67 results about "Target acquisition" patented technology

The present application relates to a kind of cross-instrument LIBS spectrum cross-calibration method.Compared with prior art, it comprises the following steps: extracting the LIBS spectrum of reference spectrum and to-be-calibrated spectrum in the same wavelength range channel, using data interpolation method for data processing;Calculate the conversion relationship of spectral intensity unit, convert the intensity unit of to-be-calibrated spectrum to the intensity unit of reference spectrum;Calculate the intensity ratio of LIBS spectrum obtained on the same target pixel by pixel, and use the ratio to correct the intensity of to-be-calibrated spectrum;With reference spectrum as reference, the spectral peak position of to-be-calibrated spectrum is corrected.The present application protects the spectral shape of to-be-calibrated data, avoids the loss of characteristic peak, can be applied to different types of LIBS equipment, corrects the intensity difference caused by instrument parameters and detection environment, improves the consistency of characteristic peak position before and after cross-calibration, reduces the influence of instrument parameters and detection environment difference on characteristic peak position difference.

This invention relates to the field of fast reflector technology, specifically to a two-dimensional large-angle fast reflector device based on a PCB eddy current sensor. The device includes: a flexible support assembly that enables the reflector assembly to deflect in a two-dimensional direction, and which, after angular displacement, returns to its original position through elastic deformation; and an eddy current sensor probe comprising multi-layer coils printed on an eddy current circuit board, with each pair of probes symmetrically arranged on the board. This invention, through the flexible support assembly and a moving-magnet drive structure, enables the reflector assembly to achieve large-angle deflection in two orthogonal directions. Compared to traditional micro-angle deflection structures, the maximum deflection angle is significantly increased, covering a wider field of view, making it suitable for applications such as large-field-of-view scanning, rapid target acquisition, and wide-angle beam control.

This characteristic distribution system comprises: an existing amount acquisition unit that acquires the existing amount that can be distributed to an intermediate product manufactured from a raw material including a characteristic material having at least a specific characteristic and that includes an amount less than or equal to the upper limit value according to the total use amount of the characteristic material for use in manufacturing the intermediate product during a prescribed period; a target acquisition unit that acquires a distribution target intermediate product or the intermediate product and the amount; and a distribution unit that executes distribution processing for distributing at least a part of the existing amount to the acquired distribution target intermediate product.

This disclosure provides a processing method, apparatus, computer device, and storage medium for an input method application. The method acquires interaction smoothness optimization instructions for the input method application; collects input event response time and page rendering time within a target acquisition period; performs application stuttering detection on the input method application based on the input event response time and page rendering time, obtaining stuttering detection results; when the stuttering detection results indicate that the input method application experiences stuttering, acquires hardware configuration data and load information of the target terminal; determines multiple target optimization operations from multiple smoothness optimization operations based on the hardware configuration data and load information; and modifies the settings of the input method application based on the multiple target optimization operations. This method can improve the detection efficiency of application pages. This method can improve the stuttering problem of input method applications.

This application relates to the fields of intelligent hardware and environmental monitoring technology, and particularly to a protocol processing method, apparatus, device, storage medium, and computer program product for environmental monitoring equipment. The method involves obtaining resource configuration information and corresponding protocol configuration information for a target acquisition channel; determining the target protocol plugin associated with the target acquisition channel based on the protocol configuration information; loading the target protocol plugin and initializing it according to a preset interface specification to establish a calling relationship between the target protocol plugin and the target acquisition channel; acquiring device interaction data based on the target acquisition channel and calling the target protocol plugin to perform protocol parsing processing on the device interaction data to obtain corresponding standardized data; sending the standardized data to a message bus for external modules to subscribe to; and dynamically updating the target acquisition channel and / or the target protocol plugin in response to configuration change or upgrade commands.

