An online automatic measurement and compensation method for digital manufacturing

Abstract

The present invention relates to an online automatic measurement and compensation method for digital manufacturing, which is mainly used to improve the accuracy and efficiency of part processing in digital manufacturing. The method first establishes a processing coordinate system of a part on a digital manufacturing device, and then uses a pre-compiled online measurement program to measure the actual coordinate value of the part's processing position through a probe. Subsequently, the method compares the actual coordinate value with the predetermined theoretical coordinate value, calculates the deviation value between the two, and determines the compensation parameters of the processing program accordingly. Finally, the processing path or tool position is adjusted according to these compensation parameters to complete the precise processing of the part. This method significantly improves the automation level and manufacturing accuracy of the processing process through real-time monitoring and automatic adjustment, and is suitable for various high-precision manufacturing fields.

Description

Technical Field

[0001] The invention relates to the field of digital manufacturing measurement technology, and in particular to an online automatic measurement and compensation method for digital manufacturing. Background Art

[0002] In existing digital manufacturing technologies, precise control of the machining process is crucial to improving product quality and efficiency. Existing technologies usually rely on pre-set programs and fixed parameters to guide machine tool operations, which includes the use of advanced CNC systems and automation tools to perform complex machining tasks. In addition, some technologies also involve the use of various sensors to monitor the machining status in real time, such as measuring the position or size of the workpiece through laser or tactile sensors.

[0003] However, although existing technologies have been able to achieve automation and precision machining to a certain extent, there are still some significant problems in practical applications. One of the main problems is that existing systems are not flexible enough to deal with real-time changes or abnormal situations, which may lead to reduced machining accuracy or limited machining efficiency. In addition, traditional methods often require manual intervention to adjust machining parameters when faced with complex or highly variable machining environments, which not only increases the complexity of operations, but also affects the continuity and stability of production.

[0004] Therefore, it is necessary to develop a new online automatic measurement and compensation method for digital manufacturing. Summary of the invention

[0005] The present application provides an online automatic measurement and compensation method for digital manufacturing to improve the accuracy and efficiency of part processing in digital manufacturing.

[0006] The present application provides an online automatic measurement and compensation method for digital manufacturing, comprising:

[0007] Establish a part processing coordinate system on digital manufacturing equipment;

[0008] Based on the established machining coordinate system, the actual coordinate value of the part to be machined is measured using a probe through a pre-programmed online measurement program.

[0009] Comparing the actual coordinate value with the predetermined theoretical coordinate value, and calculating the deviation between the actual coordinate value and the predetermined theoretical coordinate value;

[0010] Determining compensation parameters of a machining program according to the deviation value;

[0011] According to the compensation parameters, the machining path or the tool position is adjusted to complete the machining of the part.

[0012] Furthermore, establishing a processing coordinate system of a part on a digital manufacturing device includes:

[0013] Configure laser scanners on digital manufacturing equipment to accurately scan parts from at least three different angles to capture all-round 3D data of the part surface;

[0014] The obtained three-dimensional scanning data is imported into the data processing system of the digital manufacturing equipment, and the noise and error generated during the scanning process are removed by using an image processing algorithm to obtain the denoised three-dimensional scanning data;

[0015] Generate a three-dimensional model of the part based on the denoised three-dimensional scanning data;

[0016] Identifying at least five key processing points on the three-dimensional model, wherein the key processing points are selected according to functional requirements and structural characteristics of the part;

[0017] The at least five key processing points and their coordinate information are stored in a control system of the digital manufacturing equipment.

[0018] Furthermore, the process of measuring the actual coordinate values ​​of the position of the part to be processed by using a probe based on the established processing coordinate system through a pre-programmed online measurement program includes:

[0019] Install and calibrate high-precision probes on digital manufacturing equipment;

[0020] Based on the machining coordinate system, compile the probe's moving path and measurement program;

[0021] Execute the measurement program, and the probe measures each measurement point multiple times along the set path to collect the actual coordinate values.

[0022] Furthermore, the comparing the actual coordinate value with the predetermined theoretical coordinate value to calculate the deviation between the actual coordinate value and the predetermined theoretical coordinate value includes:

[0023] Receive actual coordinate value data collected by the measurement system on the digital manufacturing equipment;

[0024] Retrieving theoretical coordinate values ​​of the corresponding part from a design database, wherein the theoretical coordinate values ​​are pre-set based on the part design file and have been optimized according to the processing requirements of the part;

[0025] The data of each actual coordinate point is compared with its corresponding theoretical coordinate value to obtain the deviation value between the actual coordinate value and the predetermined theoretical coordinate value.

[0026] Furthermore, determining the compensation parameters of the machining program according to the deviation value includes:

[0027] For each measuring point , calculate the normalized deviation value according to the following formula 1 :

[0028]

[0029] in is the actual coordinate value; is the theoretical coordinate value; is a small constant used to prevent the denominator from being zero;

[0030] According to the following formula 2, calculate the overall weighted average deviation value :

[0031]

[0032] in, For measuring point The weight of is the decay rate; is the time from the start of measurement to the present;

[0033] According to the following formula 3, the compensation parameters are calculated :

[0034]

[0035] in, is the adaptive coefficient, which is calculated according to the following formula 4:

[0036]

[0037] in, yes Initial value at the start of processing; Represents time The root mean square error of the compensation so far; is the decay constant; is the adjustment factor; represents the angular frequency of the periodic component; is the phase shift of the periodic component;

[0038] The calculated compensation parameters Determine the compensation parameters for the machining program.

[0039] Furthermore, adjusting the machining path or tool position according to the compensation parameter to complete the machining of the part includes:

[0040] During the machining process, an acceleration sensor is used to monitor the tool vibration in real time and obtain the tool vibration data;

[0041] Based on the vibration data and compensation parameters, a fuzzy control algorithm is used to dynamically adjust the feed speed and spindle speed to optimize machining quality and efficiency.

[0042] Furthermore, the dynamically adjusting the feed speed and the spindle speed using a fuzzy control algorithm based on the vibration data and the compensation parameters includes:

[0043] Through a preset fuzzy control system, the following operations are performed:

[0044] Define fuzzy sets and membership functions;

[0045] Formulate clear fuzzy control rules;

[0046] Mamdani fuzzy reasoning method is applied to calculate the specific values ​​of feed speed and spindle speed according to the actual values ​​of vibration intensity and compensation parameters;

[0047] According to the specific values, adjust the feed speed and spindle speed.

