560 results about "Target range" patented technology

The invention discloses a casting density optimization system and method based on cooperative regulation and control of molding sand moisture and clay blue absorption amount, and relates to the technical field of casting control. According to the method, a self-cleaning wear-resistant alloy probe is used for synchronously collecting a molding sand high-frequency eddy current signal and a multi-spectrum near-infrared signal in the sand mixing process; inputting a pre-training support vector machine regression signal fusion model to obtain a real-time moisture content and a clay blue absorption amount; a preset density target threshold value is combined, a density-molding sand parameter association database is inquired to determine a parameter target interval, a regulation and control instruction is generated after a deviation value is calculated, and a water adding device and a clay conveying device are controlled to adjust the use amount; the density of the casting after regulation and control is detected, if the density does not reach the standard, model output weight iteration optimization is corrected until the density reaches the standard, the system comprises a detection module, a signal processing module, a regulation and control execution module, a density detection and correction module and a central control module, closed-loop control is achieved, and the density stability of the casting is improved.

The invention discloses a target range federated cross-domain threat research and judgment method and system, and aims to solve the problems of difficulty in cross-domain threat association analysis, entity splitting and low research and judgment precision caused by incapability of sharing original security data among multiple target ranges. The method comprises the following steps: each sub-target range locally performs structured processing and high-order semantic coding on original security data to generate a standardized research and judgment intermediate representation; the central coordination node executes cross-domain entity disambiguation based on the intermediate representation, constructs a time sequence event atlas, fuses multi-source evidences through a Bayesian network, and outputs a global threat research and judgment conclusion; and the result is transmitted back to a related target range according to an authority strategy to form closed-loop feedback. The system comprises a research and judgment agent unit and a central coordination node which are deployed in each sub-target range and are used for respectively realizing local feature extraction and collaborative reasoning. According to the method, on the premise of ensuring that the original data is not out of the domain, cross-domain accurate reduction and cooperative defense of complex threats such as an APT attack chain are realized.

The invention discloses an equipment access method, device and equipment based on address space identification. The method is applied to simplifying an equipment memory management unit and comprises the steps of establishing each single-level range table; acquiring an equipment access request, reading an address space identifier and a virtual address from the equipment access request, and matching a corresponding target range table from each single-level range table based on the address space identifier; and calculating a target physical address according to the target range table and the virtual address, and establishing equipment access based on the target physical address. By replacing a traditional multi-level page table with a single-level structure, the data structure design of address mapping is simplified, the dynamic configuration complexity is reduced, and hardware formal verification is facilitated. Through direct matching of the address space identifier, the traditional steps of analyzing the equipment identity identifier and querying the external table item are omitted, and the external memory access frequency is reduced. By calculating the target physical address and establishing access, the hardware address conversion logic is simplified, the hardware implementation cost and power consumption are reduced, and the data transmission efficiency is improved.

The invention relates to the technical field of LED display testing, in particular to an LED screen backlight module performance testing system which comprises the steps that a model identification code of a module to be tested is received, a corresponding standard optical parameter set is called, and initial driving current is applied. Actual optical signals driven by different currents are collected through a light sensing probe array and converted into a digital optical measurement value set containing brightness and color coordinate values of multiple sampling points. Comparing the brightness measurement value with a target brightness value point by point to generate a brightness consistency deviation matrix; and judging the color coordinate measurement value and the target range, and generating a color coordinate qualified identifier list. And calculating an actual brightness uniformity value according to the deviation matrix, and comparing the actual brightness uniformity value with a standard threshold value. And if the actual brightness uniformity value reaches the standard and the color coordinates of all the sampling points are qualified, generating a module qualification judgment instruction. According to the system, automatic and high-precision comprehensive evaluation of brightness space uniformity and chromaticity consistency of the backlight module is realized.

