Monitoring method and monitoring device for wear state of milling cutter of machine tool
By acquiring the machine tool motor current signal, extracting signal features, and calculating the wear energy coefficient, the problems of high cost and insufficient accuracy in online monitoring of milling cutter wear are solved, achieving low-cost and high-accuracy wear condition monitoring.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- DALIAN TURBOMACHINERY TECH DEV CO LTD
- Filing Date
- 2026-03-12
- Publication Date
- 2026-04-21
AI Technical Summary
In existing technologies, online monitoring of milling cutter wear is costly and lacks accuracy, especially deep learning-based methods which are prone to misjudgment when cutting parameters change.
By acquiring the current signal of the machine tool motor, extracting signal features, determining the total milling force of the milling cutter using a preset proportional relationship and the least squares method, and calculating the wear energy coefficient by combining the current power and cutting power, the wear state is reflected, thus avoiding the use of a milling force sensor.
It reduces the hardware cost of milling cutter wear monitoring while improving the accuracy of monitoring and providing a visual indicator of the milling cutter wear status.
Smart Images
Figure CN121893084A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of coal mine underground conveying equipment technology, and more specifically, to a method and device for monitoring the wear condition of machine tool milling cutters. Background Technology
[0002] In related technologies, online monitoring of milling cutter wear can be broadly divided into direct monitoring methods and indirect monitoring methods. Indirect monitoring methods mainly collect various monitoring signals through sensors, such as milling force and current signals, and then use signal processing techniques to extract and filter features, establishing a feature mapping relationship between the monitoring signals and different wear states of the milling cutter.
[0003] The milling force of a milling cutter directly reflects the interaction force between the workpiece and the cutter. Wear or breakage of the cutter will cause changes in the milling force. Numerous studies have shown that the milling force is highly sensitive to the degree of cutter wear, and the milling force signal is the most effective signal for monitoring the condition of the cutter. However, installing a milling force sensor reduces the machining range of the machine tool and increases the cost of use and maintenance. Deep learning-based classification methods can identify the wear state of the cutter through the current signal of the machine tool's motor; however, when cutting parameters change, deep learning-based classification methods are prone to misjudging the wear state of the cutter. Summary of the Invention
[0004] In view of this, embodiments of the present invention provide a method and device for monitoring the wear condition of machine tool milling cutters, the main purpose of which is to reduce the cost of online monitoring of milling cutter wear and improve the accuracy of monitoring the wear condition of milling cutters.
[0005] To achieve the above objectives, the present invention mainly provides the following technical solutions: In a first aspect, embodiments of the present invention provide a method for monitoring the wear condition of a machine tool milling cutter, comprising: Acquire the current signal of the machine tool's motor; Extracting signal characteristics from current signals; The total milling force of the milling cutter is determined based on the signal characteristics and the preset proportional relationship; Determine the cutting power of the milling cutter based on the total milling force; Determine the current power based on the current signal and motor voltage; The wear energy coefficient is determined based on the cutting power and current power; the wear energy coefficient is used to reflect the wear state.
[0006] Furthermore, the preset proportional relationship is obtained in the following way: Acquire current signals from multiple motors of the machine tool within a preset time period; Extract signal features from multiple current signals; The least squares method is used to calculate multiple signal features and determine the feature change curves; Obtain the milling force variation curve of the tangential milling force of the milling cutter within a preset time period; Based on the characteristic change curve and the milling force change curve, determine the preset proportional relationship.
[0007] Furthermore, the motor's current signal includes three-phase current signals. The signal characteristics of the current signal are extracted, including: The three-phase current signals are combined into an effective value signal; The effective value signal is decomposed using a preset decomposition algorithm to obtain the low-frequency component; The low-frequency components are filtered to obtain the signal characteristics.
[0008] Furthermore, based on the total milling force, the cutting power of the milling cutter is determined, including: The tangential milling force of the milling cutter is determined based on the total milling force and the geometric modeling parameters of the milling cutter. Determine the cutting torque of the milling cutter based on the tangential milling force and the diameter of the milling cutter; The cutting power is determined based on the cutting torque and the angular velocity of the milling cutter.
