Digital twin drive chatter suppression method and system

Abstract

The present invention discloses a digital twin-driven mechanical machining chatter suppression method and system, constructs a digital twin system for chatter suppression, and combines chatter prediction technology, online monitoring technology, and active suppression technology through information interaction and processing between the physical entity of the mechanical machining system and the digital twin, giving full play to the advantages of each method, and realizing the prediction, monitoring, and active suppression of chatter. The present invention realizes the integration and comprehensive application of mechanical machining system information, and can effectively avoid or reduce the impact of chatter on the mechanical machining process. In addition, the visualization function provided by the digital twin makes it easy for machine tool operators to monitor the mechanical machining process, discover problems in a timely manner, and participate in the decision-making of the digital twin system.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent manufacturing, and more specifically, relates to a method and system for suppressing chatter in a mechanical processing process. Background Art

[0002] Mechanical vibration is widely present in various mechanical processing processes, which has a serious impact on the machining accuracy and surface quality of the workpiece, tool wear, etc. Therefore, the prevention and control of mechanical vibration has always been a research focus in the field of mechanical processing. Among them, due to the characteristics of intermittent cutting in milling, the vibration phenomenon has a more significant impact on the machining process. According to its occurrence mechanism, mechanical vibration mainly has the following forms: free vibration, forced vibration, self-excited vibration (also known as chatter), etc. Among them, chatter phenomenon has the most significant impact on the milling process, and is one of the main factors restricting cutting efficiency and workpiece surface quality / machining accuracy.

[0003] At present, the known chatter forms are: regenerative type, friction type, and vibration coupling type. Regeneration is widely present in various types of mechanical processing. Therefore, regenerative chatter based on the principle of regeneration has the most extensive influence. The suppression of regenerative chatter has always been one of the main directions of mechanical vibration control. At present, the technologies related to the suppression of regenerative chatter are: theoretical prediction method, online monitoring method, and active suppression method. The basic principle of the theoretical prediction method is to obtain the stability lobe diagram through analytical modeling, and optimize the cutting parameters based on the stability lobe diagram to avoid the occurrence of chatter. It can predict the stability of cutting processing, but there are model simplification errors and model input parameter errors, and the prediction results will have certain errors. Online monitoring technology is based on signals such as vibration / noise generated during the cutting process. It identifies chatter by extracting features and judging thresholds on the signals. The collected signals reflect the real-time status of the mechanical processing system, but it is only a monitoring method. When the chatter is identified, other equipment / adjustment methods are needed to suppress the chatter. In addition, the existing online monitoring technology does not have the function of prediction. It can only adjust the system after the chatter occurs, and cannot completely avoid the impact of chatter on the mechanical processing process. The basic principle of active suppression technology is to increase the stability of the system by adding auxiliary equipment and adjusting the rigidity, damping, modal frequency and other parameters of the process system, thereby avoiding chatter. Chatter is suppressed by changing the system characteristics, and the reliability is high. However, it is necessary to use theoretical analysis methods to evaluate the effect of the adjustment. When real-time adjustment is required, it is necessary to use online monitoring methods to feedback the actual cutting status. In addition, the existing auxiliary devices are complex in design and cannot adapt to mechanical processing systems with variable structures / sizes, and their versatility is limited.

[0004] It should be noted that the information disclosed in the above background technology section is only used for understanding the background of the present application, and therefore may include information that does not constitute prior art known to ordinary technicians in the field. Summary of the invention

[0005] The main purpose of the present invention is to overcome the defects of the above-mentioned background technology and provide a digital twin drive vibration suppression method and system.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] A digital twin-driven chatter suppression method, the method performing information interaction and processing between a physical entity of a machining system and a digital twin of the machining system; the method comprising at least the following steps:

[0008] S1. Collecting initial information of the physical entity and transmitting it to the digital twin, the digital twin calculates the stability prediction result of the physical entity, the prediction result includes a stability lobe diagram and a tool tip vibration displacement signal, and the digital twin transmits initial cutting parameters to the control module of the physical entity based on the prediction result for cutting processing in the initial stage of the process; Preferably, the initial information of the physical entity includes a machining spindle mode and a workpiece material;

[0009] S2. During the actual cutting process, the digital twin adjusts the prediction result based on the time-varying characteristics of the modal parameters of the workpiece in the physical entity, and updates the cutting parameters to the physical entity;

[0010] S3. During the execution of step S2, when it is determined that flutter has occurred according to the real-time monitoring signal of the physical entity, the prediction result is corrected based on the optimization algorithm so that the dynamic performance of the digital twin matches the physical entity, and / or the physical entity is adjusted through auxiliary equipment so that its dynamic performance matches the current digital twin.