The application relates to a classification method and device based on microwave and laser radar observation data association features. The method comprises the following steps: an association feature learning network is constructed according to a feature decomposition autoencoder structure of a P3S network and a twin neural network, and the association feature learning network is trained, so that the association feature learning network can extract association features of observation data acquired by multiple sensors for multiple targets, and target classification is performed based on the association features of the multiple observation data. The method can effectively improve the accuracy of target classification.

The application relates to the application packaging technical field and provides an application packaging method based on regional differences and related equipment. The method comprises the following steps: receiving an application compiling request carrying a target region identifier, and identifying an application compiling target based on the application compiling request; obtaining server configuration data based on the application compiling target; performing checking processing on the server configuration data, packaging the processed server configuration data, and obtaining an application installation package corresponding to the target region identifier. The method can meet the regional difference requirements of application packaging and reduce the error rate.

This invention provides a method for identifying low-speed, small targets using radar echoes based on optical flow. The method includes receiving radar echo data in real time and redrawing the images to form a series of multi-frame radar echo images; using the pyramid LK optical flow method, sequentially performing layered analysis on the formed multi-frame radar echo images to obtain the optical flow vector of each frame; comparing the optical flow vectors of each frame to determine dynamic and static targets in each frame; and based on the dynamic and static target identification results fed back by the radar, determining whether one or more dynamic targets in each frame have not been identified by the radar. If so, the unidentified dynamic targets in each frame are considered low-speed, small targets before being acquired. Implementing this invention solves the problem of insufficient radar detection capability for low-speed, small targets and improves target acquisition efficiency.

This invention discloses an intelligent detection method for ecological violations in water source protection areas based on multi-source heterogeneous remote sensing spatiotemporal collaborative perception. The method includes: acquiring time-series data of medium-resolution multispectral satellite imagery and high-resolution imagery data; calculating spectral indices and establishing ecological base fingerprints based on the medium-resolution time-series data, and extracting suspected change hotspots through time-series anomaly detection; employing a cross-scale guided Transformer to perform cross-attention fusion using high-resolution texture features as queries and medium-resolution spectral features as keys and values; using a semantic segmentation network with distance field constraints to perform pixel-level fine segmentation of the violations; and vectorizing the segmentation results and overlaying them with the protection area zoning for analysis, outputting compliance assessment results. This invention employs a cascade mechanism of macroscopic scanning-targeted acquisition-fine analysis, significantly reducing monitoring costs, achieving effective identification of camouflaged targets, supporting high-frequency, routine integrated land-water monitoring, and meeting the operational needs of hierarchical management of water source protection areas.

The application provides a photoacoustic tomography system, method and computer program product. The system comprises a photoacoustic signal acquisition device and a controller; the controller is configured to acquire a structure image by using the photoacoustic signal acquisition device; the structure image is obtained by two-dimensional photoacoustic image reconstruction on photoacoustic information of a target region; image feature extraction and frequency domain processing are performed on the structure image to obtain a frequency domain feature vector; error data between an actual acquisition position and a target acquisition position of a photoacoustic probe of the photoacoustic signal acquisition device is calculated according to the frequency domain feature vector, and the pose of the photoacoustic probe is adjusted according to the error data to lock the target region. Through low-frequency coefficient selection and an adaptive adjustment strategy, the application automatically suppresses high-frequency noise, enhances the anti-interference ability of the image feature extraction process to a complex environment, and thus improves the overall robustness and reliability of the visual servo system.

The application provides an AI image recognition and high-speed tracking cooperation method and system, relates to the technical field of image recognition and tracking, and comprises the following steps: a radar guides a photoelectric turntable to shoot an unknown target, and acquires an AI image; based on an environment situation awareness baseline established adaptively, a white list target is removed from the image, and a target data set with a situation energy label is obtained; a cosine similarity of a pixel point and a preset feature is calculated, and a heat map image is generated; a target area is located in the heat map, a multi-scale feature vector is generated by using a multi-scale feature generation algorithm, and a feature matching degree is obtained by comparing the multi-scale feature vector with a target template library in layers; whether the target is a target to be intercepted is determined based on the matching degree, and a future track of the target is predicted; according to the predicted track and a threat level, an interception device is distributed, and a 3D interception network is formed through inter-machine communication, so that the target enters a capture range. The application can realize dynamic tracking and efficient interception, and improve the response speed and accuracy of airspace safety protection.

