Self-adaptive control method and system for cutting torque of motorized spindle

Abstract

The invention provides a self-adaptive control method and system for the cutting torque of an electric spindle, and relates to the technical field of cutting control. The method comprises the steps that control requirements are interacted, and rigid and flexible control standards are established; supervising and training an adaptive control module based on a cooperative coupling function, performing parameter control decision analysis in combination with rigid and flexible control standards, and determining a dynamic parameter control scheme; synchronously performing real-time control monitoring, and reading control response data; a feedback verification unit is set up to conduct deflection error verification and cutting torque feedback regulation and control on control response data; the auxiliary adaptive control module and the feedback verification unit carry out closed-loop vector control. According to the method and the device, the technical problems that the precision, the efficiency and the stability of control are poor due to the fact that the precision of cutting torque analysis is poor and the cutting torque cannot be precisely controlled in a targeted mode can be solved, closed-loop vector control over the cutting torque can be achieved, and the expected integrating degree of cutting torque control is improved.

Description

Technical Field

[0001] The present application relates to the field of cutting control technology, and in particular to a method and system for adaptively controlling cutting torque of an electric spindle. Background Art

[0002] Cutting torque is an important parameter in cutting processing. It is defined as the torque generated by the total cutting force of the tool on the rotation axis of the main motion. Its size is closely related to factors such as the hardness of the workpiece material, processing speed, and feed rate.

[0003] The control of electric spindle cutting torque is a key link in the machining process of machine tools, which directly affects the machining accuracy, efficiency and tool life. At present, the control methods, modeling standards and optimization methods for electric spindle cutting torque are mostly directly aimed at torque control, and there is a certain lack of overall control. At the same time, the precision of cutting torque analysis is poor, which cannot meet the control standards under complex machining tasks. In summary, the existing electric spindle cutting torque control method has the problem of poor precision in cutting torque analysis, which makes it impossible to carry out targeted and accurate control of the cutting torque, resulting in technical problems such as poor accuracy, efficiency and stability of cutting torque control. Summary of the invention

[0004] The purpose of this application is to provide an electric spindle cutting torque adaptive control method and system to solve the technical problems that the existing electric spindle cutting torque control method has poor precision in cutting torque analysis, resulting in the inability to carry out targeted and precise control of cutting torque, resulting in poor accuracy, efficiency and stability of cutting torque control.

[0005] In view of the above problems, the present application provides a method and system for adaptively controlling cutting torque of an electric spindle.

[0006] In a first aspect, the present application provides an adaptive control method for cutting torque of an electric spindle, which is implemented by an adaptive control system for cutting torque of an electric spindle, wherein the method includes: determining the control requirements of the entire machining cycle of an interactive pre-cutting task, dividing and determining a rigid control standard and a flexible control standard with the same frequency association; determining the basic parameter control characteristics of torque control related parts, and the main and auxiliary collaborative characteristics of the joint system, performing correlation analysis of working condition collaboration, and determining a collaborative coupling function, wherein the collaborative coupling function includes a parameter control collaborative dimension and a system collaborative dimension; supervising and training an adaptive control module based on the collaborative coupling function, performing parameter control decision analysis in combination with the rigid control standard and the flexible control standard, and determining a dynamic parameter control scheme; based on the dynamic parameter control scheme, performing program setting of a programmable controller, synchronously performing real-time control monitoring, and reading control response data; determining an indicator multi-group for measuring quality standards, building a feedback verification unit in combination with a quality tolerance interval, performing runout error verification and feedback regulation of cutting torque on the control response data, wherein each quality indicator has an associated identifier with a mapping parameter; assisting the adaptive control module and the feedback verification unit in performing closed-loop vector control of the cutting torque of the electric spindle.