[0011] Further:

[0012] The method further comprises the steps of:

[0013] S4. While executing steps S1-S3, the signals generated by the physical entity during the cutting process are collected in real time by sensors and transmitted to the digital twin in real time. The digital twin identifies the cutting state based on the chatter recognition algorithm according to the signals and the prediction results obtained in step S1; preferably, the signals generated during the cutting process include vibration, force, and noise.

[0014] The method further comprises the steps of:

[0015] S5. While executing steps S1-S4, based on the modeling of the physical entity, the digital twin displays the machining process in real time in a visualization module by calling one or more data including cutting position and real-time cutting signal of the workpiece. Preferably, the visualization module maps the cutting state of the physical entity and the changes in the surface morphology of the workpiece in real time.

[0016] In step S2, based on the time-varying characteristics of the modal parameters of the workpiece in the physical entity, the prediction results of the digital twin are adjusted and the cutting parameters are updated at a set update frequency. Preferably, the update frequency is between 0.1 Hz and 100 Hz.

[0017] In step S2, when in a normal cutting state, based on the feed motion and other data transmitted by the physical entity, real-time Boolean operations are performed on the workpiece in the digital twin space to achieve real-time mapping of the cutting process; based on the real-time workpiece modal parameters, the lobe diagram and optimization parameters are calculated and output in real time, and transmitted to the physical entity to optimize the cutting process; wherein, the horizontal and vertical coordinates of the lobe diagram represent the cutting parameters in the cutting process, the lower part of the lobe diagram represents the stable cutting area, and the upper part of the lobe diagram represents the vibration occurrence area, based on the real-time lobe diagram, and combined with the cutting capability, cutting efficiency and precision requirements of the process system, combined with the optimization algorithm, the real-time optimal cutting parameters are obtained.

[0018] In step S3, the prediction result is corrected based on the optimization algorithm to make the dynamic performance of the digital twin match the physical entity, specifically including: based on the principle of inverse method, using real-time cutting signals to derive errors in the input parameters of the prediction model, correcting the prediction model and the real-time lobe diagram output results, and transmitting the optimized cutting parameters to the machining system of the physical entity to achieve process optimization; when the optimized cutting parameter optimization still cannot avoid the occurrence of chatter, the prediction result is iteratively optimized, wherein, based on the lobe diagram, the cutting parameters are adjusted within a larger range, leaving a larger safety margin to compensate for the prediction error caused by model simplification.

[0019] In step S3, the physical entity is adjusted by auxiliary equipment so that its dynamic performance matches that of the current digital twin, specifically including:

[0020] Improving the stability of the physical entity by using one or more auxiliary devices including a vibration suppression equipment control unit, a driving ultrasonic auxiliary system, and a phononic crystal vibration reduction system;

[0021] Preferably, the stability of the physical entity is adjusted by one or more of the following methods: adjusting the overhang length of the tool, the length clamped by the tool holder, the diameter of the tool, the structure of the tool holder, and increasing the damping of the process system.

[0022] The information interaction is carried out through the sensor module and the control module of the physical entity. The sensor module collects data during the machining process to the digital twin to realize one-way information transmission. The two-way information transmission between the digital twin and the physical entity is realized based on the control module.

[0023] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the digital twin drive flutter suppression method is implemented.

[0024] A digital twin driven flutter suppression system comprises the physical entity and the digital twin in the method, and an information interaction module between the physical entity and the digital twin.

