10 results about "Critical regions" patented technology

A computer-implemented method for analyzing simulation results of a manufacturing or deformation process, comprising: obtaining simulation results, the simulation results comprising at least a geometry of a part (2) and a stress tensor (23) in the part (2) caused by a shaping process; for one or more origins (32) in a critical region (22), determining an origin line (3) by following a direction of maximum stress or a corresponding force; for each origin line (3), determining at least one line segment (31) of the origin line (3) and an origin trajectory (5) representing values of the stress or force directed along the origin line (3); and performing at least one of presenting information representing the line segment (31) and the origin trajectory (5) along the line segment (31) to a user and automatically adjusting parameters of the shaping process.

This invention discloses a discrete element method, system, medium, and equipment for simulating equivalent crystalline materials, relating to the field of numerical simulation of rock mechanics. The method includes: converting granite images into binary images using a binarization method to identify various minerals within the binary images; determining the size data of various minerals in the binary images based on a particle size statistical algorithm; extracting micromechanical parameters using nanoindentation experiments combined with a trial-and-error method, and constructing multiple sets of equivalent crystalline models based on the mineral size data; dividing each set of equivalent crystalline models into multiple regions using a Brazilian splitting experiment; determining the optimal magnification for each region of each set of equivalent crystalline models by magnifying from non-critical regions to critical regions using a magnification algorithm, obtaining differentiated equivalent crystalline models; and performing Brazilian splitting numerical simulation using these differentiated equivalent crystalline models to obtain simulation results.

The present application relates to the technical field of safety monitoring and industrial automation, and discloses a silo safety monitoring method and system, which synchronously acquires coal pile surface point cloud, lateral pressure, vertical load and environmental data through the arrangement of a laser scanning unit, an annular pressure sensing belt, a weighing sensor and a temperature and humidity node; a high-precision three-dimensional morphology is reconstructed based on an adaptive grid refinement algorithm, and a joint representation model is constructed by fusing mechanical data; a stability discrimination function is established in combination with coal body physical parameters to identify the instability critical region; and through pattern matching with a historical stability morphology library, hierarchical early warning of abnormal working conditions such as suspended arch, bonding and blockage and generation of blockage removal strategies are realized. The present application constructs a joint representation model of coal pile three-dimensional morphology and mechanical state by fusing laser point cloud, pressure distribution and load sensing data, breaks through the limitation of traditional single-point material level measurement which cannot reflect the overall coal pile structure, and realizes high-precision measurement with a storage calculation error of less than 2%.

This invention provides a method for intelligent monitoring and early warning of water droplet impact in substations during rainy weather, relating to the field of intelligent operation and maintenance and condition monitoring of substations. The method includes: acquiring dual-optical-path video streams; constructing a cross-spectral neural radiation field network; using joint high-dimensional features as input to output volume density and radiation color vectors; calculating the equivalent water film thickness from these two vectors to generate an equivalent water film thickness distribution field; mapping this field to a three-dimensional model, subdividing the mesh according to the thickness gradient modulus, and solving for the electric field to obtain the electric field distortion tensor and calibrate the high-discharge-risk critical region; generating a Lagrange particle set, solving the dynamic equations through smooth particle hydrodynamics, and simulating the water film evolution to obtain the probability of conductive water bridge connection; inputting the distribution field, distortion tensor, and connection probability into a multi-modal impedance reconstructor to generate an electrochemical impedance spectrum to obtain the dynamic insulation margin attenuation rate; and triggering an early warning based on the determined conditions. This invention significantly improves the timeliness and accuracy of early warning for external insulation faults during rainy weather.

The application provides a process state real-time correction method based on acoustic characteristics, and relates to the technical field of process control, and comprises the following steps: collecting acoustic signals generated by interaction between a processing medium and a processing unit when the processing unit is executing a processing task; performing real-time spectrum analysis on the acoustic signals to extract characteristic frequencies and energy distribution characteristics thereof which are related to the current physical state of the processing medium; determining whether the current physical state of the processing medium is in an abnormal critical region in real time based on changes of the characteristic frequencies and the energy distribution characteristics thereof relative to a preset reference; the abnormal critical region comprises a first precursor state in which the processing medium tends to be excessively dried or a second precursor state in which the processing medium tends to be excessively accumulated; and if it is determined that the processing medium is in the abnormal critical region, the physical state of the processing medium being currently processed is corrected in real time by adjusting at least one execution parameter which influences the physical state of the processing medium before the processing medium being currently processed reaches a target region.

