A method, device and equipment for process event-based numerical control tool management and control

Abstract

The application discloses a kind of process event-based numerical control cutter management and control method, device and equipment.The method includes according to target machining task target machining program received by target numerical control machine tool, and cutter number of target numerical control cutter, determine target machining process data and target process event flow;According to process event flow, cutting force time series data of target numerical control cutter is collected;According to target machining process data and cutter number, determine target machining process type;When identifying target machining task completion, according to target machining process type, target cutter image is collected;According to target cutting force time series data, target cutter image, target machining process data and target machining process type, predicted cutter life of target numerical control cutter is obtained by prediction, and target numerical control cutter is controlled according to predicted cutter life.The above scheme is helpful to improve the accuracy and reliability of tool life prediction, realizes the adaptive management and control of numerical control cutter.

Description

Technical Field

[0001] This application relates to the field of CNC machining technology, and more particularly to the field of CNC tool management technology, specifically to a CNC tool control method, apparatus, and equipment based on process events. Background Technology

[0002] In CNC machining, the wear condition of the cutting tool directly affects the machining accuracy, workpiece surface quality, and machining stability. Therefore, online monitoring and life prediction of the cutting tool has become an important research direction in the field of intelligent manufacturing.

[0003] Existing technologies typically collect tool operating status data using devices such as cutting force sensors and industrial cameras, and combine this data with algorithm models to achieve tool wear identification, life prediction, or tool change alarms. However, most existing solutions employ continuous or fixed-period data collection methods, lacking a direct correlation between data collection and specific machining processes, which can easily lead to insufficient consistency in the timing of multi-source data. Furthermore, most existing systems remain at the level of status monitoring or alarms, making it difficult to achieve intelligent adaptive tool control oriented towards the machining process. Summary of the Invention

[0004] This application provides a method, apparatus, and equipment for CNC tool management based on process events, in order to improve the accuracy and reliability of tool life prediction and realize adaptive management of CNC tools.

[0005] According to one aspect of this application, a CNC tool control method based on process events is provided, the method comprising: In response to the start command of the target machining task, the target machining program of the target machining task received by the target CNC machine tool and the tool number of the target CNC tool in the target CNC machine tool are used to determine the target machining process data and target process event flow of the target CNC tool. Based on the process event flow, the cutting force signal of the target CNC tool when performing the target machining task is collected to obtain the target cutting force timing data of the target CNC tool; Based on the target machining process data and the tool number, the target machining process type of the target machining task is determined; When the completion of the target machining task is detected, the target CNC tool is image acquired according to the target machining process type to obtain the target tool image of the target CNC tool; Based on the target cutting force timing data, the target tool image, the target machining process data, and the target machining process type, the tool life of the target CNC tool is predicted to obtain the predicted tool life of the target CNC tool, and the target CNC tool is controlled according to the predicted tool life.

[0006] According to another aspect of this application, a CNC tool control device based on process events is provided, the device comprising: The program parsing module is used to respond to the start command of the target machining task, and determine the target machining process data and target process event flow of the target CNC tool according to the target machining program of the target machining task received by the target CNC machine tool and the tool number of the target CNC tool in the target CNC machine tool; The data acquisition module is used to acquire the cutting force signal of the target CNC tool when performing the target machining task according to the process event flow, and obtain the target cutting force timing data of the target CNC tool; The type determination module is used to determine the target machining process type of the target machining task based on the target machining process data and the tool number. The image acquisition module is used to acquire an image of the target CNC tool according to the target machining process type when the target machining task is identified as completed, so as to obtain a target tool image of the target CNC tool. The tool life prediction module is used to predict the tool life of the target CNC tool based on the target cutting force timing data, the target tool image, the target machining process data, and the target machining process type, to obtain the predicted tool life of the target CNC tool, and to control the target CNC tool based on the predicted tool life.

[0007] According to another aspect of this application, an electronic device is provided, the electronic device comprising: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement any of the CNC tool control methods based on process events provided in the embodiments of this application.

[0008] According to another aspect of this application, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements any of the CNC tool control methods based on process events provided in the embodiments of this application.

[0009] According to another aspect of this application, a computer program product is provided, including a computer program that, when executed by a processor, implements any of the CNC tool control methods based on process events provided in the embodiments of this application.