This invention discloses an adaptive spatial filtering method to reduce the false alarm rate in laser ranging. An adaptive spatial filtering module is introduced into the laser ranging system. A real-time sky background noise acquisition module detects changes in sky background light intensity and feeds this information back to the control system for immediate response. Based on the acquired control signals, a receiving field-of-view control module enables automatic control of a series of mechanisms and circuits. A variable aperture with adjustment function limits the background noise entering the laser ranging system; when the background light radiation intensity is high, the aperture diameter decreases, and vice versa. This design is simple in structure, easy to operate, stable, and highly automated. It not only balances the system's target acquisition capability and noise suppression capability but also has good adaptability, allowing for real-time, intelligent, and efficient adjustment of system structural parameters according to observation conditions, thereby improving system stability and automation.

This application provides a remote operation and maintenance method and apparatus for intelligent weighing equipment. The method includes: acquiring initial acquisition data collected by a signal acquisition device and initial operating data corresponding to the intelligent weighing instrument; the initial acquisition data includes a initial dual-path force measurement data from a dual-redundant sensor and initial signal trigger data from a vehicle separator; preprocessing the initial acquisition data and initial operating data respectively to obtain target acquisition data and target operating data; determining a target state frame based on the target acquisition data and target operating data, and sending the target state frame to the operation and maintenance application layer; receiving a target remote control command from the operation and maintenance application layer in response to the target state frame; and controlling the weighing sensing layer to perform fault recovery operations according to the target remote control command to achieve rapid diagnosis and recovery. Through end-to-end data acquisition and closed-loop processing of remote commands, the efficiency of remote diagnosis and rapid recovery of weighing equipment is improved.

The application provides a sensor array Internet of Things system, method and medium for pipe network structure checking. The system comprises a pipe network operation management platform; the pipe network operation management platform is configured to: perform at least one pressure disturbance based on at least one set of disturbance parameters; acquire pressure response data corresponding to the at least one pressure disturbance; determine a pipe connection relationship based on the pressure response data and a current pipe network atlas; determine an updated pipe network atlas and update information based on the pipe connection relationship and the current pipe network atlas; determine a target sensor and a target acquisition parameter based on the update information; and control the target sensor to collect information of an updated area based on the target acquisition parameter.

The application relates to the technical field of network security, and discloses an application running protection method based on a large model semantic, which comprises the following steps: based on a semantic perception probe, a target API in the runtime of an application to be protected is intercepted, and a target thread is obtained; based on the target thread, original behavior data of the application to be protected is obtained, the data is desensitized, and structured prompt data is obtained; whether the structured prompt data deviates from a normal business intention is analyzed by using a preset security large model, and a risk probability score is obtained; if the risk probability score is greater than a preset score threshold, the target API is blocked, data features of the original behavior data are extracted, and malicious attack data features are obtained; the semantic perception probe is optimized according to the malicious attack data features, an optimized perception probe is obtained, and the application to be protected is protected by using the optimized perception probe. The application also provides an application running protection system based on a large model semantic, equipment and a storage medium. The application can improve the protection level of an application system.

The present disclosure provides a display method and an electronic device, which are applied to the technical field of terminals. The display method comprises the following steps: in response to detecting a change event in which state information of a target acquisition sensor is changed, if the change event meets a target condition, displaying a target identifier; in response to the target identifier being touched, displaying target information; the target information represents a target program triggering the change event; and the target acquisition sensor can be occupied by one program at the same time.