[0025] The present invention has the following beneficial effects:

[0026] Based on the three-dimensional model of digital twin, the present invention proposes a method for flutter suppression driven by digital twin, wherein a digital twin system for flutter suppression is constructed, and through information interaction and processing between the physical entity of the machining system and the digital twin, the flutter prediction technology, online monitoring technology, and active suppression technology are combined to give full play to the advantages of each method, and the prediction, monitoring, and active suppression of flutter can be achieved. The present invention realizes the integration and comprehensive application of machining system information, and can effectively avoid or reduce the impact of flutter on the machining process. In addition, the visualization function provided by the digital twin makes it easy for the machine tool operator to monitor the machining process, find problems in time and participate in the decision-making of the digital twin system. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A typical three-dimensional model diagram of a digital twin system according to an embodiment of the present invention;

[0028] Figure 2 A schematic diagram of a mechanical processing system and a data acquisition device according to an embodiment of the present invention;

[0029] Figure 3 A schematic diagram of a digital twin system for chatter suppression according to an embodiment of the present invention;

[0030] Figure 4 A real-time lobe diagram according to an embodiment of the present invention. DETAILED DESCRIPTION

[0031] The following is a detailed description of the embodiments of the present invention. It should be emphasized that the following description is only exemplary and is not intended to limit the scope and application of the present invention.

[0032] It should be noted that when an element is referred to as being "fixed to" or "disposed on" another element, it may be directly on the other element or indirectly on the other element. When an element is referred to as being "connected to" another element, it may be directly connected to the other element or indirectly connected to the other element. In addition, connection may be used for fixing as well as for coupling or communication.

[0033] It should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing the embodiments of the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0034] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0035] Digital twin is a simulation model that integrates multi-physics, multi-scale, and dynamic probability. Through precise models and sensing technology, it can map the state of physical entities in real time and optimize them in real time. It mainly consists of three components: physical entity, digital twin, and information interaction module. Through data-driven, virtual-real combination, digital twin can map the state of physical entities in real time and predict the future state of physical entities.

[0036] See also Figure 1 The digital twin system of the embodiment of the present invention includes a physical entity of a mechanical processing system, a digital twin of the mechanical processing system, and an information interaction module between the two.

[0037] The embodiment of the present invention provides a digital twin driven chatter suppression method, which performs information exchange and processing between the physical entity of a machining system and the digital twin of the machining system. The physical entity may include components such as a spindle, a tool, a workpiece to be machined, a fixture, and a workbench. The workpiece is mounted on the workbench, the spindle performs a rotation main motion, and a linear motor drives the spindle and the workbench to perform a feed motion, thereby achieving continuous cutting. The digital twin constructed by the method may include functional units such as an algorithm module, a visualization module, and a database. The algorithm module comprehensively uses technologies such as chatter prediction, online monitoring, and active suppression, and integrates static parameters in the physical entity (such as milling cutter structure parameters, workpiece material parameters, spindle modal parameters, etc.), and dynamic parameters (such as vibration, noise, force signals, etc. generated during machining). Based on the integration of physical entity information and the comprehensive application of the above three technologies, chatter monitoring and active suppression can be achieved to reduce the impact of chatter on the machining process.

[0038] The information interaction module of the method includes a control unit (such as a numerical control system) of the physical entity and arranged sensors. The sensors are used to collect signals such as vibration, force, noise, etc. during the machining process and feed them back to the digital twin. This connection method can realize one-way information transmission. The control unit transmits the cutting state information of the physical entity to the digital twin, and at the same time, receives the optimized cutting parameter information from the digital twin. The relevant parameters are used to optimize the cutting process of the physical entity. This connection method can realize two-way information transmission.

