Multi-model adaptation method and device of laser cutting numerical control system
By automatically generating initial parameters through modular design and configuration engine, combined with a virtual debugging environment, the problem of long development cycle and high cost when adapting laser cutting CNC systems to new models is solved, achieving fast, low-cost multi-model adaptation and debugging security.
Patent Information
- Application Number
- CN202511679918.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-17
- Publication Date
- 2026-02-24
AI Technical Summary
Existing laser cutting CNC systems require a lot of repetitive development work when adapting to new models, resulting in long development cycles, high costs, poor flexibility, low versatility, and high maintenance and debugging risks, making it difficult to quickly respond to the customized needs of the market and customers.
By adopting a modular system and standardized data interface design, the CNC system is decoupled into multiple functional modules. Initial configuration parameters are automatically generated through a configuration engine. Combined with a virtual debugging environment based on geometric and kinematic models, a closed-loop simulation system is constructed to achieve parameterized configuration and optimization.
It greatly shortens the development and adaptation cycle of new models, significantly reduces development costs, improves the flexibility and versatility of the system, reduces debugging risks, and supports rapid response to market and customer customization needs.
Smart Images
Figure CN121559979A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of laser cutting technology, and in particular to a method and apparatus for adapting a laser cutting CNC system to multiple models. Background Technology
[0002] Laser cutting, as one of the core processes in modern precision manufacturing, relies heavily on the control precision and intelligence level of the CNC system for its performance. Currently, most laser cutting CNC systems on the market are designed and developed using highly customized solutions tailored to specific machine models or hardware configurations. This "one-to-one" development model results in strong coupling between the system kernel, motion control algorithms, programmable logic controller (PLC) programs, and human-machine interface with the machine tool's mechanical structure, servo drives, lasers, and other hardware.
[0003] However, existing technologies have the following drawbacks: Each time a new model is adapted, a large amount of repetitive development work is required from the software level, including but not limited to rewriting the kinematic interpolation algorithm, adapting to the new PLC logic, and adjusting the process parameter library. This not only results in development cycles lasting several months but also significantly increases human and material costs. Summary of the Invention
[0004] (a) Technical problems to be solved
[0005] In view of the above-mentioned shortcomings and deficiencies of the prior art, the present invention provides a multi-model adaptation method and device for laser cutting CNC systems, which solves the technical problems of long development time and high cost in the prior art.
[0006] (II) Technical Solution
[0007] To achieve the above objectives, the main technical solutions adopted by the present invention include:
[0008] In a first aspect, embodiments of the present invention provide a method for adapting a laser cutting CNC system to multiple models. The laser cutting CNC system includes multiple functionally independent modules that interact through a standardized data interface. The method for adapting to multiple models includes:
[0009] The identification information and connection relationships of each hardware device included in the target laser cutting machine are obtained through industrial fieldbus.
[0010] Based on the identification information and connection relationship of each hardware device, the configuration engine is called to generate initial model configuration parameters, and the initial model configuration parameters are configured to the corresponding functional modules through standardized data interfaces to obtain the set of configured functional modules.
[0011] From a pre-set machine tool model library, the geometric and kinematic model corresponding to the target laser cutting machine is called, and in the virtual debugging environment, the configured set of functional modules is connected with the geometric and kinematic model to establish a closed-loop simulation system; wherein, the set of functional modules sends control commands to the geometric and kinematic model and receives sensor feedback signals from the geometric and kinematic model;
[0012] In a closed-loop simulation system, a set of functional modules is run to simulate the processing flow, and the module parameters are adjusted and optimized through a standardized data interface to obtain optimized configuration data.
[0013] The optimized configuration data is deployed to the CNC system of the target laser cutting machine through a standardized data interface to complete the adaptation.
[0014] In one possible embodiment, the multiple functional modules include a motion control module, a device drive module, and a process logic module.
[0015] In one possible embodiment, the operation of the closed-loop simulation system includes:
[0016] Logical conflict detection is performed on the initial model configuration parameters based on a predefined rule base;
[0017] If the logic conflict detection passes, the test processing code is executed in the closed-loop simulation system. By monitoring the motion trajectory, logic signals and virtual sensor data during the simulated processing, configuration errors are identified and corrected.
[0018] In one possible embodiment, the operation of the closed-loop simulation system further includes: performing physical collision and interference detection using geometric and kinematic models, and triggering an alarm and generating optimization suggestion information when a collision or interference is detected.
[0019] In one possible embodiment, before calling the configuration engine to generate the initial model configuration parameters, the multi-model adaptation method further includes: matching the matching information, which includes the identification information of each hardware device and its connection relationship, with the historical configuration database; if there is matching historical optimized configuration data in the historical configuration database, it is preferentially used as the recommended value or default value of the initial model configuration parameters.
