10 results about "Virtual machine tool" patented technology

The invention relates to the technical field of numerical control machine tool monitoring, and discloses a numerical control machine tool intelligent monitoring system based on digital twinning. A digital twin modeling module of the system obtains geometric parameters, physical attributes and historical operation data of a numerical control machine tool in real time, and constructs a dynamically updated virtual machine tool model; the working condition sensing module collects vibration, temperature and current data through a multi-source sensor, and generates a running state feature set through time sequence alignment processing. The exception response module is used for matching an exception mode library according to the feature set and outputting an exception type identifier and an influence range parameter; the decision optimization module generates an optimization instruction set containing maintenance priority ranking based on the parameters; and the strategy iteration module monitors an instruction execution result, calculates a deviation value between an actual effect and a virtual model prediction effect, and dynamically updates the abnormal mode library. According to the system, accurate sensing of the operation state of the numerical control machine tool, quick response to abnormity and dynamic optimization of a maintenance strategy are realized, and the intelligent level of monitoring is improved.

The invention discloses a process-in-the-loop numerical control device and method, and belongs to the technical field of numerical control. The process-in-the-loop numerical control device comprises a non-real-time process optimizer, and the non-real-time process optimizer carries out process optimization processing on original track data input by a user based on a track error prediction model of deep learning; comprehensive errors generated in the multi-axis machining process are effectively compensated; the interpolator and the position controller are used for calculating a middle point coordinate of the movement track and accurately controlling the cutter to reach a target position; the process prediction observer constructs a dynamic observer by using a neural network technology, and carries out real-time feed-forward compensation in the processing process; and the physical machine tool carries out machining operation. According to the technology-in-the-loop numerical control device and method, the non-real-time technology optimizer and the technology prediction observer are added, the machining technology is subjected to deep fusion prediction, optimization and dynamic closed-loop control through virtual machine tool simulation and physical machine tool feedback, the machining track is optimized in real time, and errors are compensated.

The invention provides a tool path avoidance point planning method and device, equipment, a medium and a product, and relates to the technical field of numerical control machining, and the method comprises the steps: constructing a virtual machine tool model; determining avoiding point machine tool coordinates when the virtual machine tool parts in the virtual machine tool model do not collide with one another; and according to a simulation installation position of a simulation tool clamp in the virtual machine tool model relative to a virtual machine tool and a programming coordinate system of a cutter path, converting the avoiding point machine tool coordinate into an avoiding point programming coordinate, and updating to a path end point of the corresponding cutter path according to the avoiding point programming coordinate. Compared with an avoidance point planning mode which depends on repeated iteration verification of an operator according to operation experience, the collision-free avoidance point can be efficiently determined, and the setting efficiency of the avoidance point is improved.

The invention discloses a numerical control agent execution device driven by a large model, which belongs to the technical field of intelligent manufacturing and numerical control and comprises an agent subsystem, a real-time actuator subsystem, a virtual machine tool subsystem and a physical machine tool. The agent subsystem generates a verified instruction sequence through simulation interaction with the virtual machine tool subsystem; the real-time actuator subsystem is responsible for analyzing and executing the instruction generated by the intelligent agent and driving the physical machine tool to move; the virtual machine tool subsystem is used for verifying and optimizing instructions of the intelligent agent subsystem and providing simulation verification support; and the physical machine tool is driven by the real-time actuator subsystem to execute final machining operation. According to the numerical control agent execution device driven by the large model, intelligent optimization of a machine tool machining process is achieved through driving of the cutting force model, the control model and the error model in the agent, and the machining efficiency and the machining quality are improved under the condition that the machining dynamic precision is guaranteed.

This invention provides a method, apparatus, equipment, medium, and product for toolpath avoidance point planning, relating to the field of CNC machining technology. The method includes: constructing a virtual machine tool model; determining the machine tool coordinates of avoidance points when no collision occurs between virtual machine tool components in the virtual machine tool model; converting the machine tool coordinates of the avoidance points into avoidance point programming coordinates based on the simulated installation position of the simulated tooling fixture relative to the virtual machine tool and the programming coordinate system of the toolpath in the virtual machine tool model; and updating the corresponding toolpath endpoints based on the avoidance point programming coordinates. Compared to avoidance point planning methods that rely on operators repeatedly iterating and verifying based on operational experience, this invention can efficiently determine collision-free avoidance points, improving the efficiency of avoidance point setting.

The invention discloses a collision interference detection method based on a binary tree LOD model, belongs to the field of virtual machine tool processing, and aims to solve the technical problem of insufficient efficiency of a space segmentation model based on an octree in the prior art. The method comprises the following steps: obtaining a binary tree LOD model corresponding to a geometric model participating in collision interference detection, wherein the binary tree LOD model comprises a plurality of levels of bounding boxes; performing intersection detection based on the corresponding binary tree LOD model to obtain bounding box overlapping information of the binary tree LOD model; and according to the bounding box overlapping information, dynamically optimizing the intersection detection range and path of the subsequent hierarchy until an intersection detection completion condition is met, and outputting a collision interference detection result. According to the method, the hierarchical detail model of the binary tree structure is combined with the dynamic optimization strategy in the detection process, so that unnecessary bounding box traversal and calculation can be effectively reduced, and the real-time efficiency of collision interference detection is remarkably improved.

This invention discloses a process-in-the-loop (CNC) device and method, belonging to the field of CNC technology. It includes a non-real-time process optimizer, which uses a deep learning-based trajectory error prediction model to optimize the process of the user-input raw trajectory data, effectively compensating for comprehensive errors generated during multi-axis machining. An interpolator and position controller are used to calculate the coordinates of the intermediate points of the motion trajectory and precisely control the tool to reach the target position. A process prediction observer utilizes neural network technology to construct a dynamic observer for real-time feedforward compensation during machining. A physical machine tool performs the machining operation. This invention employs the aforementioned process-in-the-loop CNC device and method, adding a non-real-time process optimizer and a process prediction observer. Through deep fusion prediction, optimization, and dynamic closed-loop control of the machining process using virtual machine tool simulation and physical machine tool feedback, it optimizes the machining trajectory in real time and compensates for errors.

The application relates to the technical field of code analysis, and discloses a model enhancement method, device, equipment, storage medium and computer program product, the method comprising the following steps: traversing a target code folder through a bottom-layer virtual machine tool, extracting an abstract syntax tree corresponding to each code, constructing a structured directed acyclic graph based on the abstract syntax tree corresponding to each code, generating a positive-negative sample pair based on the structured directed acyclic graph, training a preset large language model through contrastive learning based on the positive-negative sample pair, obtaining code structured semantic embedding output by the trained large language model, taking the structured semantic embedding as input of a code large language model, and performing enhancement training on the code large language model, so that the processing limit of a context window on a large and complex program is broken through, and the processing precision and efficiency of the code large model are improved.

The invention provides a dynamic EDA teaching practical training cloud platform construction system and method. The system comprises a front-end module, a virtualization service module, an EDA tool service module and a storage service module. The front-end module is used for receiving an environment creation request sent by a client and sending the environment creation request to the virtualization service module; the virtualization service module is used for selecting an adaptive virtualization technology to create a target virtual machine for EDA teaching according to a preset strategy and a current infrastructure state after receiving the environment creation request; the EDA tool service module is used for configuring an environment variable required by an EDA tool chain in a target virtual machine; and the storage service module is used for mounting the shared disk on the target virtual machine according to the API or the internal command of the target virtual machine. According to the scheme, the operation of EDA tool installation and environment building can be simplified, and the interactive design environment can be quickly generated, customized and isolated according to user requirements.