A Multifunctional Detection Method for Five-Axis CNC Machine Tools Based on Multi-Camera Vision

Abstract

The present invention provides a multi-functional detection method for a five-axis numerical control machine tool based on multi-view vision, including: collecting digital images of the movement of the X-axis, Y-axis, and Z-axis of the machine tool and the digital image of the rotation of the A-axis; calculating the offset of each axis of the machine tool by comparing the digital images of the initial positions of each axis of the machine tool and the digital images of each axis after the machine tool reaches thermal equilibrium; obtaining the compensation thermal drift data of each axis of the machine tool according to the offset; performing feedback compensation on the data of each axis of the machine tool according to the compensation thermal drift data; processing the workpiece according to the compensated parameters; detecting the appearance contour of the workpiece after the workpiece processing is completed, and then detecting the processing accuracy, and the qualified products are those within the error range. This method is convenient to operate and has high measurement efficiency, and has high application value. Using this method, the thermal error, positioning accuracy, and repeatability accuracy of the five-axis numerical control machine tool can be measured, and the compensation data can be updated with the numerical control system, which is convenient to use.

Description

Technical Field

[0001] The present invention relates to the technical field of numerical control machine tools, and particularly relates to a multi-functional detection method for a five-axis numerical control machine tool based on multi-view vision. Background Art

[0002] For five-axis numerical control machine tools such as X, Y, Z, A or B, C, etc., due to the addition of two rotating axes (or swinging axes), five-axis numerical control machine tools can machine more complex curved surface parts, can meet the requirements of modern high-precision machining, and the surface quality and machining efficiency of workpieces have been greatly improved. Five-axis numerical control machine tools can reduce the number of workpiece clamping times and reduce installation errors introduced due to clamping problems, thereby shortening the machining time. However, due to assembly accuracy, installation errors, and defects caused by continuous wear during long-term machining processes, the machining errors of the machine tool directly lead to a reduction in the machining accuracy of workpieces. Therefore, in order to improve and stabilize the machining accuracy of five-axis numerical control machine tools and the surface quality of workpieces as the goal, and to ensure the qualified rate of products, research on the compensation of repeat accuracy has been continuously developed.

[0003] Currently in China, a large amount of research has been done on the error detection direction of the rotating axes of machine tools, but there is no direct and unified method for measuring the errors of rotating axes. The commonly used detection methods mainly use measuring equipment such as ball bar testers, laser trackers, R-tests, regular 12-sided or 24-sided prisms, and autocollimators, etc., which have certain limitations. For the error measurement of the three translational axes, laser interferometers, displacement sensors, and comprehensive thermal error detection are mainly used. Among them, the ball bar tester is inexpensive and widely used, but it needs to be installed and debugged during measurement, and the measurement efficiency is low, and high technical requirements are imposed on the operators. The laser tracker is convenient and fast for measurement, but its price is relatively expensive. The R-test device is a contact measurement, with high requirements for test conditions and limited measurement efficiency. The regular 12-sided or 24-sided prism and the autocollimator require special tooling, and their test processes are complex. The laser interferometer is fast and convenient for measurement, but it has high measurement condition requirements for the machine tool environment. The displacement sensor is a non-contact measurement, with a moderate price for its device and convenient for measuring the spindle, but it is more complex for measuring other translational axes. The measurement of the positioning accuracy and repeat accuracy of the translational axes needs to be measured separately from the rotating axes, and the comprehensive measurement takes a long time.

[0004] In summary, these measurement methods have low measurement efficiency and high experimental costs. For both contact and non-contact measurement methods, operators need to be trained or the operators themselves need to have operation experience in this regard. The measurement results depend on the proficiency of the operators, and the measurement accuracy is limited. Summary of the Invention

[0005] The object of the present invention is to solve the defects existing in the above-mentioned prior art, and to provide a multi-functional detection method for a five-axis CNC machine tool based on multi-view vision, which has the advantages of reducing the test time, improving the measurement accuracy and compensation ability, and data intercommunication.

