488 results about "Target acquisition" patented technology

The invention provides an image acquisition control method, device and equipment based on machine vision. The method comprises the following steps: selecting a high-frame-rate image sensor acquisition mode according to environment state parameters; adjusting exposure parameters of the high-frame-rate image sensor according to the selected acquisition mode; fusing the optical flow speed and the brightness of the image flow into a weighting factor according to the exposure parameters, and injecting the weighting factor into an image space to generate a scene partition mask; and the scene partition mask is aligned with the exposure images with different exposure parameters, and the exposure images are fused into a target acquisition image. Through the implementation of the scheme of the invention, the environment state parameters are generated in real time, the corresponding acquisition mode is selected, the exposure parameters are optimized, the optical flow and the brightness data are fused to generate the weighting factor, the scene partition mask is created, the multi-exposure image is aligned through the scene partition mask, the optimal exposure part of each area is accurately fused, and the high-quality target image is obtained. Therefore, the image acquisition efficiency is improved.

The invention relates to the technical field of image recognition, in particular to a method and system for early warning below a portal crane, and the method comprises the steps: obtaining site environment sensing data, constructing a space map, and recognizing the position and motion state of equipment in real time; predicting an equipment motion track and a load swing range, and generating a predicted dangerous area; image acquisition devices are installed at a plurality of fixed positions, field images are acquired, an image recognition model is used for detecting a target, and the spatial position and the posture state of the target are obtained; tracking a target trajectory based on a motion estimation model and predicting a future position of the target trajectory; dynamically switching the image acquisition devices according to the motion state of the equipment; and comparing the future position of the target with the predicted dangerous area in real time, when the future position and the predicted dangerous area coincide, carrying out potential interference prediction, calculating predicted interference time, and carrying out grading processing in combination with the attitude state of the target. According to the invention, equipment dynamic perception and personnel behavior prediction are realized, and the intelligent protection capability of the operation area is improved.

The invention is suitable for the technical field of semiconductor testing, and provides a data acquisition method and device based on a DDIC chip, and testing equipment, and the data acquisition method comprises the steps: receiving a test pattern, controlling the DDIC chip to output a corresponding gray scale voltage signal, and achieving the comprehensive testing of the response capability of the chip in a full gray scale range; secondly, a target acquisition link composed of functional units including impedance conversion, single-ended to differential conversion, programmable gain amplification, filtering, analog-to-digital conversion and the like is utilized, so that the signal driving capability and the anti-interference capability are effectively improved, meanwhile, high-frequency noise and nonlinear distortion are reduced, and the basic quality of sampled data is guaranteed; on the basis, sampling optimization processing is carried out on the sampling data based on the FPGA unit, and the data stability is improved. According to the scheme, through high-precision transmission of the signal link, the data acquisition precision of the DDIC chip is improved, and then the technical requirements of high-precision DDIC chip testing are met.

The invention relates to the technical field of data processing, and discloses a capital project collaborative monitoring method and system based on a typical construction period. The method comprises the following steps: performing index correlation analysis processing on a multi-dimensional collaborative planning system to obtain a collaborative monitoring index system with a hierarchical structure and a data acquisition scheme; based on the data acquisition scheme, performing data acquisition according to the collaborative monitoring index system to obtain target acquisition data, and performing dynamic analysis processing on the target acquisition data to obtain a project monitoring data set; performing multi-level response strategy analysis processing on the project monitoring data set through a decision tree algorithm to obtain a collaborative response mechanism; and performing effect evaluation processing on an execution result of the collaborative response mechanism through an iterative optimization algorithm to obtain a construction period reference parameter set and a monitoring early warning rule. According to the invention, the efficiency and accuracy of capital project collaborative monitoring based on the typical construction period are improved.

The invention provides a motion video key clip extraction method based on behavior analysis. The method comprises the following steps: firstly, performing decoding and frame standardization on a match video stream, detecting and positioning a coach target, and obtaining and expanding a bounding box; extracting a candidate skeleton key point set in the extended region, selecting the skeleton with the most key points as the skeleton of the coach, and performing cross-frame tracking; analyzing the skeleton in real time, triggering hand fine analysis and extracting hand key points when a scoring trend appears, comprehensively judging based on geometry, kinematics and time sequence rules, and generating a trigger signal when a specific scoring gesture is detected; and the background thread extracts fragments before and after the triggering moment from the video stream as key fragments, and stores the key fragments in association with metadata such as event types, coach identities and competition states.