[0009] Furthermore, based on the cutting power and current power, the wear energy coefficient is determined, including: According to the preset formula Determine the wear energy coefficient; Where λ is the wear energy coefficient, P is the current power, and P c This refers to the cutting power.
[0010] Secondly, embodiments of the present invention provide a device for monitoring the wear condition of a machine tool milling cutter, comprising: The acquisition unit is used to acquire the current signal of the machine tool's motor; The extraction unit is used to extract the signal characteristics of the current signal; The determining unit is used to determine the total milling force of the milling cutter based on signal characteristics and a preset proportional relationship; Determine the cutting power of the milling cutter based on the total milling force; Determine the current power based on the current signal and motor voltage; The wear energy coefficient is determined based on the cutting power and current power; the wear energy coefficient is used to reflect the wear state.
[0011] Furthermore, the preset proportional relationship is obtained in the following way: Acquire current signals from multiple motors of the machine tool within a preset time period; Extract signal features from multiple current signals; The least squares method is used to calculate multiple signal features and determine the feature change curves; Obtain the milling force variation curve of the tangential milling force of the milling cutter within a preset time period; Based on the characteristic change curve and the milling force change curve, determine the preset proportional relationship.
[0012] Furthermore, the extraction unit is specifically used for: The three-phase current signals are combined into an effective value signal; The effective value signal is decomposed using a preset decomposition algorithm to obtain the low-frequency component; The low-frequency components are filtered to obtain the signal characteristics.
[0013] Furthermore, the specific use of the unit is determined to be: The cutting power of a fixed milling cutter includes: The tangential milling force of the milling cutter is determined based on the total milling force and the geometric modeling parameters of the milling cutter. Determine the cutting torque of the milling cutter based on the tangential milling force and the diameter of the milling cutter; The cutting power is determined based on the cutting torque and the angular velocity of the milling cutter.
[0014] Furthermore, determining the specific unit is also used for: According to the preset formula Determine the wear energy coefficient; Where λ is the wear energy coefficient, P is the current power, and P c This refers to the cutting power.
[0015] Thirdly, embodiments of the present invention provide an electronic device, including: The processor and memory store programs or instructions that can run on the processor, and when the program or instructions are executed by the processor, they implement the steps of the aforementioned method for monitoring the wear condition of machine tool milling cutters.
[0016] Fourthly, embodiments of the present invention provide a readable storage medium on which a program or instructions are stored, and when the program or instructions are executed by a processor, the steps of the aforementioned method for monitoring the wear state of a machine tool milling cutter are implemented.
[0017] By employing the above technical solution, the present invention has at least the following beneficial effects: The method for monitoring the wear state of a machine tool milling cutter provided in this embodiment of the invention acquires first three-dimensional point cloud data of the contour of the self-moving tail section of a belt conveyor; determines the running posture of the self-moving tail section of the belt conveyor relative to the coal wall of the roadway based on the first three-dimensional point cloud data; when the overlap between the running posture and the preset posture is less than a first preset value, the self-moving tail section of the belt conveyor is controlled to move to the preset posture; wherein, in the preset posture, the angle between the side wall of the self-moving tail section of the belt conveyor and the coal wall of the roadway is less than a second preset value, thereby realizing automatic closed-loop adjustment of the running posture of the self-moving tail section of the belt conveyor, thus eliminating the need for manual posture control by the operator, avoiding manpower consumption, improving the adjustment efficiency of equipment in the roadway, and reducing the safety risks to the operator. Attached Figure Description
[0018] Figure 1 A flowchart illustrating a method for monitoring the wear state of a machine tool milling cutter, provided as an embodiment of the present invention; Figure 2 A diagram illustrating the feature extraction process of the current signal from a click. Figure 3 A graph showing the trend of milling force variation extracted from the feed current signal during the full-slot milling stage; Figure 4 A graph showing the trend of milling force variation extracted from the feed current signal during the half-groove milling stage; Figure 5 To extract the milling force variation trend diagram from the feed current signal during the root clearing stage; Figure 6 A graph showing the trend of milling force variation extracted from the feed current signal during the finish milling stage; Figure 7 This is a graph showing the change in energy related to tool wear. Figure 8 A structural block diagram of a device for monitoring the wear condition of a machine tool milling cutter provided in an embodiment of the present invention; Figure 9 This is a structural block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation
[0019] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be described in more detail below with reference to the accompanying drawings.