[0048] Furthermore, the definition of fuzzy sets and membership functions includes:

[0049] Three levels of membership functions are defined for vibration intensity, specifically: low vibration (0-0.3g, g represents gravity acceleration), medium vibration (0.25-0.65g), and high vibration (0.6-1.0g). Each level of membership function is represented by a trapezoidal diagram, where the two ends of the trapezoids for low vibration and high vibration are closed.

[0050] The compensation parameters are divided into three levels: small adjustment (0%-10% speed adjustment), medium adjustment (8%-20% speed adjustment), and large adjustment (18%-30% speed adjustment); they are defined using trapezoidal membership functions to ensure smooth transitions at parameter boundaries.

[0051] Furthermore, the formulation of clear fuzzy control rules includes:

[0052] A specific fuzzy control rule is formulated, which includes: if the vibration level is high (0.6-1.0g) and the compensation parameter is a large adjustment (18%-30%), then reduce the feed rate by 25% and reduce the spindle speed by 15%.

[0053] Furthermore, the Mamdani fuzzy reasoning method is applied to calculate specific values ​​for adjusting the feed speed and spindle speed according to the actual values ​​of the vibration intensity and the compensation parameters, including:

[0054] The Mamdani reasoning mechanism is implemented to determine the activation degree of each fuzzy rule based on the input vibration intensity and compensation parameter, where the relevant fuzzy rule is considered fully activated when the vibration intensity is 0.8g and the compensation parameter is 25%;

[0055] Aggregate the outputs of all activated fuzzy rules and use the maximization method to integrate the results of these activated rules to form a comprehensive fuzzy output;

[0056] The centroid method is used to convert the comprehensive fuzzy output into specific mechanical control commands to obtain specific values ​​for adjusting the feed speed and spindle speed.

[0057] The beneficial effects of the technical solution provided by this application include:

[0058] (1) This method ensures high accuracy in the manufacturing process by establishing an accurate part machining coordinate system on the digital manufacturing equipment and continuously measuring the actual coordinate values ​​of the parts to be machined. The actual coordinate values ​​are compared with the theoretical values, and any deviations are detected and corrected in real time, significantly reducing errors and improving the quality of the final product. (2) By automating the measurement and compensation process, this method reduces the need for manual intervention, thereby speeding up the manufacturing process. This automation not only saves time but also increases the production throughput of the manufacturing facility. (3) The ability to dynamically adjust machining parameters based on observed deviations makes the manufacturing process more adaptable to different part specifications or unexpected problems that arise during the machining process. This flexibility is critical for manufacturers that deal with complex parts or require a high degree of customization. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 This is a flow chart of an online automatic measurement and compensation method for digital manufacturing provided in the first embodiment of the present application. DETAILED DESCRIPTION

[0060] Many specific details are described in the following description to facilitate a full understanding of the present application. However, the present application can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of the present application, so the present application is not limited by the specific implementation disclosed below.

[0061] The first embodiment of the present application provides an online automatic measurement and compensation method for digital manufacturing. Figure 1 , which is a schematic diagram of the first embodiment of the present application. Figure 1 The first embodiment of the present application provides an online automatic measurement and compensation method for digital manufacturing, which is described in detail.

[0062] Step S101: Establish a part processing coordinate system on a digital manufacturing device.

[0063] In this embodiment, step S101 involves establishing a part processing coordinate system on the digital manufacturing equipment. This step is the basis of the entire automatic measurement and compensation method, and provides a necessary reference framework for subsequent measurement, deviation calculation and compensation adjustment.

[0064] First, select suitable digital manufacturing equipment, such as CNC machine tools or other precision processing equipment, to ensure that the equipment can support high-precision coordinate positioning and measurement functions. Next, use a dedicated equipment interface or control software to start the procedure for establishing the coordinate system. At this stage, the operator needs to input the design parameters and processing requirements of the part, including the size, shape, and expected processing accuracy of the part.

[0065] Subsequently, the original form of the part is systematically scanned using a measuring tool such as a laser scanner or a tactile probe mounted on the manufacturing equipment. This scanning process collects the surface and structural data of the part and converts it into a digital signal to be input into the manufacturing system. By analyzing this data, the software will calculate the actual geometric center or other key feature points of the part and use this to establish a processing coordinate system.

[0066] In the process of establishing the coordinate system, it is necessary to ensure that the origin, axis and scale of the coordinate system are strictly aligned with the design and processing requirements of the part. This may require multiple rounds of scanning and adjustment to eliminate any deviation caused by equipment errors, improper part clamping or environmental factors.

[0067] After completing these steps, the machining coordinate system will be fixed in the control system to provide a coordinate reference for subsequent precise machining. At this time, the system will also perform a calibration to compare the set value of the coordinate system with the actual measured value to ensure that its accuracy meets the manufacturing standards. If any abnormality is detected, the system will prompt the operator to recalibrate or adjust the parameters.

[0068] The detailed record and accurate execution of this step are crucial to ensure the quality and efficiency of the entire processing process, and can significantly improve the accuracy and consistency of the finished product. In this way, the present embodiment can ensure the efficiency and accuracy of part processing during the digital manufacturing process.

[0069] Furthermore, establishing a processing coordinate system of a part on a digital manufacturing device includes:

[0070] Configure laser scanners on digital manufacturing equipment to accurately scan parts from at least three different angles to capture all-round 3D data of the part surface;

[0071] The obtained three-dimensional scanning data is imported into the data processing system of the digital manufacturing equipment, and the noise and error generated during the scanning process are removed by using an image processing algorithm to obtain the denoised three-dimensional scanning data;

[0072] Generate a three-dimensional model of the part based on the denoised three-dimensional scanning data;

[0073] Identifying at least five key processing points on the three-dimensional model, wherein the key processing points are selected according to functional requirements and structural characteristics of the part;

[0074] The at least five key processing points and their coordinate information are stored in a control system of the digital manufacturing equipment.

[0075] First, operators need to configure laser scanners on digital manufacturing equipment. Choosing the right laser scanner is key, as it needs to be able to scan the part from all angles. Typically, these scanners are fixed to the robotic arm of the manufacturing equipment, able to rotate around the part and scan from at least three different angles to ensure that all surface details of the part are captured.