[0039] In some embodiments, the method comprises the following steps:

[0040] S1. Collect the initial information such as spindle mode and workpiece material parameters of the physical entity of the machining system (hereinafter referred to as the physical entity) in the industrial automation scenario through RFID and other technologies, and transmit it to the database module of the digital twin of the machining system (hereinafter referred to as the digital twin) for the calculation of the stability prediction results of the digital twin algorithm module. The relevant prediction results include two parts: the stability lobe diagram and the tool tip vibration displacement signal, and are stored in the database; based on the prediction results, the digital twin transmits the initial cutting parameters to the control module of the physical entity for cutting processing in the initial stage of the process;

[0041] S2. In the actual cutting process, in order to accurately reflect the dynamic performance of the physical entity in real time, the digital twin will adjust the prediction results of the digital twin at a certain update frequency based on the time-varying characteristics of the modal parameters of the workpiece in the physical entity, and update the cutting parameters to the physical entity;

[0042] S3. When the digital twin determines that the current state has fluttered through real-time monitoring signals during the execution of S2, it means that the system dynamic performance reflected by the digital twin at this time is severely mismatched with the dynamic performance of its physical entity. The system will make emergency adjustments to the prediction results (system response time: <1ms). There are two ways to make emergency adjustments: ① Correct the prediction results of the digital twin based on the optimization algorithm to match the dynamic performance of the digital twin with the physical entity; ② Adjust the physical entity through auxiliary equipment to match its dynamic performance with the current digital twin;

[0043] S4. While executing steps S1-S3, the sensor module of the digital twin system collects the vibration, force, noise and other signals of the physical entity in the cutting process in real time, and transmits them to the database module of the digital twin in real time. The algorithm module calls the real-time signal data from the database module and the predicted signal data obtained in S1, and performs cutting state identification based on the chatter recognition algorithm;

[0044] S5. While executing steps S1-S4, based on the precise modeling of the physical entity, the digital twin can give a full picture of the machining process in real time in its visualization module by calling data such as the cutting position and the real-time cutting signal of the workpiece, which is convenient for manual monitoring.

[0045] The physical entity includes spindles, tools, workpieces to be processed, fixtures, workbenches and other parts. This physical entity can be a general CNC machine tool, machining center, industrial robot cutting platform, electric spindle work platform, etc. The motion control method of the physical entity can be based on a specific CNC system, or can be controlled based on a programmable controller or other methods; through its control system, the physical entity can receive optimized cutting parameters from its digital twin to achieve real-time optimization of the cutting process, and can also transmit its real-time cutting position and other information to the digital twin.

[0046] The digital twin includes an algorithm module, which may include a vibration online data processing unit, a real-time lobe map acquisition unit, a vibration suppression device control unit and other parts, which respectively receive real-time vibration, force, noise and other signals from the physical entity, as well as its status information, etc., for real-time monitoring of the cutting process and generating real-time optimized cutting parameters based on the lobe map.

[0047] The digital twin includes a visualization module, which can map the cutting state of the physical entity and the changes in the surface morphology of the workpiece in real time based on accurate model construction;

[0048] The information interaction module includes two parts: a sensor module and a control module of a physical entity. The sensor module collects data such as vibration, force, and noise during the machining process to the digital twin to realize one-way information transmission. Based on the control module, two-way information transmission between the digital twin and the physical entity can be realized.

[0049] The online data processing unit is based on real-time signals collected by sensors (including but not limited to vibration, force, noise and other signals). It can eliminate redundant data and extract characteristic parameters through a multi-sensor fusion algorithm, and judge the cutting processing status based on machine learning and other means.

[0050] The real-time lobe image acquisition unit can extract the optimal cutting parameters based on the real-time lobe image it acquires and in combination with the performance parameters of the process system, the efficiency and precision requirements of the cutting process in the current process, and transmit the optimal cutting parameters to the machining system;

[0051] The vibration suppression equipment control unit can call auxiliary vibration suppression equipment in the physical entity (equipment types include but are not limited to: phononic crystal vibration suppression device, ultrasonic assisted processing vibration suppression device).

[0052] The chatter suppression method driven by a digital twin provided in an embodiment of the present invention integrates theoretical prediction, online monitoring, active suppression and other means in the process of building a digital twin system, and integrates and comprehensively applies the information of the machining system. The proposed method can reduce / avoid the influence of chatter on the machining process, and can improve the machining accuracy, surface quality, machining efficiency and service life of the workpiece during the machining process.

[0053] Specific embodiments of the present invention are further described below.