[0020] like Figure 1 As shown, this embodiment of the invention provides a method for monitoring the wear state of a machine tool milling cutter. The conveyor belt includes a self-moving tail section of a belt conveyor, which includes a belt frame and a body connected to each other. The control method may include: 101. Obtain the current signal of the machine tool's motor; 102. Extract the signal characteristics of the current signal; 103. Determine the total milling force of the milling cutter based on the signal characteristics and the preset proportional relationship; 104. Determine the cutting power of the milling cutter based on the total milling force; 105. Determine the current power based on the current signal and motor voltage; 106. Determine the wear energy coefficient based on the cutting power and current power; the wear energy coefficient is used to reflect the wear state.
[0021] In this embodiment of the invention, firstly, while the machine tool is running, the current signal of the machine tool's motor can be acquired. It is understood that during machine tool operation, the motor can be controlled to rotate, thereby enabling the milling cutter to perform its milling function.
[0022] Then, the signal features of the current signal are extracted. By extracting the signal features of the current signal, the effective features in the current signal can be fully preserved, while the invalid features and noise interference in the current signal can be filtered out, thus avoiding the impact of invalid features and noise interference on the accuracy of determining the wear state of the milling cutter.
[0023] After extracting the signal characteristics of the current signal, the milling force of the milling cutter during machine tool operation can be calculated based on the signal characteristics and a preset proportional relationship. It should be noted that based on the machine tool's operating principle—that is, the machine tool uses the rotation of a motor to drive the milling cutter to rotate, and the milling cutter cuts the workpiece—there is a certain non-linear feedback relationship between the motor's current signal and the milling force of the milling cutter during actual machine tool operation. This feedback relationship allows for the determination of a preset proportional relationship between the signal characteristics and the total milling force of the milling cutter after the machine tool leaves the factory. Therefore, during machine tool operation, by extracting the signal characteristics of the motor's current signal and then using the preset proportional relationship, the total milling force of the milling cutter can be determined based on these signal characteristics.
[0024] In other words, in the process of determining the total milling force of the milling cutter, the signal characteristics of the current signal can be extracted by extracting the characteristics of the current signal. Then, the total milling force of the milling cutter can be determined according to the signal characteristics and the preset ratio relationship, without the need to detect the total milling force of the milling cutter through a milling force sensor.
[0025] Furthermore, after determining the total milling force of the milling cutter, the cutting power of the milling cutter can be calculated based on the total milling force. Then, based on the motor current signal, the motor current power can be calculated. Finally, based on the calculated cutting power and the motor current power, the wear energy coefficient of the milling cutter during machine tool operation can be determined. This wear energy coefficient reflects the wear state of the milling cutter.
[0026] The method for monitoring the wear state of milling cutters in machine tools provided in this invention acquires the current signal of the machine tool's motor, extracts the signal characteristics of the current signal, and then determines the total milling force of the milling cutter based on the signal characteristics and a preset proportional relationship, without the need for a milling force sensor to detect the total milling force, thus effectively reducing the hardware cost of the machine tool. Then, in determining the wear state of the milling cutter, the cutting power of the milling cutter can be calculated based on the total milling force. Then, based on the motor current signal, the current power of the motor can be calculated. Finally, based on the extracted cutting power and the motor current power, the wear energy coefficient of the milling cutter during machine tool operation can be determined, and this wear energy coefficient reflects the wear state of the milling cutter.
[0027] In this embodiment of the invention, the preset proportional relationship can be obtained in the following ways: Acquire current signals from multiple motors of the machine tool within a preset time period; Extract signal features from multiple current signals; The least squares method is used to calculate multiple signal features and determine the feature change curves; Obtain the milling force variation curve of the tangential milling force of the milling cutter within a preset time period; Based on the characteristic change curve and the milling force change curve, determine the preset proportional relationship.