[0076] During the scanning process, the laser scanner generates a large number of raw 3D data points, which form an accurate digital representation of the part surface. Subsequently, these raw data need to be imported into the data processing system of the digital manufacturing equipment. In the data processing stage, advanced image processing algorithms are used to analyze these data to remove noise and errors that may be introduced by mechanical vibrations during the scanning process, changes in ambient light, and other factors. This step is to ensure data quality and lay a solid foundation for subsequent steps.

[0077] The processed data is then used to generate a detailed 3D model of the part. In this step, the data processing software will build a complete digital model based on the denoised 3D scan data, which accurately reflects the geometry and size of the part. In this way, it can be ensured that the model used in the digital manufacturing process is highly consistent with the actual part.

[0078] Next, technicians or automated systems will identify at least five critical processing points on the 3D model. These critical processing points are selected based on the functional requirements and structural characteristics of the part. For example, they may include areas that bear the greatest pressure, structural connection points, or locations where dimensional accuracy is particularly high. The accurate identification of each critical processing point is essential to ensure processing accuracy and part performance.

[0079] Finally, these key processing points and their precise coordinate information are stored in the control system of the digital manufacturing equipment. In this way, the control system can accurately guide the machine tool or other processing equipment in the subsequent processing process to process these key points according to the predetermined path and method, thereby ensuring that the processing quality and performance of the entire part meet the design requirements.

[0080] Through the above steps, high-precision and high-efficiency processing of parts can be achieved.

[0081] Step S102: Based on the established processing coordinate system, the actual coordinate value of the position to be processed of the part is measured using a probe through a pre-programmed online measurement program.

[0082] In step S102, the core task is to use the probe to measure the actual coordinate value of the part to be processed based on the established processing coordinate system. This step is performed through a precise online measurement program to ensure that the actual processing status of the part can be accurately captured, providing necessary data support for subsequent processing.

[0083] First, it is necessary to ensure that the probe equipment has been fully integrated with the digital manufacturing equipment, and that the probe can accurately align and contact the surface of the part after the machining coordinate system is established. This usually involves automatic positioning technology in the control system to ensure that the probe moves along the predetermined path and can accurately locate each measurement point according to the machining coordinate system.

[0084] Next, start the measurement program. This program is pre-programmed and includes parameters such as the probe's movement trajectory, contact frequency, and pressure setting. These parameters need to be set in advance according to the material, shape, and processing accuracy requirements of the part. During the measurement process, the probe touches the key measurement points on the surface of the part one by one, and the sensor records the actual coordinate value of each point. These coordinate values ​​are transmitted back to the database of the manufacturing system in real time.

[0085] In order to improve the accuracy of the measurement, multiple measurements are usually taken at key measurement points and the average value is calculated. This can not only reduce the impact of occasional errors, but also conduct a preliminary error analysis of the measurement results and preliminarily identify possible anomalies or deviations.

[0086] After all measurement data is collected, the system will conduct a comprehensive data review to ensure that the data of all measurement points are within the allowable error range. If data anomalies are detected, the system may prompt the operator to re-measure or adjust the measurement parameters.

[0087] The implementation of the entire step S102 requires a high degree of precision control and data processing capabilities to ensure that the measured actual coordinate values ​​can accurately reflect the actual conditions of the parts, providing a reliable basis for the next step of deviation calculation and processing compensation. The successful execution of this step is crucial to the quality control of the entire digital manufacturing process.

[0088] Furthermore, the process of measuring the actual coordinate values ​​of the position of the part to be processed by using a probe based on the established processing coordinate system through a pre-programmed online measurement program includes:

[0089] Install and calibrate high-precision probes on digital manufacturing equipment;

[0090] Based on the machining coordinate system, compile the probe's moving path and measurement program;

[0091] Execute the measurement program, and the probe measures each measurement point multiple times along the set path to collect the actual coordinate values.

[0092] First, technicians need to install high-precision probes on digital manufacturing equipment. The installation position and orientation of the probes are critical to the accuracy of the measurement results, so the installation process must be carried out strictly in accordance with the equipment manufacturer's guidelines. After the installation is completed, the probes are calibrated as necessary to ensure that their measurement accuracy meets manufacturing requirements. The calibration process usually includes adjusting and testing the sensitivity, measurement range, and error range of the probes to ensure that the performance of the probes in actual operation can meet the design standards.

[0093] Next, based on the established machining coordinate system, the technician or system programmer needs to compile the probe's movement path and measurement program. This program will guide the probe to move accurately to each point to be measured on the part along the predetermined path. When compiling the program, it is necessary to consider the part's geometry, size, and machining complexity, and reasonably arrange the probe's travel path and stop points to optimize the efficiency and effectiveness of the measurement process.

[0094] Then, the measurement procedure is executed. In this process, the probe will move point by point to the key position of the part according to the set path, and perform multiple measurements at each measurement point to collect data. Multiple measurements help improve the reliability and stability of the data and reduce the impact of occasional errors. The actual coordinate values ​​obtained by measurement will be transmitted instantly to the central processing system of the digital manufacturing equipment for subsequent data analysis and processing quality control.

[0095] By implementing the above steps, the processing quality of parts can be guaranteed and high-precision manufacturing requirements can be met.

[0096] Step S103: Compare the actual coordinate value with the predetermined theoretical coordinate value, and calculate the deviation value between the actual coordinate value and the predetermined theoretical coordinate value.

[0097] In step S103, the actual coordinate value is compared with the predetermined theoretical coordinate value, and the deviation value between the two is calculated. This step is the key to achieve precise manufacturing because it directly affects the subsequent compensation measures and processing quality.

[0098] First, this step needs to collect all the actual coordinate values ​​measured in step S102. These coordinate values ​​represent the actual position of the part on the digital manufacturing equipment, and these data are usually stored in the database of the manufacturing system in digital form. At the same time, the system also needs to retrieve the corresponding theoretical coordinate values, which are pre-set based on the design file of the part and have been accurately defined by software and engineer input in the early stage of manufacturing.

[0099] The system then compares the actual coordinate values ​​with the corresponding theoretical coordinate values ​​one by one using a dedicated comparison algorithm. This comparison process is usually performed by an automated software program to ensure speed and accuracy. For each measured point, the algorithm calculates the difference between the two, which is defined as the deviation value. The specific calculation formula may be deviation value = theoretical coordinate value - actual coordinate value, or it may be different depending on the needs of the specific application.