[0007] In the second aspect, the present application also provides an electric spindle cutting torque adaptive control system for executing an electric spindle cutting torque adaptive control method as described in the first aspect, wherein the system includes: a control standard establishment module, the control standard establishment module is used to interactively pre-cutting task processing cycle control requirements, segmentation and determination to establish rigid control standards and flexible control standards with the same frequency association; a collaborative coupling function determination module, the collaborative coupling function determination module is used to determine the basic parameter control characteristics of torque control related parts, and the main and auxiliary collaborative characteristics of the joint system, perform correlation analysis of working condition coordination, and determine the collaborative coupling function, the collaborative coupling function includes parameter control collaborative dimension and system collaborative dimension; a dynamic parameter control scheme determination module, the dynamic parameter control scheme determination module is used to supervise the training based on the collaborative coupling function An adaptive control module is used to perform parameter control decision analysis in combination with the rigid control standard and the flexible control standard to determine a dynamic parameter control scheme; a control response data reading module is used to perform program setting of a programmable controller based on the dynamic parameter control scheme, synchronously perform real-time control monitoring, and read control response data; a feedback control module is used to determine a multi-group of indicators for measuring quality standards, build a feedback verification unit in combination with a quality tolerance interval, perform runout error verification and feedback control of the control response data, wherein each quality indicator and mapping parameter have an associated identifier; a closed-loop vector control module is used to assist the adaptive control module and the feedback verification unit in performing closed-loop vector control of the electric spindle cutting torque.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages: Through the control requirements of the whole machining cycle of the interactive pre-cutting task, the rigid control standard and the flexible control standard with the same frequency association are divided and determined; the basic parameter control characteristics of the torque control related parts and the main and auxiliary coordination characteristics of the joint system are determined, the correlation analysis of the working condition coordination is carried out, and the coordination coupling function is determined, and the coordination coupling function includes the parameter control coordination dimension and the system coordination dimension; the adaptive control module based on the coordination coupling function is supervised and trained, and the parameter control decision analysis is carried out in combination with the rigid control standard and the flexible control standard to determine the dynamic parameter control scheme; based on the dynamic parameter control scheme, the programmable controller is set, and real-time control monitoring is carried out synchronously, and the control response data is read; the indicator multi-group for measuring the quality standard is determined, and a feedback verification unit is built in combination with the quality tolerance interval, and the runout error verification and cutting torque feedback regulation are carried out on the control response data, wherein each quality indicator and the mapping parameter have an association mark; the adaptive control module and the feedback verification unit are assisted to carry out the closed-loop vector control of the electric spindle cutting torque. In other words, by decomposing the control requirements and analyzing the coupling correlation between the control parameters and the system, and taking the sequential conversion from the motor to the tool as the benchmark, and conducting decision analysis based on the sequential control conversion of the torque control, the refinement of the cutting torque analysis can be improved; at the same time, combining with the programmable controller for real-time global control can improve the automation, intelligence and comprehensiveness of the control; further building a feedback verification unit for multi-dimensional feedback regulation can realize closed-loop vector control of the cutting torque and improve the expected fit of the actual control of the cutting torque; thereby achieving the technical effect of improving the accuracy, efficiency and stability of cutting torque control.

[0009] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0011] Figure 1 A schematic diagram of a flow chart of an electric spindle cutting torque adaptive control method for the present application; Figure 2 A schematic diagram of a flow chart for determining a rigid control standard and a flexible control standard in an electric spindle cutting torque adaptive control method of the present application; Figure 3 This is a schematic diagram of the structure of an electric spindle cutting torque adaptive control system for the present application.

[0012] Description of reference numerals: Control standard establishing module 11, collaborative coupling function determining module 12, dynamic parameter control scheme determining module 13, control response data reading module 14, feedback regulation module 15, closed-loop vector control module 16. DETAILED DESCRIPTION

[0013] The present application provides an adaptive control method and system for cutting torque of an electric spindle, which solves the technical problem that the existing electric spindle cutting torque control method has poor precision in cutting torque analysis, which makes it impossible to carry out targeted and precise control of cutting torque, resulting in poor precision, efficiency and stability of cutting torque control. The precision of cutting torque analysis of the electric spindle, as well as the globality and automation of torque control, can be improved, thereby realizing closed-loop vector control of cutting torque, improving the expected fit of torque control, and achieving the technical effect of improving the precision, efficiency and stability of cutting torque control.

[0014] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0015] Embodiment 1 Please see attached Figure 1 The present application provides an electric spindle cutting torque adaptive control method, wherein the method is applied to an electric spindle cutting torque adaptive control system, and the method specifically comprises the following steps: Step 1: The control requirements of the whole machining cycle of the interactive pre-cutting task are divided and determined to establish rigid control standards and flexible control standards with the same frequency association; Specifically, cutting torque is an important parameter in cutting processing. The size of cutting torque directly affects the processing quality and efficiency. When the cutting torque is too large, it may cause tool wear, breakage, or even damage the equipment; while when the cutting torque is too small, it may reduce the processing efficiency. Therefore, in the cutting process, it is necessary to select the appropriate cutting torque according to different cutting conditions and requirements.

[0016] First, the control requirements of the entire machining cycle of the interactive pre-cutting task, the pre-cutting task refers to the operation of using a cutting tool to remove excess material on the workpiece to obtain the required geometric shape, size and surface quality, which can be set according to actual conditions; the control requirements of the entire machining cycle include control requirements under multiple machining nodes, such as: rough machining node, semi-finishing node, finishing node, etc. The control requirements are control quality standards and can be set according to the cutting machining tasks.

[0017] The control requirements of the entire processing cycle are divided according to the processing nodes, and the node control requirements corresponding to each processing node are determined. The node control requirements are further analyzed for rigid control and flexible control, where rigid control refers to fixed control requirements that cannot be flexibly adjusted, and flexible control refers to control requirements that can be flexibly adjusted and changed. Rigid control standards and flexible control standards with the same frequency association corresponding to multiple processing nodes are obtained, where each processing node corresponds to a rigid control standard and a flexible control standard with the same frequency association. By performing rigid control demand analysis and flexible control demand analysis on processing nodes, the parameter control decision analysis of torque control can be carried out in the next step, and the refinement of the parameter control decision analysis can be improved.

