area threshold calibration library pre-calibrates the corresponding area threshold for each workpiece model through a large number of experiments and historical machining data, and stores it in the "area threshold calibration library".

[0109] For example, the data stored in the area threshold calibration library can be: for the workpiece model WF-003, the center hole area threshold is 0.05mm 2 ; for the workpiece model "JT-001", the step surface area threshold is 0.08mm 2 , and so on.

[0110] The system reads the model number of the currently being processed, such as "WF-003", inputs it into the area threshold calibration library, and retrieves the corresponding area threshold, such as 0.03mm, through index matching. 2 This can be used as the criterion for area comparison in the S400 step.

[0111] If the occupied area is greater than or equal to the area threshold, such as the preset area threshold for the center hole being 0.05mm. 2 If the actual occupied area is 0.08mm 2 ≥0.05mm 2 If the system determines that the machining risk of the prepared tool is too high, it will automatically control the machine tool tool magazine to switch to the spare tool and start the adaptive tool change control cycle analysis, that is, re-execute the S100-S400 process to verify the machining feasibility of the spare tool.

[0112] If the occupied area is less than the area threshold, such as an actual occupied area of ​​0.03 mm. 2 <0.05mm 2 If the risk is determined to be within an acceptable range, the system will directly issue an instruction to control the pre-tool to perform the machining task according to the predetermined machining control parameters.

[0113] By implementing the adaptive tool changing control method for CNC machine tools based on three-coordinate detection provided in the embodiments of this application, at least the following can be achieved:

[0114] 1. Before machining, accurately assess the machining risk of the prepared tool based on historical modal data, and determine in advance whether the tool needs to be replaced;

[0115] 2. Make scientific decisions on tool usage based on abnormal area to balance machining quality and efficiency, and avoid over- or under-changing tools;

[0116] 3. By accurately matching the same-mode machining samples through multi-dimensional conditions, and combining quantitative thresholds to screen high-frequency abnormal coordinates and assess risks, we can eliminate interference from irrelevant samples, ensure the relevance of abnormal data, and reduce tool waste and workpiece scrap caused by misjudgment.

[0117] Example 2, as Figure 2 As shown, based on the same inventive concept as the adaptive tool changing control method for CNC machine tools based on three-coordinate detection provided in Embodiment 1, this embodiment of the invention also provides an adaptive tool changing control system for CNC machine tools based on three-coordinate detection, comprising:

[0118] The basic information acquisition module 11 is used to load the workpiece coordinate information, workpiece model, machining control parameters and pre-processing tool number when the workpiece is positioned on the CNC machine tool.

[0119] The same mode sample collection module 12 is used to extract service timing data from the service log based on the preliminary tool number, and collect a same mode tool machining sample set by combining the machining workpiece coordinate information, the workpiece model and the machining control parameter as constraints, wherein the same mode tool machining sample set includes a post-machining workpiece size anomaly detection coordinate set;

[0120] The selected detection coordinate acquisition module 13 is used to extract selected detection coordinates with a size anomaly detection frequency greater than or equal to a detection frequency threshold based on the post-machining workpiece size anomaly detection coordinate set.

[0121] The tool change strategy generation module 14 is used to perform adaptive tool change control cycle analysis after switching the preliminary tool when the selected detection coordinate occupies an area greater than or equal to an area threshold, and control the preliminary tool to perform a machining task when the selected detection coordinate occupies an area less than the area threshold.

[0122] Further, the basic information acquisition module 11 includes the following execution steps:

[0123] The preliminary tool model of the preliminary tool number is extracted;

[0124] When the workpiece is positioned in the numerical control machine tool, the workpiece coordinates are collected by a three-coordinate detection device and set as the machining workpiece coordinate information;

[0125] Based on the workpiece model, a set of associated tool numbers is matched from the machine tool tool magazine, wherein the preliminary tool number belongs to the set of associated tool numbers;

[0126] Based on the workpiece model, expected post-machining workpiece structure information and expected post-machining workpiece size information are matched;

[0127] Based on the expected post-machining workpiece structure information, the expected post-machining workpiece size information and the preliminary tool model, machining optimization is performed on the machining workpiece coordinate information to obtain the machining control parameter.