[0010] This application, in response to the start command of the target machining task, determines the target machining process data and target process event flow of the target CNC tool based on the target machining program received by the target CNC machine tool and the tool number of the target CNC tool in the target CNC machine tool; according to the process event flow, it collects the cutting force signal of the target CNC tool when executing the target machining task to obtain the target cutting force timing data of the target CNC tool; based on the target machining process data and tool number, it determines the target machining process type of the target machining task; when the completion of the target machining task is detected, it acquires an image of the target CNC tool according to the target machining process type to obtain the target tool image of the target CNC tool; based on the target cutting force timing data, target tool image, target machining process data, and target machining process type, it predicts the tool life of the target CNC tool to obtain the predicted tool life of the target CNC tool, and controls the target CNC tool according to the predicted tool life. The above technical solution adaptively acquires data and images based on the process event flow and process type of the machining process, and further predicts the tool life to control the tool. This can effectively improve the accuracy and reliability of tool life prediction and realize adaptive control of CNC tools. Attached Figure Description

[0011] Figure 1 This is a flowchart of a CNC tool control method based on process events, according to Embodiment 1 of this application; Figure 2 This is a flowchart of a CNC tool control method based on process events, provided in Embodiment 2 of this application; Figure 3 This is a schematic diagram of a CNC tool control device based on process events, provided in Embodiment 3 of this application; Figure 4 This is a schematic diagram of the structure of an electronic device that implements the CNC tool control method based on process events according to Embodiment 4 of this application. Detailed Implementation

[0012] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0013] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0014] Furthermore, it should be noted that the collection, storage, use, processing, transmission, provision, and disclosure of relevant data such as target machining procedures and tool numbers involved in the technical solution of this application all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0015] Example 1 Figure 1 This is a flowchart of a CNC tool control method based on process events, according to Embodiment 1 of this application. This embodiment is applicable to situations involving CNC tool life prediction and tool control in CNC machine tools. It can be executed by a process event-based CNC tool control device, which can be implemented in hardware and / or software and can be configured in a computer device, such as a server. Figure 1 As shown, the method includes: S110. In response to the start command of the target machining task, determine the target machining process data and target process event flow of the target CNC tool based on the target machining program of the target machining task received by the target CNC machine tool and the tool number of the target CNC tool in the target CNC machine tool.

[0016] The target machining task refers to the specific machining work to be completed, including information such as the geometry, dimensions, material, and required machining steps of the part to be machined. The start command is the instruction or signal that triggers the CNC machine tool to begin executing a specific machining task. The target CNC machine tool is the CNC machine tool designated to perform this machining task, equipped with functions such as automated coordinate control and tool changing. The target machining program is the sequence of instructions received by the target CNC machine tool and used to drive the machine tool's movement, describing machining details such as tool path, feed rate, and spindle speed. The target CNC tool refers to the cutting tool (such as a milling cutter, turning tool, drill bit, etc.) mounted on the target CNC machine tool and used to complete this machining task; its model, size, and material have been pre-selected. The tool number is the code used to uniquely identify the target CNC tool. The target machining process data refers to... The target process event flow is an ordered list describing a series of process events (such as tool changing, spindle start / stop, coolant on / off, measurement point triggering, etc.) occurring in chronological order during the execution of the target machining task, used for monitoring, fault diagnosis, or process optimization.

[0017] Optionally, semantic parsing is performed on the target machining program of the target machining task received by the target CNC machine tool to obtain the machining preparation code, machining auxiliary code, machining process segment and tool coordinate change data of the target machining task; the target machining process data of the target CNC tool is determined based on the machining preparation code and machining auxiliary code; the target process event flow of the target CNC tool is determined based on the machining preparation code, machining process segment and tool coordinate change data.

[0018] Among them, machining preparation code refers to the instruction code used to specify the machine tool's motion mode, coordinate system rules, interpolation logic, tool compensation, and other cutting trajectory and motion logic directly related to it. Machining auxiliary code refers to the instruction code used to control the machine tool's auxiliary actions, on / off states, and program flow. Machining process segment refers to the program segment describing the actual cutting process, including instructions directly related to material removal such as feed movement, depth of cut, feed rate, and spindle speed. Tool coordinate change data refers to the record of the changes in the tool's position and orientation relative to the workpiece or machine tool coordinate system over time during machining.

[0019] S120. Based on the process event flow, the cutting force signal of the target CNC tool when performing the target machining task is collected to obtain the target cutting force timing data of the target CNC tool.