[0018] Step 2: Determine the basic parameter control characteristics of the torque control related parts and the main and auxiliary coordination characteristics of the joint system, perform correlation analysis of working condition coordination, and determine the coordination coupling function, which includes the parameter control coordination dimension and the system coordination dimension; Specifically, the torque control related parts of the electric spindle are obtained, and the torque control related parts refer to the parts in the electric spindle that are associated with torque control, including motors, transmission devices, spindles, bearings and tools. The basic parameter control characteristics of the torque control related parts are further determined, and the basic parameter control characteristics refer to the operation control parameters of the torque control related parts. The combined system includes an electronic control system, a feed system and a cooling system, and the main and auxiliary synergistic characteristics of the combined system are further determined. Then, according to the basic parameter control characteristics and the main and auxiliary synergistic characteristics, the coupling correlation analysis between the parameter control and the system is performed to determine the synergistic coupling parameters, wherein the synergistic coupling function includes the parameter control synergistic dimension and the system synergistic dimension, wherein the parameter control synergistic dimension is the synergy in parameter control and adjustment, which is mainly to accurately control and adjust these parameters to ensure that the synergy between them can achieve the maximum effect; the system synergistic dimension refers to the coordination and integration between the system structure and function.

[0019] Step 3: supervise the training of the adaptive control module based on the collaborative coupling function, combine the rigid control standard and the flexible control standard to perform parameter control decision analysis, and determine the dynamic parameter control scheme; Specifically, an adaptive control module is constructed based on the collaborative coupling function. The adaptive control module is a neural network model constructed based on a feedforward neural network and can be iteratively optimized. It is used to intelligently generate a cutting torque control scheme. The input data of the adaptive control module are the rigid control standard and the flexible control standard corresponding to the processing node, and the output data are the cutting torque control scheme of the processing node. Further, multiple sample training data are obtained to perform supervised training on the adaptive control module to obtain an adaptive control module that meets the convergence constraints.

[0020] Then the rigid control standard and the flexible control standard are input into the adaptive control module for parameter control decision analysis, and a dynamic parameter control scheme is output, wherein each processing node corresponds to a parameter control scheme. By constructing an adaptive control module based on a collaborative coupling function and a feedforward neural network, the intelligence of the parameter control scheme generation can be improved, and the efficiency and accuracy of the parameter control scheme can be improved.

[0021] Step 4: Based on the dynamic parameter control scheme, program the programmable controller, perform real-time control monitoring simultaneously, and read the control response data; Specifically, the dynamic parameter control scheme is input into a programmable controller for program setting, wherein the programmable controller is an electronic system for digital computing operations, designed for use in industrial environments, which uses a programmable memory to store programs, execute user-oriented instructions such as logical operations, sequential control, timing, counting and arithmetic operations, and control various types of machinery or production processes through digital or analog input / output.

[0022] Then, based on the programmable controller, real-time control monitoring of the electric spindle cutting torque control process is synchronously performed to obtain control response data, which is the actual control data in the cutting torque control process. By using the programmable controller to perform comprehensive actual monitoring and control of the electric spindle cutting torque control process, the automation and globality of the cutting torque control in the entire machining cycle can be improved, providing support for realizing closed-loop vector control of the cutting torque.

[0023] Step 5: Determine a multi-element group of indicators for measuring quality standards, build a feedback verification unit in combination with the quality tolerance interval, perform runout error verification and feedback control of cutting torque on the control response data, wherein each quality indicator and mapping parameter have an associated identifier; Specifically, first, determine the indicator tuple for measuring the quality standard, and the indicator tuple is a quality indicator of multiple dimensions, including cutting processing accuracy, processing stability, etc. It can be set according to actual conditions. A feedback verification unit is built based on the indicator tuple and the quality tolerance interval, wherein each processing node corresponds to a quality tolerance interval, and the quality tolerance interval is set based on the control tolerance of the assembly quality and the node-shared quality. The control response data is further subjected to the feedback verification unit for runout error verification and feedback control of the cutting torque, wherein each quality indicator is associated with a mapping parameter, that is, each quality indicator will be affected by one or more parameters; wherein the runout error verification is used to detect and calibrate whether the workpiece coincides with the spindle axis during the processing process, and whether the runout offset occurs. The runout error will affect the processing accuracy and surface quality of the workpiece, thereby affecting production efficiency and product quality.

[0024] By constructing a feedback verification unit for multi-dimensional feedback regulation, the expected fit of the actual control of the cutting torque can be improved, where the expected fit refers to the consistency between the actual control effect and the expected control target. The higher the expected fit, the more accurately the control strategy can achieve the expected control target. The smaller the deviation between the actual output and the expected output, the better the control quality, thereby achieving the effect of improving the cutting torque control accuracy, efficiency and stability.

[0025] Step six: assisting the adaptive control module and the feedback verification unit to perform closed-loop vector control of the electric spindle cutting torque.