The invention discloses a river water level detection method, and relates to the technical field of computer processing, and the method comprises the following steps: S01, presetting a distributed pressure sensor array in each target collection region to obtain underwater pressure data k and real-time water flow data v of a plurality of target collection regions of a river to be detected; s02, establishing a dynamic pressure water level model based on the water flow direction pressure conduction quantity estimation of the plurality of target acquisition areas in combination with real-time water flow velocity and wave period parameters; s03, performing signal attenuation compensation on the underwater pressure data according to the dynamic pressure water level model to obtain initial water level data; s04, multi-source data fusion calibration is carried out on the preliminary water level data, a river water level detection result is generated, and the result comprises a wave height frequency spectrum and a water level change curve after peak elimination correction; and S05, generating a wave energy spectral density map according to the calibrated water level data, performing real-time comparison according to the wave energy spectral density map and a preset threshold value, and performing result return according to a comparison structure. The small-wave-height short-period wave measurement precision and the water level detection reliability are remarkably improved, the intelligent flood prevention early warning and dynamic adjusting capacity is achieved, and it is guaranteed that data collection is accurate and consistent.

The invention relates to the technical field of path planning, and provides a path planning method, device and equipment for an underwater unmanned vehicle, and a storage medium, and the method comprises the steps: obtaining a node access sequence of the underwater unmanned vehicle; determining the current state of the underwater unmanned vehicle by taking the first acquisition node as a target acquisition node; executing a current action corresponding to the current state to obtain a next state and a node residual data volume corresponding to the next state; calculating a dynamic composite reward value; judging whether the residual data volume of the node is 0; if the residual data volume of the node is not 0 and is within a preset communication range, updating a corresponding expected return value in a preset action-value table by using the dynamic composite reward value to obtain a target action-value table; and obtaining a data acquisition path of the underwater unmanned vehicle based on the target action-value table. Therefore, the throughput and efficiency of data acquisition of the unmanned underwater vehicle can be improved.

The invention relates to an unmanned aerial vehicle indoor three-dimensional reconstruction autonomous acquisition method and system based on reinforcement learning, and the method comprises the following steps: constructing a virtual indoor simulation space and a virtual unmanned aerial vehicle model, and laying target acquisition points; a reinforcement learning model is constructed and trained, in the training process, in each time step, the unmanned aerial vehicle obtains target collection point information and inputs the target collection point information into the reinforcement learning model, the reinforcement learning model generates an action instruction and transmits the action instruction to the virtual unmanned aerial vehicle model, and the virtual unmanned aerial vehicle executes geometric transformation, updates the position and orientation and reconstructs view information; and deploying the trained reinforcement learning model in an untrained virtual simulation environment, carrying out an unmanned aerial vehicle autonomous flight experiment and data acquisition, and carrying out quantitative evaluation on the acquisition performance through a plurality of performance indexes. Compared with the prior art, efficient and stable data acquisition can be realized in a complex environment.

The invention relates to an intelligent mechanical fault diagnosis method based on a progressive transfer learning network, and belongs to the technical field of mechanical part monitoring and fault diagnosis. The method comprises the following steps: respectively acquiring original signal data in a laboratory environment and a real industrial environment, and preprocessing the data; establishing a fault identification model based on a progressive transfer learning network architecture, and obtaining an optimal network parameter by combining a loss function in a propagation process and by taking a classification error of minimizing a source domain sample and a target domain sample and an inter-domain difference of minimizing sample distribution as targets; and collecting real-time signal data in a real industrial environment, inputting the real-time signal data into the optimized fault identification model based on the progressive transfer learning network architecture, and outputting a fault type by the fault identification model. According to the method, the sample migration success rate and the fault identification accuracy are improved by gradually constraining feature mapping in the sample migration learning process.