[0020] Among them, the cutting force signal refers to the measurable electrical signal output by the force sensor after the cutting force (usually including the main cutting force, feed force, and back force components) acting on the tool when the CNC tool cuts the workpiece material. It can directly reflect the load state and material removal difficulty of the cutting process. The target cutting force time series data refers to the set of cutting force data collected according to the time base of the process event flow, corresponding to the entire process of the target CNC tool executing the target machining task. With the timestamp as the core dimension, it records the numerical value and fluctuation characteristics of the cutting force at different machining stages.

[0021] Optionally, based on the event type of each candidate process event in the process event flow, a target process event is determined from each candidate process event; wherein, the event type includes at least cutting start event, cutting end event, machining stage event, photographing event, and tool change event; based on the event type of the target process event, the target data acquisition method of the target CNC tool is determined; when the target process event is triggered during the execution of the target machining task by the target CNC tool, the cutting force signal of the target CNC tool is acquired according to the target data acquisition method to obtain the target cutting force timing data of the target CNC tool.

[0022] Among them, candidate process events refer to the set of all process events in the process event stream that have not yet been screened and are considered as candidate sources, including all process nodes that may be included in the data acquisition triggering logic. Event type refers to the classification identifier of process events, used to distinguish the attributes of different process actions and match the corresponding acquisition rules. Target process events refer to the set of core process events selected from candidate process events according to acquisition requirements, used to trigger the acquisition of cutting force signals. Cutting start event refers to the process node where the target CNC tool formally cuts into the workpiece material and the cutting force rises from 0, marking the start of the effective cutting stage, and can be used as the starting trigger condition for cutting process data acquisition. Cutting end event refers to the process node where the target CNC tool completes the current cutting operation, exits the workpiece material, and the cutting force falls back to 0, marking the termination of the current effective cutting stage, and can be used as the termination trigger condition for cutting process data acquisition. Machining stage events refer to the nodes corresponding to actions that change the process state during the cutting process, such as roughing / finishing stage switching, feed rate / depth of cut adjustment, spindle speed shifting, etc., used to distinguish the data acquisition logic under different machining conditions. A photographic event refers to a process node that triggers in-situ visual inspection, workpiece dimension measurement, or other photographic actions during machining. A tool change event refers to a process node where the target CNC machine tool completes a tool change and the target CNC tool is in the cutting position, marking the official start of the corresponding tool's participation in the machining task. The target data acquisition method refers to the cutting force signal acquisition strategy matched to the event type of the target process event. It includes parameters such as triggering conditions, sampling frequency, acquisition duration, storage rules, and associated acquisition channels. Different acquisition strategies can be matched to different event types.

[0023] S130. Based on the target machining process data and tool number, determine the target machining process type for the target machining task.

[0024] The target machining process type refers to the process classification result of this machining. Based on the process attributes of the target machining process data and the tool type corresponding to the tool number, this machining is classified into a preset process classification system, which may include at least one of roughing, finishing, grooving, threading, interrupted cutting, and high-temperature alloy machining.

[0025] S140. When the target machining task is identified as completed, the target CNC tool is image acquired according to the target machining process type to obtain the target tool image.

[0026] Among them, the target tool image refers to a tool-specific image acquired after machining is completed, which is associated with the tool number, target machining task number, target machining process type, and acquisition timestamp.

[0027] For example, after the machining is completed or the preset machining stage is completed, the tool image is automatically acquired at different positions, angles and magnifications according to the corresponding tool number and process type to obtain the target tool image of the target CNC tool.

[0028] S150. Based on the target cutting force timing data, target tool image, target machining process data, and target machining process type, predict the tool life of the target CNC tool to obtain the predicted tool life of the target CNC tool, and control the target CNC tool according to the predicted tool life.

[0029] Among them, the predicted tool life refers to the numerical estimate of the remaining reliable machining time or remaining cutting length of the target CNC tool, which is the result of the fusion input of multi-source heterogeneous data (target cutting force time series data + target tool image + target machining process data + target machining process type) and the output of a life prediction model based on physical mechanism or deep learning.

[0030] Optionally, if the predicted tool life is greater than the preset life threshold, the predicted life error of the target CNC tool is determined based on the predicted tool life and theoretical remaining life of the target CNC tool; a closed-loop control algorithm is used to determine the machining adjustment parameters of the target CNC tool based on the predicted life error; and the basic feed rate of the target CNC tool is adjusted based on the machining adjustment parameters to obtain the target basic feed rate of the target CNC tool.