[0026] Specifically, based on the adaptive control module and the feedback verification unit, closed-loop vector control of the electric spindle cutting torque is finally realized. The closed-loop vector control refers to the precise control of the electric spindle cutting torque through real-time monitoring and feedback control of the cutting torque parameters.

[0027] The electric spindle cutting torque adaptive control method is applied to an electric spindle cutting torque adaptive control system, which can solve the technical problems that the existing electric spindle cutting torque control method has poor precision in cutting torque analysis, resulting in the inability to perform targeted and accurate control of the cutting torque, resulting in poor accuracy, efficiency and stability of cutting torque control. First, the control requirements of the whole machining cycle of the interactive pre-cutting task are divided and determined to establish rigid control standards and flexible control standards with the same frequency association; then, the basic parameter control characteristics of the torque control related parts and the main and auxiliary collaborative characteristics of the joint system are determined, and the correlation analysis of the working condition coordination is carried out to determine the collaborative coupling function, and the collaborative coupling function includes the parameter control collaborative dimension and the system collaborative dimension; then, the adaptive control module based on the collaborative coupling function is supervised and trained, and the parameter control decision analysis is carried out in combination with the rigid control standard and the flexible control standard to determine the dynamic parameter control scheme; next, based on the dynamic parameter control scheme, the programmable controller is set, and real-time control monitoring is carried out synchronously, and the control response data is read; in addition, the multi-tuple of indicators for measuring the quality standard is determined, and a feedback verification unit is built in combination with the quality tolerance interval, and the runout error verification and cutting torque feedback regulation are carried out on the control response data, wherein each quality indicator and the mapping parameter have an associated identifier; finally, the adaptive control module and the feedback verification unit are assisted to perform closed-loop vector control of the electric spindle cutting torque. By decomposing the control requirements and analyzing the coupling correlation between the control parameters and the system, and taking the sequential conversion from motor to tool as the benchmark, and conducting decision analysis in conjunction with the sequential control conversion of torque control, the refinement of the cutting torque analysis can be improved; at the same time, combining with a programmable controller for real-time global control can improve the automation, intelligence and comprehensiveness of the control; further building a feedback verification unit for multi-dimensional feedback regulation can achieve closed-loop vector control of the cutting torque and improve the expected fit of the actual control of the cutting torque; thereby achieving the technical effect of improving the accuracy, efficiency and stability of cutting torque control.

[0028] Further, as attached Figure 2 As shown, step one of this application includes: Setting key control nodes of the entire machining cycle based on the pre-cutting task, wherein the key control nodes are marked with control levels; Based on the key control nodes, the control requirements are decomposed and matched to determine a node control standard, wherein the node control standard has a sequential identifier; Based on universal processing and task characteristics, the node control standard is separated to determine the rigid control standard and the flexible control standard.

[0029] Specifically, first, the key control nodes of the entire machining cycle based on the pre-cutting task are set, and then the control levels of the key control nodes are marked according to the control requirements corresponding to the key control nodes. For example, the control requirements for cutting corners and edge cutting are different. The higher the control requirement, the higher the control level of the corresponding key control node. Technical personnel in this field can set the control level of the key control nodes according to the actual control requirements.

[0030] Then, based on the key control nodes, the control requirements of the entire processing cycle are decomposed and matched, that is, the node control standard corresponding to each key control node is determined, and the node control standard has a sequential identifier, which is the processing order of the key control node in the entire processing cycle. Further, based on universal processing and task characteristics, the node control standard is dissociated, that is, in order to integrate conventional processing standards and task characteristic standards, the node control standard is refined and split, so as to carry out refined control analysis and verification traceability, thereby improving the precision of control, and obtaining the rigid control standard and the flexible control standard, wherein the rigid control standard is a fixed control standard that cannot be flexibly adjusted, and the flexible control refers to a control standard that can be flexibly adjusted and changed, and can be set based on actual conditions.

[0031] Further, step 2 of this application includes: The torque control related parts include a motor, a transmission device, a spindle, a bearing and a tool; The combined system includes an electric control system, a feeding system and a cooling system; Based on the transfer conversion relationship, performing unit conversion analysis of parameters on the torque control related components to determine a first coordination relationship; Based on the system response association, performing response coordination analysis on the joint system to determine a second coordination relationship; The first cooperative relationship and the second cooperative relationship are fitted to construct the cooperative coupling function.

[0032] Specifically, the torque control related parts include motors, transmission devices, spindles, bearings and tools, and the combined system includes an electronic control system, a feed system and a cooling system, wherein the electronic control system mainly involves the power drive of the electric spindle, the control of the cutting process and the optimization of the overall performance; the feed system is responsible for controlling the motion trajectory of the workpiece during the processing and realizing the feed motion during the processing, such as tool feeding; the cooling system is used to dissipate heat in the working parts during the cutting process to ensure the normal operation of the electric spindle and improve the processing accuracy.