The invention discloses a millimeter-wave radar fine-grained human body pose sensing method based on multi-dimensional feature extraction, and belongs to the field of computer vision and radar sensing, and the method comprises the steps: managing a millimeter-wave radar sensor through an equipment access module to generate a 4D point cloud; the target tracking module performs multi-target tracking on the 4D point cloud, predicts a target position by using a Kalman filter, divides point cloud affiliation through a gate function, creates a new target by using DBSCAN clustering, eliminates continuous targets without point cloud affiliation, and obtains a target center position; the human body pose detection module converts point clouds to a local coordinate system for normalization based on a target center position and 4D point clouds, fuses continuous multi-frame point clouds, and inputs a deep learning network of PointNet and U-Net improved based on an attention mechanism to output human body pose joint point coordinates. According to the invention, the human body pose detection precision in a limited data mode is improved, and a human body health monitoring function available to a home environment is realized.

The invention discloses a distributed energy storage device data acquisition method, system, device and medium, and relates to the field of energy storage data acquisition, the method comprises the following steps: a cloud platform sends an acquisition instruction to an acquisition terminal in response to received registration information of a target energy storage device; the acquisition terminal responds to a received acquisition instruction, sends a detection frame through a physical port according to a target communication protocol, establishes communication with target energy storage equipment, acquires identification information of the target energy storage equipment, determines a target point location table from a local point location library according to the identification information of the target energy storage equipment, and acquires the target energy storage equipment according to a target acquisition strategy; and obtaining original operation data of the target energy storage equipment, and obtaining target structured data according to the target point location table and the original operation data. The problems of poor compatibility and low expansibility in the prior art can be solved, and the collection efficiency of the energy storage data is improved.

The invention discloses a self-adaptive feature point compensation method for visual SLAM in a dynamic scene, and the method comprises the steps: firstly obtaining a dynamic environment image, recognizing a dynamic target in the image through a YOLO11s target detection model, and obtaining the type of a target detection frame and the coordinate information of the target detection frame; then, a dynamic confidence scoring criterion is constructed based on target prior motion characteristics, high-dynamic object detection frame categories are distinguished, and interference feature points in the high-dynamic object detection frames are accurately eliminated; secondly, designing an adaptive threshold by combining the space coverage rate of a dynamic detection frame and the time distribution characteristic of the number of historical feature points, and dynamically compensating the number of the feature points; and finally, when the number of the feature points is lower than an adaptive threshold, delimiting a compensation area by taking the edge of the high-dynamic detection frame as a reference, compensating the ORB feature points, and ensuring that the number of the feature points is stable. By adopting the technical scheme of the invention, the robustness of the number of feature points and the positioning precision in a dynamic scene are remarkably improved while the real-time performance is ensured.

The invention relates to the technical field of pipeline positioning, in particular to a large-burial-depth pipeline positioning system based on an unmanned aerial vehicle integrated pipeline detector, and the system comprises a task generation module which is used for determining a plurality of target collection points and generating a target flight task; the magnetic field control module is used for determining a magnetic field application point of the target area based on each target acquisition point and controlling magnetic field parameters of an electromagnetic field applied to the target area; the data acquisition module comprises an unmanned aerial vehicle assembly, a pipeline detection assembly and an environment monitoring assembly; the data analysis module is used for constructing a magnetic field distribution model of the target area, determining an initial pipeline parameter of the large-burial-depth pipeline based on the magnetic field distribution model and a magnetic field parameter of an electromagnetic field applied to the target area, and determining a key influence coefficient based on the environment data and an initial flight parameter; and the parameter adjusting module is used for adjusting the pipeline parameter based on the key influence coefficient to obtain a target pipeline parameter. The detection positioning efficiency can be improved.