[0006] A multi-functional detection method for a five-axis CNC machine tool based on multi-view vision includes the following steps:

[0007] Step 1: Collect digital images of the initial positions of the linear axes and rotary axes of the machine tool;

[0008] Step 2: Collect digital images of the linear axes and rotary axes of the machine tool after thermal equilibrium;

[0009] Step 3: Compare the digital images of the initial positions with the digital images after thermal equilibrium, and calculate the offsets of the linear axes and rotary axes of the machine tool;

[0010] Step 4: Obtain the compensation thermal drift data of the linear axes and rotary axes of the machine tool according to the offsets;

[0011] Step 5: Perform feedback compensation on the data of the linear axes and rotary axes of the machine tool according to the compensation thermal drift data;

[0012] Step 6: Machine the workpiece according to the compensated parameters;

[0013] Step 7: After the workpiece machining is completed, detect its appearance contour, and then detect the machining accuracy, and the qualified product is within the error range.

[0014] Further, for the multi-functional detection method for a five-axis CNC machine tool based on multi-view vision as described above, the collection of digital images of the initial positions of the linear axes and rotary axes of the machine tool includes the following steps:

[0015] (1) Camera accuracy calibration: Complete the calibration of the internal and external parameters of the image acquisition device through a Halcon calibration plate;

[0016] (2) Machining area calibration: Based on the calibration of Halcon operators, first take pictures of the calibration plate at different angles, draw grids in the machining area, and use the extraction of grid corner points to determine the coordinates, so that the machine coordinates and the image coordinates correspond one by one;

[0017] (3) Initial image acquisition: Through the calibration of the image acquisition device and the operation of returning to the machine tool origin, take pictures and collect digital images according to the initial positions of each axis of the machine tool;

[0018] (4) Image processing: Import the digital images collected by the image acquisition device into a computer, and process the data based on Halcon software to obtain the initial data.

[0019] Further, in the multi-view vision-based multi-functional inspection method for five-axis CNC machine tools as described above, step 2 includes:

[0020] (1): The data acquisition device acquires the initial position image information of the linear axes and rotary axes of the machine tool after thermal equilibrium, and acquires the moving digital image position information of the linear axes and rotary axes of the machine tool during the machining process;

[0021] (2) Using the initial position image information as the calibration standard, the moving digital image position information is processed and analyzed based on Halcon software image processing to obtain the thermal equilibrium digital images of the linear axes and rotary axes of the machine tool after thermal equilibrium.

[0022] Further, in the multi-view vision-based multi-functional inspection method for five-axis CNC machine tools as described above, step 4 includes: using the digital images of the initial position and the thermal equilibrium digital images to calculate the error data of the linear axes and rotary axes of the machine tool, and obtaining the compensated thermal drift data according to the error data;

[0023] The error data is the error between the digital image of the initial position and the thermal equilibrium digital image;

[0024] The compensated thermal drift data is the error data Take the weighted mean square error to obtain the compensated thermal drift data.

[0025] Further, in the multi-view vision-based multi-functional inspection method for five-axis CNC machine tools as described above, after step 6, the following steps are further included:

[0026] Step 8: Classify the machining error range, and transfer the data to the computer according to the number of products in grade A, and then modify the production number of grade A products, so that the parts exceeding the error and the corresponding parts can also be assembled.

[0027] Further, in the multi-view vision-based multi-functional inspection method for five-axis CNC machine tools as described above, the digital image information acquired by the data acquisition device is transmitted to the computer through a wireless transmission chip for various processes.

[0028] Further, in the multi-view vision-based multi-functional inspection method for five-axis CNC machine tools as described above, the data acquisition device takes pictures of the machining area, and acquires 10 - 15 images and imports them into the data processing software for calculation.

[0029] Further, in the multi-view vision-based multi-functional inspection method for five-axis CNC machine tools as described above, after the machine tool is started, it runs for 2 - 3 hours for warm-up to reach the thermal equilibrium state of the machine tool.

[0030] Further, for the multi-vision-based multi-functional inspection method for five-axis CNC machine tools as described above, step 6 further includes: adding the compensated parameters and limit data to the CNC program together to process the workpiece.