The invention provides a method and device for controlling vehicle functions, a vehicle and a storage medium, and relates to the technical field of vehicle function control. According to the method, function control information is determined, an analysis object can be clearly analyzed, and introduction of irrelevant data in the initial stage is avoided. Information redundancy needing to be processed by the preset large model is reduced from the source, and a foundation is laid for subsequent efficient analysis. And further performing semantic analysis on the function control information according to a layer-by-layer screening mode through a preset large model and a vehicle function formed based on a vertical progressive layered structure. According to the hierarchical structure, the preset large model does not need to traverse all vehicle functions, and each layer only focuses on the function of the corresponding layer, so that the number of functions needing to be processed by the preset large model can be greatly reduced, and the consumption of lexical elements is directly reduced. Meanwhile, layer-by-layer screening replaces one-by-one reasoning, the target range of each layer is rapidly narrowed, and all vehicle functions do not need to be analyzed one by one. The path for determining the function of the target vehicle can be remarkably shortened, and the determination efficiency is improved.

The invention relates to the technical field of vehicles, in particular to a collaborative decision-making system and method under mixed traffic flow, a vehicle and a storage medium, and the method comprises the steps: obtaining the traffic environment information under the mixed traffic flow in a target range through a roadside sensing unit, and calculating the behavior intention probability of a manual driving vehicle through a preset intention prediction model; a vehicle end decision-making unit is utilized to construct, adjust and expand a perception domain based on traffic environment information and behavior intention probability in combination with vehicle-mounted sensor data, generate a risk constraint trajectory and a collaborative decision of the vehicle, and re-plan a driving path of the vehicle; and the cloud optimization unit is used for updating a preset intention prediction model, receiving traffic environment information, reconstructing an area-level traffic situation under mixed traffic flow, and transmitting optimized signal timing and formation parameters to the road side sensing unit and the vehicle end decision-making unit. Therefore, the problems of single adaptability of a traffic collaborative decision-making scene, no fusion of real-time road side data and the like in related technologies are solved.

The invention discloses a continuous spinning path coordination system based on real-time tension regulation and control, relates to the technical field of spinning tension control, and is used for solving the problem of poor continuous path tension coordination regulation. The method comprises a path modeling module, a state acquisition module, a coordination control module and a strategy optimization module, and comprises the following steps: establishing a path structure model from spinning to winding, planning tension measuring points, generating state vectors, identifying drafting section disturbance, winding section disturbance and local friction disturbance, and predicting the tension change of each path node in combination with a tension conduction time delay parameter; a control combination is generated among a drafting drive unit, a winding drive unit, a tensioning unit and a belt drive yarn guide component, cooperative adjustment of an execution unit is achieved, a strategy optimization module establishes a statistical relation between tension and quality based on end breakage and quality detection results, a tension target interval is updated in a self-adaptive mode, and the execution unit adjusts constraints and priorities. The end breakage rate is reduced, and the stability and the product consistency are improved.

The invention provides a single photon and visible light image fusion method and system based on a multi-scale Markov random field model, and belongs to the technical field of multi-modal image fusion. In the long-distance target ranging and imaging process, a multi-sensor fusion method is used, the high resolution advantage of a visible light intensity image is utilized, the problems that a single-photon laser radar is small in point cloud density and low in image resolution are effectively solved, and the sensing capacity of the single-photon laser radar for scene target information is effectively enhanced; by using the fusion method based on the multi-scale Markov random field model, the structural consistency and the anti-interference capability are enhanced, global structural deviation or local overfitting under a single scale is effectively avoided, and the method is suitable for image fusion under multi-modal and complex scenes.

The invention provides a TSN time synchronization method based on dynamic jitter compensation and double-clock domain collaboration, which comprises the following steps: in a single clock domain, carrying out real-time analysis on a time difference of a synchronization message and dynamically compensating clock jitter so as to establish a high-precision local synchronization reference; based on a local synchronization reference, performing time information interaction and weighted fusion with at least one other clock domain to generate system-level global reference time, and calibrating a local clock to realize time collaboration across the clock domains; predicting a future change trend of the network delay, and pre-adjusting a dynamic compensation and / or time information interaction strategy according to a prediction result; dynamic compensation, time coordination and pre-adjustment are mutually coupled and have a synergistic effect, so that the time synchronization precision of the system is maintained in a predetermined target range, clock jitter in a single clock domain is effectively inhibited, the synchronization precision is controlled within 20ns, and the strict requirements of the fields of industrial control, automatic driving and the like on high-precision synchronization within 20ns are met.