[0100] Each deviation value will be recorded and analyzed. The system will perform statistical analysis on all deviation values ​​to determine whether there is a systematic deviation trend or an occasional error. This analysis is crucial for subsequent compensation decisions, because only by correctly understanding the nature and scale of the deviation can an effective compensation strategy be formulated.

[0101] After these comparisons and calculations are completed, all deviation values ​​will be compiled into a report and stored in the system. This information will provide the necessary data support for step S104 so as to accurately adjust the processing program and ensure the final accuracy and quality of the part processing.

[0102] Through this detailed and systematic deviation analysis, step S103 not only improves the accuracy of manufacturing, but also provides a data basis for quality control and continuous improvement of the entire processing process. This method ensures the clarity and feasibility of technical operations, and helps to improve the efficiency and product quality of the entire digital manufacturing process.

[0103] Furthermore, the comparing the actual coordinate value with the predetermined theoretical coordinate value to calculate the deviation between the actual coordinate value and the predetermined theoretical coordinate value includes:

[0104] Receive actual coordinate value data collected by the measurement system on the digital manufacturing equipment;

[0105] Retrieving theoretical coordinate values ​​of the corresponding part from a design database, wherein the theoretical coordinate values ​​are pre-set based on the part design file and have been optimized according to the processing requirements of the part;

[0106] The data of each actual coordinate point is compared with its corresponding theoretical coordinate value to obtain the deviation value between the actual coordinate value and the predetermined theoretical coordinate value.

[0107] First, the system needs to receive the actual coordinate value data from the measurement system on the digital manufacturing equipment. This data is usually collected in real time through various sensors on the equipment, such as laser scanners or contact probes. The measurement system will accurately record the position information of each processing point and transmit this information to the central processing system in real time. In the process of receiving data, the system may also perform preliminary data cleaning and formatting operations to ensure the accuracy and consistency of the data.

[0108] The system then needs to retrieve the theoretical coordinate values ​​corresponding to the part being processed from the design database. These theoretical coordinate values ​​are pre-set based on the design file of the part and have been optimized to meet specific processing requirements. The acquisition of theoretical coordinate values ​​usually involves accessing the CAD model or other engineering design documents of the part, which are stored in the database of the manufacturing system or the related design management system.

[0109] Once the actual coordinate values ​​and theoretical coordinate values ​​are prepared, the system will compare the data of each actual coordinate point with its corresponding theoretical coordinate value. The comparison process can be performed by special software algorithms, which not only compare the position differences of the coordinate points, but also analyze the patterns and trends of the deviations. Through this comparison, the system can accurately obtain the deviation value between the actual coordinate value of each measured point and the predetermined theoretical coordinate value.

[0110] The execution of this step provides the necessary data support for subsequent processing compensation, ensuring that the processing process can be dynamically adjusted according to the actual situation, thereby improving processing accuracy and reducing scrap rate. When implementing this step, technicians need to ensure that all systems and software are in the correct operating state to ensure the accuracy and real-time nature of data processing.

[0111] Step S104: Determine compensation parameters of the machining program according to the deviation value.

[0112] In step S104, the compensation parameters required in the machining program are determined based on the deviation between the actual coordinate values ​​measured previously and the predetermined theoretical coordinate values. This step is to ensure that the final machining accuracy of the part meets the design requirements by dynamically adjusting the machining program to compensate for any errors found.

[0113] First, this step needs to receive the deviation value data from step S103. These data include the difference between the actual coordinates and the theoretical coordinates of each measurement point. Based on these deviation values, the technician or the automated system will evaluate the type and degree of compensation required. For example, if the actual coordinates of a particular measurement point show a systematic deviation that exceeds the acceptable range, the system needs to calculate the corresponding compensation value to correct this deviation.

[0114] Next, the corresponding compensation strategy is determined based on the nature (such as large or small) and value of the deviation. For example, if the deviation value shows that the actual coordinate is systematically lower than the theoretical coordinate, it may be necessary to increase the corresponding feed rate or adjust the depth setting of the tool. The determination of compensation parameters depends on the specific processing conditions and material properties, as well as the specific performance of the equipment.

[0115] In order to accurately perform these adjustments, step S104 also includes inputting compensation parameters into the control system of the digital manufacturing equipment. This is usually done through programming, involving modifying the NC program or dynamically adjusting the processing path. These modified parameters must be verified to ensure that they are correctly reflected in the processing operation, thereby ensuring the processing quality.

[0116] Finally, this step ensures that all adjustments are recorded for future quality control and process optimization. In this way, step S104 not only compensates for possible errors in the production process, but also improves the reliability and repeatability of the entire production process.

[0117] In this embodiment, the online measurement program is a software program that controls the measuring device (such as a probe) to automatically obtain the actual coordinate values ​​of the part. This program is usually pre-programmed, meaning that all necessary parameters and operation sequences are set before manufacturing begins. The implementation steps of the online measurement program include:

[0118] 1. Path planning: Based on the design and characteristics of the part, the program calculates the probe's movement path on the part to ensure that all critical measurement points are covered.

[0119] 2. Data collection: The program controls the probe to move along the set path and collects the coordinate data of each point on the part in real time.

[0120] 3. Data transmission: The measured data is sent to the main control system for further processing and analysis.

[0121] The machining program controls the manufacturing equipment (such as CNC machine tools) to process parts according to the predetermined machining path. When the online measurement program finds deviations between the actual coordinates and the theoretical coordinates, the machining program will adjust according to these deviations to ensure machining accuracy. The key functions of the machining program include:

[0122] 1. Compensation parameter setting: Based on the deviation data provided by the measurement program, the program will calculate the necessary compensation parameters, such as tool depth adjustment, speed change, etc.

[0123] 2. Path adjustment: According to the compensation parameters, the processing path will be adjusted accordingly to correct the deviation and ensure the processing quality.

[0124] 3. Execute processing: The adjusted parameters and paths are implemented, and the machine tool will complete the processing of the part according to the new settings.

[0125] The collaboration of these two programs ensures the efficiency and accuracy of the entire machining process, and greatly improves the manufacturing quality and qualification rate of products through the combination of real-time measurement and dynamic adjustment. This method is particularly suitable for precision machining of complex parts, such as aerospace, automobile and precision equipment manufacturing.

[0126] Through the above steps, compensation strategies can be reasonably formulated and processing procedures can be adjusted according to specific deviation values, thereby ensuring the accuracy and efficiency of part processing and achieving high-quality production goals.