[0031] Beneficial effects:

[0032] The multi-vision-based multi-functional inspection method for five-axis CNC machine tools provided by the present invention directly collects digital images of the digital translation axes and rotational axes (or swing axes) of the five-axis CNC machine tool using an image acquisition device. The digital images are transmitted to a computer through a wireless acquisition module for data processing. The positioning accuracy and repeatability accuracy of the five-axis CNC machine tool can be identified. By collecting digital images of the translation axes and rotational axes (or swing axes) of the five-axis CNC machine tool after running for a period of time and comparing them with the initial images, and calculating the data deviation based on the Halcon software, the thermal drift error of the translation axes and the motion error of the rotational axes (or swing axes) can be obtained. During the workpiece processing, the compensation data and limit data are updated in real time and exchanged with the CNC system data. There is no need to replace the measuring equipment, which improves the machining accuracy, the machining quality of the workpiece surface, shortens the measurement time, and the measurement data has high accuracy. Moreover, this method is easy to operate, has high measurement efficiency, and has high application value. Using this method, the thermal error, positioning accuracy, and repeatability accuracy of the five-axis CNC machine tool can be measured, and the compensation data can be updated with the CNC system, which is convenient to use. Description of the drawings

[0033] Figure 1 It is the detection preprocessing flow chart of the present invention;

[0034] Figure 2 It is the processing process control flow chart of the present invention;

[0035] Figure 3 It is the product grading flow chart of the present invention. Detailed implementation manners

[0036] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0037] The invention provides a multifunctional detection method for a five-axis CNC machine tool based on multi-eye vision. The equipment used in the method includes: a high-resolution CMOS camera, a data transmission module, a computer, a limit module and a compensation module. Four CMOS cameras are fixed by a camera mounting frame, and the four CMOS cameras are at a certain height from a workbench and are arranged 90 degrees apart. The camera aims at a processing area, collects digital images during the processing, transmits the data to the computer through the data transmission module, exchanges data with the limit module and the compensation module after processing by Halcon software, and transmits the updated data to the CNC system of the machine tool through the data transmission module; in addition, there is a CMOS camera, which aims at the processing area, collects a digital image of a workpiece by using the camera after processing, and performs error judgment after comparing the data with a template library by processing the data by Halcon software, and performs product classification.

[0038] To obtain clear and accurate digital images, the light source between the processing area and the camera uses the camera's own high-brightness Hi-R lighting source to illuminate the entire field of view with bright and uniform light, and the camera has an autofocus function. To obtain clear and accurate digital images, the camera uses a high-performance HP-Quad lens to capture bright and clear images. To eliminate the halo problem in the captured image, the camera is equipped with an accessory that can remove the halo.

[0039] The invention provides a multifunctional detection method for a five-axis CNC machine tool based on multi-eye vision. The method adopts a high-resolution multi-eye vision system and collects the position information of each axis of the machine tool through camera precision calibration. According to the sampling period, the visual system collects data every time the translation axis moves a certain distance, calculates the translation axis offset by comparing the initial position and the collected digital image, and takes the average value of the offset; the visual system collects data every time the rotation axis rotates a certain angle, calculates the rotation axis rotation offset by comparing the initial position and the collected digital image, and takes the average value of the offset; the offset compensation of the translation axis and the rotation axis is input into the CNC system.

[0040] Example:

[0041] The embodiment of the present invention adopts a dual-turntable five-axis CNC machine tool, that is, in addition to the three translation axes of X, Y, and Z, the worktable and the spindle can rotate. The translation axis only moves in the X, Y, and Z directions to achieve linear interpolation, or multi-axis linkage to achieve circular interpolation; the rotation axis, the spindle rotates to drive the tool to achieve milling, or the worktable rotates to achieve turning, or multi-axis linkage to achieve complex cutting motion. Because the present embodiment adopts a dual-turntable five-axis CNC machine tool, the rotational motion of the worktable, generally five-axis CNC machine tools have corresponding feedback to provide rotation compensation, so the rotation data of the worktable is not collected for the time being. In short, the most critical X, Y, Z translation axis working data and A-axis rotation working data are collected as the data source of the detection method of this application.

[0042] A multi-functional detection method for a five-axis CNC machine tool based on multi-view vision provided by an embodiment of the present invention is characterized in that it includes the following steps:

[0043] Step 1: Collect digital images of the initial positions of the linear axes and rotary axes of the machine tool;

[0044] Step 2: Collect thermal equilibrium digital images of the linear axes and rotary axes of the machine tool after thermal equilibrium;

[0045] Step 3: Calculate the offsets of the linear axes and rotary axes of the machine tool by comparing the digital images of the initial positions and the thermal equilibrium digital images;

[0046] Step 4: Obtain the compensated thermal drift data of the linear axes and rotary axes of the machine tool according to the offsets;

[0047] Step 5: Perform feedback compensation on the data of the linear axes and rotary axes of the machine tool according to the compensated thermal drift data;

[0048] Step 6: Machine the workpiece according to the compensated parameters;

[0049] Step 7: After the workpiece machining is completed, detect its appearance contour, and then detect the machining accuracy, and the qualified product is within the error range.