The invention relates to the technical field of semiconductor testing, in particular to a power semiconductor device testing method, system and equipment and a storage medium, and the method comprises the steps: collecting the current temperature data of a to-be-tested device in real time, and comparing the current temperature data with a test target temperature value, so as to judge whether the target temperature is too high or too low; the real-time feedback data is compared with the target value to judge whether the heating operation or the cooling operation should be executed, so that control guidance is provided for temperature adjustment; after the heating or cooling operation is judged to be carried out, the electric heating unit and the electric cooling unit are driven to carry out dynamic adjustment, so that the temperature of the device is stabilized in a minimum fluctuation interval near the target temperature, and the stability of the test temperature is ensured; after it is confirmed that the temperature is stabilized in the target range, the test unit is triggered to apply excitation to the to-be-tested device in a specific mode, test errors generated due to temperature fluctuation or the fact that the target temperature is not reached are eliminated, and test results of different batches and different times have high comparability.

The invention discloses an impedance matching method and system for chip testing, electronic equipment and a medium, and relates to the technical field of data processing. The method comprises the following steps: establishing electrical connection between a test probe and a to-be-tested chip test point, and sending a preset detection signal; acquiring incident power and reflection power of the detection signal; calculating a first signal reflection coefficient based on the incident power and the reflection power, and determining an impedance deviation value and an adjustment direction according to a difference value between the first signal reflection coefficient and a preset standard reflection coefficient; determining a parameter adjustment step length according to the impedance deviation value; sequentially adjusting a variable resistor, a variable capacitor and a variable inductor in the impedance matching network according to the step length and the adjusting direction; detecting a second signal reflection coefficient when the impedance real part and imaginary part of the variable element reach the target range; and judging whether the second signal reflection coefficient converges to a preset range, and if yes, taking the current matching network parameter as an impedance matching result. By implementing the technical scheme provided by the invention, the impedance matching accuracy of the chip test can be improved.

The invention relates to the technical field of laser welding, and discloses a laser welding thermal deformation compensation device based on infrared temperature measurement feedback, which comprises a conveyor belt, a preheating cabin, a laser welding head and a controller. A front infrared temperature detector and a rear infrared temperature detector are respectively arranged in front of and behind a laser welding head to measure the temperature in front of and behind a welding point in real time, and the temperature rise is calculated by a controller; and the controller compares the temperature rise with a preset target range, the output power or the welding speed of the laser welding head is dynamically adjusted through closed-loop feedback control, and accurate control over welding heat input is achieved so as to compensate thermal deformation. The device is further integrated with a cleaning assembly composed of a high-definition camera and a rolling brush, and stains on the surface of the workpiece can be automatically recognized and removed before welding. And meanwhile, a dust collection mechanism is arranged and used for collecting welding smoke dust. Thermal deformation can be effectively restrained, the welding precision and the joint quality are improved, and the working environment is improved.

A system for longitudinal assessment of nerve health includes a stimulator to deliver electrical stimuli proximate a target nerve, a sensor to detect muscle responses evoked by the stimuli, a display, and a processor in communication with the stimulator, sensor, and display. The processor controls delivery of the stimuli; determines, from the detected muscle response, one or more nerve-function parameters for the target nerve including at least a stimulation threshold; stores the parameters with a session identifier; retrieves parameters from multiple sessions to compute a longitudinal trend; and controls the display to present the trend together with an indication of the target nerve's status relative to a target range. The system supports objective session-to-session tracking to inform clinical decisions.

The invention discloses an AUV local obstacle avoidance path planning method, device and equipment and a storage medium, and relates to the field of path planning of an AUV, and the method comprises the steps: obtaining the minimum turning radius, the movement speed, the radius of an obstacle and the distance between the center of the obstacle and a route of the AUV, and carrying out the calculation to obtain the minimum obstacle avoidance distance; calculating the unblocked path length from the current position of the AUV to the obstacle encountered for the first time along the route as a free distance; comparing the free distance with the minimum obstacle avoidance distance, and determining the running state of the AUV according to a comparison result; in the obstacle avoidance state, generating a target range containing a target point on the priority obstacle avoidance side; and with the current position of the AUV as a starting point and a plurality of sampling points in the target range as terminal points, planning candidate obstacle avoidance paths corresponding to the sampling points, and selecting a path with the shortest total length as a target local obstacle avoidance path. According to the method, the accuracy of local obstacle avoidance path planning of the AUV can be improved.