[0031] The preset life threshold is set manually based on actual conditions or experience; this embodiment does not specifically limit this. The theoretical remaining life refers to the ideal remaining time or number of remaining machined parts that the tool can reliably operate under the current working conditions, calculated based on the tool's material, geometry, cutting parameters, and empirical or physical models. The predicted life error is the difference between the predicted tool life and the theoretical remaining life. The closed-loop control algorithm is a feedback-based control strategy with the following basic structure: measurement (predicted life error) >> control law (such as PID algorithm) >> output (machining adjustment parameters) >> applied to the machine tool >> new sensing data updates the error. The machining adjustment parameters are adjustable process variables output by the closed-loop control algorithm used to correct cutting conditions. The target base feed rate is the final value obtained after applying the machining adjustment parameters calculated by the closed-loop control algorithm based on the predicted life error to the original base feed rate.

[0032] Optionally, if the predicted tool life is less than or equal to a preset tool life threshold, a tool change command for the target CNC tool is generated to replace the target CNC tool.

[0033] In this embodiment, in response to the start command of the target machining task, the target CNC machine tool's target machining process data and target process event flow are determined based on the target machining program received by the target CNC machine tool and the tool number of the target CNC tool in the target CNC machine tool. Based on the process event flow, the cutting force signal of the target CNC tool during the execution of the target machining task is collected to obtain the target cutting force timing data of the target CNC tool. Based on the target machining process data and tool number, the target machining process type of the target machining task is determined. When the completion of the target machining task is detected, the target CNC tool is image-captured based on the target machining process type to obtain the target tool image. Based on the target cutting force timing data, the target tool image, the target machining process data, and the target machining process type, the tool life of the target CNC tool is predicted to obtain the predicted tool life, and the target CNC tool is controlled based on the predicted tool life. The above technical solution adaptively acquires data and images based on the process event flow and process type of the machining process, and further predicts the tool life to control the tool. This can effectively improve the accuracy and reliability of tool life prediction and realize adaptive control of CNC tools.

[0034] Example 2 Figure 2This is a flowchart of a CNC tool control method based on process events, according to Embodiment 2 of this application. Based on the technical solutions of the above embodiments, this embodiment refines the process of "predicting the tool life of the target CNC tool based on target cutting force time-series data, target tool image, target machining process data, and target machining process type to obtain the predicted tool life of the target CNC tool" into "performing sliding window feature extraction on the target cutting force time-series data to obtain target cutting force feature data of the target CNC tool; wherein, the target cutting force feature data includes the average cutting force, root mean square value of the cutting force, peak cutting force, cutting force fluctuation characteristics, and cutting force frequency domain characteristics; performing wear identification on the target tool image to obtain the current wear data of the target CNC tool, and determining the target tool wear value of the target CNC tool based on the current wear data; predicting the tool life of the target CNC tool based on the target cutting force feature data, target tool wear value, target machining process data, and target machining process type to obtain the predicted tool life of the target CNC tool." It should be noted that for parts not detailed in this embodiment, please refer to the relevant descriptions in other embodiments. Figure 2 As shown, the method includes: S210. In response to the start command of the target machining task, determine the target machining process data and target process event flow of the target CNC tool based on the target machining program of the target machining task received by the target CNC machine tool and the tool number of the target CNC tool in the target CNC machine tool.

[0035] In one alternative implementation, in response to the start command of the target machining task, the machining process identifier of the target machining task is determined according to the target machining program of the target machining task received by the target CNC machine tool and the tool number of the target CNC tool in the target CNC machine tool. This identifier is used to associate the machining program, tool position number, cutting force data, tool image, wear value, life prediction result and control command in this machining process, so as to form a data association link for a single machining task.

[0036] Among them, the processing technology identifier refers to a globally unique identifier generated for a single processing task.

[0037] Furthermore, after determining the target machining process data and target process event flow for the target CNC tool, the target machining process data and target process event flow are bound to the machining process identifier.

[0038] S220. Based on the process event flow, the cutting force signal of the target CNC tool when performing the target machining task is collected to obtain the target cutting force timing data of the target CNC tool.

[0039] S230. Based on the target machining process data and tool number, determine the target machining process type for the target machining task.

[0040] S240. When the target machining task is identified as completed, the target CNC tool is image acquired according to the target machining process type to obtain the target tool image.

[0041] S250. Perform sliding window feature extraction on the target cutting force time series data to obtain the target cutting force feature data of the target CNC tool; wherein, the target cutting force feature data includes the mean cutting force, the root mean square value of the cutting force, the peak value of the cutting force, the cutting force fluctuation characteristics, and the cutting force frequency domain characteristics.