[0028] In the above embodiments, firstly, multiple current signals of the machine tool motor can be acquired within a preset time period. The preset time period can be one test cycle of the milling cutter, and the test cycle for one side of the milling cutter specifically refers to the entire life cycle of the milling cutter, that is, the process from when the milling cutter's wear state reaches the point where it can no longer perform normal machining.
[0029] Within a preset time period, multiple current signals from the machine tool's motor are acquired. Specifically, the acquisition interval for these multiple circuit signals can be set according to the machining requirements, such as the milling cutter's machining accuracy and wear condition. For example, the acquisition interval for multiple circuit signals can be set to 0.5ms, 1ms, or 5ms. Then, for each current signal, the signal characteristics are extracted, and based on the least squares method, multiple signal characteristics are calculated to determine the characteristic change curve.
[0030] Meanwhile, within the preset time period corresponding to the current signal, that is, within the same preset time period, the milling force variation curve of the tangential milling force of the milling cutter is obtained. Then, the milling force variation curve is compared with the characteristic variation curve corresponding to the current signal. Based on the difference between the two variation curves, the preset proportional relationship between the signal characteristics and the total milling force can be determined.
[0031] This invention, through acquiring the signal characteristic change curves corresponding to the motor's current signal and the milling force change curve of the milling cutter's tangential milling force within a preset time period, allows for the comparison of the milling force change curve with the characteristic change curve corresponding to the current signal. Based on the differences between the two curves, a preset proportional relationship between the signal characteristics and the total milling force can be determined. Thus, during machine tool operation, the total milling force of the milling cutter can be determined based on the signal characteristics corresponding to the motor's current signal and the preset proportional relationship, eliminating the need for a milling force sensor and effectively reducing the machine tool's hardware costs.
[0032] In this embodiment of the invention, the motor current signal includes a three-phase current signal. Extracting the signal features of the current signal includes: synthesizing the three-phase current signal into an effective value signal; decomposing the effective value signal using a preset decomposition algorithm to obtain a low-frequency component; and filtering the low-frequency component to obtain signal features.
[0033] In the above embodiments, it can be understood that during machine tool operation, a three-phase alternating current supply is typically required. That is, the machine tool motor usually rotates under the influence of three-phase alternating current, and correspondingly, the motor's current signal is typically a three-phase current signal. Based on this, as... Figure 2 As shown, the feature extraction process of the motor's current signal is as follows: First, after obtaining the three-phase current signals of the motor, the three-phase current signals can be synthesized into an effective value signal. Specifically, the calculation formula for synthesizing the effective value signal from the three-phase current signals is as follows: ; Among them, I rms For the effective value signal, i u For the u-phase current signal, i v For the phase V current signal, i w This is the w-phase current signal.
[0034] Furthermore, after combining the three-phase current signals into an effective value signal, a preset decomposition algorithm can be used to decompose the effective value signal to obtain its low-frequency components. It is understandable that by decomposing the effective value signal to obtain low-frequency components, non-stationary and nonlinear signals within the effective value signal can be processed, thereby avoiding interference from these signals in the extraction of current signal characteristics and ensuring the accuracy of the extracted signal characteristics.
[0035] Specifically, Variational Mode Decomposition (VMD) can be used to decompose the RMS signal, thereby obtaining the low-frequency components of the RMS signal. In the VMD process, the number of decompositions K can be set to 5, and the penalty factor can be set to 2000. Furthermore, the number of decompositions and the penalty factor can be set to different values according to actual needs.
[0036] Finally, after obtaining the low-frequency component of the effective signal value, the low-frequency component can be filtered to remove the carrier frequency from the low-frequency component, so as to avoid the carrier frequency affecting the determination of the preset ratio in the subsequent process.