[0054] The present invention provides a method for suppressing mechanical machining chatter driven by digital twins. The technical scheme of the method includes three parts: a physical entity of a mechanical machining system, a digital twin of the mechanical machining system, and an information interaction module between the two. The physical entity of the mechanical machining system includes a spindle, a tool, a workpiece to be processed, a fixture, a workbench and other parts, which are the objects to be mapped by the digital twin. In the process of constructing the digital twin, means such as chatter theory prediction, online monitoring, and active suppression are integrated, and the information of the mechanical machining system is integrated and comprehensively used. The digital twin can map the working state of the mechanical machining system in real time, provide a visual human-computer interaction window, and predict, monitor and adjust the chatter in the machining process in real time. The information interaction module includes two parts: a sensor and a control module of the mechanical machining system, which can realize two-way transmission of information such as cutting parameters and cutting status. The present invention can improve the machining accuracy, surface quality, machining efficiency and tool life of the workpiece during the mechanical machining process.

[0055] The physical entity of the embodiment of the present invention is as follows Figure 2 As shown, the fixture workpiece module 5 is installed on the workbench 6, and the workbench 6 can be driven by a motor to perform three-way linear motion or tilt rotation, and the spindle system 4 drives the tool to perform a rotational main motion. In addition, the spindle system 4 can also perform linear motion or tilt rotation based on needs. Under the coordinated movement of the spindle system 4 and the workbench 6, continuous cutting of the workpiece can be achieved. Figure 2 The object to be characterized can be an ordinary CNC machine tool, an electric spindle work platform, or an industrial robot cutting platform. The related main / feed cutting motion can be controlled by a professional CNC system, or by a programmable logic controller (PLC). Figure 2 The general arrangement of the dynamometer 7, microphone 8 and vibration sensor 9 is also given, which are used to collect force, noise and vibration acceleration signals during the cutting process.

[0056] based on Figure 2 object, Figure 3 A digital twin system for flutter suppression was constructed, which is divided into physical entity 11, information interaction module 12, and digital twin 13. The digital twin 13 is mainly divided into algorithm module, visualization module, and database. The algorithm module is further divided into online signal processing unit, real-time leaflet image acquisition unit, and vibration suppression equipment control unit. Figure 3 , the implementation method of flutter suppression under digital twin drive is introduced in detail.

[0057] 1) Operation of digital twin in initial cutting state

[0058] The digital twin system needs to input initial parameters so that the digital twin can obtain the initial state of the physical entity and determine the initial cutting parameters of the physical entity. The main contents are as follows:

[0059] S1 initialization parameter input

[0060] The algorithm module requires initial model parameter input for subsequent model calculations. These parameters include the material parameters of the workpiece, the structural parameters of the tool, the modal parameters of the spindle system 4 under static conditions, etc. The relevant parameters need to be obtained through experiments and measurements, and the information can be bound to the electronic tag. The electronic tag is attached to the corresponding component. Based on RFID technology, the relevant information can be obtained through the reader and transmitted to the database module of the digital twin system 13. Other modules can directly call the database data. This information binding and collection method facilitates automated operation in industrial application scenarios;

[0061] S2 Initial cutting parameters determination

[0062] After obtaining the initial state information of the physical entity in step S1, the digital twin can calculate the stability prediction results under the initial state based on this. The relevant prediction results include two parts: stability lobe diagram and tool tip vibration displacement and other signals, which are stored in the database; based on the prediction results, the digital twin transmits the initial cutting parameters to the control module of the physical entity for cutting processing in the initial stage of the process;

[0063] S3 visualization function implementation

[0064] In order to realize the visualization function and the subsequent physical simulation needs, the three-dimensional model file of the physical entity 11 needs to be input into the digital twin 13, and the model needs to be consistent with the physical entity in terms of structural size, material, joint surface type / parameters, initial position, etc.

[0065] Before the formal cutting process begins, based on the precise construction of the model and the preset cutting path of the physical entity 11, the cutting process simulation and tool path simulation analysis can be performed in the digital twin 13 to avoid problems such as mechanical collision caused by unreasonable paths;

[0066] During the initial cutting process, the digital twin calls the cutting position and other data of the physical entity to perform real-time Boolean operations on the tool and workpiece model, and can give the real-time status of the machining process in the visualization module of the digital twin.