This invention provides a collaborative path planning method for underwater target search and tracking based on AUVs and multiple USVs. It employs a distributed, cross-domain, heterogeneous collaborative path planning architecture. By setting different fitness functions in the search and tracking phases, the USV cluster and AUVs can dynamically adjust their path planning strategies according to mission requirements, achieving close collaboration between cross-domain platforms within the same time period and overcoming the information transmission lag problem in traditional phased collaborative modes. In the tracking phase, this invention introduces a dynamic periodic underwater target position prediction method to predict the target's future trajectory, enabling the AUV to switch from tracking mode to interception mode, improving the target acquisition success rate. The algorithm effectively balances global exploration capability and local development accuracy by introducing adaptive explosion radius, Levy flight strategy, and Gaussian mutation operation, resulting in stronger global optimization capability and faster convergence speed in the optimization of multi-USV and AUV collaborative path planning.

This application relates to a method, apparatus, storage medium, and electronic device for in-situ batch acquisition of MS2 data, belonging to the field of mass spectrometry imaging technology. The method includes: acquiring MS1 data of a sample to be acquired; determining at least one specific mass-to-charge ratio based on the MS1 data; reducing the initial resolution of the sample to be acquired to a target resolution to obtain a target acquisition sample; determining target acquisition pixels for each specific mass-to-charge ratio precursor ion from all pixels in the target acquisition sample, wherein the target acquisition pixel is the pixel with the highest mass spectrometric signal intensity for the corresponding specific mass-to-charge ratio among all pixels; acquiring MS2 data for the corresponding precursor ions with the specific mass-to-charge ratio based on each target acquisition pixel to obtain corresponding initial MS2 data; and performing quality screening on each initial MS2 data to obtain screened target MS2 data. This application improves the quality of the acquired MS2 data.

The application provides an image splicing system and method for a mobile C-arm, and an electronic device, comprising: a transverse movement unit arranged on an image chain assembly of the mobile C-arm, used to drive the image chain assembly to move linearly in the transverse direction, the image chain assembly comprising an X-ray ball tube and a flat panel detector; a control unit in communication connection with the transverse movement unit, used to control the transverse movement unit to move the image chain assembly to a plurality of target acquisition positions according to a movement planning path; and an image processing unit in communication connection with the control unit and the flat panel detector, used to perform image acquisition at the plurality of target acquisition positions and perform splicing processing on the acquired sequence images. The application overcomes the traditional manual or whole-machine moving positioning mode, and the image chain is driven by the built-in transverse movement unit, so that the movement of the image chain is fast, stable and the position can be accurately reproduced, and the operation difficulty and collision risk are greatly reduced.

This application discloses an electronic device and a processing method, including: an environmental information sensing module, an image acquisition module, and a detection module. The environmental information sensing module is configured to be continuously active, used to detect environmental information in the environment where the electronic device is located, and when the environmental information meets a first condition, triggers the image acquisition module to start and sends the environmental information to the image acquisition module; the image acquisition module is used to adjust the image acquisition parameters to target acquisition parameters according to the environmental information, and acquire a target image based on the target acquisition parameters; after the quality of the acquired target image meets a preset image quality condition, triggers the detection module to start and sends the target image to the detection module; the detection module is used to perform target object detection on the target image, and controls the working state of the electronic device based on the detection result of the target object.

This invention discloses an adaptive network data acquisition method and system based on error detection, belonging to the field of power distribution communication network operation monitoring and data acquisition technology. The method includes: acquiring error detection results based on a preset multi-error detection algorithm and pre-acquired power distribution network data; triggering frequency adjustment when a network error is detected; acquiring the number of errors based on a preset sliding time window and the error detection results; acquiring the error severity based on the number of errors and a preset anomaly threshold; acquiring a target acquisition frequency based on preset frequency adjustment parameters when a preset frequency adjustment condition is met; updating the current acquisition frequency to the target acquisition frequency, and acquiring the current power distribution network data based on the target acquisition frequency, thus achieving adaptive network data acquisition. This invention discloses an adaptive network data acquisition method and system based on error detection, which can solve the technical problem of the lack of adaptive capability in existing acquisition strategies.

