29results about How to "Effective data support" patented technology

The invention provides a fracture morphology automatic identification and learning method based on multi-modal fusion learning, and relates to the field of metal fracture morphology analysis, and the method comprises the steps: S1, constructing a data set; s2, carrying out fracture image shooting and image annotation, and after annotation is completed, dividing a data set into a training set, a verification set and a test set; step S3, carrying out multi-modal fusion learning; and S4, feature importance analysis and SHAP analysis are carried out. According to the method, image recognition and machine learning are combined, accurate prediction of dimple fracture and brittle fracture areas of the aluminum alloy is achieved, meanwhile, key factors influencing the metal fracture morphology can be effectively obtained, and therefore an important reference basis is provided for effective optimization of material performance.

The invention discloses a feed feeding control system and method based on data analysis, and relates to the technical field of feed feeding, and the method comprises the steps: obtaining feed feeding data and corresponding livestock growth data according to a historical feed feeding cycle; analyzing the feed feeding data, and extracting a matching sequence of historical feed feeding data; combining the corresponding livestock growth data to establish an associated data group; constructing a feed ratio prediction model based on a support vector regression method; performing feed preparation and feeding according to the real-time matching sequence; analyzing an adaptive value of the real-time matching sequence of the current feed feeding period according to the real-time monitoring data set, and judging the continuous condition of the current feed feeding period according to the adaptive value; and constructing an update cycle matching model based on the update cycle matching set, and analyzing the total number of days of the subsequent feed feeding cycle according to the update cycle matching model. The rationality of feed feeding is improved, and intelligent and reasonable feeding is realized.

The invention discloses an unmanned workshop data processing system based on data analysis, particularly relates to the technical field of big data, and comprises a monitoring area determination module, a data acquisition module, a data preprocessing module, a data analysis module, a quality evaluation module, a judgment module and a man-machine interaction module. The monitoring area determination module is used for determining a single sub-time monitoring area and a single PCB monitoring area; the data acquisition module is used for acquiring a first unmanned workshop key information value; the data preprocessing module is used for obtaining a second unmanned workshop key information value; the data analysis module is used for performing data processing on the second unmanned workshop key information value to obtain a third unmanned workshop key information value; the quality evaluation module is used for constructing a quality evaluation model to obtain a PCB manufacturing comprehensive evaluation value; the judgment module judges whether the manufacturing of the PCB meets the standard or not; and the man-machine interaction module is used for providing a visual interface. The production efficiency of an unmanned workshop is effectively improved, and the qualified rate of PCBs is improved.

The invention discloses a system and method for managing review data by adopting an online large model, and the method comprises the steps: building a data collection process, building an index algorithm, building a review opinion data large model, standardizing a data format, formulating a result standard, treating non-compliant data, checking key information, and achieving file archiving through an OSS service. Effective data support is provided for design review, and the method comprises the steps of basic data acquisition and integration, standardized formulation of a design review material list and accurate uploading and verification of design review materials; the method comprises the following steps: constructing a review opinion data large model, splitting historical review opinion data into large model components, supporting autonomous configuration of a review opinion model according to review specifications, finally splicing to generate a review opinion report, standardizing a data format, formulating an achievement standard, treating non-compliant data, and checking key information. And file archiving is realized through OSS service, and effective data support is provided for design review.

The invention relates to the technical field of crop spectrum, and discloses a crop spectrum and photosynthesis monitoring device, which comprises a main control unit, a sensing unit and a spectrograph unit, and the main control unit comprises a microcontroller and is used for realizing acquisition, calculation, storage and transmission of spectrum and temperature data of the sensing unit and further controlling the temperature control unit to adjust the temperature of the equipment, and a framework of an embedded core board and a bottom board is adopted as a whole. By integrating a single wide-spectrum and high-resolution optical fiber spectrometer, crop spectrum information of 400-900 nm can be obtained, high-resolution detection smaller than or equal to 1 nm is achieved, wavelength, irradiance, radiance, reflectivity and light intensity information within the wide-spectrum range of crops are output, and the spectrum information of the crops can be obtained through an algorithm library integrated in the main control unit. And inversion output of indication parameters such as sunlight-induced chlorophyll fluorescence, a novel leaf chlorophyll index, a normalized vegetation index, an enhanced vegetation index, a normalized red edge index and a photochemical vegetation index of crops is completed.

