38results about How to "Optimize data processing" patented technology

The invention discloses a water quality prediction method based on multi-source data, and constructs a water quality prediction model based on a long short-term memory network (LSTM) and a graph neural network (GNN) of multi-source data (surface water monitoring data, meteorological data, hydrological data and pollution source on-line monitoring data), so that short-term real-time on-line prediction of surface water quality factors can be realized. According to the method, on the basis of multi-source data such as section water quality monitoring data, historical meteorological data, forecast meteorological data, hydrological monitoring data, pollution source online monitoring data and upstream and downstream relations, multiple main water quality influence factors such as water quality, meteorology, hydrology, pollution sources and upstream and downstream section water quality are comprehensively considered; the LSTM or the graph neural network is adopted to establish a water quality prediction model, and the comprehensive influence of various influence factors and the time-space relationship on the water quality is simulated, so that the simulation result is more accurate and reliable.

The invention discloses a power grid load interaction data anomaly detection method, device and equipment, a medium and a product. The method comprises the following steps: acquiring to-be-detected power grid load interaction data generated by at least two load main bodies; performing feature extraction on the to-be-detected power grid load interaction data to obtain target power grid load interaction data with power utilization mode features; performing initial classification on the target power grid load interaction data based on a preset robust principal component analysis method to obtain an initial classification result; performing outlier removal on the first power utilization load mode data set and the second power utilization load mode data set according to a preset clustering algorithm to obtain corresponding anomaly detection results; according to the embodiment of the invention, through the technical scheme, the abnormal data detection of the power grid load information interaction can be realized, and the detection efficiency and accuracy are improved, so that the safety interaction protection capability among the power grid load information is realized, and the improvement of the safety and reliability of a power system is facilitated.

The invention provides a method for measuring plasma generated by electro-chemical coupling explosion, which adopts a device for measuring plasma generated by electro-chemical coupling explosion, the device comprises an explosion cavity and an oscilloscope, and a Langmuir three-probe is arranged in the explosion cavity; and the Langmuir three-probe is connected with an oscilloscope. The Langmuir three-probe comprises a probe P1, a probe P2 and a probe P3. The device provided by the invention has the characteristics of being suitable for transient plasma diagnosis based on Langmuir three probes, simple in structure and convenient in data processing, voltage signals measured by a probe circuit are acquired and are converted into plasma electron temperature and density after being analyzed and calculated, and the electron density ne of the plasma is calculated according to the electron density ne of the plasma. Therefore, the plasma generated by the electro-chemical coupling explosion can be measured.

This invention belongs to the field of impurity detection technology for ethanol solutions, and particularly relates to a method for detecting trace impurities in ethanol solutions based on near-infrared spectroscopy, comprising the following steps: (1) examining the standard deviation (RSD) value and calculating the required sample size N; (2) acquiring samples; (3) outlier removal and spectral preprocessing; (4) dividing the dataset; (5) using the difference spectrum method to screen feature signals; (6) establishing a "background silence" discrimination criterion; and (7) using an external prediction set for discrimination. The detection method model described in this invention has a wide range of applications. It establishes a model based on the background system, effectively identifying normal samples. For impurity samples or abnormal situations that are inconsistent with the near-infrared absorption characteristics of the background system, as long as they cause changes in the background system, they can be effectively detected. Compared with traditional PLS, PLSDA and other modeling methods, background silence discrimination only requires calculation using relevant statistical methods, resulting in a smaller overall computational load and more convenient data processing.

The present invention provides a monitoring method for steel bar management at a construction site, which relates to the technical field of steel bar management, and aims to achieve more accurate, timely and efficient steel bar management, including using colored wireframes to divide the steel bar storage area in a steel bar warehouse, and setting a type mark for each steel bar storage area to calibrate the steel bar type of the corresponding steel bar storage area; arranging multiple image acquisition devices to acquire images of each steel bar storage area; identifying the placement position, quantity and type of steel bars in each steel bar stacking area through the top view and side view of the acquired image; judging whether there are abnormal conditions, and the abnormal conditions include the placement position of the steel bar exceeding the preset range, the wrong area for the steel bar placement and the number of steel bars of a certain type being lower than the corresponding quantity threshold. The present invention has the advantages of intelligent, efficient, high-quality and safer management of steel bars.