The invention discloses a road traffic network safety target range construction method based on an MCP protocol. The method belongs to the technical field of network security simulation. According to the method, automatic access and management of various target range services are realized through registration and discovery of an MCP server; a user triggers target range construction through an application layer instruction, and an intelligent decision-making layer automatically plans a test task by means of a large language model (LLM), dynamically calls simulation and attack resources and completes test chain execution. In the process, a monitoring system collects multi-dimensional data such as traffic flow, equipment state and abnormal flow in real time, all related information is aggregated after the test is finished, a structured safety evaluation report is generated through LLM comprehensive analysis, and the physical influence of attacks on the environment is evaluated. The system supports environment one-key destruction and reconstruction, the reusability and safety of a target range are guaranteed, and automatic and intelligent testing and evaluation of road traffic network safety are achieved.

The invention discloses a light weapon shooting training intelligent target range data processing method and system, and relates to the technical field of target range data processing, and the method comprises the following steps: constructing a nanosecond-level unified time baseline, and carrying out the synchronous collection of multi-source sensing signals of a shooting training target range through a high-resolution optical array and an acoustic sensing matrix, and performing time synchronization and delay compensation on each sensing signal through a phase alignment mechanism to form a unified sensing base plane for multi-target recognition. According to the method, high-precision synchronous acquisition and interference feature stripping are realized by constructing a nanosecond-level unified time base line and fusing multi-source sensing, and the target distinguishing and recognition precision under a complex background is remarkably improved; and meanwhile, a space-time coupling identification and anti-fact playback mechanism is combined, a dynamic credibility map is generated, phase conjugate regulation and control are implemented, an identification and correction closed loop is formed, misjudgment and drift are effectively reduced, and stable tracking and continuous identification in a multi-target scene are ensured.

The invention provides a radar multi-target tracking and imaging echo simulation method and system, and belongs to the technical field of radar echo simulation. The method comprises the following steps of: pushing the position and the motion state of a radar platform and RCS point set data of a plurality of targets to an impact function generation FPGA (Field Programmable Gate Array), and latching data through the FPGA to form a multi-target data set when a radar signal is detected; point set data, postures and world coordinates of the targets in the multi-target data set are split into a plurality of calculation instances, sub-range profile data of each calculation instance are calculated in parallel, the sub-range profile data of the multiple calculation instances are merged and superposed into range profile data of a single target, similarly, range profile data of all the targets are calculated in parallel, and the range profile data of all the targets are calculated in parallel; and after obtaining multi-target range profile data, carrying out convolution on the multi-target range profile data and a radar signal, after obtaining a convolution signal, carrying out signal delay and multi-branch amplitude-phase modulation, and outputting the amplitude-phase modulated convolution signal. According to the invention, signal echo simulation can be carried out in parallel pipeline, and high-quality large-scene echo signals are output.

The invention relates to the technical field of cell culture, and discloses a stem cell differentiation degree identification method based on image features. The method comprises the following steps: continuously capturing multi-temporal image data in a stem cell culture process through a high-resolution microscopic imaging system, and generating an image and environment synchronous data set; processing the data set, extracting dynamic morphological features and texture change modes of the stem cells, and constructing a fusion feature set; outputting a differentiation process index based on the fusion feature set; a differentiation degree grade division rule is set, and a differentiation process index and differentiation grade mapping table is established; in a real-time application stage, acquiring real-time imaging data and environment readings, and inputting the real-time imaging data and the environment readings into an evaluation network to calculate real-time differentiation process indexes; querying the mapping table according to the real-time index to obtain a differentiation grade judgment result; comparing the judgment result with a preset target range, and if the judgment result falls into the target range, automatically executing differentiation state marking and culture parameter adjusting operation.