[0127] Furthermore, determining the compensation parameters of the machining program according to the deviation value includes:

[0128] For each measuring point , calculate the normalized deviation value according to the following formula 1 :

[0129]

[0130] in is the actual coordinate value; is the theoretical coordinate value; is a small constant used to prevent the denominator from being zero;

[0131] According to the following formula 2, calculate the overall weighted average deviation value :

[0132]

[0133] in, For measuring point The weight of is the decay rate; is the time from the start of measurement to the present;

[0134] According to the following formula 3, the compensation parameters are calculated :

[0135]

[0136] in, is the adaptive coefficient, which is calculated according to the following formula 4:

[0137]

[0138] in, yes Initial value at the start of processing; Represents time The root mean square error of the compensation so far; is the decay constant; is the adjustment factor; represents the angular frequency of the periodic component; is the phase shift of the periodic component;

[0139] The calculated compensation parameters Determine the compensation parameters for the machining program.

[0140] For each measuring point , calculate the normalized deviation value , the formula used is as follows:

[0141]

[0142] in is the actual coordinate value; is the theoretical coordinate value, i.e. the coordinate position expected in the design; It is a very small constant used to prevent the denominator from being zero and ensure the stability of the calculation.

[0143] This normalization process helps eliminate scale differences in the measurements, making the deviation values ​​more comparable, while also avoiding division by zero errors and improving the reliability of the calculations.

[0144] Next, calculate the overall weighted average deviation value , the formula used is as follows:

[0145]

[0146] in, For measuring point The weight can be assigned according to the importance of the measuring point in the process.

[0147] is the attenuation rate, which is used to adjust the timeliness of the measurement points so that the impact of early measurement data gradually decreases over time.

[0148] It is the time from the start of measurement to the present, which is used to realize the timeliness decay of data.

[0149] This formula helps determine the combined impact of the data at each measurement point, taking into account factors such as time and importance, making the compensation more in line with actual processing needs.

[0150] Then, based on the calculated average deviation value To determine the compensation parameters , the formula used is:

[0151]

[0152] in, is the adaptive coefficient, which is calculated according to the following formula 4:

[0153]

[0154] in, yes Initial values ​​at the start of processing, usually determined based on preliminary testing or historical data that reflect typical operating conditions during the manufacturing process. The initial values ​​may also be set based on simulation results that predict expected changes during the manufacturing process;

[0155] Represents time The root mean square error of the compensation so far is used to adjust the adaptive coefficient and reflect the effect of compensation. It can be calculated from the square root of the average of the square differences between the predicted value and the actual value.

[0156] is the decay constant, which is used to adjust the adaptive coefficient to decrease as the error decreases. The decay constant can be optimized by simulating the machining process and analyzing the error response to ensure that the system responds to the error quickly without excessive oscillation;

[0157] It is an adjustment factor used to introduce periodic adjustment. Its size can be adjusted according to the historical data of machining errors and the expected compensation effect to achieve the best compensation effect.

[0158] The angular frequency of the periodic component is usually related to the operating frequency of the processing equipment or the vibration characteristics of the processing process. This parameter can be determined by experiments or actual measurement of vibration data during the processing process, such as using a spectrum analyzer to analyze the vibration spectrum of the equipment during operation, so as to select a suitable angular frequency to match the natural frequency of the equipment or avoid the resonant frequency;

[0159] is the phase shift of the periodic component. The choice of phase shift is usually based on the need to synchronize the periodic adjustment with known periodic changes in the process. For example, if certain periodic errors in the process (such as those caused by the runout of the machine tool axis) are known, the phase shift can be adjusted to ensure that the compensation measures are most effective when the periodic error reaches its peak;

[0160] The calculated compensation parameters Applied to the machining program to adjust the machining path or tool position to achieve accurate machining compensation. This step ensures that the manufacturing process can be dynamically optimized based on actual measurement data, improving product quality and manufacturing efficiency.

[0161] Step S105: adjusting the machining path or tool position according to the compensation parameters to complete the machining of the part.

[0162] In step S105, the processing path or tool position of the digital manufacturing equipment is adjusted according to the compensation parameters calculated previously to ensure that the processing of the part meets the predetermined design accuracy and quality standards. This step is the key link in the actual implementation of compensation in the entire manufacturing process and requires precise control to achieve the best processing effect.

[0163] First, this step involves inputting the compensation parameters determined in step S104 into the control system of the digital manufacturing device. The compensation parameters may include adjustment instructions for the feed speed of the machine tool, the depth of the tool, and the tool path. The adjustment of these parameters is based on the deviation values ​​calculated in the previous step, and is intended to correct these deviations and ensure the accuracy of the machining process.

[0164] Next, the control system will analyze these parameters and re-plan the machining path according to the compensation parameters. This may involve modifying the NC programming or adjusting the relevant settings directly on the machine tool operation interface. For example, if the deviation value shows that the actual machining depth is shallower than the theoretical value, the system may increase the depth of the tool's undercut or adjust the tool's speed to meet more precise cutting requirements.

[0165] In addition, during the adjustment process, the system will monitor the processing status in real time and continue to track the actual performance of the processing process through sensors on the equipment. This includes real-time feedback of the tool position during the processing and monitoring of the cutting force to ensure that after the adjustment is implemented, the processing process can run stably according to the new parameters.

[0166] Finally, once the machining path or tool position is adjusted, the equipment will start or continue the machining process. After the machining is completed, there is usually a quality inspection step to verify whether the machining results meet the design specifications and quality requirements. If the expected effect is not achieved, it may be necessary to make adjustments again, or go back to the previous steps to calculate and determine the compensation parameters again.

[0167] In this way, step S105 not only realizes dynamic processing adjustment based on actual measurement data, but also ensures that the processing quality and consistency of the product are improved through accurate compensation measures.

[0168] Furthermore, adjusting the machining path or tool position according to the compensation parameter to complete the machining of the part includes:

[0169] During the machining process, an acceleration sensor is used to monitor the tool vibration in real time and obtain the tool vibration data;

[0170] Based on the vibration data and compensation parameters, a fuzzy control algorithm is used to dynamically adjust the feed speed and spindle speed to optimize machining quality and efficiency.

[0171] First, tool vibration monitoring is achieved by installing acceleration sensors on processing equipment. These sensors can capture the vibration data generated by the tool during the processing, which is the key to evaluating the operating status of the tool. The vibration sensor should be installed at or near the tool holding device to ensure the accuracy and real-time nature of the data. After the processing starts, the sensor records the vibration intensity in real time and transmits this data to the processing control system.