The invention relates to the technical field of intelligent early warning, in particular to a corn disease monitoring and early warning system based on agricultural Internet of Things, which comprises a data fusion calibration module, a multi-dimensional feature extraction module, a self-adaptive fusion reference construction module, a feature evaluation and fusion module, a classification and recognition module and an early warning decision generation module, carrying out fusion calibration on the visible light image data and the corresponding environment data to obtain standard monitoring data; performing multi-dimensional feature extraction on the standard monitoring data to obtain image feature information and environment feature information; constructing a multi-source feature adaptive fusion reference; evaluating the disease influence degree of the image feature information and the environment feature information to obtain a comprehensive feature index; identifying a disease type and a disease grade as a disease identification result of the corn; according to a disease early warning mapping relation in a disease early warning rule base and a continuous monitoring period condition required for triggering early warning, obtaining early warning information; according to the invention, the efficiency of corn disease monitoring and early warning can be improved.

The invention relates to a rapid positioning detection method for a high-precision pipeline route. The method comprises the following steps: S1, firstly, putting a detection device into a pipeline along the flowing direction of a fluid medium; s2, starting a measuring instrument of the head mechanism, performing data fusion by a Kalman filter, and transmitting the data to a control center of the head mechanism in real time; s3, opening a fan plate, and then starting propellers on the head mechanism and the propelling mechanism: the two mechanisms work together to realize the swimming and steering movement of the detection device in the pipeline, and detecting the condition in the pipeline by using a sensor; s4, when the head mechanism detects that the flow velocity in the pipeline changes suddenly, the sector plate is withdrawn, the position and range of the flow velocity change are recorded, a warning signal is sent out through a control center of the head mechanism, and then other parts in the pipeline continue to be detected; and if the signal cannot be sent, ending detection and immediately returning. According to the invention, the pipeline can be automatically, efficiently and automatically detected, the accuracy is high, the real-time performance is good, the labor cost is reduced, and the manual operation risk is reduced.

The application discloses an operating mechanism data acquisition system and a driving loop module and method thereof, and the module comprises a high-voltage direct-current power supply HM, a high-voltage direct-current power supply KM, a power adapter DP, an embedded control module QK, a control switching plug HT, a supply and discharge circuit, a closing and opening knob KK and a rotary switch ZH2; the high-voltage direct-current power supply HM provides an energy storage power supply and a closing power supply for a measured operating mechanism, the high-voltage direct-current power supply KM provides an opening power supply for the measured operating mechanism, the power adapter DP provides a working power supply for the embedded control module QK, and the required operating power supply voltage for testing can be met; the embedded control module QK can realize program control of driving, the rotary switch ZH2 can realize mode conversion between manual control and program control of driving, and the closing and opening knob KK can realize manual control of driving, so that the problem that traditional operating mechanism research experiments cannot simultaneously integrate automatic control of multiple characteristic parameters is solved.

The present invention relates to the field of network communication and video monitoring technology, and discloses a video tracing system. The present invention utilizes a tracing device to embed tracing information into video data before the video data is transmitted back, and then encrypts the video data, which can not only improve data security, but also ensure that even if the video data is accidentally leaked, the video data can be tracked according to the tracing information, which is crucial to the high-quality operation and maintenance of urban rail transit, and can provide safe and effective data support for urban rail transit management.

The invention discloses a pressure channeling prevention and control simulation system and method. The pressure channeling prevention and control simulation system comprises a material pumping module, a runner simulation module and a data processing module. The runner simulation module comprises a groove body, a cover plate positioned above the groove body and a waste barrel; the groove body is in a cuboid shape, and a liquid inlet and a liquid outlet are formed in the two opposite side faces of the groove body respectively. A liquid inlet of the tank body is connected with the material pumping module through a water pipe; a liquid outlet of the tank body is connected with the waste barrel through a water pipe; a porous medium simulation flow channel is placed in the tank body; a plurality of pressure monitoring holes and filtration holes are formed in the bottom surface of the tank body; the filtration hole is used for simulating a fracturing fluid filtration channel; the data processing module is used for processing the collected data of the pressure gauge to obtain pressure channeling prevention and control simulation data, evaluation of the prevention and control effect of a pressure channeling prevention and control strategy under different reservoir geological background conditions is achieved, and the efficiency of pressure channeling prevention and control is improved.

