8results about How to "Reduce Simulation Costs" patented technology

The invention provides an XR glasses total factor fusion simulation verification platform building method, and belongs to the technical field of airborne simulation cockpit display, and the method comprises the steps: building a simulation environment sensor system working model, and obtaining sensor system model data; dividing working modes of the XR glasses according to the flight scene; constructing a simulation environment man-machine interaction and control model; based on sensor system model data and a simulation environment man-machine interaction and control model, a simulation verification environment corresponding to all XR glasses working modes is built, and an XR glasses total factor fusion simulation verification platform is built. A verification platform built by the method realizes fusion display function simulation of airborne sensor data in the XR glasses, and a total factor simulation model of the XR glasses is built; the real flight and man-machine interaction process of the fighter can be simulated, and the real degree of the simulation verification process is improved; the simulation cost can be reduced, and the pre-research function can be conveniently verified.

This invention discloses a load scheduling architecture based on fractal topology, comprising self-similar fractal units, each with multiple load sensing points. When some sensing points are triggered, local load splitting is performed; when all sensing points are triggered, a load splitting mode switch is executed. The unit as a whole moves and simultaneously sends trigger signals to adjacent units through all sensing points, activating topological force flow ripples, causing the load to propagate step-by-step along the fractal hierarchy. This invention also discloses applications of this architecture in computer resource scheduling, integrated circuits, micromaterials, and mechanical simulation. This invention overcomes the traditional technical bias of "avoiding dead points" and achieves decentralized adaptive load scheduling.

The invention discloses a rapid expansion cloud chamber environment simulation method and system based on artificial intelligence, and the method comprises the steps: obtaining the experimental data and experimental conditions of a to-be-simulated expansion cloud chamber, carrying out the structural classification based on the experimental data according to the experimental conditions and expansion stages, and obtaining the feature vector of each stage, meta learning is carried out through a neural network according to the feature vectors, a cloud simulation model and simulation errors are obtained, a cloud chamber working condition interval is identified based on the simulation errors and experimental data, an output result of the cloud simulation model in a high-deviation interval is obtained according to the working condition interval, and an interval result is corrected through a CFD equation based on the output result. And obtaining a cloud room environment simulation result. According to the method, the cloud expansion stage is split, the fog drop growth process is fitted, CFD local correction is carried out on the simulated high-deviation interval, the prediction error control precision is improved, the prediction and collaborative analysis efficiency of the fog forming process in the complex environment is improved, and meanwhile good interpretability is achieved.

The invention provides a chip particle interconnection interface clock and power decoupling system, a chip particle, a chip system and a power consumption management method. The system comprises a main band module and a sideband module which are physically separated, the main band module comprises a main band PHY and a main band controller, the sideband module comprises a sideband PHY and a sideband controller, the main band module and the sideband module have independent power domains, a power supply of the main band module can be turned off to realize low power consumption, and a power supply of the sideband module is always kept on. The main band responsible for high-speed data transmission and the sideband responsible for control management are thoroughly separated in physics, clock and power supply, the layout is flexible, the difficulty and cost of chip rear-end design, advanced packaging design and signal / power supply integrity analysis are remarkably reduced, and meanwhile refined power consumption control is achieved.

The utility model belongs to the technical field of flight confrontation simulation, and particularly discloses a flight confrontation simulation device, which comprises a control module, a front control module, a left control module and a right control module, and is characterized in that the front control module comprises a front frame, a front middle display screen, a front left display screen, a front right display screen, a head-up display, a left pedal and a right pedal; the left control module comprises a left frame, a rocker and a left display screen, the right control module comprises a right frame, a pull rod and a right display screen, a plurality of windows are formed in the upper sides of the left frame and the right frame, and the display screens are divided into a plurality of display areas. According to the utility model, the display screen is used for simulating a display instrument in the cabin of the fighter, and a plurality of windows are formed on the upper side of the frame to simulate one display screen into a plurality of instruments, so that the simulation cost of the fighter is effectively reduced on the premise of realizing accurate simulation. Meanwhile, different display instruments can be flexibly simulated by modifying the content displayed by the display screen, so that different models are simulated, and the simulation training cost is further reduced.

The invention belongs to the field of automatic control technology and multi-agent system cooperative control, and particularly relates to a multi-agent system fault-tolerant inclusion control method and system based on a neural network, and the control method comprises the following steps: S1, constructing a second-order multi-agent system; s2, constructing a full connection-fuzzy neural network; performing high-precision online fitting and approximation on non-ideal factors in the second-order multi-agent system to generate corresponding compensation items; s3, constructing a fixed time state observer, and estimating unknown position states and speed states of all the following intelligent agents within a preset time upper limit irrelevant to the initial state of the system; s4, constructing a fixed time sliding mode control law based on the estimation state and the compensation item; and S5, applying a fixed time sliding mode control law to the following agents, so that all the following agents converge and are stabilized in a dynamic convex hull formed by a plurality of leader states within a fixed time, and realizing inclusion control. According to the invention, the risk in practical application can be effectively reduced.

The application discloses a rapid expansion cloud chamber environment simulation method and system based on artificial intelligence, comprising: obtaining experimental data and experimental conditions of a to-be-simulated expansion cloud chamber, structurally classifying according to the experimental conditions according to the expansion stages based on the experimental data, obtaining feature vectors of each stage, carrying out meta-learning through a neural network according to the feature vectors, obtaining a cloud and fog simulation model and a simulation error, identifying a cloud chamber working condition interval based on the simulation error and the experimental data, obtaining an output result of the cloud and fog simulation model in a high deviation interval according to the working condition interval, correcting interval results through a CFD equation based on the output result, and obtaining cloud chamber environment simulation results. The method splits the cloud and fog expansion stages, fits the fog droplet growth process, carries out CFD local correction on the simulation high deviation interval, improves the prediction error control precision, improves the prediction and collaborative analysis efficiency of the fog formation process in a complex environment, and has good interpretability.

The utility model relates to a vehicle-mounted weighing device, which comprises a pressure data acquirer, a vehicle-mounted weighing controller and a display, the pressure data acquirer comprises a plurality of suspension embedded pressure sensors, the suspension embedded pressure sensors are uniformly arranged on a vehicle suspension, and the suspension embedded pressure sensors are electrically connected with the vehicle-mounted weighing controller through cables with shielding layers; the vehicle-mounted weighing controller is fixed to the inner wall of a vehicle cab, the displayer is embedded into a center console of a vehicle, and the vehicle-mounted weighing controller is connected with the displayer through a CAN bus interface. The pressure data acquisition device acquires pressure data borne by the current vehicle and sends the pressure data to the vehicle-mounted weighing controller; and the vehicle-mounted weighing controller reads the pressure data, sends the pressure data to an external data platform by using an internal communicator, and sends the returned load data to a display for displaying. The device can break through technical bottlenecks among data accuracy, operation and maintenance efficiency and working condition adaptability.