The invention relates to the technical field of fault detection, in particular to an ultralow-temperature refrigerator refrigeration fault detection method. Information is collected through the information sensing layer, external sensing data and refrigerating system data are output, and the defect of a single external sensor is overcome; the external sensing unit and the refrigeration sensing unit respectively perform targeted acquisition, and when an external sensor is abnormal, fault detection can be realized through refrigeration system data, so that the stability and reliability of detection are improved, and the problem of detection failure caused by sensor faults is avoided; according to the method, the data stability index is obtained by identifying the external sensing data, the data health signal is obtained by performing health assessment on the data stability index, the external sensing abnormal total value and the refrigerating system abnormal total value are comprehensively analyzed, abnormal levels are divided, the corresponding fault alarm strategy is generated, the fault severity degree can be matched, and the fault alarm accuracy is improved. False report and missing report are reduced, and safe operation of the refrigerator is guaranteed.

The invention discloses an express sheet identification method and system and a related device. The method comprises the following steps: acquiring a target acquisition image matched with a target sheet of a target object by using an identification robot; acquiring an initial information code image matched with the target object from the target acquisition image, and determining a plurality of target attention areas in the initial information code image; acquiring a corresponding target key point based on each target concerned area; correcting the initial information code image by using the target key point to obtain a corrected target information code image; and based on the target information code image, obtaining an identification result matched with the target express sheet. In this way, the express sheet identification efficiency and accuracy can be improved.

The invention discloses a tracking shooting method based on an infrared thermal imaging system, and relates to the technical field of infrared thermal imaging, and the method comprises the steps: S1, obtaining a visible light image and a thermal infrared image of the same shooting scene, determining whether a human body exists in the thermal infrared image through a control unit, and marking the determined human body as a pre-following target when the human body exists; s2, the control unit performs distance detection on the pre-following target according to the visible light image and the thermal infrared image, and after distance detection, the control unit controls a lens electric control focusing module to focus the pre-following target to obtain a clear image of the pre-following target; s3, determining whether a pre-following target is a set following target from the clear image obtained in the step S2; if yes, turning to step S4; if not, turning to step S5; s4, the control unit controls the lens electric control focusing module to keep focusing shooting of the set following target; s5, focusing to a set focal length, and continuing to operate the step S1; accurate tracking shooting can be carried out on a specified crowd or a specified target.

The present disclosure provides a multi-channel signal sampling device and a calibration system, belonging to the technical field of signal processing; the multi-channel signal sampling device comprises a PXIe chassis and at least two acquisition cards arranged in the PXIe chassis; the multi-channel signal sampling device further comprises a synchronization program component, which is executed to determine the delay data between each channel of each acquisition card and the trigger channel according to the trigger channel currently located in the first target acquisition card and the pre-stored synchronization calibration basic data, and to synchronize each channel and the trigger channel according to the delay data; the synchronization calibration basic data comprises single-board calibration data and cross-board calibration data; the multi-channel signal sampling device can solve the problems of high synchronization calibration cost and design difficulty existing in the current PXIe sampling device.

The invention discloses a data collection method and device for an automatic driving vehicle, and the method comprises the steps: carrying out the analysis processing of a data collection instruction in response to the data collection instruction, and obtaining a target task and a target collection range; target vehicles in the target acquisition range and real-time vehicle state information are acquired; determining a target path corresponding to the target vehicle according to the target task and the real-time vehicle state information; obtaining a vehicle model data acquisition strategy relation library corresponding to the target task, and searching a data acquisition strategy matched with the target vehicle model in the vehicle model data acquisition strategy relation library to obtain a target data acquisition strategy; sending the target path, the target task and the target data acquisition strategy to a vehicle end server corresponding to the target vehicle; the target vehicle is enabled to run along the target path, the target task is executed according to the target data acquisition strategy in the running process, and real-time acquisition data is obtained. According to the invention, the data acquisition efficiency of the automatic driving vehicle is improved.

A control device includes: a control pattern selection unit configured to select a control pattern for an IRS based on a codebook and a reference value acquired from a target of the IRS, the codebook indicating a correspondence relation between a representative value specified based on the reference value and the control pattern for the IRS; and a control unit configured to control the IRS based on the control pattern. The codebook is generated by clustering a plurality of reference value samples of a target of an IRS into a plurality of clusters, calculating a representative value in each cluster based on reference values clustered in each cluster, calculating a control pattern corresponding to the representative value, and calculating a correspondence relation between the representative value and the control pattern.