The invention discloses a side slope tiny deformation monitoring system and method based on wireless optical communication, and belongs to the technical field of side slope deformation detection.The side slope tiny deformation monitoring system comprises a power module, a shielding module, an optical signal coding module, a laser transmitting module, a laser receiving module, an optical signal decoding module and a wireless communication module; the micro deformation degree of the side slope is judged according to the optical signal receiving deviation degree of the laser transmitting module and the laser receiving module, micro deformation monitoring of the side slope is achieved, the monitoring result of the micro deformation of the side slope is uploaded to an external upper computer through the wireless communication module for data storage, and the shielding module is used for shielding the micro deformation of the side slope. The laser transmitting module and the laser receiving module are covered, and interference of the external environment on optical communication is reduced. According to the invention, based on wireless optical communication, the micro deformation monitoring result of the slope can be timely and directly sent to the upper computer for statistical storage, the data volume transmission pressure is small, the data processing is convenient, different deformation grades can be divided, and a manual inspection strategy is convenient to formulate.

The invention discloses a scheduling method for electric vehicle aggregation to participate in power market auxiliary peak regulation service, which relates to the technical field of smart power grids, and comprises the steps of integrating vehicle-mounted and user APP data, dividing regions through a GIS technology, managing and analyzing a charging margin by an aggregator according to power grid requirements, dividing a scheduling cluster, and evaluating the scheduling potential of the aggregator. According to user travel characteristics, automobiles are classified, a peak regulation strategy is optimized, an electric automobile cluster peak regulation optimization model is constructed, charging and discharging are planned for load fluctuation, a particle swarm algorithm is adopted to optimize a charging and discharging strategy, electric automobiles are efficiently dispatched to participate in power grid peak regulation, and the flexibility and efficiency of a power grid are improved. Through integration of vehicle-mounted and APP data and combination of a GIS technology and an optimization model, electric vehicle charging, efficient scheduling and quantification of schedulable capacity are accurately analyzed, regulation and control are classified according to travel characteristics, the peak regulation efficiency of an electric vehicle auxiliary power grid is greatly improved, resource utilization is optimized, the flexibility and stability of the power grid are enhanced, and power supply and demand balance, energy conservation and emission reduction are promoted.

The invention relates to the technical field of hearth coking monitoring, and discloses a monitoring method for judging a hearth coking state, which comprises the following steps of: acquiring basic data of six heating surfaces in a boiler operation combustion state; calculating operation heat transfer coefficients of the six heating surfaces; initial data of the boiler in a healthy state are collected, and an optimal heat transfer coefficient prediction model is trained; boiler operation parameters in the boiler operation combustion state are obtained, and the trained optimal heat transfer coefficient prediction model is adopted to obtain the optimal heat transfer coefficient in the boiler operation combustion state; and comparing the operation heat transfer coefficient with the optimal heat transfer coefficient to determine whether the hearth of the boiler is coked or not. According to the method, the whole boiler is divided into six heating surfaces, whether adjustment or optimization such as coking or soot blowing needs to be carried out or not is judged through the optimal heat transfer coefficient prediction model according to the six coking surface heat transfer coefficients, boiler shutdown is not needed, the coking condition of the boiler is found in time, power generation losses are reduced, and the operation health state and the operation efficiency of a combustion hearth are improved.