[0067] 2) Digital twin operation under normal cutting conditions

[0068] After process 1), the system completes the initialization settings and performs cutting based on the initial cutting parameters. The following steps introduce the operation process of the digital twin system in a stable cutting state:

[0069] S1. Real-time lobe image acquisition under stable cutting state

[0070] In the actual cutting process, in order to accurately reflect the dynamic performance of the physical entity in real time, the digital twin will adjust the prediction results of the digital twin at a certain update frequency based on the time-varying characteristics of the modal parameters of the workpiece in the physical entity, and update the cutting parameters to the physical entity. Specifically: When in a normal cutting state, based on the feed motion and other data transmitted by the physical entity 11, real-time Boolean operations can be performed on the workpiece in the digital twin space 13 to achieve real-time mapping of the cutting process. Based on the workpiece in the real-time state, the workpiece mode in the corresponding state can be quickly acquired through simulation and other methods. Based on the real-time workpiece mode and parameters, the real-time lobe diagram acquisition unit can calculate the output lobe diagram and optimization parameters in real time, and transmit them to the physical entity 11 to optimize the cutting process. The cutting parameter update frequency that can be achieved by this digital twin is 0.1Hz-100Hz;

[0071] An example of a real-time lobe map is Figure 4 As shown, the horizontal and vertical coordinates of the lobe diagram 14 represent the cutting parameters (rotation speed, cutting depth, etc.) during the cutting process. The lower part of the lobe diagram represents the stable cutting area. The cutting parameters selected in this area can achieve stable cutting. The upper part of the lobe diagram represents the vibration occurrence area. The cutting parameters selected in this area are prone to cause vibration. As the cutting position of the milling cutter 16 on the workpiece 15 changes, the lobe diagram also changes accordingly. This change is mainly due to the difference in the rigidity of the workpiece at different positions and the influence of material removal on the workpiece mode. Figure 4 As shown in the figure, the position of the lobe diagram changes from t1 to t3 during the continuous cutting stage. Based on the real-time lobe diagram, combined with the cutting capability of the process system, the requirements of cutting efficiency / precision, and the corresponding optimization algorithm, the real-time optimal cutting parameters can be obtained.

[0072] S2. Signal monitoring under stable cutting state

[0073] While executing the S1 step, the online signal processing unit of the digital twin collects data in real time through sensors, outputs the current cutting status, and monitors the machining process.

[0074] S3. Visualization of cutting process

[0075] In the process of executing S1-S2, based on the accurate modeling of the physical entity, the digital twin performs real-time Boolean operations on the tool and workpiece models by calling the cutting position and other data of the physical entity. The real-time status of the mechanical processing process can be given in the visualization module of the digital twin in real time, which is convenient for manual monitoring of the processing process.

[0076] In addition, based on the real-time signals collected by S2 and the analytical model of the real-time signals and the workpiece surface quality, the surface morphology of the workpiece under the current cutting state can be obtained, which is convenient for manual monitoring of the workpiece surface quality during the cutting process.

[0077] 3) Digital Twin Operation When Flutter Occurs

[0078] When the digital twin determines that the current state has fluttered through real-time monitoring signals during the execution of step 2), it means that the system dynamic performance reflected by the digital twin does not match the dynamic performance of its physical entity. The system will make emergency adjustments to the prediction results (system response time: < 1ms). There are two ways to make emergency adjustments:

[0079] ① Based on the optimization algorithm, the prediction results of the digital twin are corrected to match the dynamic performance of the digital twin with the physical entity;

[0080] The relevant optimization algorithm implementation process: Based on the principle of inverse method, the real-time cutting signal is used to deduce the errors in the input parameters of the prediction model (such as spindle modal error, workpiece cutting force coefficient error, etc.), the prediction model and the real-time lobe map output results are corrected, and the optimized cutting parameters are transmitted to the machining system 11 to achieve process optimization;

[0081] Since the prediction error of the theoretical model comes not only from the model input parameters, but also from the simplified description of the model during the modeling process, when the above-mentioned optimization of cutting parameters still cannot avoid the occurrence of chatter, it is necessary to iteratively optimize the prediction results. Specifically, based on the above-mentioned lobe diagram, the cutting parameters are adjusted in a larger range to leave a larger safety margin to compensate for the prediction error caused by the simplification of the model.