[0020] In one possible embodiment, each geometric and kinematic model stored in the machine tool model library is bound to a specific hardware configuration fingerprint; the hardware configuration fingerprint is generated by the identification information of the hardware device and its connection relationship according to predefined rules.
[0021] In one possible embodiment, the multi-model adaptation method further includes: exporting optimized configuration data from the target laser cutting machine and importing it into another laser cutting machine to complete batch deployment.
[0022] Secondly, embodiments of the present invention provide a multi-model adaptation device for a laser cutting CNC system. The laser cutting CNC system includes multiple functionally independent modules that interact through a standardized data interface. The multi-model adaptation device includes:
[0023] The acquisition module is used to acquire the identification information and connection relationships of each hardware device included in the target laser cutting machine through the industrial fieldbus.
[0024] The configuration generation module is used to generate initial model configuration parameters based on the identification information and connection relationship of each hardware device, and then configure the initial model configuration parameters to the corresponding functional modules through a standardized data interface to obtain a set of configured functional modules.
[0025] The connection module is invoked to retrieve the geometric and kinematic model corresponding to the target laser cutting machine from a pre-set machine tool model library. In the virtual debugging environment, the configured set of functional modules is connected to the geometric and kinematic model to establish a closed-loop simulation system. The set of functional modules sends control commands to the geometric and kinematic model and receives sensor feedback signals from the geometric and kinematic model.
[0026] The runtime module is used to run a set of functional modules in a closed-loop simulation system, simulate the processing flow, and adjust the module parameters through a standardized data interface for debugging and optimization to obtain optimized configuration data.
[0027] The deployment module is used to deploy the optimized configuration data to the CNC system of the target laser cutting machine through a standardized data interface to complete the adaptation.
[0028] In one possible embodiment, the multiple functional modules include a motion control module, a device drive module, and a process logic module.
[0029] In one possible embodiment, the multi-model adaptation device further includes: a logic conflict detection module, used to perform logic conflict detection on the initial model configuration parameters based on a predefined rule base; and a configuration correction module, used to execute test processing code in a closed-loop simulation system if the logic conflict detection passes, and to identify and correct configuration errors by monitoring the motion trajectory, logic signals and virtual sensor data during the simulated processing.
[0030] (III) Beneficial Effects
[0031] The beneficial effects of this invention are as follows: This application provides a multi-model adaptation method and apparatus for a laser cutting CNC system. Through system modularization and standardized data interface design, the CNC system is decoupled into multiple functional modules, and initial configuration parameters are automatically generated by a configuration engine. This transforms the adaptation work for new models from "code-level modification" to "parameterized configuration," thereby greatly shortening the development and adaptation cycle of new models, significantly reducing development costs, and enabling a unified software system to flexibly and universally adapt to various laser cutting machine models with different hardware configurations, quickly responding to market and customer customization needs.
[0032] To make the above-mentioned objectives, features and advantages to be achieved by the embodiments of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description
[0033] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.
[0034] Figure 1 This paper presents a flowchart illustrating a multi-model adaptation method for a laser cutting CNC system according to an embodiment of this application.
[0035] Figure 2 This paper shows a structural block diagram of a calling engine provided in an embodiment of the present application;
[0036] Figure 3 The diagram shows a structural block diagram of a multi-model adapter for a laser cutting CNC system provided in an embodiment of this application. Detailed Implementation
[0037] To better explain and facilitate understanding of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.
[0038] In addition to the problems of long development cycles and high costs, existing technologies also have the following problems:
[0039] The system suffers from poor flexibility and low versatility: existing systems struggle to quickly adapt to diverse combinations of mechanical structures (e.g., three-axis, five-axis, robot), drive components, laser types, and peripheral equipment (e.g., autofocus, capacitor height adjustment, exchangeable worktables) in laser cutting machines. This results in slow response to rapid customer customization demands and market changes, severely hindering the improvement of product competitiveness.
[0040] Maintenance and upgrade difficulties: Maintaining multiple independent branches of software versions for different machine models creates a complex version management dilemma. When a common software defect is discovered, it needs to be fixed, tested, and released separately on each branch, which is inefficient and easily introduces new errors, posing a serious challenge to the overall stability and reliability of the system.
[0041] High debugging risks and heavy reliance on personnel: On-site debugging heavily relies on the personal experience of engineers. It lacks a high-fidelity virtual verification process, which means that configuration errors can only be exposed through trial and error on real machines. This is not only inefficient, but also carries high risks such as equipment collisions and component damage.
[0042] Based on this, embodiments of this application provide a multi-model adaptation method and apparatus for a laser cutting CNC system. Through system modularization and standardized data interface design, the CNC system is decoupled into multiple functional modules, and initial configuration parameters are automatically generated by a configuration engine. This transforms the adaptation work for new models from "code-level modification" to "parameterized configuration," thereby greatly shortening the development and adaptation cycle of new models, significantly reducing development costs, and enabling a unified software system to flexibly and universally adapt to various laser cutting models with different hardware configurations, quickly responding to market and customer customization needs.