[0128] Wherein, based on the expected post-machining workpiece structure information, the expected post-machining workpiece size information and the preliminary tool model, machining optimization is performed on the machining workpiece coordinate information to obtain the machining control parameter, including:

[0129] The machining size constraint interval and the machining angle constraint interval of the preliminary tool model are obtained;

[0130] Based on the expected post-machining workpiece structure information and the expected post-machining workpiece size information, a plurality of expected post-machining workpiece coordinate information is constructed based on the machining workpiece coordinate information;

[0131] obtaining a plurality of sets of initial machining control parameters satisfying the plurality of expected post-machining workpiece coordinate information based on the machining dimension constraint interval and the machining angle constraint interval by machining the pre-machining workpiece coordinate information;

[0132] obtaining the machining control parameter by shortest cutting path sorting of the plurality of sets of initial machining control parameters.

[0133] Further, the same modality sample collection module 12 includes the following execution steps:

[0134] extracting workpiece structure information and workpiece material information based on the workpiece model;

[0135] obtaining a to-be-analyzed tool machining sample, wherein the to-be-analyzed tool machining sample includes a tool record model, tool service time record data, pre-machining workpiece record coordinate information, pre-machining workpiece record structure information, workpiece record material information, machining record control parameters, and post-machining workpiece record coordinate information;

[0136] when the tool record model is the same as the prepared tool model, the tool service time record data is consistent with the service time data, the pre-machining workpiece coordinate information is consistent with the pre-machining workpiece record coordinate information, the pre-machining workpiece record structure information is consistent with the workpiece structure information, and the machining control parameter is consistent with the machining record control parameter, extracting the coordinate in the post-machining workpiece record coordinate information that does not satisfy the expected post-machining workpiece structure information and the expected post-machining workpiece dimension information as a post-machining workpiece dimension abnormality detection coordinate;

[0137] storing the to-be-analyzed tool machining sample in association with the post-machining workpiece dimension abnormality detection coordinate and adding it to the same modality tool machining sample.

[0138] When the tool record model is the same as the prepared tool model, the tool service time record data is consistent with the service time data, the pre-machining workpiece coordinate information is consistent with the pre-machining workpiece record coordinate information, the pre-machining workpiece record structure information is consistent with the workpiece structure information, and the machining control parameter is consistent with the machining record control parameter, it includes:

[0139] When the similarity of the tool service state of the tool service time record data and the service time data is greater than or equal to a service state similarity threshold, the tool service time record data is considered to be consistent with the service time data, otherwise, the tool service time record data is considered to be inconsistent with the service time data.

[0140] When the coordinate intersection ratio of the pre-processing workpiece coordinate information and the pre-processing workpiece record coordinate information is greater than or equal to a coordinate intersection ratio threshold, the pre-processing workpiece coordinate information is considered to be consistent with the pre-processing workpiece record coordinate information, otherwise, the pre-processing workpiece coordinate information is considered to be inconsistent with the pre-processing workpiece record coordinate information.

[0141] When the structure similarity of the pre-processing workpiece record structure information and the workpiece structure information is greater than or equal to a structure similarity threshold, the pre-processing workpiece record structure information is considered to be consistent with the workpiece structure information, otherwise, the pre-processing workpiece record structure information is considered to be inconsistent with the workpiece structure information.

[0142] Further, the selected detection coordinate acquisition module 13 includes the following execution steps:

[0143] The post-processing workpiece size abnormality detection coordinate set is grouped in the same position, and the number of coordinates in the group is counted to obtain a first position size abnormality detection frequency to an Nth position size abnormality detection frequency;

[0144] The positions in the first position size abnormality detection frequency to the Nth position size abnormality detection frequency greater than or equal to the detection frequency threshold are extracted and set as the selected detection coordinates.

[0145] Further, the tool changing strategy generation module 14 includes the following execution steps:

[0146] The area threshold calibration library is loaded, wherein the area threshold calibration library is used to store a one-to-one correspondence between a workpiece model and an area threshold;

[0147] The workpiece model is input into the area threshold calibration library, and the area threshold is output.