[0172] Next, the collected vibration data will be input into the fuzzy control system. A fuzzy control system is an intelligent control system based on fuzzy logic, which processes fuzzy, uncertain or low-precision input information. In this application, the control system dynamically adjusts the feed rate and spindle speed of the machine tool based on the vibration data and pre-set compensation parameters. The compensation parameters are usually provided by the previous measurement and calculation steps, including deviation values ​​and necessary adjustment instructions.

[0173] In a fuzzy control system, relevant fuzzy sets and membership functions are first defined, which describe the relationship between vibration intensity, feed rate, and spindle speed. Then, based on these definitions, the system constructs fuzzy rules, such as "if the vibration intensity is high, reduce the feed rate." By evaluating real-time vibration data, the system applies these rules and converts fuzzy control decisions into specific machine control commands through a defuzzification process.

[0174] Finally, according to the commands derived from the fuzzy control algorithm, the control system adjusts the machining parameters, such as feed rate and spindle speed, to adapt to the current machining conditions and optimize machining efficiency and surface quality. This adjustment is carried out dynamically and can respond to changes in tool status in real time, thereby reducing machining errors and improving product quality.

[0175] Through the above steps, real-time monitoring and response of tool vibration in the digital manufacturing process can be achieved to ensure efficient and high-quality completion of the processing process. This method not only improves processing accuracy, but also improves the operating efficiency of the equipment and the consistency of the product.

[0176] Furthermore, the dynamically adjusting the feed speed and the spindle speed using a fuzzy control algorithm based on the vibration data and the compensation parameters includes:

[0177] Through a preset fuzzy control system, the following operations are performed:

[0178] Define fuzzy sets and membership functions;

[0179] Formulate clear fuzzy control rules;

[0180] Mamdani fuzzy reasoning method is applied to calculate the specific values ​​of feed speed and spindle speed according to the actual values ​​of vibration intensity and compensation parameters;

[0181] According to the specific values, adjust the feed speed and spindle speed.

[0182] First, the system needs to define fuzzy sets and membership functions. Fuzzy sets are used to describe the uncertainty and ambiguity of input and output variables. For example, for vibration intensity, fuzzy sets such as "low", "medium" and "high" can be defined. Membership functions are mathematical expressions used to describe these fuzzy sets, which determine the degree to which each specific input value belongs to different fuzzy sets. These definitions must be based on actual processing experience and analysis of vibration data to ensure that they accurately reflect the actual situation.

[0183] Next, clear fuzzy control rules need to be developed. These rules are the core of the fuzzy control system, and they are based on fuzzy logic to link input variables (such as vibration data) and output variables (such as feed speed adjustment). For example, a simple fuzzy rule might be: "If the vibration intensity is high, increase the spindle speed." The development of the rules needs to be combined with actual machine operation experience and previous test results to ensure that they can effectively deal with various situations.

[0184] Then, the Mamdani fuzzy reasoning method is applied to implement these rules. The Mamdani method is a common fuzzy reasoning technique that handles input uncertainty through fuzzy logic to produce precise output decisions. In this step, the system calculates the contribution of each rule and combines the outputs of all rules to obtain a fuzzy decision result.

[0185] Finally, the system needs to convert the fuzzy decision results into specific mechanical control commands, a process called defuzzification. The purpose of defuzzification is to convert the fuzzy output into precise values, such as specific feed rate and speed adjustment values. This is usually achieved through methods such as the centroid method or the maximum membership method.

[0186] Through the above steps, the operating parameters of the CNC machine tool can be dynamically adjusted according to the real-time collected vibration data and the preset compensation parameters, the machining process can be optimized, and the machining accuracy and efficiency can be improved. This method is particularly suitable for application scenarios with high-precision machining requirements, such as aerospace parts manufacturing and precision instrument processing.

[0187] Furthermore, the definition of fuzzy sets and membership functions includes:

[0188] Three levels of membership functions are defined for vibration intensity, specifically: low vibration (0-0.3g, g represents gravity acceleration), medium vibration (0.25-0.65g), and high vibration (0.6-1.0g). Each level of membership function is represented by a trapezoidal diagram, where the two ends of the trapezoids for low vibration and high vibration are closed.

[0189] The compensation parameters are divided into three levels: small adjustment (0%-10% speed adjustment), medium adjustment (8%-20% speed adjustment), and large adjustment (18%-30% speed adjustment); they are defined using trapezoidal membership functions to ensure smooth transitions at parameter boundaries.

[0190] First, define the membership function of vibration intensity. Vibration intensity is divided into three levels: low vibration, medium vibration, and high vibration. The specific value range is: low vibration from 0 to 0.3g, medium vibration from 0.25 to 0.65g, and high vibration from 0.6 to 1.0g. Here g represents the acceleration of gravity, which is a unit for measuring vibration intensity. In order to more accurately reflect the vibration state of each level, a ladder diagram is used to represent the membership function of each vibration intensity level. The choice of the ladder diagram allows a certain overlap area between the levels. For example, the range of medium vibration partially overlaps with low vibration and high vibration, which helps to maintain a smooth response of the system when the vibration level is switched.

[0191] Next, the compensation parameters are divided into three levels: small adjustment, medium adjustment and large adjustment. These levels correspond to the speed adjustment range that may be required during the processing, which are 0%-10%, 8%-20% and 18%-30% speed adjustment respectively. Using trapezoidal membership functions to define these compensation parameter levels also ensures a smooth transition between different adjustment levels. This definition allows the system to flexibly switch between different compensation requirements and optimize processing speed and efficiency.

[0192] With this setting, the fuzzy control system can dynamically adjust the feed speed and spindle speed of the machine tool according to the vibration intensity measured during the actual processing. For example, if the vibration intensity detected by the system suddenly jumps from low vibration to high vibration, the control system will calculate the corresponding compensation parameters according to the preset fuzzy rules and membership functions, and quickly increase the adjustment range of the feed speed to ensure that the processing quality is not affected.

[0193] This detailed definition of membership functions and compensation parameter levels not only ensures the high sensitivity and response speed of the control system, but also makes the entire digital manufacturing process more stable and reliable. By implementing these detailed steps, technicians can effectively optimize and adjust the processing program to meet complex manufacturing challenges and ensure product quality and production efficiency.