[0037] Specifically, the carrier frequency is typically 50Hz or 100Hz. Time-shifting can be used to remove the low-frequency carrier frequency components. Time-shifting involves adding the current signal to the signal after half a cycle to remove the fundamental frequency. The time-shifting process can be represented as: ; Among them, I rms The low-frequency component of the RMS signal. t Indicates the current moment. R I represents the fundamental frequency period. res This represents the superposition value of the currents, which is the signal characteristic obtained after time-shifting and filtering out the carrier frequency.
[0038] This invention combines the three-phase current signals into an effective value signal, and then uses a preset decomposition algorithm to decompose the effective value signal to obtain a low-frequency component. This avoids interference from non-stationary and nonlinear signals in the extraction of signal features from the current signal, ensuring the accuracy of the extracted signal features. The low-frequency component is then filtered to remove the carrier frequency, preventing it from affecting the subsequent determination of the preset proportional relationship, thereby improving the accuracy of the final obtained signal features.
[0039] In this embodiment of the invention, determining the cutting power of the milling cutter based on the total milling force includes: determining the tangential milling force of the milling cutter based on the total milling force and the geometric modeling parameters of the milling cutter; determining the cutting torque of the milling cutter based on the tangential milling force and the diameter of the milling cutter; and determining the cutting power based on the cutting torque and the angular velocity of the milling cutter.
[0040] In the above embodiments, after determining the total milling force of the milling cutter, the cutting power of the milling cutter can be determined based on the total milling force and relevant parameters of the milling cutter body. Specifically, the relevant parameters of the milling cutter body may include the geometric modeling parameters of the milling cutter, such as the height of the cutting edge, the height micro-element of the cutting edge, the number of cutting edge micro-element, the diameter of the milling cutter, and the coefficient of friction between the milling cutter and the workpiece.
[0041] First, the tangential milling force of the milling cutter can be determined based on the total milling force and the geometric modeling parameters of the milling cutter. Specifically, the total milling force of the milling cutter is determined by the radial milling force and the tangential milling force at the tip of the milling cutter, and its expression is as follows: (1); Among them, F r For radial milling force, F t The tangential milling force is represented by z, where z represents the height of the cutting edge, j represents the j-th cutting edge, and n and m represent the number of height infinitesimal elements and cutting edge infinitesimal elements, respectively. Radial force With tangential force The tangent angle.
[0042] Furthermore, based on the tangential milling force and the diameter of the milling cutter, the cutting torque of the milling cutter can be determined. It should be noted that during the milling process, the axial resistance contributes very little to the load; the load torque mainly comes from the radial and tangential forces. The radial force affects the frictional torque, and the cutting force affects the cutting torque. Their mathematical relationship is as follows: (2); R represents the coefficient of friction between the milling cutter and the workpiece, and R represents the diameter of the milling cutter. and These are the cutting torque and the friction torque, respectively. After the end mill wears, the contact area between the cutting edge and the chip increases, therefore the coefficient of friction increases. Increase.
[0043] The total torque consists of three parts: inertial torque, frictional torque, and cutting torque. For machining at a constant spindle speed, the inertial torque is zero; therefore, the relationship can be expressed as: (3); in, Let be the total motor torque, K be the motor torque coefficient, and i be the motor current. For milling at constant speed, the formulas for calculating current power and cutting power are: (4); Among them, P and These represent current power and cutting power, respectively; u represents the constant voltage of the machine tool; and ω represents the angular velocity of the milling cutter.
[0044] This invention provides a method to obtain the geometric modeling parameters of the milling cutter, such as the height of the cutting edge, the height micro-element of the cutting edge, the number of cutting edge micro-element, the diameter of the milling cutter, and the friction coefficient between the milling cutter and the workpiece. Combined with the total milling force of the milling cutter, the cutting power of the milling cutter is obtained, thereby preparing for the determination of the wear energy coefficient of the milling cutter and thus determining the wear state of the milling cutter.
[0045] In this embodiment of the invention, the wear energy coefficient is determined based on the cutting power and the current power, including: According to the preset formula Determine the wear energy coefficient; Where λ is the wear energy coefficient, P is the current power, and Pc is the cutting power.