The application provides a large model application method and system for data retrieval, and belongs to the technical field of data management, and specifically comprises the following steps: obtaining constituent data of a matching deviation target, combining matching data of different matching deviation targets and retrieval information items with a retrieval processing number, determining a matching update target of different cache information items according to different update targets and matching conditions of text vectors of the cache information items when it is determined that the update processing of the cache data of the large model does not need to adopt a preset update strategy, obtaining matching data of different cache information items and retrieval information items with a retrieval processing number, and combining a matching update target of different cache information items, a matching update target and a retrieval result matching condition with a retrieval processing number to determine an update processing strategy of different cache information items, thereby improving the timeliness of the update processing of the cache data of the large model.

The invention, which belongs to the technical field of electric power operation and maintenance management, discloses an operation and maintenance fault detection and identification system comprising a preparation analysis module, an acquisition module, an edge end and a cloud end. The preparation analysis module is used for performing preparation analysis on operation and maintenance fault detection and generating a corresponding equipment information graph according to target equipment; determining a target acquisition data type of each target device according to the device information graph, classifying each target device according to the target device information and the target acquisition data type to obtain edge classes, and configuring a corresponding edge end for each edge class; the acquisition module is used for performing data acquisition on each target device to obtain operation and maintenance acquisition data; the edge end is used for processing the operation and maintenance collection data to obtain target collection data and sending the target collection data to the cloud end; the cloud comprises a fault diagnosis module, and the fault diagnosis module is used for analyzing the received target collection data to obtain a fault diagnosis result.

The invention provides a high-energy laser damaged material surface temperature monitoring system and method.The high-energy laser damaged material surface temperature monitoring system comprises a high-energy laser light source, a homogenizing optical fiber beam expanding system, a material sample fixing system and a material surface temperature monitoring system, and laser generated by the high-energy laser light source is output after being homogenized and expanded by the homogenizing optical fiber beam expanding system; the output homogenized high-energy laser acts on an irradiation target material sample after beam expansion, the material surface temperature monitoring system comprises a high-precision target acquisition system, a binocular vision imaging system and a multispectral wavelength temperature measurement system, and the target acquisition system is used for acquiring infrared heat radiation on the surface of a laser irradiation material; the binocular vision imaging system is used for realizing three-dimensional thermal imaging of the laser irradiation target material sample piece according to the collected infrared thermal radiation, and the multispectral wavelength temperature measurement system is used for realizing three-dimensional temperature measurement of the laser irradiation target material sample piece according to the three-dimensional thermal imaging. By applying the technical scheme of the invention, the technical problem that three-dimensional temperature monitoring is difficult to realize in the prior art is solved.

The invention provides a page content processing method and device based on a large model, equipment and an intelligent agent, and relates to the technical field of artificial intelligence, in particular to the technical fields of page content processing, natural language processing, large language models and the like. According to the implementation scheme, in response to a received processing demand for a target page, a page content extraction target is determined based on the processing demand; obtaining page content in the target page; extracting a target according to the page content, and obtaining target content in the page content; based on the large model, determining whether the target content is sufficient to reply the processing demand; and in response to determining that the target content is sufficient for replying the processing demand, generating reply content for replying the processing demand based on the target content.

A spring loaded device for launching projectiles in a hostile environment. The device has an articulable launch assembly. The launch assembly has a spring loaded carriage for holding the projectile when loaded by an operator or a superjacent magazine. The carriage is retracted by a screw to a predetermined position based upon spring rate and the desired initial launch velocity and launch angle. Upon command or target acquisition a release mechanism releases the carriage for forward translation and launch of the projectile.

The invention provides a continuous wave mud pulse code modulation method, device and equipment and a storage medium, and belongs to the technical field of oil and gas drilling. The method comprises the following steps: encoding detected target acquisition information into a multi-system code element; two code elements are taken as a group to form a code element group, and the code element group controls the rotating speed of a rotor together to form a modulated pressure wave signal for determining a phase delay degree and a phase switching position corresponding to the phase delay degree; wherein the phase switching position is a time period when the corresponding phase delay degree occurs in a modulation period of the code element group to the pressure wave signal. According to the invention, on the premise of not additionally occupying frequency band resources, the transmission information amount is doubled, so that the signal transmission rate based on the continuous wave mud pulse is doubled, and the defect of low transmission rate in the traditional code modulation mode for the continuous wave mud pulse is overcome.