[0033] Based on the transfer conversion relationship, the transfer conversion relationship refers to the progressive control relationship of the torque control related parts in the cutting process, such as: motor power, speed regulation, providing rotational torque, driving a series of progressive control processes of spindle cutting control, etc., the unit conversion analysis of the parameters of the torque control related parts is performed, wherein the unit conversion analysis refers to calculating the association relationship between adjacent components in the transfer conversion relationship, for example: if the motor power increases by 10, how should the adjacent speeds be adjusted, etc., to determine the first collaborative relationship.

[0034] Based on the system response association, the response coordination analysis of the joint system is performed. For example, when the torque is a certain large value, the cutting temperature is high, which is easy to cause tool damage or affect the quality. At this time, the cooling system needs to be activated and cooling management needs to be performed, and the corresponding cooling parameter control standards need to be determined to obtain the second coordination relationship. Finally, the first coordination relationship and the second coordination relationship are fitted, that is, the coupling association analysis of the parameter control and the system is performed, and the mapping relationship is determined to build the coordination coupling function.

[0035] Further, step five of this application includes: Identify multivariate indicators as coordinate axes and build a multivariate coordinate system; Identify the rigid control standard and the flexible control standard, determine the control fault tolerance based on the assembly quality and the node-shared quality, and determine the quality tolerance range; Based on the indicator multi-group and the quality tolerance interval, distribution positioning is performed in the multi-element coordinate system to determine a multi-element verification space; The feedback verification unit is constructed based on the multivariate verification space, and sample verification records are obtained to perform training detection on the feedback verification unit based on convergence conditions.

[0036] Specifically, first, determine the multivariate indicators, and use the multivariate indicators as coordinate axes to build a multivariate coordinate system; then identify the rigid control standard and the flexible control standard, and determine the control tolerance based on the assembly quality and the node-shared quality, that is, identify the proportion of the influence of the node-shared quality on the assembly quality, wherein the higher the rigid control standard and the flexible control standard, the greater the node-shared quality, and the smaller the corresponding control tolerance, that is, the smaller the range of control deviation allowed, and further set the quality tolerance interval according to the control tolerance, wherein the control tolerance is proportional to the quality tolerance interval.

[0037] Then, based on the multivariate group of indicators and the quality tolerance interval, they are distributed in the multivariate coordinate system to obtain a multivariate verification space, which includes multiple indicators and corresponding quality tolerance intervals. The feedback verification unit is further constructed based on the multivariate verification space. The feedback verification unit is a neural network model constructed based on the BP neural network, which is used to trace the abnormal state of torque control during the cutting process. The input data of the feedback verification unit is the abnormal indicator value, and the output data is the abnormal indicator. Further obtain a sample verification record, the sample verification record includes the sample abnormal indicator value and the corresponding sample traceability indicator, and then supervise the feedback verification unit according to the sample verification record until a feedback verification unit that meets the preset convergence condition is obtained. The preset convergence condition is the output accuracy indicator, which can be set by technicians in this field according to the actual verification accuracy requirements.

[0038] Further, the control response data is subjected to a deflection error check, and step five of the present application includes: Identifying the control response data and extracting a multi-tuple index value, the control response data comprising dynamic data of a complete conversion control cycle; Perform positive serialization integration on the multi-tuple index values, transmit them to the feedback verification unit, and trace and locate the over-limit deviation index; Mapping parameters of the over-limit deviation index are read, and the error source is determined by tracing the source based on the external influence; Based on the error source, feedback control of the electric spindle cutting torque is performed.

[0039] Specifically, the control response data is identified based on the indicator tuple, and a tuple indicator value is obtained based on the identification result, wherein the control response data includes dynamic data of the complete conversion control cycle, that is, monitoring data within the entire processing cycle. Then, the tuple indicator values ​​are positively serialized and integrated, wherein positive serialization and integration refers to arranging them from the first to the last in the order of monitoring nodes to obtain a tuple indicator value sequence, and the tuple indicator value sequence is further transmitted to the feedback verification unit for analysis, and the deviation index is determined and traced back. For example, a set of control parameters may be a control abnormality of a certain item in the process of motor-tool conversion, and at the same time, it will cause the subsequent control deviation of the item, then trace back and locate the item with the initial abnormality; obtain the over-limit deviation index.

[0040] Further, the mapping parameters of the over-limit deviation index are read, that is, the abnormal deviation parameters of the over-limit deviation index are determined, and at the same time, the exogenous influence analysis of the over-limit deviation index is performed, that is, the influence of external factors on the index deviation state is analyzed to determine the error source, which is the error caused by the internal parameter deviation or the error caused by the influence of external factors. Feedback control is performed on the electric spindle cutting torque according to the error source.

[0041] Further, based on the error source, feedback control of the electric spindle cutting torque is performed, and the present application also includes the following steps: Performing a generalization degree analysis on the error source, and generating a control constraint condition if it is a generalized error source that meets a frequency threshold; Based on the control constraint condition, performing incremental learning on the adaptive control module; If it is a non-generalized error source, identify the error processing part and generate a feedback correction scheme; The feedback correction scheme is inserted into the dynamic parameter control scheme.