[0050] Among them, the collection of digital images of the initial positions of the linear axes and rotary axes of the machine tool includes the following steps:

[0051] (1) Camera accuracy calibration: Complete the calibration of the internal and external parameters of the image acquisition device through the Halcon calibration plate;

[0052] (2) Machining area calibration: Based on the calibration of Halcon operators, first take pictures of the calibration plate at different angles, draw grids in the machining area, and use the extraction of grid corner points to determine the coordinates, and the machine coordinates and image coordinates correspond one by one;

[0053] (3) Initial image acquisition: Through the calibration of the image acquisition device and the operation of returning to the machine tool origin, take pictures and collect digital images according to the initial positions of each axis of the machine tool;

[0054] (4) Image processing: Import the digital images collected by the image acquisition device into the computer, and process the data based on the Halcon software to obtain the initial data.

[0055] The said Step 2 includes:

[0056] (1): The data acquisition device collects the initial position image information of the linear axes and rotary axes of the machine tool after thermal equilibrium, and collects the motion digital image position information of the linear axes and rotary axes of the machine tool during the machining process;

[0057] (2) Using the initial position image information as the calibration standard, the motion digital image position information is processed based on Halcon software image processing and data analysis to obtain the thermal balance digital images of the linear axes and rotary axes of the machine tool after thermal balance of the machine tool.

[0058] Specifically, among various error sources, the machine tool error accounts for 45% - 65% of the total proportion, and among them, the machine tool thermal error accounts for 25% - 35% of the total proportion. Machine tool thermal balance means that after the machine tool is started, a temperature dynamic balance is reached, where the influence of temperature rise on each component of the machine tool reaches an equilibrium value. Using this data as the benchmark for subsequent processing, the errors of the motion data of each axis during the processing are more accurate compared to the case where thermal balance data is not used as the benchmark. Otherwise, calibration and separation of thermal errors are required for each measurement. Therefore, two types of data need to be collected, which can also be used to obtain the measurement methods for the thermal errors of each axis.

[0059] Step 4 includes: using the digital image at the initial position and the thermal balance digital image to calculate the error data and limit data of the linear axes and rotary axes of the machine tool, and obtaining the compensated thermal drift data based on the error data and limit data;

[0060] The error data is the error between the digital image at the initial position and the thermal balance digital image;

[0061] The compensated thermal drift data is for the error data Take the weighted mean square error to obtain the compensated thermal drift data.

[0062] Specifically, each axis is moved to the test specified position, the camera collects the digital image and transmits it to the computer. This image is used as the digital image at the initial position, denoted as Image 0. Each axis is moved away from the test specified position, the five-axis CNC machine tool is started and run continuously for a period of time, then the machine tool is stopped and each axis is moved to the test specified position, and the image at this time is recorded, denoted as Image 1. Comparing Image 0 and Image 1, according to Step 2, calculate the thermal offset of each axis, that is, obtain the thermal elongation of each axis generated during this period; then move each axis away from the test specified position, run the machine tool continuously, and repeat the above steps at regular intervals. By comparing the offsets of each axis in the image m collected at different times with the initial image 0, the thermal elongation of each axis at different times can be measured, and the weighted mean square error of the data is taken as the compensated thermal drift data.

[0063] After Step 6 in this embodiment, the following steps are further included:

[0064] Step 8: Perform hierarchical processing on the machining error range, and transmit the data to the computer according to the number of products in Grade A to modify the production quantity of Grade A products, so that the parts exceeding the error and the corresponding parts can also be assembled in a matching manner.

[0065] Specifically, since not only one type of part is produced in the production line, but multiple parts are assembled together to produce the finished product, grading the parts is to enable parts with errors beyond the tolerance and compatible parts to be assembled together (without affecting the general assembly and meeting the product requirements), reduce the rejection rate, improve the production efficiency, and lower the cost.