[0043] To better understand the above technical solutions, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that the present invention can be understood more clearly and thoroughly, and that the scope of the present invention can be fully conveyed to those skilled in the art.
[0044] Please see Figure 1 , Figure 1 A flowchart illustrating a multi-model adaptation method for a laser cutting CNC system according to an embodiment of this application is shown. It should be understood that this multi-model adaptation method can be executed by a multi-model adaptation device for the laser cutting CNC system, and the specific device can be configured according to actual needs; this embodiment is not limited thereto. For example, the multi-model adaptation device can be a computer or a server, etc. Specifically, the laser cutting CNC system includes multiple functionally independent modules that interact through a standardized data interface; the multi-model adaptation method includes:
[0045] Step S110: Obtain the identification information and connection relationships of each hardware device included in the target laser cutting machine through the industrial fieldbus. The identification information of each hardware device can be numbers, letters, or a combination of numbers and letters.
[0046] Specifically, the multi-model adapter is connected to the industrial fieldbus network in the electrical control cabinet of the target laser cutting machine via standard industrial Ethernet cables. The fieldbus can be a high-performance real-time bus based on Ethernet, such as EtherCAT, PROFINET, or EtherNet / IP.
[0047] Furthermore, after the multi-device adapter is powered on, it initializes the bus protocol stack and broadcasts a discovery data packet to the network. All hardware devices connected to the bus will respond to the discovery request from the multi-device adapter in sequence. Subsequently, the multi-device adapter parses and extracts the identification information from the response message of each hardware device. This identification information includes the device manufacturer ID, device serial number, and device name.
[0048] Furthermore, by analyzing the communication timing and device response sequence on the bus, or by directly reading the topology mapping table provided by the bus controller, this multi-model adapter can automatically construct the physical connection order and hierarchical relationship of hardware devices on the bus. This topology mapping table clearly records the connection order, physical location, and type information of all hardware devices on the network.
[0049] Step S120: Based on the identification information of each hardware device and its connection relationship, the configuration engine is called to generate initial model configuration parameters, and the initial model configuration parameters are configured to the corresponding functional modules through standardized data interfaces to obtain a set of configured functional modules.
[0050] It should be understood that the specific process of calling the configuration engine to generate initial model configuration parameters based on the identification information of each hardware device and their connection relationship can be set according to actual needs, and the embodiments of this application are not limited thereto.
[0051] Optionally, such as Figure 2 As shown, the calling engine includes a feature extraction and standardization module, a motion control parameter generation module, an equipment driver parameter generation module, a cutting process parameter generation module (also known as a process logic parameter generation module), and a parameter fusion and conflict resolution module. The feature extraction and standardization module is connected to the motion control parameter generation module, the equipment driver parameter generation module, and the cutting process parameter generation module, respectively, and the parameter fusion and conflict resolution module is also connected to these modules.
[0052] For this feature extraction and standardization module, it parses the identification information of each hardware device, removes irrelevant descriptive fields, and ensures the integrity of key data (such as model and power). Next, the module constructs a standardized feature vector from the processed identification information of each hardware device and its connections. The order of elements within this standardized feature vector can be set according to actual needs.
[0053] Furthermore, the motion control parameter generation module includes a first feature selection and attention mechanism module for highly focusing on features that determine the machine tool's motion performance and mechanical structure (e.g., the number and type of axes). After receiving a complete normalized feature vector, the motion control parameter generation module activates its internal first feature selection and attention mechanism module. It extracts the number and type (linear or rotational) of axes and their connections from the normalized feature vector. Based on this information, the motion control parameter generation module first determines the machine tool's kinematic architecture, such as whether it is a simple three-axis Cartesian coordinate motion or a complex five-axis linkage motion, and selects the appropriate forward and inverse kinematics algorithm for this architecture.
[0054] Subsequently, the motion control parameter generation module focuses on the dynamic characteristics of the machine tool. Based on the mass and structure of the mechanical components (implied in the rigidity level) and the travel range of each axis, it begins to infer the optimal servo control parameters. For a gantry inferred to be highly rigid, the module recommends higher servo gain and more aggressive feedforward parameters to achieve high-speed, high-precision motion; while for a long cantilever structure, it recommends a more conservative gain to prevent vibration. Simultaneously, the module sets safe acceleration, deceleration, and jerk values based on the physical limits and dynamic capabilities of the axes. Finally, it calculates a suitable number of path look-ahead points based on the overall dynamic performance of the machine tool to balance machining efficiency and path accuracy.