This invention relates to a method for constructing a terrain navigability cost map based on cosine soft thresholding and probabilistic fusion, belonging to the field of robot environmental perception and map building technology. It includes elevation grid construction, step height feature extraction, local slope feature extraction, roughness feature extraction, cosine soft thresholding, probabilistic OR fusion, visual semantic-assisted correction, and cost map generation. Advantages include: cosine soft thresholding allows the cost map to reflect terrain difficulty in a gradient manner; probabilistic OR fusion enables multi-dimensional safety-priority fusion; semantic-geometric joint correction reduces the terrain misclassification rate from approximately 18% to below 5%; the parameterized design of six physical parameters adapts to different robot platforms; the output is compatible with the ROS costmap_2d interface; and zero-derivative boundary conditions eliminate cost jumps in critical regions.

This invention provides a method and device for early warning of thermal runaway in MiniLED displays based on a coupling model. It involves activating multi-scale sensing nodes on the MiniLED display to collect continuous sampling records of chip junction temperature fluctuations, electro-optical conversion efficiency decay, and substrate thermal conduction differences throughout the entire operating cycle. This yields a multi-scale photoelectric and thermal time-series dataset anchored to the conduction links. Based on this dataset, a causal convolutional network is used to mine the conduction causal chains of photoelectric and thermal interactions between different stages of thermal runaway. By using reverse causal verification logic to remove pseudo-correlated sampling records, a set of cross-stage coupling-dominant causal chains is obtained. This set is then subjected to bidirectional feedback calibration to obtain a feedback-corrected coupled conduction causal network. This network drives a thermal coupling evolution model, generating a coupled-driven thermal operation evolution probability map and a dynamically updated instability critical region as the derivation process progresses. Combined with real-time sampling records from the MiniLED display, conduction causal chain matching and early warning judgment are performed to provide thermal runaway early warning. This invention effectively enhances the risk prevention and control capabilities of MiniLED thermal runaway.

The present application relates to the technical field of vertebral puncture, and particularly relates to a vertebral puncture path planning method and system using an orthopedic surgery machine, which acquires a multi-modal image parameter set of a patient's vertebral region in real time, performs three-dimensional structure feature clustering processing, and generates a vertebral structure clustering feature set. The clustering feature set is input into an adaptive spatial planning network model to dynamically predict and construct a puncture path evolution trend sequence. Based on the sequence, a risk critical region is identified, a collision warning signal is triggered and a dynamic response is monitored to obtain a path avoidance response behavior data set. Through multi-dimensional coupling analysis of the response data and the evolution trend, a high-risk anatomical region is determined to form a regional risk degree identification data set. Finally, according to the identification data, a priority is divided and adjusted to generate an adaptive path adjustment instruction set, and a precise and safe vertebral puncture path planning result is output.

A method for determining the reliability of a hypothesis about the orientation of an object near a motor vehicle is described. The method is implemented by a computer using a cluster of object detection points collected by a radar or lidar system mounted on the vehicle and at least one hypothesis about the object's orientation. The method comprises: determining the object's outline from the cluster of detection points and the hypothesis about the object's orientation; determining at least one critical zone of the object from the relative positions of the object and the vehicle; and calculating the reliability of the hypothesis based on the position of the detection points relative to the critical zone. Abstract: Figure 3b

This application provides a method and apparatus for multi-UAV collaborative detection path planning, relating to the field of UAV path planning technology. The method includes: preprocessing a 3D model to extract multiple surfaces to be detected; determining the risk level of each surface through risk assessment; dividing the projection area of ​​each surface into multiple grid cells; determining the center point of each grid cell as the detection viewpoint of the surface corresponding to that grid cell; dividing the detection viewpoint set into a critical viewpoint set and a non-critical viewpoint set based on the spatial overlap between the grid cells and high-risk surfaces; establishing a multi-objective optimized path planning model; solving the multi-objective optimized path planning model to obtain the optimal detection path sequence for the multiple UAVs. By employing the above-mentioned multi-UAV collaborative detection path planning method and apparatus, the problems of insufficient coverage and acquisition density, and low detection accuracy in critical area detection are solved.