[0066] The digital image information collected by the data acquisition device in this embodiment is transmitted to a computer through a wireless transmission chip for various processes. The data acquisition device takes pictures of the processing area and collects 10 to 15 images and imports them into data processing software for calculation. After the machine tool starts, it runs for 2 to 3 hours for warm-up to reach the thermal equilibrium state of the machine tool.

[0067] In addition, for step (6), when performing blind hole machining, for example, the data for compensating thermal drift is error data. However, in actual machining, in addition to the thermal error data, there is also an error between the actual machining and the theoretical data of the machining program (at this time, the thermal drift data has been included in the compensation). Such an error is called limit data in the present invention. This data is applied to obtain the actual machining data by indirect data in blind hole machining and the like, and is recorded together with the thermal error data for calculating the compensation data. Different compensation data is added to the numerical control program to reach a value as close as possible to the theoretical machining value. Therefore, in calculating the compensation for thermal drift data, the limit data is not involved, while in machining, the limit data and the thermal drift data need to be added to the numerical control program together to meet the production requirements.

[0068] The detection method provided by the present invention will be further elaborated below. As Figure 1 、 Figure 2 、 Figure 3 shown, it includes three parts: a detection preprocessing process, a machining process control process, and a product grading process.

[0069] Among them, the detection preprocessing process is as Figure 1 shown and includes:

[0070] (1) Camera accuracy calibration: Based on the calibration function of the Halcon software, the calibration plate has the characteristics of easy extraction of calibration points and high calibration accuracy. The internal and external parameters of the camera are calibrated through the Halcon calibration plate.

[0071] (2) Machining area calibration: Based on the calibration of the Halcon operator, first take pictures of the calibration plate at different angles, draw a grid in the machining area, and use the extraction of grid corner points to determine the coordinates, so that the machine coordinates and the image coordinates correspond one by one.

[0072] (3) Initial image acquisition: Through camera calibration and the operation of returning to the machine tool origin, digital images are taken according to the initial positions of each axis of the machine tool.

[0073] (4) Image processing: Import the digital images collected by the camera into the computer, process the data based on the Halcon software, and import it into the template library.

[0074] The processing process control flow is as Figure 2 shown, and includes the following steps:

[0075] (5) Detection startup: Process the machine tool according to a predetermined program for processing tests;

[0076] (6) Digital image acquisition: Collect the digital image position information after the thermal balance of each axis through the camera, and collect the digital image position information of the movement of each axis during the processing process;

[0077] Specifically, among various error sources, the machine tool error accounts for 45%-65% of the total proportion, of which the machine tool thermal error accounts for 25%-35% of the total proportion. The machine tool thermal balance means that after the machine tool starts, it reaches a temperature dynamic balance, where the influence of the temperature rise on each component of the machine tool reaches the balance value. This data is used as the benchmark for subsequent processing. Subsequently, the error of the movement data of each axis during the processing process is more accurate compared to the case where the thermal balance data is not used as the benchmark. Otherwise, each measurement requires calibration and separation of the thermal error. Therefore, two types of data need to be collected. Furthermore, it can also be used to obtain the measurement method of the thermal error of each axis.

[0078] (7) Image distortion processing and data processing: After transmitting the collected digital image data to the computer, perform image processing and data analysis based on the Halcon software, and compare it with the data in the template library;

[0079] (8) Compensation calculation: After comparing the collected data with the data in the template library, perform error calculation, limit calculation, and compensation calculation;

[0080] (9) Import feedback data: Import the compensation data calculated by the computer into the machine tool numerical control system;

[0081] (10) Processing matching: Perform matching processing on the workpiece according to the imported data.

[0082] The product grading process is as Figure 3 shown, and includes the following steps:

[0083] (11) Processing accuracy detection: After the product processing is completed, detect its appearance contour, and then perform processing accuracy detection. Products within the error range are qualified products;

[0084] (12) Product classification: Classify the processing error range, and modify the production quantity of Class A products after transmitting the data to the computer according to the situation where i products are in Class A.

[0085] In the above detection method, the camera takes pictures of the processing area during the processing, and 10 to 15 images are collected and imported into the data processing software for calculation.

