147results about How to "Rich data support" patented technology

The invention discloses an intelligent network-connected automobile operation system based on vehicle-road collaboration. The intelligent networked automobile operation system comprises a high-precision map platform, a cloud control platform, a vehicle-mounted terminal platform, a vehicle-mounted computing platform and an information security platform. The high-precision map platform provides a real-time dynamic high-precision map; the cloud control platform and the vehicle-mounted terminal platform are subjected to cooperative management and control through a communication network; the cloudcontrol platform executes data storage, cloud computing and standardized data interconnection; the vehicle-mounted terminal platform executes information reporting; wherein the vehicle-mounted computing platform is connected with the vehicle-mounted terminal platform through the vehicle-mounted Ethernet, over-the-horizon perception data, map data, environment data and the like are obtained, a vehicle driving scheme is formulated through fusion calculation, and the cloud control platform, the vehicle-mounted terminal platform, the vehicle-mounted computing platform and the map platform are allprovided with safety monitors. Common basic services are provided for operation of the intelligent network connection automobile, and national and industrial development requirements are met.

The invention discloses an unmanned vehicle data processing method and device, and a black box system. The method includes one specific implementation way: obtaining unmanned vehicle driving information which includes driving road information, collision sensing information, vehicle condition information and control information; according to the driving information, detecting whether the unmanned vehicle is abnormal; and in response to a detected case that the unmanned vehicle is abnormal, sending driving information in a preset time period to a cloud server. The implementation way can send the unmanned vehicle accident or failure related information to the cloud server in a timely manner, and provides comprehensive and accurate data support for analysis of the abnormal state of the unmanned vehicle.

The invention relates to a mobile tunnel laser detection data processing method. The method comprises steps of acquiring original, actual tunnel section point cloud data; correcting tunnel section mileage data based on accumulated errors; performing tunnel point deformation analysis, convergent diameter analysis, multi-phase data comparison and analysis and comparison and analysis of multiple measurement manners according to point cloud on the inner wall of the tunnel, so as to acquire tunnel deformation situation; determining whether the tunnel section point cloud is within a standard profileenclosed by limiting points by using a horizontal ray method, so as to determine whether invasion points exist; converting section point cloud data into a designed absolute coordinate system, so as to restore a design line type of the tunnel; and performing texture mapping by using an orthogonal projection image of the inner wall of the tunnel so as to acquire a 3D model of the tunnel. In the method, tunnel deformation analysis, mileage correction, boundary detection, recovery of the design line type of the tunnel and 3D modelling of the tunnel can be performed according to the original, actual section, and data is processed rapidly.

The invention provides a bill image field positioning method and system based on a location template and a semantic template. The method comprises the following steps: analyzing four types of locationattributes of the fields in the bill image; respectively formulating different template configuration xml files for different bill types; analyzing the bill type of the bill image through a bill sorting system, and loading the template configuration xml file with the same bill type as the bill image; positioning all field location coordinates in the bill image; performing positioning computationthrough the template configuration xml file and according to four types of location attributes, thereby acquiring the location coordinate of the field needing to recognize in the bill image, and acquiring the field local image, wherein the character recognition system recognizes the field local image as the character string by using the OCR technology. Through the method and system provided by theinvention, the specific location coordinate of the field in the bill image can be effectively acquired, a large number of data about the invoice type characteristic rule is effectively saved, and more data support is provided for the invoice character positioning and character recognition.

The invention discloses an expendable air-sea flux buoy which comprises a micro weather station, a temperature and moisture measuring instrument, a supporting rod, an instrument control cabin, a core pulling floating ball and a counterweight. A cabin body of the instrument control cabin is arranged in the core pulling floating ball. The micro weather station and the temperature and moisture measuring instrument are arranged on the supporting rod above the instrument control cabin. The bottom end of the instrument control cabin is connected with the counterweight through a connecting rod. The instrument control cabin is internally provided with a hydrologic module, a wave module and a measurement and control unit. The upper end face of the instrument control cabin is provided with a satellite antenna. The expendable air-sea flux buoy floats along with flow, collects the meteorological parameters at an air-sea interface and the hydrologic parameters of the sea surface, calculates the air-sea flux and provides a novel observation method for observation and research of multi-scale air-sea interaction. The expendable air-sea flux buoy and an existing observation method are used in a combined mode, the observation capacity of the air-sea flux in the global ocean range can be greatly improved, and important datum support is provided for ocean disaster prevention and reduction, ocean environment guarantee, global climate change research and the like.