The invention provides a data processing method and device, a medium and a program product, which can be applied to the technical field of computers. The data processing method comprises the following steps: analyzing a performance index from gateway equipment, and determining an alarm index; processing alarm data related to the alarm indexes based on a kernel density estimation method to obtain a predicted alarm probability, the alarm data including alarm time, an alarm position and an alarm level, and the kernel density estimation method being used for constraining a balance relationship between the alarm data and the predicted alarm probability; based on the historical probability density and the predicted alarm probability of the alarm index, adjusting the acquisition frequency of the gateway device for the alarm index to obtain a target acquisition frequency; and sending the target acquisition frequency to the gateway device.

The invention discloses a network security protection method and device based on distributed threat identification, and relates to the field of network security. The method comprises the following steps: firstly, determining target acquisition granularity and frequency based on equipment type distribution, service load and link quality data; capturing the original flow in real time by an edge computing node, and extracting a distributed threat fingerprint containing a behavior sequence and a protocol variation feature; after block chain consensus verification, synchronizing to a collaborative detection network, and constructing an on-chain trusted threat knowledge base; simulating a target threat fingerprint propagation path in combination with real-time network topology and an on-chain trusted threat knowledge base, and generating a dynamic threat propagation map; and determining a multi-dimensional risk score based on the atlas, and further generating a self-adaptive protection strategy and issuing and executing the self-adaptive protection strategy. According to the method, technologies such as multi-dimensional data perception, edge calculation and block chain consensus are fused, and efficient, credible and real-time response distributed network security protection is realized.

The invention provides a data processing method, a storage medium, electronic equipment and a program product, and relates to the technical field of data as a service. The data processing method comprises the steps of determining a trial acquisition parameter set based on a data acquisition demand of a user; on the basis of the pilot production parameter set, pilot production operation is executed, and pilot production data of the intelligent equipment with the body are obtained; if the trial production data passes the quality verification, generating a data acquisition specification based on the trial production parameter set; and executing mass production acquisition operation based on the data acquisition specification to obtain target acquisition data of the intelligent device with the body. According to the method, the data acquisition specification is dynamically generated according to the quality verification result of the trial acquisition data, so that the accuracy and effectiveness of the obtained target acquisition data are improved.

The present application relates to the field of operation, inspection, and control technology, and in particular to a device data acquisition method, system, terminal device, and storage medium, the method comprising obtaining a target acquisition item; obtaining corresponding acquisition data according to the type of the target acquisition item; judging whether the acquisition data meets the preset operation standard; if the acquisition data meets the preset operation standard, verifying the acquisition data according to the preset verification rules, and generating verification items as data acquisition reports; if the acquisition data does not meet the preset operation standard, obtaining corresponding abnormal acquisition data, and processing the abnormal acquisition data according to the preset tracing rules, and generating tracing items as the data acquisition report; analyzing the data acquisition report, and generating corresponding data acquisition results. The device data acquisition method, system, terminal device, and storage medium provided in the present application have the effect of improving the detection of power grid equipment.

The application discloses a camera alignment method, device, equipment, storage medium and product, and relates to the technical field of computers.The camera alignment method comprises the following steps: when it is detected that there is a target to be aligned in a panoramic picture shot by a first shooting device, obtaining target pixel coordinates of the target to be aligned in the panoramic picture; inputting the target pixel coordinates into a preset moving angle mapping network to obtain a target moving angle; and controlling a second shooting device to align the target to be aligned based on the target moving angle.After the target to be aligned is detected, the pixel coordinates of the target to be aligned in the panoramic picture are determined, and the moving angle of the second shooting device for alignment is obtained through the preset moving angle mapping network according to the pixel coordinates, so that the positioning calculation process does not need to involve a close-up lens, a large deviation is caused by direct mapping due to the field of view difference between two cameras, and the problem of reducing the accuracy of camera alignment is solved.