[0042] Among them, the target cutting force feature data refers to the set of quantitative features specifically corresponding to the target CNC tool obtained after feature extraction through a sliding window.

[0043] In one alternative implementation, after determining the target cutting force characteristic data, the target cutting force characteristic data is bound to the machining process identifier and stored in a preset central database.

[0044] S260. Perform wear recognition on the target tool image to obtain the current wear data of the target CNC tool, and determine the target tool wear value of the target CNC tool based on the current wear data.

[0045] The current wear data refers to the quantitative result of the wear of the target CNC tool at the current inspection moment; it may include wear area, wear length, chipping or edge defect characteristics, etc. The target tool wear value is a quantitative value used to assess the current severity of wear of the target CNC tool.

[0046] For example, wear recognition is performed on the target tool image to obtain the wear area, wear length, and chipping or edge defect features of the target CNC tool; the wear area, wear length, and chipping or edge defect features are weighted and summed to obtain the target tool wear value of the target CNC tool.

[0047] In one alternative implementation, after determining the target tool wear value, the target tool wear value is bound to the machining process identifier and stored in a preset central database.

[0048] S270. Based on the target cutting force characteristic data, target tool wear value, target machining process data, and target machining process type, predict the tool life of the target CNC tool to obtain the predicted tool life of the target CNC tool, and control the target CNC tool according to the predicted tool life.

[0049] Optionally, based on the target machining process type, the target failure mode of the target CNC tool is determined from the candidate failure modes; based on the target failure mode, the target machining material in the target machining process data, and the tool type of the target CNC tool, the target life prediction model is determined from the candidate life prediction models; based on the target life prediction model, the tool life of the target CNC tool is predicted according to the target cutting force characteristic data, the target tool wear value, and the target machining process data, to obtain the predicted tool life of the target CNC tool.

[0050] Candidate failure modes refer to the collection of all possible failure modes of CNC tools under various machining conditions, such as wear, chipping, fracture, tip spalling, and dulling. These serve as a pool of candidates to be selected for the target failure mode. The target failure mode refers to the specific failure mode most likely to occur under the current working conditions, selected from the candidate failure modes based on information such as the target machining process type, machining material, and tool type. It is the key basis for selecting the corresponding life prediction model. Candidate life prediction models refer to the collection of all existing models that can be used for CNC tool life prediction, such as mechanism models based on cutting force / wear, numerical models based on finite element simulation, and intelligent prediction models based on machine learning. The target life prediction model refers to the tool life prediction model that best suits the current working conditions, selected from the candidate life prediction models based on information such as the target failure mode, machining material, tool type, and available input data dimensions.

[0051] In one optional implementation, based on the machining process identifier, target cutting force characteristic data, target tool wear value, and target machining process data corresponding to the current machining process are read from the central database. A machining state vector is constructed based on the target cutting force characteristic data, target tool wear value, and machining parameters and equipment operating parameters in the target machining process data. Based on the target machining process type, the target failure mode of the target CNC tool is determined from candidate failure modes. Based on the target failure mode, the target machining material in the target machining process data, and the tool type of the target CNC tool, a target life prediction model is determined from candidate life prediction models. The machining state vector is input into the target life prediction model to obtain the predicted tool life of the target CNC tool, and the predicted tool life is associated with the machining process identifier.

[0052] It is understandable that a unique machining process identifier is generated when a machining task is started, and the machining program, cutting force characteristics, tool image, wear value, life prediction result and control command are uniformly linked to form a data organization method with a single machining process as the main line, so as to realize the unified management and traceability of data throughout the machining process.

[0053] In this embodiment, in response to the start command of the target machining task, the target CNC machine tool's target machining process data and target process event flow are determined based on the target machining program received by the target CNC machine tool and the tool number of the target CNC tool in the target CNC machine tool. Based on the process event flow, the cutting force signal of the target CNC tool during the execution of the target machining task is collected to obtain the target cutting force timing data of the target CNC tool. Based on the target machining process data and tool number, the target machining process type of the target machining task is determined. Upon identification of the completion of the target machining task, the target CNC tool is image-captured based on the target machining process type to obtain the target tool image of the target CNC tool. A sliding window feature extraction method is used to extract the target cutting force time-series data to obtain the target cutting force feature data of the target CNC tool. This target cutting force feature data includes the mean cutting force, root mean square cutting force, peak cutting force, cutting force fluctuation characteristics, and frequency domain characteristics. Wear recognition is performed on the target tool image to obtain the current wear data of the target CNC tool, and the target tool wear value is determined based on this data. Based on the target cutting force feature data, target tool wear value, target machining process data, and target machining process type, the tool life of the target CNC tool is predicted, resulting in a predicted tool life. The target CNC tool is then managed based on this predicted tool life. This technical solution, by adaptively acquiring data and images based on the process event flow and process type of the machining process, and further predicting tool life for tool management, can effectively improve the accuracy and reliability of tool life prediction, achieving adaptive management of CNC tools.