[0148] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0149] Those skilled in the art should understand that the embodiments of the present application can provide a method, a system or a computer program product. Therefore, the present application can take the form of a completely hardware embodiment, a completely software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program code.

[0150] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 means for functionally implementing the one or more flowcharts and / or blocks

[0151] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 means for functionally implementing the one or more flowcharts and / or blocks

[0152] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 means for functionally implementing the one or more flowcharts and / or blocks

[0153] While the preferred embodiments of the application have been described, additional variations and modifications can be made to the embodiments by those of skill in the art once they have the benefit of the present disclosure without departing from the spirit and scope of the application.

[0154] Obviously, numerous modifications and variations of the present application are possible in light of the above teachings. It is therefore to be understood that within the scope of the application, modifications and variations of this application can be practiced otherwise than as specifically written.

Claims

1. An adaptive tool changing control method for CNC machine tools based on coordinate measuring machine (CMM) detection, characterized in that, include: When the workpiece is positioned on the CNC machine tool, load the workpiece coordinate information, workpiece model, machining control parameters and pre-processed tool number before machining. Based on the pre-cutting tool number, service time sequence data is extracted from the service log. Combined with the pre-processing workpiece coordinate information, the workpiece model, and the processing control parameters as constraints, a processing sample set of the same mode tool is collected. The processing sample set of the same mode tool includes the coordinate set of workpiece size anomaly detection after processing. Based on the set of coordinates for detecting dimensional anomalies in the processed workpiece, select coordinates for which the detection frequency of dimensional anomalies is greater than or equal to the detection frequency threshold are extracted. When the area occupied by the selected detected coordinates is greater than or equal to the area threshold, an adaptive tool change control loop analysis is performed after switching the pre-tool. When the area occupied by the selected detected coordinates is less than the area threshold, the pre-tool is controlled to perform the machining task; Based on the set of coordinates for detecting dimensional anomalies in the processed workpiece, selected coordinates with a detection frequency greater than or equal to a detection frequency threshold are extracted, including: The coordinate set of the detected dimensional anomalies of the processed workpiece is grouped by the same position, and the number of coordinates in the group is counted to obtain the detection frequency of dimensional anomalies at the first position up to the detection frequency of dimensional anomalies at the Nth position. Extract the positions from the first position size anomaly detection frequency up to the Nth position size anomaly detection frequency that are greater than or equal to the detection frequency threshold, and set them as the selected detection coordinates; The process of obtaining the area threshold includes: Load the area threshold calibration library, wherein the area threshold calibration library is used to store one-to-one corresponding workpiece models and area thresholds; Input the workpiece model into the area threshold calibration library and output the area threshold.

2. The method as described in claim 1, characterized in that, When the workpiece is positioned on the CNC machine tool, the pre-machining workpiece coordinate information, workpiece model, machining control parameters, and pre-prepared tool number are loaded, including: Extract the pre-tool model number from the pre-tool number; When the workpiece is positioned on the CNC machine tool, the workpiece coordinates are collected by a coordinate measuring machine and set as the workpiece coordinate information before processing. Based on the workpiece model, match the associated tool number set from the machine tool tool magazine, wherein the prepared tool number belongs to the associated tool number set; Based on the workpiece model, match the expected workpiece structure information and the expected workpiece size information after processing; Based on the desired workpiece structure information, the desired workpiece size information, and the pre-prepared tool model, machining optimization is performed on the workpiece coordinate information before machining to obtain the machining control parameters.

3. The method as described in claim 2, characterized in that, Based on the desired post-machining workpiece structure information, the desired post-machining workpiece size information, and the pre-prepared tool model, machining optimization is performed on the pre-machining workpiece coordinate information to obtain the machining control parameters, including: Obtain the machining dimension constraint range and machining angle constraint range of the prepared tool model; Based on the expected workpiece structure information and the expected workpiece size information, several expected workpiece coordinate information are randomly constructed from the workpiece coordinate information before processing. Based on the machining dimension constraint range and the machining angle constraint range, the workpiece coordinate information before machining is processed to obtain several sets of initial machining control parameters that satisfy the several expected workpiece coordinate information after machining. The machining control parameters are obtained by sorting the several sets of initial machining control parameters according to the shortest cutting path.