The invention discloses an outdoor power distribution cabinet with flood prevention early warning, which comprises a power distribution cabinet body, the left side and the right side of the power distribution cabinet body are fixedly connected with a cooling box and a transfer box respectively, and the back of the power distribution cabinet body is fixedly connected with a heat dissipation box. According to the outdoor power distribution cabinet with the flood prevention early warning function, rainwater is collected through the rainwater collecting assembly and guided into the heat dissipation box to be stored, circulation driving of the rainwater is achieved under cooperation of the cooling water pipe, the transfer box, the cooling box and the water circulation power part, heat dissipation and cooling are carried out on the power distribution cabinet body, effective utilization of the rainwater is achieved, and in the process, the rainwater is recycled. The power distribution cabinet body is kept closed, interference of the external humid environment on the internal environment of the power distribution cabinet body can be effectively avoided, meanwhile, the rainwater flow can be judged in the rainwater collection process, and effective data support is provided for flood prevention early warning.

The present application provides a kind of sedimentation tank sludge quantity prediction system and method, it is related to sedimentation tank sludge control technical field, comprising: for each sedimentation period of sedimentation tank, at least one group of historical water inlet parameters and corresponding historical sludge-water interface height in non-sludge discharge period are obtained respectively, and total actual sludge production after sludge discharge period ends and corresponding total sludge-water interface height;According to each historical sludge-water interface height, total actual sludge production and total sludge-water interface height, the real-time actual sludge production corresponding to historical water inlet parameters is obtained by processing;Real-time water inlet parameters are obtained as input, and the sludge quantity prediction model corresponding to the real-time actual sludge production as output is trained;A group of real-time water inlet parameters of sedimentation tank in non-sludge discharge period is obtained, and real-time water inlet parameters are input into sludge quantity prediction model, to obtain the sludge quantity prediction result of sedimentation tank.The beneficial effect is that the real-time sludge production of sedimentation tank can be effectively predicted;Self-adaptive training and correction of sludge quantity prediction model can be realized.

The utility model discloses a fault bearing test platform, comprising a signal acquisition device which comprises a bottom plate, and a force application driver, a bearing installation seat and a rotation driver which are successively arranged on the bottom plate, the bearing installation seat comprises an outer ring seat and an inner ring seat which are coaxially sleeved from outside to inside, and a fault bearing is installed between the outer ring seat and the inner ring seat; the outer ring seat is rotatably arranged, the driving end of the rotary driver is connected with the outer ring seat and is used for driving the outer ring seat to rotate, the driving end of the force application driver is coaxially connected with the inner ring seat and is used for applying an axial load to a fault bearing, and a sensor is arranged in the inner ring seat. The fault bearing test platform can simulate the real use condition of a fault bearing, can provide effective data support for a bearing diagnosis algorithm, and also can verify the reliability of a sensor and a cable thereof under the real use condition.

The invention discloses a device for on-line monitoring of a storage battery pack and a use method thereof, the device comprises an on-line monitoring platform and a monitoring circuit, the monitoring circuit is used for integrating a voltmeter, a plurality of first switches and a plurality of second switches and is used for carrying out voltage detection on a plurality of storage battery packs, and the invention relates to the technical field of storage battery monitoring. According to the device for online monitoring of the storage battery pack and the use method of the device, through the arrangement of the voltmeter, the plurality of first switches and the plurality of second switches, under the cooperation of the online monitoring platform, the on-off adjustment of the first switches and the second switches is carried out, so that the voltage detection of independent storage batteries in the storage battery pack is realized; and the voltage of the single storage battery can be monitored in a single measurement mode and an overall measurement mode by adjusting the on-off of different first switches and second switches, so that accurate and convenient conditions can be provided for voltage monitoring through a mode switching mode while the monitoring modes are diversified.