The invention provides a medical and health acquiring system, a medical and health acquiring device, and a medical and health acquiring method. The medical and health acquiring system comprises a core module, an information input module, a physiological parameter acquiring module, a storage module and a power supply module, wherein the core module is used for controlling other modules to work, verifying whether the verification information of a user is in local storage equipment, and if not, prompting the user to register; the information input module is used for inputting the verification information of the user, and submitting the verification information to the core module for verifying; the physiological parameter acquiring module is used for measuring and acquiring the physiological parameters of the user after the verification is done by the core module; the storage module is used for storing the measuring results under the control of the core module after the measurement, in order to search conveniently later; and the power supply module is used for supplying power to other modules. According to the medical and health acquiring system, the device and the method, various detections can be completed by a one-station mode, so that the service efficiency of the user is improved.

The invention provides an intelligent blade mould. The intelligent blade mould comprises a fixing face mould and an overturning face mould, an overturning system, a locking and jacking system, a heating system and a vacuum system, and further comprises a distance and displacement sensor, a temperature sensor, an angle and displacement sensor, a hydraulic sensor, an air pressure sensor and an operating table; the distance and displacement sensor is arranged between the fixing face mould and the overturning face mould, the temperature sensor is arranged in the fixing face mould, and the angle and displacement sensor and the hydraulic sensor are arranged in the overturning system; and the air pressure sensor is arranged in the vacuum system, and the operating table is in signal connection with the distance and displacement sensor, the temperature sensor, the angle and displacement sensor, the hydraulic sensor and the air pressure sensor. According to the intelligent blade mould, monitoring, alarming, fault query and data collection are integrated to one.

The invention discloses an on-line detection method for industrial control loop multi-period oscillation. The method includes the following steps that in a control loop to be detected, a set of progress data are collected in real time in an on-line mode; improved intrinsic time-scale decomposition is performed on the progress data in real time in an on-line mode, and monitoring statistics corresponding to all obtained decomposition sub-signals are calculated in real time; whether all the monitoring statistics exceed a set threshold value omega or not is judged, and an on-line detection result is obtained according to all judgment results. By the utilization of the on-line detection method, multi-period oscillation behaviors of the industrial control loop can be detected in a quantified mode to obtain regularity degrees and periods of all oscillation components in the multi-period oscillation. Rich data supports are provided for evaluating the oscillation behaviors and diagnosing a fault source.

The invention, which belongs to the field of lithium ion battery production process, provides a method for testing the mass ratio capacity of a lithium battery material so that a problem of a detection difference of a total battery gram volume and a button battery gram volume can be solved and thus the safety performance of the total battery can be improved. The method comprises the following steps that: a positive electrode piece is made; a negative electrode piece is made; die punching and weighing are carried out, wherein masses of positive and negative pieces are selected based on positiveand negative electrode material types and corresponding pairing is carried out and then the positive and negative pieces are placed in a glove box for two hours; button electricity assembling of theglove box is carried out; the made button battery is clamped at an electrochemical testing cabinet and charge and discharge currents are calculated according to testing multiplying powers (0.2C, 1C, 3C, 5C) based on a formula: current=multiplying power* theoretical gram volume*(M2-M1)*omega%.

The invention discloses a policy key information extraction method and device, a storage medium and electronic equipment. The method comprises the following steps: acquiring policy information from aplurality of data sources; classifying the policy information according to keywords based on preferential policies to obtain declaration policy texts in the policy information; performing regular expression matching and semantic similarity calculation on the declaration policy text, extracting policy key information, wherein the policy key information comprises declaration conditions supported bypolicies, support amount and declaration time. By adopting the technical scheme of the invention, category labeling can be carried out on policies, and key information such as support conditions, support capital amount and declaration time in declaration policy texts can be extracted; and annotated and analyzed policy information can be used for multi-dimensional data analysis and oriented pushingof enterprises.