[0055] Therefore, the motion control parameter generation module ultimately outputs a set of motion control parameters. For example, this set includes servo control parameters (e.g., servo gain and feedforward parameters), trajectory planning parameters (e.g., acceleration, deceleration, jerk, and the number of look-ahead points), and kinematic model parameters (e.g., the kinematic type of the machine tool (three-axis, five-axis, etc.) and its corresponding forward and inverse kinematics algorithms). The kinematic model can represent a model used to describe motion relationships, and it is determined by information including the number and type of axes, thus determining whether the kinematic model is three-axis or five-axis, etc.
[0056] Additionally, the device driver parameter generation module includes a second feature selection and attention mechanism module to focus entirely on specific hardware models and connection addresses (e.g., a list of servo driver models). This module scans each device model in the standardized feature vector and matches it against a built-in hardware driver library. For each identified servo driver model, the module retrieves its optimal default configuration parameters from the driver library, such as control mode (position, speed, or torque mode), electronic gear ratio, and feedback filter parameters, ensuring the driver is correctly initialized and performs at its best.
[0057] Subsequently, the device drive parameter generation module automatically generates an input / output mapping table based on the location information provided by the device topology. According to the safety logic and functional requirements of standard machine tools, it assigns specific channels of the input module to sensors such as limit switches and enable signals, and assigns specific channels of the output module to actuators such as relays and solenoid valves. Simultaneously, for specialized equipment such as laser controllers, the module configures its dedicated communication protocol (such as EtherCAT's CoE driver) and control instruction set to ensure that the CNC system can correctly communicate with it and issue commands such as light output and power adjustment. Specifically, this input / output (IO) mapping table is used to assign specific channels of the input module to sensors such as limit switches and enable signals, and also to assign specific channels of the output module to actuators such as relays and solenoid valves.
[0058] Therefore, the device driver parameter generation module ultimately outputs a device driver parameter set. For example, the device driver parameter set includes servo driver configuration parameters (e.g., it may include control mode, electronic gear ratio, and feedback filter parameters), input / output (IO) mapping table, and dedicated device communication and control configuration (e.g., it may include dedicated communication protocol and control instruction set).
[0059] Furthermore, the cutting process parameter generation module includes a third feature selection and attention mechanism module for focusing on the laser type and maximum laser power. This module first determines the processing "capability range" based on the laser type and maximum power. For example, a 6000-watt fiber laser and a 3000-watt carbon dioxide laser have drastically different cutting characteristics. Subsequently, the module accesses its built-in process knowledge database, which stores validated optimal combinations of cutting parameters for different lasers, materials (such as carbon steel, stainless steel, and aluminum alloys), and thicknesses.
[0060] Furthermore, the core function of this cutting process parameter generation module is to "populate" the process database of this specific laser cutting machine. Based on the laser's actual capabilities, it matches and generates a series of process parameter sets from the knowledge base. Each parameter set includes cutting speed, laser power, pulse frequency, assist gas type and pressure, and piercing parameters for a specific material and thickness. In addition, this cutting process parameter generation module defines different cutting modes, such as "standard mode," "high-speed mode," and "high-quality mode," and recommends a set of fine-tuned parameters for each mode to meet different processing quality requirements.
[0061] Therefore, the cutting process parameter generation module ultimately outputs a set of cutting process parameters (or a set of process logic parameters). For example, this set includes combinations of cutting parameters for specific materials (carbon steel, stainless steel, aluminum alloy) and thicknesses, as well as cutting mode definition data. The combinations of cutting parameters may include cutting speed, laser power pulse frequency, auxiliary gas type, and piercing parameters; the cutting mode definition data includes different cutting modes and a set of fine-tuned parameters for each mode.
[0062] Furthermore, the parameter fusion and conflict resolution module intelligently splices and assembles the received motion control parameter set, device drive parameter set, and cutting process parameter set according to a predefined system configuration architecture template. This process is not a simple list merging, but rather integrates them into a unified, structured initial model configuration tree based on the functional semantics between the parameters. For example, it associates the "X-axis servo gain" in the motion control parameter set with the "X-axis driver control mode" in the device drive parameter set under the same "X-axis drive configuration" node in the configuration tree, forming a complete axis control scheme. As another example, it associates the "cutting speed" for "6mm carbon steel" in the cutting process parameter set with the "Y-axis maximum speed" in the motion control parameter set. The former is populated into the "process database" branch of the configuration tree, and the latter into the "motion performance limit" branch, establishing a logical connection for subsequent conflict detection.
[0063] Subsequently, the parameter fusion and conflict resolution module scans the integrated configuration tree based on a predefined conflict resolution rule base to identify and resolve inconsistencies between parameters. The resolution process primarily handles the following types of conflicts:
[0064] Performance Limit Conflict: Checks whether the process parameters exceed the performance boundaries set by the motion control parameters. For example, the recommended "cutting speed" for "cutting 8mm stainless steel" in the cutting process parameter set is 12 m / min, but the "maximum design speed of the Y-axis" defined in the motion control parameter set is only 10 m / min. Therefore, the parameter fusion and conflict resolution module applies the "hardware limit priority" rule, automatically corrects the upper limit of this cutting speed parameter in the process database to 10 m / min, and records a warning log.