The application provides a complex trait gene mining method and system based on a large language model and multi-modal data, and belongs to the technical field of gene data analysis. The method comprises the following steps: obtaining a statistical data set containing multi-modal data of different legume populations; annotating all genes in the statistical data set based on a reference genome to obtain a whole genome semantic graph; if the large language model receives a site of a target significant trait, calculating the comprehensive scores of each gene at the site based on the whole genome semantic graph and the site by using the large language model, and determining a complex trait gene based on the comprehensive scores of each gene; if the large language model does not receive the site of the target significant trait, determining candidate genes based on the target significant trait by using the large language model, and determining the complex trait gene from each candidate gene by using the large language model based on the whole genome semantic graph. The application can locate the most essential gene affecting the target significant trait.

The present invention discloses a medical data processing method and system based on artificial intelligence NLP technology, and relates to the field of medical data processing technology. The method includes: acquiring and aggregating medical institution data based on NLP technology to obtain medical data processing results; acquiring and aggregating government data based on NLP technology to obtain government data processing results; acquiring and processing local hospital data based on NLP technology to obtain local data processing results; and constructing a medical knowledge graph based on the medical data processing results, government data processing results, and local data processing results, in combination with a data cognitive thinking model and a knowledge graph architecture. The present invention can perform comprehensive and accurate processing and analysis of medical data, and provide effective data support for subsequent medical services.

The invention relates to the technical field of sealing detection, and particularly discloses a steel-plastic composite pipe sealing detection method and device based on an electric spark detection device, a processor and a storage medium, and the method comprises the steps: determining the expected thickness and the minimum thickness of a sealing layer of a steel-plastic composite pipe; determining a first breakdown voltage, corresponding to the expected thickness, of the electric spark detection device and a second breakdown voltage, corresponding to the lowest thickness, of the electric spark detection device; first sealing scanning operation is executed on the sealing layer of the steel-plastic composite pipe according to the first breakdown voltage based on the electric spark detection device, and a first scanning result is obtained; judging whether the sealing layer has sealing deviation or not based on the first scanning result; if yes, second sealing scanning operation is executed on the sealing layer according to the second breakdown voltage based on the electric spark detection device, and a second scanning result is obtained. The detection principle of an existing electric spark detection device is reversely applied, so that accurate detection of the sealing layer is achieved, the reliability of a sealing detection result is improved, and the actual requirements of enterprises are met.

This invention discloses a method, apparatus, electronic device, and readable storage medium for NCFI carbon emission responsibility allocation that considers fairness. The allocation apparatus includes a power flow distribution acquisition module, an original allocation result acquisition module, an allocation fairness interval acquisition module, an original satisfaction acquisition module, and a satisfaction optimization and adjustment module. The satisfaction optimization and adjustment module includes an original satisfaction calculation module, a first satisfaction optimization and adjustment module, and a second satisfaction optimization and adjustment module. This invention, on the one hand, can better link the historical emission responsibility of load nodes, individual development opportunities, and node carbon emission responsibility, considering fairness without changing the total responsibility allocation, thus avoiding the phenomenon of unfair allocation schemes; on the other hand, it reduces the responsibility allocation of most load nodes based on reasonable and feasible allocation results, providing effective data support for the formulation of corporate carbon reduction strategies, and is of great significance to coordinated economic development.

This invention discloses a method and system for detecting the cleanliness of photovoltaic panels, relating to the field of photovoltaic panel detection technology. The method includes first collecting benchmark data of a standard clean photovoltaic panel, dividing the effective light-receiving surface of the panel under test into several independent detection zones, calculating the cleanliness of each zone, extracting the spatial distribution characteristics of cleanliness, calculating the uniformity of light absorption in combination with local light absorption intensity, and obtaining an initial judgment result of overall cleanliness through correlation determination; then, based on the cleanliness threshold of each zone and the natural contamination pattern of the array, selecting contamination characteristic areas and clean benchmark areas to obtain on-site verification data, calibrating the initial judgment result, and obtaining the final detection result. The system includes modules corresponding to the steps of the method. This method can provide specific information on the contamination distribution in each area for the clean operation and maintenance of photovoltaic panels, improve the pertinence and actual implementation effect of photovoltaic panel clean operation and maintenance work, and provide effective data support for the daily operation and maintenance of photovoltaic power plants.