The invention provides a multilingual public opinion analysis-based tourism big data system. The multilingual public opinion analysis-based tourism big data system comprises a cross-language big datacollecting subsystem, a cross-language big data processing subsystem and a cross-language big data analysis and application subsystem, wherein the cross-language big data collecting subsystem is usedfor collecting and in real time transmitting multi-dimensional tourism public opinion data to the cross-language big data processing subsystem and the cross-language big data analysis and applicationsubsystem; the cross-language big data processing subsystem intelligently processes and analyzes collected multilingual data and transmits analyzing results to the cross-language big data analysis andapplication subsystem; the cross-language big data analysis and application subsystem popularizes and applies the analyzing results. Through collection and automatic machine translation and processing worldwide multilingual data and fusion with domestic tourism big data, the multilingual public opinion analysis-based tourism big data system can produce worldwide tourism big data knowledge graphsand tourism think tanks, thereby promoting tourism development from a global perspective.

The invention discloses a method for detecting intermittent oscillation of industrial control circuits in an online manner. The method includes steps of (1), preliminarily acquiring a big window historical datum from each to-be-detected control circuit, processing the big window historical data and initializing detection systems; (2), acquiring a small window process datum from each to-be-detected control circuit in real time in an online manner, and updating the big window data by the aid of the small window process data; (3), combining the small window data with the original big window data, processing the small window data and the big window data and recombining the small window data with the big window data to obtain various frequency recombined sub-signals of the updated big window data; (4), computing monitoring statistics corresponding to the various recombined sub-signals and judging real-time detection results; (5), repeatedly carrying out steps (2), (3) and (4) and integrating all judgment results to obtain online detection results. The method has the advantages that intermittent and multi-period oscillation behavior of the industrial control circuits can be quantitatively detected by the aid of the method, compositions such as multiple-oscillation, intermittent oscillation and non-stationary signals in the intermittent and multi-period oscillation behavior can be differentiated from one another, and regular degrees and periods of various oscillation components can be acquired.

The invention relates to a smart grid control operation continuous analog simulation method. The method includes the following steps that a model is built for a smart grid; smart grid control operation is simulated; a model state in future is determined; simulation data of the smart grid are determined. Through the implementation steps, the complex simulation calculation task of the smart grid is decomposed into a plurality of calculation modules, the calculation modules are interacted with the smart grid through the distributed MAS, and the joint analog simulation of the multi-time scale and full-life cycle for the operation behavior, optimal control strategy and different operational modes of the smart grid is achieved. On the basis of the simulation method, the application range can be broadened continuously, and more thorough and comprehensive analog and analysis of the smart grid control operation are achieved.

The invention discloses a product information processing method and device. The product information processing method and device are applied to a server side. The server side stores product identifications and production information corresponding to the product identifications, and the product identifications are used for generating two-dimension codes arranged on products. The product information processing method comprises the steps that the product identifications sent by at least one circulation terminal, and circulation information corresponding to the product identifications are received, wherein the product identifications are obtained in the mode that the circulation terminal analyzes the two-dimension codes of the products; the circulation information is stored according to the product identifications. Compared with the mode that in the prior art, two-dimension codes only correspond to production information of products, the two-dimension codes adopted for the product information processing method correspond to the production information of the products and the circulation information of the products at the same time, comprehensive product information can be tracked through the two-dimension codes, more data supports are brought to users for verifying product authenticity, and then applicability of the product information processing method and device is improved.

The invention relates to a preparation and characterization method for a precious metal ultrafine wire EBSD test sample. The comprises the steps: stretching a precious metal ultrafine wire sample andbonding the precious metal ultrafine wire sample to the top end of the inclined surface of a double-inclined sample table; placing the precious metal ultrafine wire sample in a sample bin to select asample section preparation and test area; tilting the sample table, carrying out carbon plating treatment, ion beam cutting and ion beam surface polishing treatment on the sample in the field of viewto obtain a cross section observation sample of the noble metal ultrafine wire without surface stress, and observing and obtaining a microstructure morphology image of a wire cross section observationarea through ion beam channel contrast imaging; tilting the double-tilting sample table until the angle between the observation section and the incident electron beam is 70 degrees, and performing electron back scattering diffraction detection on the section of the ultrafine wire through a CCD detector to obtain an EBSD image and a crystallography signal of the section of the sample micro-area. The EBSD and the ion beam channel contrast image are combined to provide more systematic and comprehensive data support for microcell analysis of precious metal ultrafine wires, and the comprehensive analysis range of samples can be expanded.