[0194] Furthermore, the formulation of clear fuzzy control rules includes:

[0195] A specific fuzzy control rule is formulated, which includes: if the vibration level is high (0.6-1.0g) and the compensation parameter is a large adjustment (18%-30%), then reduce the feed rate by 25% and reduce the spindle speed by 15%.

[0196] Here, a specific fuzzy control rule is proposed: if the vibration level is high (0.6-1.0g) and the compensation parameters are adjusted greatly (18%-30%), then reduce the feed rate by 25% and reduce the spindle speed by 15%. This rule is based on the measured values ​​of two key parameters: vibration intensity and required compensation amplitude.

[0197] The implementation process and examples are as follows:

[0198] 1. Monitor vibration intensity:

[0199] During the machining process, the acceleration sensor installed on the machine tool monitors the vibration of the tool or machine tool in real time. When the vibration value reaches between 0.6g and 1.0g, the system identifies this state as "high vibration".

[0200] 2. Determine compensation parameters:

[0201] At the same time, the system determines the compensation parameters that need to be made based on the previous error analysis. If the calculated compensation range is between 18% and 30%, this is marked as a "large adjustment".

[0202] 3. Apply fuzzy rules:

[0203] When these two conditions are met at the same time, the fuzzy control system automatically triggers the preset control rules. The system sends a command to the machine tool to instruct it to reduce the feed speed by 25% and the spindle speed by 15%.

[0204] Assume that during a high-precision part processing, abnormal vibration is caused by some external factors (such as machine tool wear or uneven material hardness). At this time, the acceleration sensor measures a vibration value of 0.8g, and based on the real-time feedback of the processing error, the system determines that a 20% compensation adjustment is required. Based on the above rules, the control system automatically adjusts the machine tool settings to ensure that the processing quality is not reduced due to excessive vibration.

[0205] In this way, the control rules here help ensure that the processing process can maintain high quality and high precision even under challenging conditions, reducing the scrap rate of products. This automated adjustment process is a key part of modern digital manufacturing, which enables the production line to respond more flexibly to various production challenges and improve overall efficiency and benefits.

[0206] Furthermore, the Mamdani fuzzy reasoning method is applied to calculate specific values ​​for adjusting the feed speed and spindle speed according to the actual values ​​of the vibration intensity and the compensation parameters, including:

[0207] The Mamdani reasoning mechanism is implemented to determine the activation degree of each fuzzy rule based on the input vibration intensity and compensation parameter, where the relevant fuzzy rule is considered fully activated when the vibration intensity is 0.8g and the compensation parameter is 25%;

[0208] Aggregate the outputs of all activated fuzzy rules and use the maximization method to integrate the results of these activated rules to form a comprehensive fuzzy output;

[0209] The centroid method is used to convert the comprehensive fuzzy output into specific mechanical control commands to obtain specific values ​​for adjusting the feed speed and spindle speed.

[0210] First, implementing the Mamdani inference mechanism requires setting up and tuning a fuzzy controller that activates the corresponding fuzzy rules based on the input vibration intensity and compensation parameters. For example, when the vibration intensity measurement is 0.8g and the compensation parameter is 25%, the system will recognize that the fuzzy rule in this particular case is fully activated. This means that the rule will have a decisive influence on the final control output.

[0211] Next, the system aggregates the outputs of all activated fuzzy rules. In the case of multiple rules being activated at the same time, each rule may suggest adjustments of varying degrees. The system uses a maximization approach to integrate these different outputs, selecting the output with the greatest impact as the dominant one to form a comprehensive fuzzy output. This approach ensures that when faced with multiple different action suggestions, the factors that have the greatest impact on the machining process are prioritized.

[0212] Finally, the resulting integrated fuzzy output is converted into a specific mechanical control command. This step is achieved by using the centroid method, which calculates the center of gravity of all activated fuzzy rule outputs to determine the final feed rate and spindle speed adjustment values. The centroid method is a commonly used defuzzification technique that calculates an accurate value by considering the degree of each output and the corresponding actual influence, making the control command both specific and accurately reflecting the results of fuzzy logic.

[0213] Through this series of operations, technicians can accurately adjust processing parameters based on real-time collected data to meet actual challenges in the processing process. For example, when processing a hard material that is particularly prone to vibration, if a high vibration intensity is sensed, the system can automatically slow down the feed speed and reduce the speed, thereby reducing the negative impact of vibration on processing quality and ensuring a smooth processing process and high product quality. This intelligent adjustment process not only improves the adaptive ability of the machine tool, but also optimizes processing efficiency and product quality.

[0214] The above process is explained in detail below through a specific example, that is, the whole process of adjusting the feed speed and spindle speed according to the vibration intensity and compensation parameters using the Mamdani fuzzy reasoning method.

[0215] Suppose you are machining a precision aviation component made of titanium alloy, which requires extremely high machining accuracy. During the machining of titanium alloy materials, large tool vibration is likely to occur, which has a direct impact on the machining quality.

[0216] Step 1: Install and calibrate the sensor

[0217] First, an acceleration sensor is installed on the CNC machine tool to monitor the vibration intensity of the tool in real time during the machining process. It is assumed that the sensor can measure the vibration data once a second to ensure the real-time and accuracy of the data.

[0218] Step 2: Define fuzzy logic control rules

[0219] Based on previous tests and data analysis, membership functions for three vibration intensity levels were defined: low vibration (0-0.3g), medium vibration (0.25-0.65g), and high vibration (0.6-1.0g). At the same time, corresponding compensation parameter adjustment strategies were developed according to different levels of vibration intensity. For example, a rule was defined: if the vibration intensity is high (0.6-1.0g), a larger compensation is required.

[0220] Step 3: Implement Mamdani inference and adjust parameters

[0221] During the machining process, the sensor measured a vibration intensity of 0.8g at a certain moment. According to the fuzzy rules, this vibration level was identified as "high vibration". According to the set rules, the system automatically triggered the compensation mechanism, specifically reducing the feed speed by 25% and the spindle speed by 15%.

[0222] Step 4: Perform defuzzification of fuzzy output

[0223] The system calculates the comprehensive output based on all activated fuzzy rules. The centroid method is used to calculate the specific adjustment values, that is, to determine the new feed rate and spindle speed. For example, if the original feed rate is 100mm / min and the spindle speed is 2000rpm, the adjusted feed rate is 75mm / min and the spindle speed is 1700rpm.