4. The method as described in claim 2, characterized in that, Based on the pre-processed tool number, service time sequence data is extracted from the service log. Combined with the pre-processing workpiece coordinate information, the workpiece model, and the processing control parameters as constraints, a sample set of machining operations using the same mode of tool is collected, including: Based on the workpiece model, extract the workpiece structure information and workpiece material information; Obtain a machining sample of the tool to be analyzed, wherein the machining sample of the tool to be analyzed includes tool record model, tool service time record data, workpiece pre-machining record coordinate information, workpiece pre-machining record structure information, workpiece record material information, machining record control parameters, and workpiece post-machining record coordinate information; When the tool recording model is the same as the pre-tool model, the tool service time recording data is consistent with the service time data, the workpiece coordinate information before processing is consistent with the workpiece coordinate information before processing, the workpiece structure information before processing is consistent with the workpiece structure information, and the processing control parameters are consistent with the processing record control parameters, the coordinates in the workpiece coordinate information after processing that do not meet the expected workpiece structure information and the expected workpiece size information are extracted and set as the workpiece size anomaly detection coordinates after processing; The machining sample of the tool to be analyzed is associated with the coordinates of the abnormal size of the workpiece after machining and stored, and then added to the machining sample of the same mode tool.

5. The method as described in claim 4, characterized in that, When the tool recording model is the same as the pre-prepared tool model, and the tool service timing record data is consistent with the service timing data, and the workpiece coordinate information before machining is consistent with the workpiece coordinate information recorded before machining, and the workpiece structure information recorded before machining is consistent with the workpiece structure information, and the machining control parameters are consistent with the machining record control parameters, including: If the similarity between the tool service time sequence record data and the tool service status of the service time sequence data is greater than or equal to the service status similarity threshold, the tool service time sequence record data is considered to be consistent with the service time sequence data; otherwise, the tool service time sequence record data is considered to be inconsistent with the service time sequence data. If the intersection ratio of the workpiece coordinate information before processing with the workpiece coordinate information recorded before processing is greater than or equal to the intersection ratio threshold, the workpiece coordinate information before processing is considered to be consistent with the workpiece coordinate information recorded before processing; otherwise, the workpiece coordinate information before processing is considered to be inconsistent with the workpiece coordinate information recorded before processing. If the structural similarity between the pre-processing workpiece record structure information and the workpiece structure information is greater than or equal to the structural similarity threshold, the pre-processing workpiece record structure information is considered to be consistent with the workpiece structure information; otherwise, the pre-processing workpiece record structure information is considered to be inconsistent with the workpiece structure information.

6. An adaptive tool changing control system for CNC machine tools based on three-coordinate measuring machine (CCM) detection, characterized in that, The system is used to implement the adaptive tool changing control method for CNC machine tools based on three-coordinate detection as described in any one of claims 1-5, including: The basic information acquisition module is used to load the workpiece coordinate information, workpiece model, machining control parameters and pre-processed tool number when the workpiece is positioned on the CNC machine tool. The same-mode sample acquisition module is used to extract service time sequence data from the service log based on the pre-tool number, and combine the pre-processing workpiece coordinate information, the workpiece model and the processing control parameters as constraints to acquire a same-mode tool processing sample set, wherein the same-mode tool processing sample set includes a workpiece size anomaly detection coordinate set after processing; The selected detection coordinate acquisition module is used to extract selected detection coordinates whose size anomaly detection frequency is greater than or equal to the detection frequency threshold based on the set of size anomaly detection coordinates of the processed workpiece. The tool-changing strategy generation module is used to perform adaptive tool-changing control loop analysis after switching the pre-tool when the occupied area of ​​the selected detected coordinate is greater than or equal to the area threshold; and to control the pre-tool to perform the machining task when the occupied area of ​​the selected detected coordinate is less than the area threshold.

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