[0082] ② Adjust the physical entity through auxiliary equipment to match its dynamic performance with the current digital twin;

[0083] In the adjustment process of ①, the cutting parameters are often adjusted in the direction of reducing the cutting efficiency. In order to improve the cutting efficiency, the stability of the physical entity 11 can be improved by using auxiliary equipment such as the vibration suppression equipment control unit, driving the ultrasonic auxiliary system, or the phononic crystal vibration reduction system, so as to achieve rapid suppression of the chatter without adjusting the cutting parameters, and timely avoid the influence of the chatter on the surface accuracy of the workpiece.

[0084] In addition, this method can also be used to optimize the physical entity cutting parameters in the initial state, so that the initial cutting parameters of the system have higher cutting efficiency.

[0085] In addition to the methods mentioned above, other ways to adjust the stability of the physical entity include: adjusting the overhang length of the tool, the length clamped by the tool holder, the diameter of the tool, the structure of the tool holder, etc., and increasing the damping of the process system (such as: embedding damping material in the tool holder).

[0086] exist Figure 3 In the digital twin of the physical entity 11, a rich human-computer interaction module is provided, and the operator of the physical entity 11 can participate in the operation of the digital twin 13 throughout the process, and can participate in decision-making based on the information provided by the digital twin 13. The form of human-computer interaction can be continuously enriched based on the application of technologies such as artificial intelligence. For example, based on VR helmets and data gloves, the digital twin 3D model can be changed and more model details can be observed.

[0087] As mentioned above, the digital twin-driven chatter suppression strategy is given for the two processes of machining preparation and machining. In addition, the digital twin system for chatter suppression proposed in the present invention also has good versatility and scalability, and the algorithm modules therein can be modified based on this to solve more physical problems (such as workpiece thermal deformation, tool wear, etc.), and can also be oriented to product life cycle management, including more functional module units (such as: size detection and error analysis model after workpiece processing).

[0088] The background section of the present invention may contain background information about the problem or environment of the present invention, but does not necessarily describe the prior art. Therefore, the content included in the background section is not an admission by the applicant that the prior art is available.

[0089] The above content is a further detailed description of the present invention in combination with specific / preferred embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, without departing from the concept of the present invention, they can also make several substitutions or modifications to these described embodiments, and these substitutions or modifications should be regarded as belonging to the protection scope of the present invention. In the description of this specification, the description of reference terms "an embodiment", "some embodiments", "preferred embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in combination with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily target the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In the absence of mutual contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples. Although the embodiments of the present invention and their advantages have been described in detail, it should be understood that various changes, substitutions and modifications can be made herein without departing from the scope of protection of the patent application.

Claims

1. A method for suppressing chatter driven by a digital twin, characterized in that: The method performs information interaction and processing between a physical entity of a machining system and a digital twin of the machining system; the method comprises at least the following steps: S1. Collecting initial information of the physical entity and transmitting it to the digital twin, the digital twin calculates the stability prediction result of the physical entity, the prediction result includes a stability lobe diagram and a tool tip vibration displacement signal, and the digital twin transmits initial cutting parameters to the control module of the physical entity based on the prediction result for cutting processing in the initial stage of the process; the initial information of the physical entity includes a processing spindle mode and a workpiece material; S2. During the actual cutting process, the digital twin adjusts the prediction result based on the time-varying characteristics of the modal parameters of the workpiece in the physical entity, and updates the cutting parameters to the physical entity; when in a normal cutting state, based on the feed motion data transmitted by the physical entity, a real-time Boolean operation is performed on the workpiece in the digital twin space to achieve real-time mapping of the cutting process; based on the real-time modal parameters of the workpiece, a lobe diagram and optimization parameters are calculated and output in real time, and transmitted to the physical entity to optimize the cutting process; wherein the horizontal and vertical coordinates of the lobe diagram represent the cutting parameters during the cutting process, the lower part of the lobe diagram represents the stable cutting area, and the upper part of the lobe diagram represents the vibration occurrence area, based on the real-time lobe diagram, combined with the cutting capability, cutting efficiency and precision requirements of the process system, combined with the optimization algorithm, the real-time optimal cutting parameters are obtained; S3. During the execution of step S2, when it is determined that flutter has occurred according to the real-time monitoring signal of the physical entity, the prediction result is corrected based on the optimization algorithm so that the dynamic performance of the digital twin matches the physical entity, and / or the physical entity is adjusted through auxiliary equipment so that its dynamic performance matches the current digital twin.