The invention discloses a method for detecting multi-period oscillation behaviors of industrial control loops. The method includes the following steps: (1) collecting a set of process data xt in the to-be-detected control loops, (2) carrying out wavelet packet conversion decomposition on the process data xt to obtain an original binary-tree-shaped decomposition structure T0, (3) simplifying the original binary-tree-shaped decomposition structure T0 according to the minimum shannon entropy rule, the non-Gaussian indexes and the quasi oscillation indexes to obtain an optimal binary-tree-shaped decomposition structure Tbest, and (4) signing subspace corresponding to non-Gaussian distribution leaf nodes according to the non-Gaussian indexes TG of all leaf nodes on the optimal binary-tree-shaped decomposition structure Tbest to obtain a coordinate position set I corresponding to the leaf nodes with the signed subspace. By means of the method, the multi-period oscillation behaviors of the industrial control loops can be quantitatively detected, the regulation degrees and the periods of oscillation components of multi-period oscillation are obtained, and abundant data supports are provided for evaluation and fault source diagnoses of the oscillation behaviors.

The invention discloses a slope seismic stability time frequency analysis method comprising the following steps: carrying out experience modal decomposition for measured seismic wave time histories, thus forming a plurality of intrinsic modal functions; carrying out Hilbert transformation for each formed intrinsic modal function, thus obtaining a time frequency spectrum of each intrinsic modal function, and extracting time, frequency and amplitude of the seismic wave time history from the time frequency spectrum; calculating a stress state on a slope bedding plane according to separated amplitude and instantaneous frequency of each intrinsic modal function; accumulating calculation results of all intrinsic modal functions, thus obtaining the stress state of the slope bedding plane under the seismic wave time history effect; calculating a sliding force and an anti-sliding force of the slope bedding plane under the seismic wave time history effect; calculating a safety factor of the slope stratified slope. The method can fully consider the seismic wave time-frequency-amplitude factors when making time frequency analysis on the slope seismic stability, thus obviously improving the slope seismic stability evaluation accuracy and reliability.

The invention discloses a conductive material defect high-precision imaging detection method based on a pulsed eddy current. The method comprises the following steps: 1, arranging two rows of magneticsensors in an excitation magnetic field uniform region on the surface of a conductive material to be detected in an array manner, and arranging a second row of sensors in a gap position of the firstrow of sensors; 2, sending an acquisition instruction to the magnetic sensor array in the scanning detection process by utilizing a speed encoder provided with a distance measuring wheel; 3, processing an acquired magnetic sensor signal by using an equal spatial interpolation method to obtain a magnetic field characteristic image of the detected area; according to the invention, high-precision imaging detection of defects of the conductive material can be realized.

The invention relates to an electronic mutual inductor performance real-time monitoring system and method, and belongs to the technical field of automation of an electric power system. The method comprises: first of all, synchronously acquiring the protection, measuring and metering voltage and current quantities of a routine mutual inductor and an electronic mutual inductor in a transformer station and the state information of the electronic mutual inductor itself; and then according to a set time interval, comparing an amplitude difference and a phase difference between the same-phase sampling data of the routine mutual inductor and the electronic mutual inductor, determining whether the amplitude difference and the phase difference of the two are within a set permissible scope, if the amplitude difference or the phase difference exceeds the set scope, performing calculating on the amplitude difference or the phase difference, sending alarm information, and at the same time, recording the state information of the electronic mutual inductor itself at the moment so as to realize real-time monitoring of the electronic mutual inductor. The method provided by the invention is simple, is easy to implement, can monitor the electronic mutual inductor in real time, and provides abundant data support for examination of the operation reliability and the long-term stability of the electronic mutual inductor.