[0224] Step 5: Apply adjustments and monitor results

[0225] The CNC machine tool processes according to the new parameters and continuously monitors the vibration data. If the vibration drops to an acceptable range, the current settings are maintained; if the vibration is still too high, the system will adjust again until the optimal processing state is achieved.

[0226] Through the above steps, the vibration problem in the processing process can be effectively controlled to ensure high-quality processing results. This method based on real-time feedback and dynamic adjustment improves processing efficiency and product quality.

[0227] A second embodiment of the present application provides an electronic device, the electronic device comprising:

[0228] processor;

[0229] The memory is used to store a program, and when the program is read and executed by the processor, the program executes the online automatic measurement and compensation method for digital manufacturing provided in the first embodiment of the present application.

[0230] The third embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the online automatic measurement and compensation method for digital manufacturing provided in the first embodiment of the present application is executed.

[0231] Although the present application is disclosed as above in the form of a preferred embodiment, it is not intended to limit the present application. Any technical personnel in this field may make possible changes and modifications without departing from the spirit and scope of the present application. Therefore, the scope of protection of the present application shall be based on the scope defined by the claims of the present application.

Claims

1. An online automatic measurement and compensation method for digital manufacturing, characterized in that: include: Establish a part processing coordinate system on digital manufacturing equipment; Based on the established machining coordinate system, the actual coordinate value of the part to be machined is measured using a probe through a pre-programmed online measurement program. Comparing the actual coordinate value with the predetermined theoretical coordinate value, and calculating the deviation between the actual coordinate value and the predetermined theoretical coordinate value; Determining compensation parameters of a machining program according to the deviation value; According to the compensation parameters, the machining path or the tool position is adjusted to complete the machining of the part; Wherein, adjusting the processing path or tool position according to the compensation parameter to complete the processing of the part includes: During the machining process, an acceleration sensor is used to monitor the tool vibration in real time and obtain the tool vibration data; Based on the vibration data and compensation parameters, a fuzzy control algorithm is used to dynamically adjust the feed speed and spindle speed to optimize machining quality and efficiency; The method of dynamically adjusting the feed speed and the spindle speed based on the vibration data and the compensation parameters using a fuzzy control algorithm includes: Through a preset fuzzy control system, the following operations are performed: Define fuzzy sets and membership functions; Formulate clear fuzzy control rules; Mamdani fuzzy reasoning method is applied to calculate the specific values ​​of feed speed and spindle speed according to the actual values ​​of vibration intensity and compensation parameters; According to the specific values, the feed speed and the spindle speed are adjusted; Wherein, the definition of fuzzy sets and membership functions includes: Three levels of membership functions are defined for vibration intensity, specifically set as follows: the range of low vibration is 0 to 0.3 times the acceleration of gravity, the range of medium vibration is 0.25 to 0.65 times the acceleration of gravity, and the range of high vibration is 0.6 to 1.0 times the acceleration of gravity; the membership function of each level is represented by a trapezoidal diagram, in which the trapezoids of low vibration and high vibration are closed at both ends; The compensation parameters are divided into three levels: the speed adjustment range for small adjustment is 0% to 10%, the speed adjustment range for medium adjustment is 8% to 20%, and the speed adjustment range for large adjustment is 18% to 30%; they are defined using trapezoidal membership functions to ensure smooth transitions at the boundaries of parameters.

2. The online automatic measurement and compensation method for digital manufacturing according to claim 1 is characterized in that: The process of establishing a machining coordinate system of a part on a digital manufacturing device includes: Configure laser scanners on digital manufacturing equipment to accurately scan parts from at least three different angles to capture all-round 3D data of the part surface; The obtained three-dimensional scanning data is imported into the data processing system of the digital manufacturing equipment, and the noise and error generated during the scanning process are removed by using an image processing algorithm to obtain the denoised three-dimensional scanning data; Generate a three-dimensional model of the part based on the denoised three-dimensional scanning data; Identifying at least five key processing points on the three-dimensional model, wherein the key processing points are selected according to functional requirements and structural characteristics of the part; The at least five key processing points and their coordinate information are stored in a control system of the digital manufacturing equipment.

3. The online automatic measurement and compensation method for digital manufacturing according to claim 1 is characterized in that: The processing coordinate system established according to the invention uses a probe to measure the actual coordinate value of the position of the part to be processed through a pre-programmed online measurement program, including: Install and calibrate high-precision probes on digital manufacturing equipment; Based on the machining coordinate system, compile the probe's moving path and measurement program; Execute the measurement program, and the probe measures each measurement point multiple times along the set path to collect the actual coordinate values.

4. The online automatic measurement and compensation method for digital manufacturing according to claim 1 is characterized in that: The step of comparing the actual coordinate value with the predetermined theoretical coordinate value and calculating the deviation between the actual coordinate value and the predetermined theoretical coordinate value comprises: Receive actual coordinate value data collected by the measurement system on the digital manufacturing equipment; Retrieving theoretical coordinate values ​​of the corresponding part from a design database, wherein the theoretical coordinate values ​​are pre-set based on the part design file and have been optimized according to the processing requirements of the part; The data of each actual coordinate point is compared with its corresponding theoretical coordinate value to obtain the deviation value between the actual coordinate value and the predetermined theoretical coordinate value.

5. The online automatic measurement and compensation method for digital manufacturing according to claim 1 is characterized in that: The formulation of clear fuzzy control rules includes: A specific fuzzy control rule is formulated, and the fuzzy control rule includes: if the vibration level is the high vibration and the compensation parameter is the large adjustment, the feed speed is reduced by 25% and the spindle speed is reduced by 15%.

6. The online automatic measurement and compensation method for digital manufacturing according to claim 5 is characterized in that: The Mamdani fuzzy reasoning method is applied to calculate the specific values ​​of the feed speed and the spindle speed according to the actual values ​​of the vibration intensity and the compensation parameters, including: The Mamdani reasoning mechanism is implemented to determine the activation degree of each fuzzy rule based on the input vibration intensity and compensation parameter, where the relevant fuzzy rule is considered fully activated when the vibration intensity is 0.8g and the compensation parameter is 25%; Aggregate the outputs of all activated fuzzy rules and use the maximization method to integrate the results of these activated rules to form a comprehensive fuzzy output; The centroid method is used to convert the comprehensive fuzzy output into specific mechanical control commands to obtain specific values ​​for adjusting the feed speed and spindle speed.

Images