[0042] Specifically, first, the generalization degree analysis of the error source is performed, and the generalization degree analysis refers to statistically analyzing the occurrence frequency of the error source to obtain the generalization number of the error source; the generalization number of the error source is further judged according to the frequency threshold, and the frequency threshold can be set by technicians in this field according to actual conditions. If the generalization number is greater than the frequency threshold, the error source is generalized and marked to obtain the generalized error source. Then, a control constraint analysis is performed based on the generalized error source to generate control constraint conditions, and the control constraint conditions refer to the parameter adjustment scheme to solve the generalized error source.

[0043] The basic idea of ​​incremental learning is to gradually optimize and expand the capabilities of the model based on the existing knowledge or model by continuously learning and accumulating new information or data to adapt to the ever-changing environment and needs. Its advantage is that it does not need to train the model from scratch every time, but can use the previous learning results to accelerate the acquisition of new knowledge, which can not only save computing resources but also improve learning efficiency. Then, based on the incremental learning principle, the adaptive control module is incrementally learned according to the control constraints to achieve the optimization adjustment of the adaptive control module. By analyzing the generalized error source to generate control constraints, and based on the incremental learning principle, the adaptive control module is incrementally learned according to the control constraints, the precision and accuracy of the output parameter control scheme of the adaptive control module can be further improved, and the training efficiency of the adaptive control module can be improved.

[0044] If the generalization times of the error source are less than or equal to the frequency threshold, the error processing part is identified, and a parameter control adjustment analysis is performed based on the error processing part to determine a feedback correction scheme, and the feedback correction scheme is further inserted into the dynamic parameter control scheme to complete the optimization adjustment of the dynamic parameter control scheme.

[0045] Furthermore, the feedback control of the electric spindle cutting torque may further include the following steps: Reading the control response data within a predetermined period, performing parameter control homology mapping, and determining a plurality of parameter control sequences, wherein each parameter control sequence corresponds to a time series dynamic value of the same parameter; Based on the multiple parameter control sequences, dynamic control verification of the cutting torque is performed to determine a dynamic verification index, wherein the dynamic verification index at least includes control stability and uniformity; The traceability is based on the influencing factors of the dynamic verification index to perform feedback control of the cutting torque.

[0046] Specifically, the control response data within a predetermined period is read. The predetermined period can be set by a technician in this field according to the actual situation, for example, the predetermined period is set to 10 days; and the control homology mapping is performed based on the control response data to obtain multiple control sequences, wherein each control sequence corresponds to the time series dynamic value of the same parameter, that is, each control sequence includes control parameters at multiple different time nodes. Further based on the multiple control sequences, the dynamic control verification of the cutting torque is performed, that is, the correlation between the control sequence and the dynamic verification index is identified, and whether the parameter change in the control sequence will affect the dynamic verification index is determined, and the dynamic verification index is determined, wherein the dynamic verification index at least includes control stability and uniformity, that is, the influence degree of parameter change on control stability and control uniformity is determined, and the control type that affects the dynamic verification index, that is, the influencing factor, is determined. Further, the influencing factors based on the dynamic verification index are traced back and analyzed, and the cutting torque is feedback-regulated according to the traceability results.

[0047] In summary, the electric spindle cutting torque adaptive control method provided by the present application has the following technical effects: 1. By decomposing the control requirements and analyzing the coupling correlation between the control parameters and the system, and taking the sequential conversion from the motor to the tool as the benchmark, the sequential control conversion of the torque control is combined for decision analysis, which can improve the refinement of the cutting torque analysis; at the same time, combined with the programmable controller for real-time global control, the automation, intelligence and comprehensiveness of the control can be improved; further building a feedback verification unit for multi-dimensional feedback regulation can realize closed-loop vector control of the cutting torque and improve the expected fit of the actual control of the cutting torque; thereby achieving the technical effect of improving the control accuracy, efficiency and stability of the cutting torque.

[0048] 2. By constructing an adaptive control module based on collaborative coupling functions and feedforward neural networks, the intelligence of the control scheme generation can be improved, and the efficiency and accuracy of the control scheme can be improved; by analyzing the generalized error source to generate control constraints, and based on the incremental learning principle, the adaptive control module is incrementally learned according to the control constraints, which can further improve the precision and accuracy of the control scheme output by the adaptive control module, and at the same time improve the training efficiency of the adaptive control module.