The invention discloses a big data statistics-based remote sensing satellite relative radiometric calibration method. The method comprises the following steps of: carrying out histogram statistic on data by adoption of a remote sensing satellite 0-level stripe data full statistic method; solving a statistical probability according to the histogram statistic, and carrying out boundary processing ona DN value which is 0 and a DN value which is a maximum quantized value; matching a histogram with the statistical probability to form a search table; and carrying out relative radiometric calibration on 0-level data according to the search table. Through the method, the problem that existing remote sensing satellite relative radiometric calibration is low in labor efficiency and incomplete in sample statistic is solved.

The invention discloses a digital twin technology equipment product carbon footprint digital accounting method and system, and belongs to the technical field of enterprise product carbon emission, and the method comprises the steps: S1, building a model field information code; s2, establishing a configurable carbon footprint accounting model; s3, establishing a configurable carbon accounting strategy; s4, establishing a mapping relation between a carbon accounting strategy and basic data; s5, establishing a unified product category library, formulating a standard coding rule and mapping BIM model data; s6, making a standard coding rule by the unified material coding library and mapping BIM model data; s7, based on a twin model and an interface technology, realizing data acquisition in multiple data acquisition modes; s8, equipment product automatic accounting based on a twin model or real-time data; s9, comparing the carbon emissions based on different carbon accounting schemes; s10, real-time monitoring of enterprise product carbon emission is carried out; and S11, analyzing and evaluating the carbon emission in the whole life cycle of the product.

The invention discloses a nonvolatile memory bandwidth detection method. The method comprises the following steps: setting a nonvolatile memory to be in an APD mode; creating a namespace in the APD mode, and formatting the namespace into an EXT4 format; reading / writing the bandwidth of all the namespaces through each CPU by utilizing a tool for testing memory delay and bandwidth; and collecting and arranging the data of the CPU read / write bandwidth, and evaluating the nonvolatile memory bandwidth performance based on the data. The invention further discloses a nonvolatile memory bandwidth detection device, computer equipment and a readable storage medium. According to the method, the bandwidth performance of the nonvolatile memory is tested in the hard disk mode of the nonvolatile memory by using a tool for testing the memory delay and the bandwidth, so that errors caused by single-mode testing are avoided, the tested data is more complete and accurate, and more data support is provided for performance evaluation of the nonvolatile memory.

The invention discloses a contact net support looseness intelligent monitoring device. The device comprises a data acquisition unit, a data processing unit, a storage unit and a signal input and output unit. The data acquisition unit collects an acceleration value of a contact net support to be tested in a triaxial direction; the storage unit records an initial triaxial angle, a vibration quantityfeature value, a preset angle difference threshold value and a preset vibration quantity feature value difference threshold value; the data processing unit analyzes and processes the collected triaxial acceleration value and compares the difference between the obtained real-time triaxial angle and an initial value and the difference between the obtained real-time vibration quantity feature valueand the initial value with the angle difference threshold value and the vibration quantity feature value difference threshold value respectively to obtain an output signal reflecting the looseness situation of the monitored contact net support. On this basis, the invention also discloses a contact net support looseness online monitoring system and a method thereof. Through the device, the system and the method thereof, an accurate judgment of the looseness situation of the contact net support can be achieved, and the construction difficulty and the construction cost are reduced.

Embodiments of the invention provide a query statement processing method and device, and relates to the field of databases. The method comprises the following steps of: analyzing a query statement, anexecution consumed time of which does not exceed a set threshold value, so as to obtain an analysis result; judging whether the analysis result satisfies a risk judgement condition or not on the basis of the analysis result; and if the analysis result satisfies the risk judgement condition, determining the query statement as a risky query statement. The query statement processing method and device are beneficial for providing effective and comprehensive data support for database optimization.

The invention discloses an intelligent greening maintenance method and system based on the Internet of Things, and the system comprises a data collection end which is used for obtaining the greening related data of a greenbelt region based on the Internet of Things, and transmitting the greening related data to a management and maintenance cloud brain in real time; a management and maintenance cloud brain which is used for realizing analysis and processing of greening related data based on an artificial intelligence algorithm so as to guide intelligent maintenance work; a greening supervisionclient which is used for checking the analysis and processing result of the management and maintenance cloud brain and distributing maintenance tasks to the greening mobile client so as to supervise intelligent maintenance through the greening mobile client; and a greening mobile client which is used for receiving the maintenance task distributed by the greening supervision client and uploading atask completion condition. The objective of the invention is to solve the problem that an existing manual patrol maintenance method cannot guarantee the refinement, real-time performance and integrityof management.