[0065] Resource configuration conflict: Check for duplicate definitions or usage of resources. For example, in the automatically generated IO mapping table of the device driver parameter set, the same output point may be assigned to both "laser enable" and "workbench lighting" logical functions. The parameter fusion and conflict resolution module will then apply the "uniqueness" rule to determine this as a conflict. It will automatically reassign the resource based on functional priority (usually safety functions take precedence) or mark it as a serious error requiring engineer intervention.
[0066] Logical consistency conflict: Check whether the logical relationship between related parameters is reasonable. For example, if the "maximum acceleration on the Z-axis" defined in the motion control parameter set is much higher than the theoretical value that its "jerk" can support, it will lead to a mismatch in dynamic performance. Therefore, the parameter fusion and conflict resolution module applies the "physical consistency" rule and provides optimization suggestions based on the dynamic model. For example, it may suggest "the current jerk value may limit the acceleration capability, and it is recommended to increase it to the X value", or automatically make coordinated adjustments.
[0067] It should also be understood that the specific modules of the multiple functional modules can be set according to actual needs, and the embodiments of this application are not limited thereto.
[0068] Optionally, the multiple functional modules include a motion control module, an equipment drive module, and a process logic module. The motion control module can control the movement of all axes; the equipment drive module can drive physical equipment such as lasers, auxiliary gases, and loading / unloading devices; and the process logic module can manage and execute processes.
[0069] After receiving the initial device configuration parameters generated by the configuration engine, the system can parse these parameters and determine which functional module to send the relevant configuration parameters to. Subsequently, the relevant configuration parameters are sent to the corresponding functional module via a standardized data interface.
[0070] Step S130: From a pre-set machine tool model library, the geometric and kinematic model corresponding to the target laser cutting machine is retrieved. In the virtual debugging environment, the configured set of functional modules is connected to the geometric and kinematic model to establish a closed-loop simulation system. The set of functional modules sends control commands to the geometric and kinematic model and receives sensor feedback signals from the geometric and kinematic model.
[0071] It should be understood that each geometric and kinematic model stored in the machine tool model library is bound to a specific hardware configuration fingerprint; the hardware configuration fingerprint is generated by the identification information of the hardware device and its connection relationship according to predefined rules.
[0072] For example, the identification information and connection relationships of hardware devices can be standardized and sorted according to predefined rules. Then, the sorted identification information and connection relationships are concatenated into a string. Finally, the string is encrypted using a preset encryption algorithm (e.g., SHA-256, MD5) to obtain the hardware configuration fingerprint.
[0073] The geometric and kinematic models together constitute the digital entity of the controlled object of the target laser cutting machine in the virtual environment. They simulate the physical existence and behavior of a real machine tool and are the part of the virtual debugging system that receives control commands and generates physical responses.
[0074] The geometric model refers to a digital collection that accurately represents the shape, size, and assembly relationships of all physical components of the target laser cutting machine in three-dimensional space. It includes not only fixed components such as the bed, crossbeam, and protective cover, but also all moving components, such as sliders, lead screws, and cutting heads along the X, Y, and Z axes. Essentially, the model is a computer-aided design dataset containing three-dimensional meshes, surfaces, and assembly constraints. Its core function in virtual debugging is physical collision and interference detection. When the virtual machine tool runs in the simulation environment, the system calculates the minimum distances between moving components and between moving components and fixed components in real time. Once an unexpected contact or penetration is detected, a collision alarm signal is immediately triggered.
[0075] A kinematic model is an abstract mathematical model that describes the mathematical dependencies and motion laws between the various motion axes of a machine tool. It precisely defines the mapping relationship from the drive space (displacement and velocity of each servo motor) to the task space (position and orientation of the cutting head tip in the workpiece coordinate system), and its inverse process. The core of this model is the machine tool's kinematic chain and the corresponding forward and inverse kinematics calculation algorithms. In simulation, it receives axis control commands from the CNC system's functional modules and drives the components in the geometric model to perform corresponding movements through forward kinematics calculations; conversely, it can also provide virtual encoder feedback signals.
[0076] Based on the above, in a virtual debugging environment, through software interfaces and signal mapping, the set of configured functional modules in operation (which can be regarded as the "brain" of the system) and the geometric and kinematic models (which can be regarded as the "virtual body" of the controlled object) are interconnected and logically bound to each other, so as to build a closed-loop simulation system with a feedback mechanism.
[0077] Step S140: In the closed-loop simulation system, run the set of functional modules to simulate the processing flow, and adjust the module parameters through the standardized data interface for debugging and optimization to obtain optimized configuration data.