[0049] Embodiment 2 Based on the same inventive concept as the electric spindle cutting torque adaptive control method in the aforementioned embodiment, the present application also provides an electric spindle cutting torque adaptive control system, see the attached Figure 3 , the system comprising: A control standard establishing module 11, wherein the control standard establishing module 11 is used to control the full cycle of the processing of the interactive pre-cutting task, and to segment and determine the rigid control standard and the flexible control standard with the same frequency association; A collaborative coupling function determination module 12, which is used to determine the basic parameter control characteristics of the torque control related parts and the main and auxiliary collaborative characteristics of the joint system, perform correlation analysis on the working condition collaboration, and determine the collaborative coupling function, wherein the collaborative coupling function includes the parameter control collaborative dimension and the system collaborative dimension; A dynamic parameter control scheme determination module 13, which is used to supervise the training of the adaptive control module based on the collaborative coupling function, perform parameter control decision analysis in combination with the rigid control standard and the flexible control standard, and determine the dynamic parameter control scheme; A control response data reading module 14, which is used to perform program setting of the programmable controller based on the dynamic parameter control scheme, perform real-time control monitoring simultaneously, and read control response data; A feedback control module 15, wherein the feedback control module 15 is used to determine a multi-element group of indicators for measuring quality standards, and to build a feedback verification unit in combination with a quality tolerance interval, to perform runout error verification and feedback control of cutting torque on the control response data, wherein each quality indicator and mapping parameter has an associated identifier; The closed-loop vector control module 16 is used to assist the adaptive control module and the feedback verification unit in performing closed-loop vector control of the electric spindle cutting torque.

[0050] Furthermore, the control standard establishing module 11 in the system is also used for: Setting key control nodes of the entire machining cycle based on the pre-cutting task, wherein the key control nodes are marked with control levels; Based on the key control nodes, the control requirements are decomposed and matched to determine a node control standard, wherein the node control standard has a sequential identifier; Based on universal processing and task characteristics, the node control standard is separated to determine the rigid control standard and the flexible control standard.

[0051] Further, the collaborative coupling function determination module 12 in the system is also used for: The torque control related parts include a motor, a transmission device, a spindle, a bearing and a tool; The combined system includes an electric control system, a feeding system and a cooling system; Based on the transfer conversion relationship, performing unit conversion analysis of parameters on the torque control related components to determine a first coordination relationship; Based on the system response association, performing response coordination analysis on the joint system to determine a second coordination relationship; The first cooperative relationship and the second cooperative relationship are fitted to construct the cooperative coupling function.

[0052] Furthermore, the feedback control module 15 in the system is also used for: Identify multivariate indicators as coordinate axes and build a multivariate coordinate system; Identify the rigid control standard and the flexible control standard, determine the control fault tolerance based on the assembly quality and the node-shared quality, and determine the quality tolerance range; Based on the indicator multi-group and the quality tolerance interval, distribution positioning is performed in the multi-element coordinate system to determine a multi-element verification space; The feedback verification unit is constructed based on the multivariate verification space, and sample verification records are obtained to perform training detection on the feedback verification unit based on convergence conditions.

[0053] Furthermore, the feedback control module 15 in the system is also used for: Identifying the control response data and extracting a multi-tuple index value, the control response data comprising dynamic data of a complete conversion control cycle; Perform positive serialization integration on the multi-tuple index values, transmit them to the feedback verification unit, and trace and locate the over-limit deviation index; Mapping parameters of the over-limit deviation index are read, and the error source is determined by tracing the source based on the external influence; Based on the error source, feedback control of the electric spindle cutting torque is performed.

[0054] Furthermore, the feedback control module 15 in the system is also used for: Performing a generalization degree analysis on the error source, and generating a control constraint condition if it is a generalized error source that meets a frequency threshold; Based on the control constraint condition, performing incremental learning on the adaptive control module; If it is a non-generalized error source, identify the error processing part and generate a feedback correction scheme; The feedback correction scheme is inserted into the dynamic parameter control scheme.

[0055] Furthermore, the feedback control module 15 in the system is also used for: Reading the control response data within a predetermined period, performing parameter control homology mapping, and determining a plurality of parameter control sequences, wherein each parameter control sequence corresponds to a time series dynamic value of the same parameter; Based on the multiple parameter control sequences, dynamic control verification of the cutting torque is performed to determine a dynamic verification index, wherein the dynamic verification index at least includes control stability and uniformity; The traceability is based on the influencing factors of the dynamic verification index to perform feedback control of the cutting torque.

[0056] Each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The electric spindle cutting torque adaptive control method and specific examples in the aforementioned embodiment 1 are also applicable to an electric spindle cutting torque adaptive control system in this embodiment. Through the aforementioned detailed description of an electric spindle cutting torque adaptive control method, those skilled in the art can clearly understand an electric spindle cutting torque adaptive control system in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0057] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0058] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. The electric spindle cutting torque adaptive control method is characterized by: The method comprises: The control requirements of the whole machining cycle of the interactive pre-cutting task are divided and determined to establish rigid control standards and flexible control standards with the same frequency association; Determine the basic parameter control characteristics of the torque control related parts and the main and auxiliary coordination characteristics of the joint system, perform correlation analysis on the working condition coordination, and determine the coordination coupling function, wherein the coordination coupling function includes the parameter control coordination dimension and the system coordination dimension; Supervise the training of the adaptive control module based on the collaborative coupling function, perform parameter control decision analysis in combination with the rigid control standard and the flexible control standard, and determine a dynamic parameter control scheme; Based on the dynamic parameter control scheme, program setting of the programmable controller is performed, real-time control monitoring is performed synchronously, and control response data is read; Determine a multi-element group of indicators for measuring quality standards, build a feedback verification unit in combination with the quality tolerance interval, perform runout error verification and feedback control of cutting torque on the control response data, wherein each quality indicator and mapping parameter have an associated identifier; Assisting the adaptive control module and the feedback verification unit to perform closed-loop vector control of the electric spindle cutting torque.