[0046] In the above embodiments, it can be understood that when the milling cutter wears, the width of the cutting edge increases, and the coefficient of friction between the milling cutter and the workpiece increases. As the current increases, the overall trend of the ratio between the motor's current power and the milling cutter's cutting power also increases. That is... The overall trend of change is increasing.
[0047] Combining formulas (1) to (4) above, the ratio of current power to cutting power can be expressed as: (5); Based on this, embodiments of this application propose a wear energy coefficient λ to indirectly reflect the wear state of the milling cutter. Specifically, the expression for the wear energy coefficient of the milling cutter is as follows: ; Where λ represents the wear energy coefficient of the milling cutter.
[0048] It is understandable that during the milling process, the spindle speed remains constant while the depth of cut changes dynamically. The proposed wear energy coefficient is only related to the wear state of the milling cutter and does not change with the depth of cut.
[0049] Specifically, the wear energy coefficient reflects the changing trend of the end mill's wear state. The amplitude change of the wear energy coefficient throughout the end mill's life is calculated using the calculated torque power and current power, and the changing trend of the wear energy coefficient is extracted using the least squares method. Figure 7 As shown, observing the changing trend of the wear energy coefficient throughout the entire life of the milling cutter reveals that the wear energy coefficient can monitor the wear state of the milling cutter in variable parameter cutting, providing a visual indicator of the wear state of the milling cutter.
[0050] In actual testing, the milling process can specifically include full-groove milling, half-groove milling, root clearing, and finish milling stages, such as... Figure 3 , Figure 4 , Figure 5 and Figure 6 As shown, the milling force variation trend of the milling cutter can be extracted from the motor current signal in the full-groove milling stage, the root clearing stage of the half-groove milling stage, and the finish milling stage.
[0051] Based on the overall trend of the increasing change in the ratio between the motor current power and the milling cutter cutting power after the milling cutter wears, this invention proposes to indirectly reflect the wear state of the milling cutter through the wear energy coefficient λ, thus providing a visual indicator for the wear state of the milling cutter.
[0052] like Figure 8 As shown, this embodiment of the invention also provides a monitoring device 200 for the wear state of a machine tool milling cutter, comprising: an acquisition unit 201 for acquiring the current signal of the machine tool motor; an extraction unit 202 for extracting the signal characteristics of the current signal; and a determination unit 203 for determining the total milling force of the milling cutter based on the signal characteristics and a preset proportional relationship; determining the cutting power of the milling cutter based on the total milling force; determining the current power based on the current signal and the motor voltage; and determining the wear energy coefficient based on the cutting power and the current power; wherein the wear energy coefficient is used to reflect the wear state.
[0053] The method for monitoring the wear state of milling cutters in machine tools provided in this invention acquires the current signal of the machine tool's motor, extracts the signal characteristics of the current signal, and then determines the total milling force of the milling cutter based on the signal characteristics and a preset proportional relationship, without the need for a milling force sensor to detect the total milling force, thus effectively reducing the hardware cost of the machine tool. Then, in determining the wear state of the milling cutter, the cutting power of the milling cutter can be calculated based on the total milling force. Then, based on the motor current signal, the current power of the motor can be calculated. Finally, based on the extracted cutting power and the motor current power, the wear energy coefficient of the milling cutter during machine tool operation can be determined, and this wear energy coefficient reflects the wear state of the milling cutter.
[0054] Furthermore, the preset proportional relationship is obtained in the following way: within a preset time period, the current signals of multiple motors of the machine tool are acquired; the signal characteristics of multiple current signals are extracted; the least squares method is used to calculate the multiple signal characteristics to determine the characteristic change curve; the milling force change curve of the tangential milling force of the milling cutter is acquired within the preset time period; and the preset proportional relationship is determined based on the characteristic change curve and the milling force change curve.
[0055] This invention, through acquiring the signal characteristic change curves corresponding to the motor's current signal and the milling force change curve of the milling cutter's tangential milling force within a preset time period, allows for the comparison of the milling force change curve with the characteristic change curve corresponding to the current signal. Based on the differences between the two curves, a preset proportional relationship between the signal characteristics and the total milling force can be determined. Thus, during machine tool operation, the total milling force of the milling cutter can be determined based on the signal characteristics corresponding to the motor's current signal and the preset proportional relationship, eliminating the need for a milling force sensor and effectively reducing the machine tool's hardware costs.