The invention discloses a distributed training method for a new energy cluster power prediction model. The method comprises the following steps: collecting time sequence data of each power station in a target range, and carrying out abnormal data detection, deletion and missing data filling operation; constructing a basic structure of a power prediction model corresponding to the edge nodes, the regional coordination nodes and the global center node in the target range, and initializing model parameters; performing regional adaptation fine tuning on training data of the edge nodes, performing iterative training on a power prediction model of the edge nodes to obtain local model parameters of each edge node, performing regional aggregation and global aggregation on the local model parameters of each edge node to obtain a power prediction model of each edge node; obtaining model parameters of power prediction models corresponding to the regional coordination nodes and the global center node; and carrying out convergence judgment on the model parameters corresponding to the global center node, if the model parameters converge, stopping iterative training, and if the model parameters do not converge, executing next iterative training, so that engineering practicability and expandability are considered.

The invention discloses a self-adaptive updating method and device for a range hood parameter control model, and the method comprises the steps: collecting the current multi-dimensional scene parameter information corresponding to a current scene where a target range hood is located, and collecting the historical multi-dimensional scene parameter information corresponding to the current scene; based on the current multi-dimensional scene parameter information and the historical multi-dimensional scene parameter information, determining a target smoke discharge demand; judging whether the target smoke exhaust demand is matched with an initial smoke exhaust demand corresponding to a predetermined initial range hood parameter control model or not; and if not, performing model adjustment operation on the initial range hood parameter control model based on the current multi-dimensional scene parameter information and the historical multi-dimensional scene parameter information to obtain a matched target range hood parameter control model. It can be seen that by implementing the method and device, self-adaptive updating of the range hood parameter control model can be achieved, and the accuracy and intelligence of the generated range hood parameter control model and the experience feeling and comfort of a user using the range hood can be improved.

A continuous nanoparticle processing system includes a continuous flow path between an inlet and an outlet. The system has at least one sensor positioned to generate a signal indicative of a quality attribute of nanoparticles within the flow path, at least one actuator coupled to the flow path; and a controller operatively coupled to the sensor and the actuator and configured to, during operation, adjust the actuator in response to the signal to maintain the quality attribute of the nanoparticles within a target range while the nanoparticles traverse the flow path. A computer program product is disclosed.

The invention discloses a target range-oriented data acquisition and analysis method and system and a storage medium. The method comprises the following steps: acquiring action posture information, physiological state information, environment state information and shooting hit information of a trainer; training effect analysis is conducted on the obtained action posture information, physiological state information, environment state information and shooting hit information, and evaluation indexes are generated; and through a large language model technology, a personalized automatic evaluation report is generated based on the evaluation indexes. According to the method, the trainee can obtain accurate feedback in real time in the training process, meanwhile, training effect analysis greatly improves the shooting training efficiency and individuation level, various information data in the shooting training process can be comprehensively collected and analyzed, the trainee is helped to know the training state, progress and defects of the trainee in real time, and the training effect is improved. And a personalized automatic evaluation report is provided according to an analysis result, so that a more efficient shooting training effect is finally realized.

The invention discloses an automatic penetration test path planning method and system based on agent collaboration, and relates to the technical field of network security. Performing initialization starting on the plurality of intelligent agents based on the penetration test target range; collecting the target system and writing the target system into a shared blackboard mechanism; matching the asset feature information with a preset vulnerability knowledge base according to the test strategy mode to generate vulnerability utilization conditions, and constructing a global attack graph according to the asset feature information and the vulnerability utilization conditions; generating an attack path based on the global attack map, executing an attack operation on the target system according to an attack step sequence of the attack path, when an execution result is failure, updating the global attack map according to a feedback failure result, and re-planning to generate a new attack step sequence; and when the execution result is successful, generating a penetration test report for the penetration test target range according to the success result. By implementing the method, the actual demand of deep security assessment of the complex heterogeneous system is met.

This invention proposes a method and apparatus for processing AI target instances in an artificial intelligence security training range. First, an AI training cluster is constructed based on the requirements of the training task. During attack and defense exercises, the operating status, system resource usage, and AI security risks of multiple AI target instances in the cluster are monitored in real time from multiple dimensions. When a security anomaly is detected in an AI target instance, an adaptive adjustment operation is triggered. This involves selecting a candidate instance from a pre-set AI target library that meets the requirements of the current training task to replace the abnormal instance, or switching the traffic of the abnormal instance to a healthy instance, and generating corresponding alarm information. This invention achieves dynamic load balancing and fault self-healing capabilities with AI perception, significantly improving the realism, robustness, and efficiency of the training environment.