2. The method according to claim 1, characterized in that The method further comprises: Setting key control nodes of the entire machining cycle based on the pre-cutting task, wherein the key control nodes are marked with control levels; Based on the key control nodes, the control requirements are decomposed and matched to determine a node control standard, wherein the node control standard has a sequential identifier; Based on universal processing and task characteristics, the node control standard is separated to determine the rigid control standard and the flexible control standard.

3. The method according to claim 1, characterized in that The method further comprises: The torque control related parts include a motor, a transmission device, a spindle, a bearing and a tool; The combined system includes an electric control system, a feeding system and a cooling system; Based on the transfer conversion relationship, performing unit conversion analysis of parameters on the torque control related components to determine a first coordination relationship; Based on the system response association, performing response coordination analysis on the joint system to determine a second coordination relationship; The first cooperative relationship and the second cooperative relationship are fitted to construct the cooperative coupling function.

4. The method according to claim 1, characterized in that The method further comprises: Identify multivariate indicators as coordinate axes and build a multivariate coordinate system; Identify the rigid control standard and the flexible control standard, determine the control fault tolerance based on the assembly quality and the node-shared quality, and determine the quality tolerance range; Based on the indicator multi-group and the quality tolerance interval, distribution positioning is performed in the multi-element coordinate system to determine a multi-element verification space; The feedback verification unit is constructed based on the multivariate verification space, and sample verification records are obtained to perform training detection on the feedback verification unit based on convergence conditions.

5. The method according to claim 1, characterized in that Performing a yaw error check on the control response data, the method further comprising: Identifying the control response data and extracting a multi-tuple index value, the control response data comprising dynamic data of a complete conversion control cycle; Perform positive serialization integration on the multi-tuple index values, transmit them to the feedback verification unit, and trace and locate the over-limit deviation index; Mapping parameters of the over-limit deviation index are read, and the error source is determined by tracing the source based on the external influence; Based on the error source, feedback control of the electric spindle cutting torque is performed.

6. The method according to claim 5, characterized in that Based on the error source, feedback control of the electric spindle cutting torque is performed, and the method further includes: Performing a generalization degree analysis on the error source, and generating a control constraint condition if it is a generalized error source that meets a frequency threshold; Based on the control constraint condition, performing incremental learning on the adaptive control module; If it is a non-generalized error source, identify the error processing part and generate a feedback correction scheme; The feedback correction scheme is inserted into the dynamic parameter control scheme.

7. The method according to claim 5, characterized in that The method for performing feedback control of the electric spindle cutting torque also includes: Reading the control response data within a predetermined period, performing parameter control homology mapping, and determining a plurality of parameter control sequences, wherein each parameter control sequence corresponds to a timing dynamic value of the same parameter; Based on the multiple parameter control sequences, dynamic control verification of the cutting torque is performed to determine a dynamic verification index, wherein the dynamic verification index at least includes control stability and uniformity; The traceability is based on the influencing factors of the dynamic verification index to perform feedback control of the cutting torque.

8. The electric spindle cutting torque adaptive control system is characterized by: For implementing the steps of the method according to any one of claims 1 to 7, the system comprises: A control standard establishment module, wherein the control standard establishment module is used for the control requirements of the whole processing cycle of the interactive pre-cutting task, and for segmenting and determining the establishment of rigid control standards and flexible control standards with the same frequency association; A collaborative coupling function determination module, which is used to determine the basic parameter control characteristics of the torque control related parts and the main and auxiliary collaborative characteristics of the joint system, perform correlation analysis on the working condition coordination, and determine the collaborative coupling function, wherein the collaborative coupling function includes the parameter control collaborative dimension and the system collaborative dimension; A dynamic parameter control scheme determination module, which is used to supervise the training of the adaptive control module based on the collaborative coupling function, perform parameter control decision analysis in combination with the rigid control standard and the flexible control standard, and determine the dynamic parameter control scheme; A control response data reading module, which is used to perform program setting of the programmable controller based on the dynamic parameter control scheme, synchronously perform real-time control monitoring, and read control response data; A feedback control module, wherein the feedback control module is used to determine a multi-element group of indicators for measuring quality standards, and to build a feedback verification unit in combination with a quality tolerance interval to perform runout error verification and feedback control of cutting torque on the control response data, wherein each quality indicator and a mapping parameter have an associated identifier; A closed-loop vector control module is used to assist the adaptive control module and the feedback verification unit in performing closed-loop vector control of the electric spindle cutting torque.

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