[0056] Further, the extraction unit 202 is specifically used to: synthesize the three-phase current signals into effective value signals; decompose the effective value signals using a preset decomposition algorithm to obtain low-frequency components; and filter the low-frequency components to obtain signal characteristics. This invention combines the three-phase current signals into an effective value signal, and then uses a preset decomposition algorithm to decompose the effective value signal to obtain a low-frequency component. This avoids interference from non-stationary and nonlinear signals in the extraction of signal features from the current signal, ensuring the accuracy of the extracted signal features. The low-frequency component is then filtered to remove the carrier frequency, preventing it from affecting the subsequent determination of the preset proportional relationship, thereby improving the accuracy of the final obtained signal features.
[0057] This invention provides a method to obtain the geometric modeling parameters of the milling cutter, such as the height of the cutting edge, the height micro-element of the cutting edge, the number of cutting edge micro-element, the diameter of the milling cutter, and the friction coefficient between the milling cutter and the workpiece. Combined with the total milling force of the milling cutter, the cutting power of the milling cutter is obtained, thereby preparing for the determination of the wear energy coefficient of the milling cutter and thus determining the wear state of the milling cutter.
[0058] Furthermore, the determining unit 203 is specifically used to: determine the cutting power of the milling cutter, including: determining the tangential milling force of the milling cutter based on the total milling force and the geometric modeling parameters of the milling cutter; determining the cutting torque of the milling cutter based on the tangential milling force and the diameter of the milling cutter; and determining the cutting power based on the cutting torque and the angular velocity of the milling cutter.
[0059] This invention provides a method to obtain the geometric modeling parameters of the milling cutter, such as the height of the cutting edge, the height micro-element of the cutting edge, the number of cutting edge micro-element, the diameter of the milling cutter, and the friction coefficient between the milling cutter and the workpiece. Combined with the total milling force of the milling cutter, the cutting power of the milling cutter is obtained, thereby preparing for the determination of the wear energy coefficient of the milling cutter and thus determining the wear state of the milling cutter.
[0060] Furthermore, the determining unit 203 is specifically used for: according to a preset formula Determine the wear energy coefficient; where λ is the wear energy coefficient, P is the current power, and Pc is the cutting power.
[0061] Based on the overall trend of the increasing change in the ratio between the motor current power and the milling cutter cutting power after the milling cutter wears, this invention proposes to indirectly reflect the wear state of the milling cutter through the wear energy coefficient λ, thus providing a visual indicator for the wear state of the milling cutter.
[0062] like Figure 9 As shown, this embodiment of the invention also provides an electronic device 300, including a processor 301 and a memory 302. The memory 302 stores programs or instructions that can run on the processor 301. When the program or instructions are executed by the processor 301, they implement the steps of the machine tool milling cutter wear state monitoring method as described in any of the above technical solutions.
[0063] The electronic device 300 provided in this embodiment of the invention includes a memory 302 and a processor 301, and also includes a program or instructions stored in the memory 302. When the program or instructions are executed by the processor, they can implement the steps of the above-described method for monitoring the wear state of machine tool milling cutters. Therefore, the electronic device has all the beneficial effects of the above-described method for monitoring the wear state of machine tool milling cutters, which will not be elaborated here.
[0064] This invention also provides a readable storage medium storing a program or instructions, which, when executed by a processor, implements the steps of a machine tool milling cutter wear monitoring method as described in any of the above technical solutions.
[0065] The readable storage medium provided in this embodiment of the invention stores a program or instructions thereon. When the program or instructions are executed by a processor, they can implement the steps of the machine tool milling cutter wear condition monitoring method as described in any of the above-described technical solutions. Therefore, this readable storage medium possesses all the beneficial effects of the above-described machine tool milling cutter wear condition monitoring method, which will not be elaborated further here.