The application discloses a data acquisition method, device, equipment and computer storage medium, the method comprises the following steps: in the case that the data acquisition instruction is received, according to the corresponding relationship between the preset acquisition task information and the acquisition task ID, the target acquisition task information corresponding to the acquisition task ID in the data acquisition instruction is found, and the target acquisition task information includes the interface model ID; according to the interface model ID, the interface configuration information is acquired, and the calling interface is assembled based on the interface configuration information; in the case that the communication connection of the SDN controller corresponding to the interface model ID is established through the calling interface, the original data of the SDN controller corresponding to the SDN interface model corresponding to the interface model ID is acquired; according to the preset mapping relationship between the SDN interface model and the business model, the original data is converted into target business data; the target business data is stored to the data warehouse, so as to realize the low-code development interface, and the efficiency of data acquisition is improved.

This invention belongs to the field of free-space laser communication technology, specifically disclosing a second-level anti-disturbance link establishment method and ground simulation system for inter-satellite laser communication. The method includes: using an inverse dynamics feedforward algorithm to compensate in real-time for the inertial coupling torque of the coarse tracking mechanism caused by satellite platform disturbances, achieving inertial spatial stability of the line of sight; employing a spectrum grading and saturation unloading strategy to further suppress line-of-sight jitter caused by satellite platform disturbances through the high-bandwidth operation of the fine tracking mechanism, and unloading low-frequency components to the coarse tracking mechanism to prevent saturation of the fine tracking mechanism; and initiating a high-frequency probabilistic spiral scan at the initial stage of link establishment to achieve rapid target acquisition. This invention solves the problem of lacking efficient anti-disturbance strategies and optimization strategies for second-level rapid response during mode switching from large-scale "blind search" to high-precision "lock-in" in inter-satellite laser link establishment.

This invention relates to the field of pole monitoring technology, specifically to a dual-rocker pole monitoring system and method. The system includes: a graph modeling module, used to generate a pole monitoring association graph corresponding to the target dual-rocker pole based on the data acquisition type and installation layout information of the sensor acquisition units on the target dual-rocker pole, as well as the linkage relationship between the sensor acquisition units and other sensor acquisition units; and an association modeling module, used to determine the operating condition identifier of the target dual-rocker pole based on the pole operation data obtained by the sensor acquisition units, and to determine all target acquisition nodes in the pole monitoring association graph based on the operating condition identifier. Through graph modeling, association modeling, and operating condition coding modules, this invention enables the system to accurately acquire the operating data of the dual-rocker pole, monitor its operating condition changes in real time, and generate corresponding operating condition sub-association graphs, ensuring a comprehensive understanding of the equipment's operating status.

A method and system for controlling a device includes training a low-level policy to form a trained low-level policy and a low-level value function to form a trained goal conditioned value function, wherein training is performed using a static data set using goal conditioned episodes, training a high-level goal planner having high level goals having high-level sub-goals corresponding to a plurality of future time steps using the low-level value function to maximize a cumulative reward over the sub-goals for the plurality of future time steps so that the sub-goals are reachable by the low-level policy, obtaining an observation of a device, and generating an executable action using the low-level policy and the high-level goal planner and operating the device with the executable action.