The invention discloses a blade rotating speed debugging method and system for an automobile engine cylinder cover test, computer equipment and a storage medium. The method comprises the following steps that the blade rotating speed is collected; filtering and averaging the blade rotating speed data to obtain a rotating speed average value; carrying out interval recalibration on the processed rotating speed mean value data; and outputting and displaying the calibrated blade rotating speed. According to the invention, the rotation speed fluctuation in unit time can be reduced, invalid values in the blade rotation speed are filtered out, the rotation speed is calibrated in different intervals, the influence of the blade rotation speed fluctuation on the test result is eliminated to the greatest extent, and the output rotation speed precision is improved, so that the accuracy of the test result is improved.

The invention relates to a petrochemical engineering emergency early warning method and device based on large model data distillation. The method comprises the steps of obtaining original data, preprocessing and standardizing the original data, and constructing a data set. The method comprises the following steps: mapping a data set from a high-dimensional space to a low-dimensional space through linear transformation, and performing eigenvalue decomposition on a covariance matrix of data in the data set to obtain eigenvalues and eigenvectors; and sorting the feature vectors according to the feature values from large to small, selecting the feature vectors of which the feature value ranking is not lower than a first threshold value to form a new feature space, and extracting important features from the feature space through LASSO regression. And calling a CNN deep learning model to extract key features from the important features, distilling representative features in the original data, and outputting a feature set after distillation. And performing anomaly detection on the petrochemical engineering system through a clustering algorithm according to the feature set after distillation, and triggering early warning when a detection result does not meet a preset condition.

The invention discloses a data real-time compression and transmission system and method based on a thinning algorithm, and relates to the technical field of data processing. The system comprises a data acquisition module, a data preprocessing module, a thinning algorithm module, a data compression module, a real-time display module and a data transmission module. The system uses 3D laser scanning to obtain three-dimensional point cloud data, and the data are preprocessed, denoised and partitioned. The thinning algorithm module recognizes and retains feature points, carries out thinning on non-feature points, and keeps data integrity and details. The compression module reduces the data volume, and the real-time display module dynamically loads the data blocks by using a graphics library, so that the display efficiency is improved. And finally, the data transmission module transmits the processed data to a client or a server through a network, and supports efficient data transmission and reception. The whole system integrates all links of data processing, and efficient and real-time data compression and transmission are achieved.

The embodiment of the present invention discloses a data transmission system, method and medium based on the Internet of Things and big data. The system includes: a collection unit, which is used for diverse data collection; a preprocessing unit, which is used to package the data collected by the collection unit according to a preset period to form a data packet, and process the data in each data packet to obtain a corresponding data change rate and data correlation index; a marking unit, which is used to compare the obtained data change rate and data correlation index with a preset threshold value, and mark the data packet corresponding to the data exceeding the threshold value; a transmission unit, which is used to give priority to the transmission of the marked data packet; the beneficial effect is: by acquiring the data change rate and data correlation index in each collected data packet, marking the data packet exceeding the threshold value, so that data with larger differences are transmitted first, which is beneficial to subsequent data processing and improves the performance of data fusion.

This application discloses an information recommendation method, which may be applied to the field of artificial intelligence. The method includes: obtaining a target feature vector; and processing the target feature vector by using a recommendation model, to obtain recommendation information, where the recommendation model includes a cross network, a deep network, and a target network; the target network is used to perform fusion processing on a first intermediate output that is output by the first cross layer and a second intermediate output that is output by the first deep layer, to obtain a first fusion result, and the target network is further used to: process the first fusion result to obtain a first weight corresponding to the first cross layer and a second weight corresponding to the first deep layer, and weight the first fusion result with the first weight and the second weight separately, to obtain a first intermediate input and a second intermediate input. In this application, the target network learns heterogeneous parameter distribution for different interaction networks, to avoid excessive sharing, and introduces interaction signals between different interaction networks. This improves prediction accuracy of the model.

The present disclosure provides a method and device for determining power characteristics of a wind turbine. The method comprises: obtaining first operating data of the wind turbine before applying a predetermined control strategy and second operating data of the wind turbine after applying the predetermined control strategy, the first operating data comprising first environmental data and first output power data, and the second operating data comprising second environmental data and second output power data; determining an environmental space intersection of the first operating data and the second operating data by performing environmental space matching on the first operating data and the second operating data according to the first environmental data and the second environmental data; predicting a first predicted power of the wind turbine before applying the predetermined control strategy and a second predicted power of the wind turbine after applying the predetermined control strategy based on the environmental space intersection; and determining a power characteristic difference of the wind turbine before and after applying the predetermined control strategy according to the first predicted power and the second predicted power.

