336 results about "Target acquisition" patented technology

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 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 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 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 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 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.

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 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 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.

The application discloses a kind of cross array ballistic measurement radar beam scheduling and task allocation method, to improve the target acquisition and tracking efficiency of radar system.The present application is based on cross array antenna, and two kinds of beam scheduling modes are designed:TWS mode and TAS mode;TWS mode allows radar to track the target captured in real time while searching for targets, suitable for occasions handling multiple targets;While TAS mode first searches comprehensively, then tracks the target of interest, effectively avoids multiple beam emission to no target area.Radar can identify and capture targets in the shortest time, improve response speed;After target track is generated, radar can track targets in real time, ensure the accuracy of data;Reduce the number of invalid beam emission, improve resource utilization efficiency.System can dynamically adjust beam scheduling strategy according to target, so as to realize fast acquisition and accurate tracking target, optimize resource utilization efficiency.

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.

The application discloses a kind of geometric error calibration method, device, multi-axis motion system and storage medium, it is related to multi-axis motion system technical field, method includes: according to user operation instruction manual calibration, obtains the initial corresponding relationship between the mechanical coordinate system of multi-axis motion system and the calibration coordinate system of calibration plate;According to initial corresponding relationship, target acquisition point based on calibration plate and the target pose of visual camera, determine corresponding target calibration point on mechanical coordinate system;According to target calibration point generation automatic calibration instruction;According to automatic calibration instruction, control visual camera and target calibration point carry out point operation, obtain the final corresponding relationship between mechanical coordinate system and calibration coordinate system.The application solves the problem that the geometric error calibration of existing multi-axis motion system is lower in efficiency, realizes the effect that multi-axis motion system is geometrically error calibrated automatically, quickly and efficiently.

This invention relates to the field of feature analysis, and more particularly to a rating feature classification method for a technology enterprise rating model. The invention sets a search target, obtains several search interfaces associated with the search target, performs visual analysis on the search interfaces, and determines visual clustering regions based on the relative positions of target features. It calculates the correlation parameters between target features and the search target, sets classification labels for each visual clustering region, and performs adaptive selection analysis on target features within the visual clustering regions based on the labels. This includes selecting and removing target features from ambiguous areas of the search target, retaining features with high correlation to the search target, or removing all target features from the visual clustering regions. Subsequently, the retained target features are transmitted to a preset language rating model. This invention can effectively reduce irrelevant features in web pages, improve the efficiency and accuracy of feature extraction from web pages, and ensure the accuracy of feedback from the language rating model.

The application discloses a kind of based on whole link's equipment running life cycle monitoring system and method, it is related to equipment monitoring technical field, including: obtaining the running record of equipment in building site, obtain the running data set of each life cycle stage;According to operation data, obtain the first characteristic value of equipment in each life cycle stage;Sensor is deployed in building site, according to the change condition of sensor in running stage and stop stage, obtain the second characteristic value of each equipment to building site, obtain the total target value of each equipment;Obtain the acquisition frequency when monitoring each equipment in building site currently, calculate reliability, and then obtain the target acquisition frequency of each equipment in building site.The application is analyzed by combining equipment life cycle stage and equipment layout in building site, obtain reliable target acquisition frequency, help to meet the pertinence and representativeness of data acquisition, balanced equipment monitoring strength.

The invention relates to a data acquisition method, a data acquisition system and related equipment. The method comprises the following steps: in response to starting of a data acquisition task, adaptively selecting a target acquisition channel from a plurality of acquisition channels through an acquisition scheduling engine, and issuing the data acquisition task to a corresponding target terminal, so that the target terminal acquires target data through the target acquisition channel; performing credibility verification on target data returned by the target terminal through the security verification engine; and storing the target data passing the credibility verification through a data storage module. The method at least partially solves the problems of high data acquisition task failure rate, insufficient data acquisition integrity and narrow scheme application scene due to the adoption of a data acquisition system with a preset single fixed acquisition channel in a data acquisition method in related technologies.

The invention provides a cooperative control method and system of a bed moving type magnetic resonance scanning system, a medium, a program and an electronic terminal. According to the end time T0 of a current collection sequence, the bed moving time tij corresponding to each remaining to-be-collected sequence Aij and the predicted waiting time uij of each remaining to-be-collected sequence Aij, the bed moving time tij and the predicted waiting time uij of each remaining to-be-collected sequence Aij are calculated; and selecting a next to-be-executed target acquisition sequence Atarget from the remaining to-be-acquired sequences Aij on the basis of a shortest time principle. The moving process of the scanning bed is arranged to be overlapped with'garbage time 'which is not suitable for collection in the physiological cycle of a patient, so that when a bed body accurately arrives at a target position, the physiological state of the patient is just or is about to enter a corresponding target triggering time phase; the two processes of'bed moving 'and'waiting time phase' which originally must be executed in series are parallelized to the maximum extent, and the scanning efficiency and the equipment throughput are remarkably improved.

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.