2. The digital twin drive chatter suppression method according to claim 1, characterized in that: The method further comprises the steps of: S4. While executing steps S1-S3, the signals generated by the physical entity during the cutting process are collected in real time through sensors and transmitted to the digital twin in real time. The digital twin identifies the cutting state based on the chatter recognition algorithm according to the signals and the prediction results obtained in step S1; the signals generated during the cutting process include vibration, force, and noise.

3. The digital twin drive chatter suppression method according to claim 1 or 2, characterized in that: The method further comprises the steps of: S5. While executing steps S1-S4, based on the modeling of the physical entity, the digital twin displays the machining process in real time in the visualization module by calling one or more data including cutting position and real-time cutting signal of the workpiece.

4. The digital twin drive chatter suppression method according to claim 3, characterized in that: In step S5, the visualization module maps the cutting state of the physical entity and the changes in the surface morphology of the workpiece in real time.

5. The chatter suppression method for digital twin drive according to any one of claims 1 to 2, characterized in that: In step S2, based on the time-varying characteristics of the modal parameters of the workpiece in the physical entity, the prediction results of the digital twin are adjusted and the cutting parameters are updated at a set update frequency.

6. The digital twin drive chatter suppression method according to claim 5, characterized in that: The update frequency is between 0.1 Hz and 100 Hz.

7. The chatter suppression method of digital twin drive according to any one of claims 1 to 2, characterized in that: In step S3, the prediction result is corrected based on the optimization algorithm so that the dynamic performance of the digital twin matches the physical entity, specifically including: based on the principle of inverse method, the real-time cutting signal is used to derive the errors in the input parameters of the prediction model, the prediction model and the real-time lobe diagram output results are corrected, and the optimized cutting parameters are transmitted to the machining system of the physical entity to achieve process optimization; when the optimized cutting parameter optimization still cannot avoid the occurrence of chatter, the prediction result is iteratively optimized, wherein the cutting parameters are adjusted within a larger range based on the lobe diagram, leaving a larger safety margin to compensate for the prediction error caused by model simplification.

8. The method for suppressing chatter of a digital twin drive according to any one of claims 1 to 2, characterized in that: In step S3, the physical entity is adjusted by auxiliary equipment so that its dynamic performance matches that of the current digital twin, specifically including: The stability of the physical entity is improved by one or more auxiliary devices including a vibration suppression equipment control unit, a driving ultrasonic auxiliary system, and a phononic crystal vibration reduction system.

9. The digital twin drive chatter suppression method according to claim 8, characterized in that: In step S3, the stability of the physical entity is also adjusted by one or more of the following methods: adjusting the overhang length of the tool, the length clamped by the tool holder, the diameter of the tool, the structure of the tool holder, and increasing the damping of the process system.

10. The digital twin drive chatter suppression method according to any one of claims 1 to 2, characterized in that: The information interaction is carried out through the sensor module and the control module of the physical entity. The sensor module collects data during the machining process to the digital twin to realize one-way information transmission. The two-way information transmission between the digital twin and the physical entity is realized based on the control module.

11. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the flutter suppression method of the digital twin drive according to any one of claims 1 to 10 is implemented.

12. A digital twin driven flutter suppression system, characterized in that: It includes the physical entity and the digital twin in the method as claimed in claim 1, and an information interaction module between the physical entity and the digital twin.

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