The invention relates to the technical field of UWB range finding, and discloses a UWB range finding method, a base station, a UWB positioning method and a UWB system.The UWB range finding method comprises the steps that CIR information of a target label is acquired, first-path preliminary detection is carried out on the CIR information, and an initial first-path index is obtained; obtaining an energy characteristic, a slope characteristic and a peak value characteristic according to the CIR information and the initial first path index; according to the energy characteristic, the slope characteristic and the peak value characteristic, carrying out first diameter secondary detection to obtain a first diameter detection result; and performing correction or calculation according to the first diameter detection result to obtain a target distance measurement value. According to the invention, the ranging and positioning precision of the UWB technology in a complex indoor environment can be improved, the error is reduced, and the system stability is improved.

The utility model relates to a kind of pool automatic cleaning equipment, the pool automatic cleaning equipment includes equipment main body, height adjusting structure and image acquisition device;The image acquisition device is installed in the equipment main body by the height adjusting structure, the equipment main body is cleaned in the process in pool, the height adjusting structure can make the position of the image acquisition device elevated, to make the image acquisition device can gather the environmental image around the equipment main body.Image acquisition device after position elevation is no longer blocked by equipment main body, blind area reduces, visual range is no longer limited to the side of equipment main body, and can be expanded to the environmental image around equipment main body.Further, when local object identification can expand target range, efficiently plan cleaning path, improve the garbage cleaning efficiency and endurance time of machine.

The problem to be solved by the present invention is to provide a spot welding spatter detection method that can detect spatter generation without resetting the voltage detection line. To solve the above problem, in the spot welding method, a pulsed waveform welding current is provided to the workpiece by alternately performing the following steps in multiple cycles: a step of maintaining the welding current within a set peak current range; a step of decreasing the welding current from the peak current range towards the bottom current, and then increasing the welding current towards the peak current range when the effective value of the welding current reaches a set target range. In the spatter detection method, the pulse widths IW(1), IW(2), ... of the pulsed waveform in each cycle are measured. If the pulse width difference D(M) = IW(M) - IW(M-1) between the pulse width IW(M) in the target cycle (the Mth cycle) and the pulse width IW(M-1) in the previous cycle exceeds a width threshold Dth, then the generation of spatter is detected.

An example includes receiving a read request specifying a target range and a target checkpoint, and executing a first query to retrieve a first entry of a metadata table. The first entry is a most recent entry of those entries that are older than the target checkpoint and record write ranges overlapping the target range. The example also includes, if the write range in the first entry does not cover all of the target range, determining a remaining portion of the target range that excludes the write range in the first entry. The example also includes executing a second query to retrieve a second entry of the metadata table, where the second entry is a most recent record in a second subset of entries that are older that the target checkpoint and record write ranges overlapping the remaining portion of the target location range.

The invention discloses an intelligent analysis method and system for operation data of an electric power communication network, and relates to the technical field of data management.The method comprises the steps that firstly, time-frequency feature extraction and resonance cumulative effect judgment are conducted on optical cable link node signals of a voltage class area, so that an area possibly causing abnormal oscillation can be accurately locked; a target range is provided for subsequent modeling; secondly, a deviation factor is extracted on the basis of disturbance propagation dynamic response between simulation nodes, dynamic physical model parameters of the power communication network are corrected in real time, and the model is made to be closer to the actual operation state; and finally, fusing the corrected physical model with a machine learning model, and realizing active suppression and pre-adjustment dynamic state according to the disturbance response sensitivity and resonance triggering probability of the node, thereby optimizing the operation stability and anti-interference performance of the power communication network. Not only is the intelligent processing capability of the operation data of the power communication network improved, but also the precision and response speed of the system in the aspects of resonance risk early warning and oscillation source positioning are remarkably enhanced.

Examples of the present disclosure include a method for approximating a non-carth imaging camera model for a non-earth sensor includes obtaining a physical camera model, receiving a target range value, determining a plurality of space-based coordinates of a plurality of points about a line of sight of the sensor in proximity to a distance corresponding to the received target range value, for each of the plurality of locations, determining line and sample coordinates on an image thereof via the physical camera model based on the space-based coordinates of the plurality of points, and based on the determined line and sample coordinates for each of the plurality of points, fitting an approximate camera model thereto.