The invention discloses a BCG signal noise reduction method and system. The method comprises the steps that an initial BCG signal is acquired; removing body movement interference of the initial BCG signal according to a preset method to obtain a second BCG signal; processing the second BCG signal according to a weighting window function to obtain a third BCG signal; processing the third BCG signalaccording to a low-pass filtering method to obtain a fourth BCG signal; processing the fourth BCG signal according to a wavelet threshold denoising method, reconstructing the M layers of features toobtain a final BCG signal, and outputting the final BCG signal; the method and the system are high in adaptability, have a good denoising effect on different signals, are simple in parameter structureand low in calculation complexity, and solve the problems that an existing BCG signal is poor in denoising effect and a denoising algorithm is single and complex.

The invention discloses a three-degree-of-freedom flapping wing motion test experimental platform. Integrated transfer type differential gear train design is adopted, at the bottom, a differential gear train is driven by a pair of motors to achieve two-degree-of-freedom motion of a flapping wing, the top is driven by another motor, a bottom experimental device is driven to conduct integrated transfer motion, and three-degree-of-freedom motion is achieved. A six-axis force sensor is integrated between the wing and a motion shaft and connected with the experimental platform through a coupler. The experimental platform is high in degree of freedom and can simulate a more comprehensive motion form of an insect flapping wing; adaptability is wide, and various flapping wings can be tested only through replacement of a flapping wing structure; and meanwhile, the six-axis force sensor is connected with the flapping wing, so that measurement accuracy is improved.

The invention relates to the field of data analysis, in particular to a pre-examination information interaction method based on data analysis and related equipment. The method includes the steps of acquiring pre-examination information to be processed from an interaction platform, wherein the pre-examination information to be processed includes voice input information or character input information or preset item selection information; identifying the content of the obtained pre-examination information to be processed, extracting keywords in the content, traversing a pre-examination information database according to the extracted keywords, conducting relevancy matching, extracting corresponding information data and generating data to-be-output instruction if the matching is successful, andgenerating a guide instruction if the matching is not successful; outputting the generated data to-be-output instruction or guide instruction to an interaction platform. By receiving, recognizing andmatching the pre-examination information of a patient and outputting feedback content corresponding to the pre-examination information, the efficiency of pre-examination information data processing is improved, and the pre-examination information provided by the patient can obtain more data support which is more comprehensive.

The invention discloses an iconography examination report structuralization method and device. The method comprises the steps: carrying out the preset specific information extraction of historical iconography examination reports, obtaining specific information, and constructing a word segmentation dictionary based on the specific information; based on the word segmentation dictionary and a presetentity word part-of-speech label, performing word segmentation processing on the iconography inspection report to obtain entity words; constructing a dependency relationship tree of the entity words based on the entity words and a preset storage structure of specific information; determining a directed acyclic graph of the entity words with part-of-speech values based on the dependency tree of thepre-underwriting iconography inspection report and the entity words, the directed acyclic graph comprising a plurality of dependency paths; determining an optimal path in the plurality of dependencypaths; determining a structured iconography examination report based on the optimal path; and underwriting processing is carried out by using the structured iconography inspection report. Structured automatic extraction can be automatically carried out on the physical examination image examination report, and richer data support is provided for underwriting.

The invention relates to a multi-scene performance index prediction method and system for a semiconductor production line, and the system comprises a production scene quantitative dividing module which is driven by data, carries out the quantitative mapping of a product value, a product average processing period and the utilization rate of all equipment of the production line, and divides the production line into a light-load scene, a normal-load scene and a heavy-load scene; a main prediction network construction module which is used for constructing a prediction network in a normal load scene by taking the divided normal load data as sample data and combining a deep neural network algorithm with semiconductor production line performance prediction; and a multi-scene prediction model construction module which is used for applying the idea of transfer learning to production line prediction and constructing networks under light-load and heavy-load scenes according to the constructed main prediction network so as to form a multi-scene prediction model. Compared with the prior art, the production line scenes are quantitatively divided, multiple production line performance indexes under different load scenes can be more accurately predicted, and online use can be achieved.