[0054] Example 3 Figure 3 This is a schematic diagram of a CNC tool control device based on process events, provided in Embodiment 3 of this application. It is applicable to situations involving CNC tool life prediction and tool control in CNC machine tools. This process event-based CNC tool control device can be implemented in hardware and / or software and can be configured in a computer device, such as a server. Figure 3 As shown, the device includes: The program parsing module 310 is used to respond to the start command of the target machining task, and determine the target machining process data and target process event flow of the target CNC tool based on the target machining program of the target machining task received by the target CNC machine tool and the tool number of the target CNC tool in the target CNC machine tool. The data acquisition module 320 is used to acquire the cutting force signal of the target CNC tool when performing the target machining task according to the process event flow, and obtain the target cutting force timing data of the target CNC tool; The type determination module 330 is used to determine the target machining process type of the target machining task based on the target machining process data and the tool number. The image acquisition module 340 is used to acquire images of the target CNC tool according to the target machining process type when the target machining task is identified as completed, so as to obtain the target tool image of the target CNC tool. The tool life prediction module 350 is used to predict the tool life of the target CNC tool based on the target cutting force timing data, target tool image, target machining process data and target machining process type, to obtain the predicted tool life of the target CNC tool, and to control the target CNC tool based on the predicted tool life.

[0055] In this embodiment, in response to the start command of the target machining task, the target CNC machine tool's target machining process data and target process event flow are determined based on the target machining program received by the target CNC machine tool and the tool number of the target CNC tool in the target CNC machine tool. Based on the process event flow, the cutting force signal of the target CNC tool during the execution of the target machining task is collected to obtain the target cutting force timing data of the target CNC tool. Based on the target machining process data and tool number, the target machining process type of the target machining task is determined. When the completion of the target machining task is detected, the target CNC tool is image-captured based on the target machining process type to obtain the target tool image. Based on the target cutting force timing data, the target tool image, the target machining process data, and the target machining process type, the tool life of the target CNC tool is predicted to obtain the predicted tool life, and the target CNC tool is controlled based on the predicted tool life. The above technical solution adaptively acquires data and images based on the process event flow and process type of the machining process, and further predicts the tool life to control the tool. This can effectively improve the accuracy and reliability of tool life prediction and realize adaptive control of CNC tools.

[0056] Optionally, the lifetime prediction module 350 includes: The feature extraction unit is used to perform sliding window feature extraction on the time series data of the target cutting force to obtain the target cutting force feature data of the target CNC tool; wherein, the target cutting force feature data includes the mean cutting force, the root mean square value of the cutting force, the peak value of the cutting force, the cutting force fluctuation characteristics, and the cutting force frequency domain characteristics; The wear recognition unit is used to perform wear recognition on the target tool image, obtain the current wear data of the target CNC tool, and determine the target tool wear value based on the current wear data. The tool life prediction unit is used to predict the tool life of the target CNC tool based on the target cutting force characteristic data, the target tool wear value, the target machining process data, and the target machining process type, so as to obtain the predicted tool life of the target CNC tool.

[0057] Optional, lifetime prediction unit, specifically used for: Based on the target machining process type, determine the target failure mode of the target CNC tool from the candidate failure modes; Based on the target failure mode, the target machining material in the target machining process data, and the tool type of the target CNC tool, the target lifetime prediction model is determined from the candidate lifetime prediction models. Based on the target life prediction model, the tool life of the target CNC tool is predicted according to the target cutting force characteristic data, the target tool wear value and the target machining process data, thus obtaining the predicted tool life of the target CNC tool.