[0078] Specifically, logical conflict detection is performed on the initial model configuration parameters based on a predefined rule base. If the logical conflict detection passes, the test processing code is executed in the closed-loop simulation system. By monitoring the motion trajectory, logic signals and virtual sensor data during the simulated processing, configuration errors are identified and corrected.
[0079] For example, the system invokes a predefined rule base to perform a comprehensive logical conflict scan on the generated initial machine configuration parameters. This rule base encapsulates expert knowledge in machine tool design, electrical logic, and safety, and its rules include, but are not limited to:
[0080] Port address uniqueness rule: Ensure that different logical functions (such as "X-axis positive limit" and "laser ready") are not mapped to the same physical input / output address;
[0081] Axis travel logic consistency rule: Check whether the soft limit setting of each axis is within the hard limit range, and whether the zero offset matches the travel logic;
[0082] Power-speed matching rule: Verify whether the cutting speed recommended in the process parameter library exceeds the maximum design speed capability of the servo axis under this configuration.
[0083] If a static check detects a conflict, the system generates a detailed diagnostic report, indicating the location of the conflict and suggesting modifications, and pauses subsequent processes. If the logic conflict detection passes, standard test machining code is loaded into the pre-built closed-loop simulation system. This machining code typically includes linear, circular, rapid positioning, and even complex five-axis linkage instructions to fully test the machine tool's dynamic performance. Subsequently, the system runs the simulation at full speed and identifies potential configuration errors by monitoring data in three key dimensions:
[0084] Motion trajectory: Observe whether the actual motion trajectory of the tool tip of the virtual machine tool is consistent with the theoretical path of the G code instruction, and whether there are phenomena such as excessive tracking error, contour distortion or motion jitter.
[0085] Logic signals: Monitor the input / output status sequence of the PLC to verify whether safety interlock logic such as "the laser will only emit light after the gas pressure reaches the preset value" and "processing is allowed to start only after each axis returns to zero" is executed correctly;
[0086] Virtual sensor data: Receives and analyzes virtual encoder position, virtual load torque, and real-time signals from the collision detection system fed back from the geometric and kinematic models. For example, a sustained abnormally high load torque may indicate excessive servo gain; while a sudden collision alarm directly reveals interference between the motion path and the tooling fixture.
[0087] It's important to note that logic conflict detection is performed on a complete, operational, closed-loop simulation system. It focuses on identifying errors in "business logic" and "system-level behavior" exposed by configurations within a dynamic runtime context. In this case, the system no longer examines isolated parameters, but rather the overall behavior exhibited by the interaction of parameters under specific processing scenarios.
[0088] In addition, the operation of the closed-loop simulation system also includes: physical collision and interference detection through geometric and kinematic models, and triggering alarms and generating optimization suggestions when a collision or interference is detected.
[0089] For example, during the execution of test machining code in a closed-loop simulation system, the geometric and kinematic models, as entities of the virtual machine tool, continuously perform high-precision calculations. The collision detection engine calculates in real time the minimum distance between the 3D mesh models of moving parts (such as the cutting head and Z-axis slide) and other machine tool parts (such as fixtures, machined workpieces, and the machine bed). When the system predicts or detects that these geometric models, which should be separated, unexpectedly intersect or penetrate each other, it is considered a physical collision. Simultaneously, the system also monitors whether moving parts enter singularities or dangerous postures defined by the kinematic model that are not permitted by its physical structure; this is considered a motion interference.
[0090] If any of the above situations occur, the system will immediately trigger a high-level alarm and forcibly suspend the simulation. The alarm message will precisely indicate the name of the component that collided or interfered, its G-code line number, and its specific location in 3D space. Following this, the system will activate the optimization suggestion generation module. This module matches solutions from a predefined expert rule base based on the collision context information. For example, if the Z-axis collided with the worktable during descent, the suggestion might be "Z-axis overtravel detected; check the workpiece coordinate system Z-zero point setting, or increase the 'safe height' parameter"; another example is if the cutting head collided with the fixture, the suggestion might be "Cutting head interference detected with the 'village fixture'; set an avoidance zone in the CAM software, or select a smaller fixture."
[0091] Step S150: Deploy the optimized configuration data to the CNC system of the target laser cutting machine through a standardized data interface to complete the adaptation.
[0092] Furthermore, the optimized configuration data is exported from the target laser cutting machine and imported into another laser cutting machine to complete the batch deployment.
[0093] In addition, before calling the configuration engine to generate the initial model configuration parameters, the multi-model adaptation method also includes: matching the matching information, which includes the identification information of each hardware device and its connection relationship, with the historical configuration database; if there is matching historical optimized configuration data in the historical configuration database, it is given priority as the recommended value or default value of the initial model configuration parameters.