The application discloses a rubber track finished product longitudinal tension testing device, which comprises a testing machine body, a track fixing device and a fixing device lifting guide rail, wherein the track fixing device is connected with the testing machine body through the fixing device lifting guide rail, and the track fixing device comprises a fixing base, a fixing wheel, a carrier wheel, a hydraulic oil cylinder, a supporting wheel and a pressure sensor. The testing device makes the testing steps simpler, reduces the testing cost and shortens the testing period.

The invention discloses a digital wind tunnel balance with temperature and inertia compensation elements, and belongs to the technical field of wind tunnel balance design. The digital wind tunnel balance comprises a body, a force measuring module, a temperature measuring module and a three-axis acceleration and angular velocity measuring module, so that the surface temperature, the three-axis acceleration and the angular velocity of the balance can be measured on the basis of measuring aerodynamic force and moment; accurate information is provided for temperature compensation for static calibration and inertia compensation for dynamic calibration of the balance, so that the balance load measurement error is reduced.

The invention discloses an enterprise data element governance method and device based on big data, and the method comprises the steps: determining a target enterprise needing data element governance, and collecting the public data information of the target enterprise; dividing the public data information into a plurality of data classifications according to data correlation; determining a weight coefficient corresponding to each data classification according to the enterprise type of the target enterprise; determining a mapping relationship between the data classification and the data element tag according to the historical data classification and the historical data element tag, and determining a target data tag of the target enterprise according to the mapping relationship; and according to the target data label and the weight coefficient, generating a target enterprise portrait to complete data element treatment of the target enterprise. According to the method, the data can be classified, weight analysis is carried out by utilizing the multi-dimensional data, specific labels can be conveniently marked on each type of data, the enterprise portraits are generated according to the labels and the corresponding weight coefficients, and convenience is provided for subsequent data processing.

The invention discloses an online calibration method for a pressure measurement system in a pressure test bench, and the method comprises the steps: selecting a standard device matched with the pressure measurement system according to the parameter information of the pressure measurement system; connecting the selected standard device with a pressure test bench; the pressure field calibrator is connected with the standard device through a special connecting line, and the pressure test bench and the pressure field calibrator are controlled to be started for preheating; starting pressure measurement according to the selected pressure calibration point, and reading and recording a measurement result; and completing online calibration of the pressure measurement system according to the recorded measurement result. According to the online calibration method, the consistency of the calibration environment and the actual working environment of the pressure measurement system can be ensured, errors caused by height difference are effectively reduced, and data processing is simple and convenient.

The invention discloses a heterogeneous information conversion method and device. The method comprises the following steps: if an upper computer and a plurality of devices exist in a ground control vehicle of the unmanned aerial vehicle, each device interface is different in type, and when the upper computer is different from each device interface in type, each device interface and an upper computer interface are initialized; when the data of each device is uploaded to the upper computer and the data of the upper computer is issued to each device, whether data update exists in a receiving cache region of each device and an interface of the upper computer or not is detected at the same time; processing the data of the receiving cache region of each equipment interface, putting the data into a network sending cache region, and sending the data to an upper computer; and processing the data of the receiving cache region of the upper computer interface, putting the data into the data cache region of each equipment interface, and sending the data to each equipment. According to the invention, the technical problems of multiple interface types, complex interface protocol and inconvenient communication among various devices in the ground control vehicle of the unmanned aerial vehicle are solved.