[0058] Optionally, the program parsing module 310 is specifically used for: Semantic parsing is performed on the target machining program of the target machining task received by the target CNC machine tool to obtain the machining preparation code, machining auxiliary code, machining process segment and tool coordinate change data of the target machining task; Based on the machining preparation code and machining auxiliary code, determine the target machining process data for the target CNC tool; Based on the machining preparation code, machining process segment, and tool coordinate change data, determine the target process event flow for the target CNC tool.

[0059] Optional, the data acquisition module 320 is specifically used for: Based on the event type of each candidate process event in the process event flow, the target process event is determined from each candidate process event; wherein, the event type includes at least the cutting start event, cutting end event, machining stage event, photographing event, and tool change event; Based on the event type of the target process event, determine the target data acquisition method for the target CNC tool; During the execution of the target machining task by the target CNC tool, when the target process event is triggered, the cutting force signal of the target CNC tool is collected according to the target data acquisition method to obtain the target cutting force timing data of the target CNC tool.

[0060] Optional, lifetime prediction module 350, specifically used for: If the predicted tool life is greater than the preset life threshold, the predicted life error of the target CNC tool is determined based on the predicted tool life and the theoretical remaining life of the target CNC tool. A closed-loop control algorithm is used to determine the machining adjustment parameters of the target CNC tool based on the predicted life error; Based on the machining adjustment parameters, the basic feed rate of the target CNC tool is adjusted to obtain the target basic feed rate of the target CNC tool.

[0061] The CNC tool control device based on process events provided in this application can execute the CNC tool control method based on process events provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects for executing each CNC tool control method based on process events.

[0062] According to embodiments of this application, this application also provides an electronic device, a readable storage medium, and a computer program product.

[0063] Example 4 Figure 4 This is a schematic diagram of the structure of an electronic device 410 implementing the CNC tool control method based on process events according to embodiments of this application. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present application described and / or claimed herein.

[0064] like Figure 4 As shown, the electronic device 410 includes at least one processor 411 and a memory, such as a read-only memory (ROM) 412 or a random access memory (RAM) 413, communicatively connected to the at least one processor 411. The memory stores computer programs executable by the at least one processor. The processor 411 can perform various appropriate actions and processes based on the computer program stored in the ROM 412 or loaded from storage unit 418 into the RAM 413. The RAM 413 may also store various programs and data required for the operation of the electronic device 410. The processor 411, ROM 412, and RAM 413 are interconnected via a bus 414. An input / output (I / O) interface 415 is also connected to the bus 414.

[0065] Multiple components in electronic device 410 are connected to I / O interface 415, including: input unit 416, such as keyboard, mouse, etc.; output unit 417, such as various types of displays, speakers, etc.; storage unit 418, such as disk, optical disk, etc.; and communication unit 419, such as network card, modem, wireless transceiver, etc. Communication unit 419 allows electronic device 410 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0066] Processor 411 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 411 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 411 performs the various methods and processes described above, such as CNC tool control methods based on process events.

[0067] In some embodiments, the process event-based CNC tool control method can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 418. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 410 via ROM 412 and / or communication unit 419. When the computer program is loaded into RAM 413 and executed by processor 411, one or more steps of the process event-based CNC tool control method described above can be performed. Alternatively, in other embodiments, processor 411 can be configured for the process event-based CNC tool control method by any other suitable means (e.g., by means of firmware).

[0068] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0069] Computer programs used to implement the methods of this application may be written in any combination of one or more programming languages. These computer programs may be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable process event-based CNC tool control device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0070] In the context of this application, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0071] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0072] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0073] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0074] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this application can be achieved, and this is not limited herein.

[0075] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A CNC tool control method based on process events, characterized in that, include: In response to the start command of the target machining task, the target machining program of the target machining task received by the target CNC machine tool and the tool number of the target CNC tool in the target CNC machine tool are used to determine the target machining process data and target process event flow of the target CNC tool. Based on the process event flow, the cutting force signal of the target CNC tool when performing the target machining task is collected to obtain the target cutting force timing data of the target CNC tool; Based on the target machining process data and the tool number, the target machining process type of the target machining task is determined; When the completion of the target machining task is detected, the target CNC tool is image acquired according to the target machining process type to obtain the target tool image of the target CNC tool; Based on the target cutting force timing data, the target tool image, the target machining process data, and the target machining process type, the tool life of the target CNC tool is predicted to obtain the predicted tool life of the target CNC tool, and the target CNC tool is controlled according to the predicted tool life.