[0094] Therefore, by means of the above technical solution, this application has the following technical effects:
[0095] This application, through modular system design and standardized data interfaces, decouples the laser cutting CNC system into independent functional modules. Combined with a configuration engine, it automatically generates initial configuration parameters, transforming the adaptation process for new models from "code-level modification" to "parameterized configuration." This significantly shortens the development and adaptation cycle for new models, substantially reduces development costs, and enables a unified software system to flexibly and universally adapt to various laser cutting machine models with different hardware configurations, quickly responding to market and customer customization needs.
[0096] Furthermore, this application introduces a virtual debugging environment based on geometric and kinematic models to construct a closed-loop simulation system, enabling technicians to safely and comprehensively simulate the processing flow and debug parameters in a virtual space. This fundamentally avoids the equipment collision risks that may arise during on-site debugging, achieves "zero physical risk" debugging, and reduces excessive reliance on the experience of debugging personnel.
[0097] Furthermore, because the core of this application's system architecture lies in modularity and the separation of configuration and code, the specific information for each device model is encapsulated in independent configuration files. This allows for general feature upgrades or defect fixes where only the core functional modules need to be updated once, benefiting all devices. This completely solves the problem of chaotic maintenance across multiple software branches, greatly improving maintenance efficiency and overall system stability.
[0098] Furthermore, this application inherently supports configuration migration and batch deployment. Once the optimized configuration for a single device is completed, it can be quickly and accurately cloned to multiple devices of the same model through export and import, greatly simplifying the deployment of batch devices and further amplifying its efficiency advantages in engineering applications.
[0099] It should be understood that the above-described method for adapting laser cutting CNC systems to multiple models is merely exemplary. Those skilled in the art can make various modifications based on the above method, and the modified solutions also fall within the scope of protection of this application.
[0100] Please see Figure 3 , Figure 3 This diagram illustrates a structural block diagram of a multi-model adapter 300 for a laser cutting CNC system according to an embodiment of this application. It should be understood that the multi-model adapter 300 is capable of executing the steps described in the above method embodiments. The specific functions of the multi-model adapter 300 can be found in the description above; to avoid repetition, detailed descriptions are omitted here. The multi-model adapter 300 includes at least one software function module that can be stored in a memory or embedded in the operating system (OS) of the multi-model adapter 300 in the form of software or firmware. Specifically, the laser cutting CNC system includes multiple functionally independent modules that interact through a standardized data interface; the multi-model adapter 300 includes:
[0101] The acquisition module 310 is used to acquire the identification information and connection relationship of each hardware device included in the target laser cutting machine through the industrial fieldbus.
[0102] The configuration generation module 320 is used to generate initial model configuration parameters by calling the configuration engine based on the identification information and connection relationship of each hardware device, and to configure the initial model configuration parameters to the corresponding functional modules through the standardized data interface to obtain a set of configured functional modules.
[0103] The connection module 330 is invoked to retrieve the geometric and kinematic model corresponding to the target laser cutting machine from a pre-set machine tool model library, and to connect the configured set of functional modules with the geometric and kinematic model in a virtual debugging environment to establish a closed-loop simulation system; wherein, the set of functional modules sends control commands to the geometric and kinematic model and receives sensor feedback signals from the geometric and kinematic model;
[0104] The running module 340 is used to run the set of functional modules in the closed-loop simulation system, simulate the processing flow, and adjust the module parameters through the standardized data interface for debugging and optimization to obtain optimized configuration data.
[0105] The deployment module 350 is used to deploy the optimized configuration data to the CNC system of the target laser cutting machine through the standardized data interface to complete the adaptation.
[0106] In one possible embodiment, the plurality of functional modules include a motion control module, a device drive module, and a process logic module.
[0107] In one possible embodiment, the multi-model adaptation device further includes:
[0108] The logic conflict detection module is used to perform logic conflict detection on the initial model configuration parameters based on a predefined rule base.
[0109] The configuration correction module is used to execute test processing code in the closed-loop simulation system if the logic conflict detection passes. It identifies and corrects configuration errors by monitoring the motion trajectory, logic signals and virtual sensor data during the simulated processing.
[0110] Since the apparatus described in the above embodiments of the present invention is an apparatus used to implement the methods of the above embodiments of the present invention, those skilled in the art can understand the specific structure and variations of the apparatus based on the methods described in the above embodiments of the present invention, and therefore will not be described again here. All apparatuses used in the methods of the above embodiments of the present invention fall within the scope of protection of the present invention.
[0111] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0112] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions.
[0113] It should be noted that any reference numerals placed between parentheses in the claims should not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In claims that enumerate several means, several of these means may be embodied by the same hardware. The use of the terms first, second, third, etc., is merely for convenience of expression and does not indicate any order. These terms can be understood as part of the component names.
[0114] Furthermore, it should be noted that in the description of this specification, the terms "one embodiment," "some embodiments," "embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.