[0086] In the above detection method, after the machine tool is started, it runs for 2 to 3 hours for warm-up to reach the thermal equilibrium state of the machine tool.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multi-functional detection method for five-axis CNC machine tools based on multi-view vision, characterized in that, It includes the following steps: Step 1: Collect digital images of the initial positions of the linear axes and rotary axes of the machine tool; Step 2: Collect digital images of the thermal equilibrium of the linear axes and rotary axes of the machine tool after thermal equilibrium; Step 3: Calculate the offsets of the linear axes and rotary axes of the machine tool by comparing the digital images of the initial positions and the digital images of the thermal equilibrium; Step 4: Obtain the compensated thermal drift data of the linear axes and rotary axes of the machine tool according to the offsets; Step 5: Perform feedback compensation on the data of the linear axes and rotary axes of the machine tool according to the compensated thermal drift data; Step 6: Machine the workpiece according to the compensated parameters; Step 7: After the workpiece machining is completed, detect its appearance contour, and then detect the machining accuracy. Parts within the error range are qualified products.

2. The multi-functional inspection method for a five-axis CNC machine tool based on multi-view vision according to claim 1, wherein, The collection of digital images of the initial positions of the linear axes and rotary axes of the machine tool includes the following steps: (1) Camera accuracy calibration: Complete the calibration of the internal and external parameters of the image acquisition device through the Halcon calibration plate; (2) Machining area calibration: Based on the calibration of Halcon operators, first take pictures of the calibration plate at different angles, draw grids in the machining area, use the extraction of grid corner points to determine the coordinates, and establish a one-to-one correspondence between the machine coordinates and the image coordinates; (3) Initial image acquisition: Through the calibration of the image acquisition device and the operation of returning to the machine tool origin, take pictures and collect digital images according to the initial positions of each axis of the machine tool; (4) Image processing: Import the digital images collected by the image acquisition device into the computer, and process the data based on the Halcon software to obtain the initial positions.

3. The multi-functional inspection method for a five-axis CNC machine tool based on multi-view vision according to claim 2, wherein Step 2 includes: (1): The data acquisition device collects the initial position image information of the linear axes and rotary axes of the machine tool after thermal equilibrium, and collects the motion digital image position information of the linear axes and rotary axes of the machine tool during the machining process; (2) Taking the initial position image information as the calibration standard, perform image processing and data analysis on the motion digital image position information based on the Halcon software to obtain the digital images of the thermal equilibrium of the linear axes and rotary axes of the machine tool after thermal equilibrium.

4. The multi-functional detection method for a five-axis CNC machine tool based on multi-view vision according to claim 1, characterized in that, Step 4 includes: Calculate the error data of the linear axes and rotary axes of the machine tool by using the digital images of the initial positions and the digital images of the thermal equilibrium, and obtain the compensated thermal drift data according to the error data; The error data is the error between the digital images of the initial positions and the digital images of the thermal equilibrium; The compensated thermal drift data are the error data Take the weighted mean square error to obtain the compensated thermal drift number data.

5. The multi-functional inspection method for a five-axis CNC machine tool based on multi-view vision according to claim 1, wherein, After Step 6, the following steps are also included: Step 8: Classify the machining error range, transfer the data to the computer according to the number of products in Grade A, and modify the production number of Grade A products so that parts exceeding the error and corresponding parts can also be assembled.

6. The multi-functional inspection method for a five-axis CNC machine tool based on multi-view vision according to claim 1, wherein, The digital image information collected by the data acquisition device is transmitted to the computer through the wireless transmission chip for various processes.

7. The multi-functional inspection method for a five-axis CNC machine tool based on multi-view vision according to claim 1, characterized in that The data acquisition device takes pictures of the machining area, collects 10 - 15 images and imports them into the data processing software for calculation.

8. The multi-functional inspection method for a five-axis CNC machine tool based on multi-view vision according to claim 1, wherein, After the machine tool is started, perform warm-up for 2 to 3 hours to reach the thermal equilibrium state of the machine tool.

9. The multi-functional inspection method for a five-axis CNC machine tool based on multi-view vision according to claim 4, characterized in that Step 6 also includes: Add the compensated parameters and limit data to the numerical control program together to machine the workpiece; The limit data refers to the error between the data obtained from the indirect measurement in the machining process and the theoretical data of the program.

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