2. The method according to claim 1, characterized in that, The step of predicting the tool life of the target CNC tool based on the target cutting force timing data, the target tool image, the target machining process data, and the target machining process type, to obtain the predicted tool life of the target CNC tool, includes: Sliding window feature extraction is performed on the target cutting force time series data to obtain the target cutting force feature data of the target CNC tool; wherein, the target cutting force feature data includes the mean cutting force, the root mean square value of the cutting force, the peak value of the cutting force, the cutting force fluctuation characteristics, and the cutting force frequency domain characteristics; Wear recognition is performed on the target tool image to obtain the current wear data of the target CNC tool, and the target tool wear value of the target CNC tool is determined based on the current wear data; Based on the target cutting force characteristic data, the target tool wear value, the target machining process data, and the target machining process type, the tool life of the target CNC tool is predicted to obtain the predicted tool life of the target CNC tool.

3. The method according to claim 2, characterized in that, The step of predicting the tool life of the target CNC tool based on the target cutting force characteristic data, the target tool wear value, the target machining process data, and the target machining process type, to obtain the predicted tool life of the target CNC tool, includes: Based on the target machining process type, determine the target failure mode of the target CNC tool from the candidate failure modes; Based on the target failure mode, the target machining material in the target machining process data, and the tool type of the target CNC tool, a target lifetime prediction model is determined from the candidate lifetime prediction models. Based on the target life prediction model, the tool life of the target CNC tool is predicted according to the target cutting force characteristic data, the target tool wear value and the target machining process data, so as to obtain the predicted tool life of the target CNC tool.

4. The method according to claim 1, characterized in that, Based on the target machining program of the target machining task received by the target CNC machine tool, and the tool number of the target CNC tool in the target CNC machine tool, the target machining process data and target process event flow of the target CNC tool are determined, including: Semantic parsing is performed on the target machining program of the target machining task received by the target CNC machine tool to obtain the machining preparation code, machining auxiliary code, machining process segment and tool coordinate change data of the target machining task; Based on the machining preparation code and the machining auxiliary code, the target machining process data of the target CNC tool is determined; Based on the machining preparation code, the machining process segment, and the tool coordinate change data, the target process event flow for the target CNC tool is determined.

5. The method according to claim 1, characterized in that, The step of acquiring the cutting force signal of the target CNC tool when performing the target machining task according to the process event flow, and obtaining the target cutting force timing data of the target CNC tool, includes: Based on the event type of each candidate process event in the process event flow, the target process event is determined from each candidate process event; wherein, the event type includes at least the cutting start event, cutting end event, machining stage event, photographing event, and tool change event; Based on the event type of the target process event, determine the target data acquisition method for the target CNC tool; When the target process event is triggered during the execution of the target machining task by the target CNC tool, the cutting force signal of the target CNC tool is collected according to the target data acquisition method to obtain the target cutting force timing data of the target CNC tool.

6. The method according to claim 1, characterized in that, The step of controlling the target CNC tool based on the predicted tool life includes: If the predicted tool life is greater than the preset life threshold, then the predicted life error of the target CNC tool is determined based on the predicted tool life and the theoretical remaining life of the target CNC tool. A closed-loop control algorithm is used to determine the machining adjustment parameters of the target CNC tool based on the predicted life error; Based on the machining adjustment parameters, the basic feed rate of the target CNC tool is adjusted to obtain the target basic feed rate of the target CNC tool.

7. A CNC tool control device based on process events, characterized in that, include: The program parsing module is used to respond to the start command of the target machining task, and determine the target machining process data and target process event flow of the target CNC tool based on the target machining program of the target machining task received by the target CNC machine tool and the tool number of the target CNC tool in the target CNC machine tool; The data acquisition module is used to acquire the cutting force signal of the target CNC tool when performing the target machining task according to the process event flow, and obtain the target cutting force timing data of the target CNC tool; The type determination module is used to determine the target machining process type of the target machining task based on the target machining process data and the tool number. The image acquisition module is used to acquire an image of the target CNC tool according to the target machining process type when the target machining task is identified as completed, so as to obtain a target tool image of the target CNC tool. The tool life prediction module is used to predict the tool life of the target CNC tool based on the target cutting force timing data, the target tool image, the target machining process data, and the target machining process type, to obtain the predicted tool life of the target CNC tool, and to control the target CNC tool based on the predicted tool life.

8. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the CNC tool control method based on process events as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the CNC tool control method based on process events as described in any one of claims 1-6.

10. A computer program product comprising a computer program that, when executed by a processor, implements the CNC tool control method based on process events according to any one of claims 1-6.

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