The present invention provides a method for automatic recognition and learning of fracture morphology based on multimodal fusion learning, which relates to the field of metal fracture morphology analysis, including: step S1, constructing a data set; step S2, taking fracture images and annotating the images, after the annotation is completed, dividing the data set into a training set, a validation set and a test set; step S3, multimodal fusion learning; step S4, feature importance analysis and SHAP analysis. The method combines image recognition with machine learning to achieve accurate prediction of dimple fracture and brittle fracture areas of aluminum alloys, and can also effectively obtain key factors affecting metal fracture morphology, thereby providing an important reference basis for the effective optimization of material properties.

The invention discloses a handheld image point cloud and laser point cloud fusion detection method for a bridge prefabricated part. The method comprises the following steps: synchronously obtaining a laser point cloud and a sequence image of the prefabricated part; reconstructing the sequence image to obtain an image point cloud; performing normalization by taking the laser point cloud as a reference to obtain the laser point cloud and the image point cloud with consistent physical scales; initial attitude alignment of the two sets of point clouds is completed, rigid fine registration is carried out, the laser point clouds are corrected, and fused point clouds are obtained; generating a standard virtual point cloud; performing semantic segmentation on the fused point cloud, and outputting a point cloud set of each sub-component; extracting line-plane features of the key points; calculating the key geometric dimension of the prefabricated part, comparing the key geometric dimension with the standard virtual point cloud, and judging whether the dimension deviation meets a preset deviation or not; and evaluating the flatness quality of the surface of the component, and generating a three-dimensional full-field deviation chromatogram which covers the whole surface of the component. According to the invention, rapid, comprehensive and high-precision detection of the geometric dimension and the appearance flatness of the prefabricated part is realized.

The invention provides a fund flow analysis method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining fund flow time series data of a target fund flow index, and carrying out the processing of the fund flow time series data, and obtaining the processed target time series data and feature data; predicting the fund flow based on the target time sequence data through a first time sequence prediction algorithm to obtain first fund flow prediction sequence data; predicting the fund flow based on the target time sequence data and the feature data through a second time sequence prediction algorithm to obtain second fund flow prediction sequence data; fusing the first fund flow prediction sequence data and the second fund flow prediction sequence data to obtain fund flow prediction result data; abnormal root cause analysis is carried out on fund flow prediction result data through a multi-dimensional data index root cause system, fund flow abnormal root cause elements are determined, the prediction precision is improved, and abnormal analysis and positioning are achieved.

The application discloses a kind of based on enterprise service whole scene business progress query hub system and method, it is related to enterprise service technical field, solve the scene coverage not comprehensive, data island is serious, query efficiency is low, authority control is not accurate, the degree of visualization is insufficient, lack of intelligent early warning and other technical problems existing in present enterprise business progress query.System includes data acquisition layer, data processing layer, hub core layer, application service layer, authority control layer and storage layer, each layer cooperates and works, realizes the unified acquisition of enterprise service whole scene (including customer management, project management, supply chain management, financial management, human resource management, operation and maintenance management etc.) business data, standardization processing, intelligent analysis and convenient query.Through multi-source data fusion technology, break data island, adopt intelligent search algorithm to improve query efficiency, in combination with fine-grained authority control to guarantee data security, intuitively present business progress by the aid of multidimensional visualization display.

The invention discloses a new energy power system coordinated operation simulation system, and relates to the technical field of new energy power dispatching simulation systems, and the system comprises a wind power calculation module which predicts and calculates the wind power integration capacity # imgabs0 # based on meteorological data; the photoelectric calculation module is used for predicting and calculating photoelectric grid-connected capacity # imgabs1 # based on the meteorological data; and the grid-connected optimization module is used for calculating an electric power system adjustment parameter and calculating a wind power and photoelectric grid-connected deviation parameter based on the wind power grid-connected capacity # imgabs2 # and the photoelectric grid-connected capacity # imgabs3 #. According to the method, the solar photovoltaic grid-connected capacity is finely calculated through the time period sequence and comprehensive consideration of the illumination intensity data corresponding to the time period sequence, the accuracy and reliability of solar photovoltaic grid-connected capacity calculation are remarkably improved, meanwhile, accurate calculation of wind power and photovoltaic power distribution is achieved, and reliable data support is provided for follow-up power system coordinated operation.