[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A method for monitoring the wear condition of a machine tool milling cutter, characterized in that, include: Obtain the current signal of the machine tool's motor; Extract the signal features of the current signal; The total milling force of the milling cutter is determined based on the signal characteristics and the preset proportional relationship; The cutting power of the milling cutter is determined based on the total milling force. The current power is determined based on the current signal and the motor voltage; The wear energy coefficient is determined based on the cutting power and the current power; wherein the wear energy coefficient is used to reflect the wear state.
2. The monitoring method according to claim 1, characterized in that, The preset proportional relationship is obtained through the following method: Within a preset time period, acquire the current signals of multiple motors of the machine tool; Extract the signal features of multiple current signals; The least squares method is used to calculate multiple signal features to determine the feature change curves; Obtain the milling force variation curve of the tangential milling force of the milling cutter within the preset time period; The preset proportional relationship is determined based on the characteristic change curve and the milling force change curve.
3. The monitoring method according to claim 1, characterized in that, The motor's current signal includes a three-phase current signal, and the extraction of the signal features of the current signal includes: The three-phase current signals are combined into an effective value signal; The effective value signal is decomposed using a preset decomposition algorithm to obtain low-frequency components; The low-frequency components are filtered to obtain the signal characteristics.
4. The monitoring method according to claim 1, characterized in that, Determining the cutting power of the milling cutter based on the total milling force includes: The tangential milling force of the milling cutter is determined based on the total milling force and the geometric modeling parameters of the milling cutter. The cutting torque of the milling cutter is determined based on the tangential milling force and the diameter of the milling cutter; The cutting power is determined based on the cutting torque and the angular velocity of the milling cutter.
5. The monitoring method according to claim 1, characterized in that, The step of determining the wear energy coefficient based on the cutting power and the current power includes: According to the preset formula Determine the wear energy coefficient; Wherein, λ is the wear energy coefficient, P is the current power, and Pc is the cutting power.
6. A device for monitoring the wear condition of a machine tool milling cutter, characterized in that, include: The acquisition unit is used to acquire the current signal of the machine tool's motor; Extraction unit, used to extract signal features of the current signal; The determining unit is used to determine the total milling force of the milling cutter based on the signal characteristics and a preset proportional relationship; The cutting power of the milling cutter is determined based on the total milling force. The current power is determined based on the current signal and the motor voltage; The wear energy coefficient is determined based on the cutting power and the current power; wherein the wear energy coefficient is used to reflect the wear state.
7. The monitoring device according to claim 6, characterized in that, The preset proportional relationship is obtained through the following method: Within a preset time period, acquire the current signals of multiple motors of the machine tool; Extract the signal features of multiple current signals; The least squares method is used to calculate multiple signal features to determine the feature change curves; Obtain the milling force variation curve of the tangential milling force of the milling cutter within the preset time period; The preset proportional relationship is determined based on the characteristic change curve and the milling force change curve.
8. The monitoring device according to claim 6, characterized in that, The extraction unit is specifically used for: The three-phase current signals are combined into an effective value signal; The effective value signal is decomposed using a preset decomposition algorithm to obtain low-frequency components; The low-frequency components are filtered to obtain the signal characteristics. The determining unit is specifically used for: Determining the cutting power of the milling cutter includes: The tangential milling force of the milling cutter is determined based on the total milling force and the geometric modeling parameters of the milling cutter. The cutting torque of the milling cutter is determined based on the tangential milling force and the diameter of the milling cutter; The cutting power is determined based on the cutting torque and the angular velocity of the milling cutter; The determining unit is further specifically used for: According to the preset formula Determine the wear energy coefficient; Wherein, λ is the wear energy coefficient, P is the current power, and Pc is the cutting power.
9. An electronic device, characterized in that, include: A processor and a memory, the memory storing a program or instructions executable on the processor, the program or instructions, when executed by the processor, implementing the steps of the method for monitoring the wear condition of a machine tool milling cutter as described in any one of claims 1 to 5.
10. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the steps of the method for monitoring the wear condition of a machine tool milling cutter as described in any one of claims 1 to 5.