[0115] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the claims should be interpreted to include both the preferred embodiments and all changes and modifications falling within the scope of the invention.
[0116] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, then this invention should also include these modifications and variations.
Claims
1. A method for adapting a laser cutting CNC system to multiple models, characterized in that, The laser cutting CNC system includes multiple functional modules that are independent in function and interact through standardized data interfaces; The multi-model adaptation method includes: The identification information and connection relationships of each hardware device included in the target laser cutting machine are obtained through industrial fieldbus. Based on the identification information and connection relationship of each hardware device, the configuration engine is invoked to generate initial model configuration parameters, and the initial model configuration parameters are configured to the corresponding functional modules through the standardized data interface to obtain a set of configured functional modules. From a pre-set machine tool model library, the geometric and kinematic model corresponding to the target laser cutting machine is called, and in a virtual debugging environment, the configured set of functional modules is connected to the geometric and kinematic model to establish a closed-loop simulation system; wherein, the set of functional modules sends control commands to the geometric and kinematic model and receives sensor feedback signals from the geometric and kinematic model; In the closed-loop simulation system, the set of functional modules is run to simulate the processing flow, and the module parameters are adjusted and optimized through the standardized data interface to obtain optimized configuration data. The optimized configuration data is deployed to the CNC system of the target laser cutting machine through the standardized data interface to complete the adaptation.
2. The multi-model adaptation method according to claim 1, characterized in that, The multiple functional modules include a motion control module, an equipment drive module, and a process logic module.
3. The multi-model adaptation method according to claim 1, characterized in that, The operation process of the closed-loop simulation system includes: Logical conflict detection is performed on the initial model configuration parameters based on a predefined rule base; If the logic conflict detection passes, the test processing code is executed in the closed-loop simulation system. By monitoring the motion trajectory, logic signals and virtual sensor data during the simulated processing, configuration errors are identified and corrected.
4. The multi-model adaptation method according to claim 3, characterized in that, The operation process of the closed-loop simulation system also includes: Physical collision and interference detection is performed using the geometric and kinematic model, and an alarm is triggered and optimization suggestions are generated when a collision or interference is detected.
5. The multi-model adaptation method according to claim 1, characterized in that, Before the configuration engine is invoked to generate the initial device configuration parameters, the multi-device adaptation method further includes: The matching information, including the identification information of each hardware device and their connection relationships, is matched with the historical configuration database. If matching historical optimized configuration data exists in the historical configuration database, it will be used as the recommended or default value for the initial model configuration parameters.
6. The multi-model adaptation method according to claim 1, characterized in that, Each of the geometric and kinematic models stored in the machine tool model library is bound to a specific hardware configuration fingerprint; the hardware configuration fingerprint is generated by the identification information of the hardware device and its connection relationship according to predefined rules.
7. The multi-model adaptation method according to claim 1, characterized in that, The multi-model adaptation method also includes: The optimized configuration data is exported from the target laser cutting machine and imported into another laser cutting machine to complete the batch deployment.
8. A multi-model adapter for a laser cutting CNC system, characterized in that, The laser cutting CNC system includes multiple functional modules that are independent in function and interact through standardized data interfaces; The multi-model adapter includes: The acquisition module is used to acquire the identification information and connection relationships of each hardware device included in the target laser cutting machine through the industrial fieldbus. A configuration generation module is used to generate initial model configuration parameters by calling the configuration engine based on the identification information and connection relationship of each hardware device, and to configure the initial model configuration parameters to the corresponding functional modules through the standardized data interface to obtain a set of configured functional modules. The connection module is invoked to retrieve the geometric and kinematic model corresponding to the target laser cutting machine from a pre-set machine tool model library, and to connect the configured set of functional modules with the geometric and kinematic model in a virtual debugging environment to establish a closed-loop simulation system; wherein, the set of functional modules sends control commands to the geometric and kinematic model and receives sensor feedback signals from the geometric and kinematic model; The running module is used to run the set of functional modules in the closed-loop simulation system, simulate the processing flow, and adjust the module parameters through the standardized data interface for debugging and optimization to obtain optimized configuration data. The deployment module is used to deploy the optimized configuration data to the CNC system of the target laser cutting machine through the standardized data interface to complete the adaptation.
9. The multi-model adaptation device according to claim 8, characterized in that, The multiple functional modules include a motion control module, an equipment drive module, and a process logic module.
10. The multi-model adaptation device according to claim 8, characterized in that, The multi-model adapter also includes: The logic conflict detection module is used to perform logic conflict detection on the initial model configuration parameters based on a predefined rule base. The configuration correction module is used to execute test processing code in the closed-loop simulation system if the logic conflict detection passes. It identifies and corrects configuration errors by monitoring the motion trajectory, logic signals and virtual sensor data during the simulated processing.