The present invention relates to the field of crane control technology, and in particular to a cargo positioning system based on a crane. The present invention lifts cargo through a lifting mechanism, a positioning mechanism, obtains cargo images, a detection module obtains a clamp force value, and obtains a cargo movement trajectory during the cargo lifting process. A classification unit identifies a cargo center point according to the cargo image, controls the clamp to clamp the cargo, controls the lifting mechanism to lift the cargo to a preset height and maintains it for a preset time, calculates a cargo stability characterization value to classify the cargo, a control unit selects a cargo positioning strategy according to the cargo category, and a determination unit determines whether cargo positioning identification is accurate according to the cargo movement trajectory during the cargo lifting process. The present invention classifies cargo according to weight balance and adopts different cargo positioning methods for different categories of cargo, thereby preventing cargo from tilting during the cargo lifting process and improving the safety of crane operation.

The invention discloses a petroleum-based carbon material performance prediction method, device and equipment and a storage medium, and the prediction method comprises the steps: constructing a refinery data database; setting the structure data of the carbon material in the refinery data as first preset data; preprocessing the refinery data, including updating first preset data; taking various data of the refinery plant data as characteristic data, and establishing a prediction model for predicting the performance of the target carbon material; according to the method, multi-dimensional analysis is carried out on the raw material data of the petroleum-based carbon material, the process control data of the carbon material, the structure data of the carbon material and the performance data of the carbon material, the refinery data is preprocessed, and a high-accuracy prediction model is established, so that the guidance on the production of the petroleum-based carbon material is higher.

The present invention relates to a spacecraft system evaluation system and evaluation method. The spacecraft system evaluation system includes: an evaluation scheme management module, an evaluation index construction module, an evaluation data processing module, an evaluation index calculation module and an evaluation result generation module. The present invention, in combination with the basic theory of spacecraft evaluation, builds an evaluation system framework that can be flexibly configured to achieve accurate evaluation of system capabilities and effectiveness. It can build an evaluation index system of capabilities, effectiveness and other types based on the demonstration and R&D needs of the system, and carry out multi-dimensional evaluation of the system by combining multi-source heterogeneous data such as system data, spacecraft performance data, process data, environmental data and simulation result data, and provides autonomous and flexible configuration of evaluation indicators, evaluation data, evaluation models, evaluation result display forms, evaluation reports and other contents, providing reasonable, scientific and effective data support for spacecraft evaluation demonstration.

This application provides a method, apparatus, electronic device, and storage medium for testing the capacity of a storage battery. The method includes: receiving discharge start information and periodically recording the discharge load current and individual battery cell voltages; the discharge start information is the start of battery discharge when the power supply system fails; calculating the discharged capacity based on the discharge load current and individual battery cell voltages, and plotting a time-capacity discharge curve and a voltage-capacity discharge curve; comparing the time-capacity discharge curve and the voltage-capacity discharge curve with a standard discharge curve to evaluate the remaining battery capacity; and generating first capacity evaluation information based on the remaining battery capacity, the first capacity information including the battery's remaining runtime. This method reduces the workload of the capacity testing process and can also provide timely and effective data support for emergency response and dispatch.

The invention relates to the technical field of three-dimensional displacement monitoring, in particular to a three-dimensional displacement monitor and a monitoring visualization system thereof.The three-dimensional displacement monitor comprises a tripod and a high-speed camera. The temperature and humidity values of the working area of the monitor are adaptively adjusted, the environmental adaptability is improved, and the flow direction and flow velocity of the airflow in the area can be changed and accelerated while local shading of the monitor is carried out through the arranged air guide sheet, so that the temperature uniformity of the area where the monitor is located is improved, and the precision degree of three-dimensional displacement data acquisition is improved. Effective data support is provided for subsequent image generation and discrimination, the high-speed camera is used for continuous snapshot in a short time, displacement and strain of each pixel point in a visual field range are tracked, a 3D digital image is established, and accurate collection and measurement of the three-dimensional displacement data volume of an operation object are carried out.