The application provides a UAV identification method and device, electronic equipment and storage medium, and relates to the technical field of image processing. The method comprises the following steps: taking a target base station as the center, acquiring a plurality of images of a detection range; acquiring position information of a to-be-identified target sensed by a sensing sensor, and acquiring a target image of a position where the to-be-identified target is located based on the position information; based on the position information, superimposing an identification of the to-be-identified target on the target image to obtain a target superimposed image, and determining that the to-be-identified target is a flying target based on the target superimposed image; acquiring trajectory information of the to-be-identified target, and determining that the to-be-identified target is a UAV based on the trajectory information. The identification is superimposed on the image corresponding to the position of the to-be-identified target to make a preliminary judgment, which reduces the calculation amount of the subsequent accurate judgment process and improves the judgment efficiency. The trajectory information of the to-be-identified target is acquired for analysis, a precise identification process of the UAV is realized, and the accuracy of UAV identification is improved.

The smaller the laser beam divergence angle of a long-range lidar, the more difficult it is to scan and cover a large field of view and accurately acquire the target in a short time. Therefore, although the narrow beam divergence angle of lidar is beneficial for high-precision angular resolution, the difficulty of effectively acquiring and tracking the target in real time increases accordingly. This invention proposes a lidar narrow beam scanning and target acquisition method. After being guided to the field of view of interest by passive optoelectronic equipment or inertial navigation equipment, the laser beam is further scanned rapidly to complete the subdivision scanning within the field of view, and the target is detected and located simultaneously. This enables rapid in-field coverage scanning and simultaneous target detection.

This invention relates to the field of UAV collaborative technology, providing a method and system for intelligent security patrol inspection using multiple UAVs at night. The method divides the inspection area into a continuous three-dimensional virtual grid, assigns a deployment position to each UAV, and monitors the surrounding grid, sharing grid status information through inter-UAV communication. When a moving target is detected, the grid it occupies is marked as a triggered state grid, and only surrounding UAVs are dispatched to observe it closely. Multiple observation UAVs share position data, calculate the target's speed and direction in real time, predict the grid sequence it may pass through in the future, and mark these as pre-triggered state grids. Warning commands are sent to UAVs surrounding the pre-triggered grids to adjust their positions and viewing angles in advance. All detection data is fused in real time, the target motion model is corrected, and the triggered and pre-triggered state grids are dynamically updated. This invention achieves proactive prediction and relay tracking of moving targets at night, improving inspection efficiency and target acquisition capabilities.

The application provides a tracking target position information acquisition method, a hovering navigation method and an unmanned aerial vehicle. The tracking target position information acquisition method comprises the following steps: selecting a tracking target; acquiring parameters such as a heading angle β of a flying vehicle and an optoelectronic platform azimuth angle α; calculating a horizontal distance X between the flying vehicle and the tracking target; making the flying vehicle fly around the tracking target; and acquiring tracking target position information such as a latitude circle radius R of a latitude circle where the flying vehicle is located, a latitude circle half angle θ of the latitude circle, a longitude deviation amount ΔL of the flying vehicle and the tracking target, and the like in sequence. w The application summarizes the calculation methods of an east component ΔE and a north component ΔN when the unmanned aerial vehicle flies at different heading angles β and observes the tracking target at different optoelectronic platform azimuth angles α. Meanwhile, the application can automatically set a hovering mode and a hovering radius through the optoelectronic platform azimuth angle α and the horizontal distance X between the unmanned aerial vehicle and the tracking target, thereby solving the problems of poor real-time performance and poor observation effect of the traditional method.

This application relates to a method, apparatus, device, storage medium, and program product for power grid fault location. The method includes: first, acquiring current state data, historical state data, and environmental data of the target power grid at the time of a fault; then, inputting the current state data, historical state data, and environmental data into a preset material type prediction model, determining the material type of the fault initiator based on the output of the material type prediction model; next, determining the fault target based on the current state data, acquiring image data corresponding to the fault target, and determining abnormal areas based on the image data; finally, inputting the fault initiator material type, abnormal areas, and environmental data into a preset fault detection model, determining the fault object ranking based on the output of the fault detection model, thereby determining the fault location result of the target power grid based on the abnormal areas and the fault object ranking. This method can improve the efficiency of power grid fault handling.