The invention relates to the technical field of plastic pipe cutting, and provides a multi-angle band saw operation control method and system.The method comprises the steps that vibration data, current data and rotor angles at different collection moments are collected in the plastic pipe cutting process, and the target collection moment is marked; constructing a vibration sequence, a current sequence and a rotor angle sequence at a target acquisition moment; determining a cutting misalignment degree, a cutting misalignment degree sequence and a cutting misalignment degree predicted value sequence at the target acquisition moment, and determining a notch form offset degree at the target acquisition moment according to the difference between the cutting misalignment degree sequence at the target acquisition moment and the cutting misalignment degree predicted value sequence; and an integral gain adjustment value at the target acquisition moment is calculated, and real-time adjustment of operation of the multi-angle band saw for plastic pipe cutting is achieved in combination with the rotor angle at the target acquisition moment. According to the method, the integral gain is adaptively valued, and the cutting track offset is reduced.

The invention discloses an individual care product process optimization method and system based on user behavior data, and relates to the field of intelligent data processing, and the method comprises the steps: collecting a historical user behavior data set in a historical time range after a target product is put into the market through multiple channels, and carrying out the data preprocessing and product improvement correlation feature extraction, obtaining a historical product improvement associated feature set; determining an optimal process adjustment time period by combining a predicted product demand growth rate and a predicted product demand fluctuation coefficient within a preset time range; according to the user behavior data set in the optimal process adjustment time period, determining a product improvement index according to the product quality associated feature set; and obtaining an optimal process adjustment scheme by taking approximation to a product improvement index as an optimization target, and carrying out production process iterative optimization within a preset time range. According to the method and the device, the problems of poor user experience, low optimization strategy scene adaptability and inaccurate process optimization direction in the prior art are solved.

A computing apparatus executes an application configured to perform a process for one or more web browser applications, each configured receive an input URL and acquire code from a web server location identified by the input URL, and generate a client-side representation of the acquired code, the process comprising: causing the web browser application to execute with a target URL as the input URL; obtaining, as a first client-side representation, a client-side representation of the acquired code as generated by the web browser application; obtaining, as a second client-side representation, a second client-side representation of code acquired from the target URL; calculating a difference metric; comparing the difference metric with a threshold, and based on the comparison: causing an analytics script to run on the target URL to obtain a set of performance indicators; and causing the first client-side representation to be stored in association with the performance indicators.

Embodiments of the present disclosure provide an information acquisition method and device, a storage medium and an electronic apparatus. Herein, the method comprises: in response to a preset trigger operation, displaying an information acquisition page which includes therein at least one level of display information; in response to a trigger operation on any one piece of the display information, displaying at least part of same-level display information corresponding to selected display information, and / or displaying at least part of next-level display information of the selected display information, wherein the displayed display information of each level is selectable display information; in the case of detecting that a selection ending condition is satisfied, determining target acquisition information based on the selected display information of each level.

The invention provides a test method and platform for a target capture square wave signal frequency calculation module. The method comprises the following steps: S1, determining a plurality of target capture square wave signal waveform templates which correspond to a tested module and meet preset test requirements; s2, generating a plurality of target capture square wave signals which respectively correspond to the plurality of target capture square wave signal waveform templates, meet preset test requirements and are adjustable in single period; s3, selecting a target capture square wave signal and inputting the target capture square wave signal into the tested module; s4, executing the tested module to obtain a target capture square wave signal frequency measured value; s5, judging whether the measured frequency value of the target capture square wave signal is consistent with the expected frequency value of the target capture square wave signal or not; the target capture square wave signal frequency expected value is calculated based on a target capture square wave signal input into the tested module; and S6, under the condition of consistency, determining that the test result is passed. According to the scheme, the function test, the boundary test and the like of the target capture square wave signal frequency calculation module can be more accurately carried out.

The invention discloses an automatic building modeling method based on an unmanned aerial vehicle image, and belongs to the technical field of data processing. Comprising the following steps: acquiring a geographic range and a modeling precision requirement of a target area, and acquiring an initial position and a flight state parameter of an unmanned aerial vehicle; determining a data acquisition priority of each area, and generating a preset flight path of the unmanned aerial vehicle in combination with the geographic range and the data acquisition priority; controlling the unmanned aerial vehicle to sequentially move to each target acquisition area according to a preset flight path, and performing image acquisition on the target acquisition areas; performing preliminary noise elimination, distortion correction and image enhancement processing on the to-be-processed image data; creating a four-dimensional space-time index structure containing three-dimensional space information and time dimension; combining information of different scales by using an attention mechanism to form comprehensive building characterization, and identifying the change of the building along with time in real time; the detection sensitivity parameters are automatically adjusted according to the building change condition and the current environment condition, and the significant change part is identified.

The invention provides a target processing method and device and a vehicle, and belongs to the technical field of vehicle control. The method comprises the steps that under the condition that a monitoring module monitors a target signal, N targets are determined according to the target signal, N is a positive integer, target levels corresponding to the N targets are determined, environment state information is acquired, feature information corresponding to the target is acquired for any target, and the target is determined based on the environment state information and the feature information corresponding to the target. And predicting behavior information corresponding to the target, and processing the target according to the target level corresponding to the target, the behavior information and the feature information. Therefore, the target is processed based on the target level, the feature information and the behavior information corresponding to the target, and the target can be adaptively processed accurately and timely.

The present invention relates to target acquisition and related devices, and more particularly to telescopic gunsights and associated equipment used to achieve shooting accuracy at, for example, close ranges, medium ranges and extreme ranges at stationary and moving targets.