The utility model provides an AMT gearbox and gear shifting execution mechanism control system of a new energy mine truck, which comprises a TCU master control module, a sensor unit, an execution unit, an MCU and a power supply module, the sensor unit is used for collecting signals, and the collected signals comprise motor rotating speed, vehicle speed, gear data and gear displacement signals; the signals are transmitted to the TCU main control module through the sensor signal processing module; the execution unit comprises a gear electromagnetic valve and a speed sensing electromagnetic valve. Signals such as motor rotating speed, vehicle speed, gear data, gear displacement and the like can be collected through the sensor unit, analysis of the TCU master control module is facilitated, a gear electromagnetic valve and a speed induction electromagnetic valve of the execution unit are used for adjusting a gear shifting execution motor, and accelerator, motor rotating speed and brake signals can be transmitted to the TCU master control module through the MCU. Data processing is facilitated, the motor efficiency is improved, and the economical efficiency of the whole vehicle is improved.

The present invention discloses a platform limit measurement method based on laser point cloud, and the specific steps are as follows: S1: install a line laser measuring instrument on a line laser measuring instrument installation trolley, and debug the line laser measuring instrument; S2: adjust the position of the line laser measuring instrument and fix it, start the power supply, and then start the line laser measuring instrument; S3: start the line laser measuring instrument to measure, scan the platform morphology through the line laser measuring instrument, continuously read the detection results from the line laser measuring instrument to form point cloud data, and store the point cloud data set in a thread sharing list; S4: filter, downsample, remove invalid points, and convert the tilt coordinates of the point cloud data to form platform feature data and complete the measurement. The present invention divides data reading and point cloud data processing into two independent thread steps, which is convenient for data processing. For defective platforms, the position of the locator can be accurately located and sent to the background, and the cause of the defect can also be accurately determined.

The invention relates to the technical field of industrial production, and discloses an industrial intelligent production method and system based on a pre-training large model, and terminal equipment, and the method comprises the steps: constructing the pre-training large model, obtaining a production index and a production parameter, obtaining a production index score, obtaining a strongly correlated production index, obtaining a correlated production parameter, and generating an early warning data set. The system and the terminal device both correspond to the method. According to the method, the industrial production data is simplified by accurately acquiring the production indexes and the production parameters, so that an administrator can conveniently acquire the production data with relatively high value, data-driven production analysis is realized by pre-training the large model, the proportion of human factors is reduced, and the production efficiency is improved. The obtained strong correlation production indexes and associated production parameters provide a data basis for industrial production problem traceability, the problem traceability is optimized, complementation of key data volume and optimization of a data processing mode are realized, and the industrial intelligence level is improved. And finally, industrial intelligent production based on the pre-training large model is realized.

The invention provides an underwater surveying and mapping system and method based on a rotary scanning type three-dimensional imaging sonar. The surveying and mapping system comprises a water surface moving platform (unmanned ship), an underwater scanning unit (three-dimensional imaging sonar), a pose and coordinate measuring unit (RTK / IMU), a data processing and converting unit and a remote display and control unit. The surveying and mapping method specifically comprises the following steps: controlling the unmanned ship to move to the center of each sub-region; a sonar is started to plot the sub-regions to obtain underwater three-dimensional point clouds of the underwater terrain and the underwater creatures; based on the position information and the attitude information of the underwater surveying and mapping system, the coordinates of the underwater three-dimensional point cloud are converted into an east-north-sky rectangular coordinate system, and the final coordinates of the underwater three-dimensional point cloud are obtained; and on the basis of the underwater three-dimensional point clouds of the sub-regions, a complete underwater three-dimensional point cloud of the region to be measured is generated through fusion. The method is suitable for underwater topographic surveying and mapping and dynamic target monitoring of rivers, lakes and offshore waters, the measurement efficiency is high, data processing is convenient, and the method does not depend on platform tracks and measuring lines.

The present invention provides a method and device for online monitoring of switchgear, which realizes data preprocessing by filtering the real-time mechanical characteristic curve, can reduce the amount of data calculation, is beneficial to subsequent data processing, and occupies little data memory. In addition, since the similarity of the curves is compared, it is not affected by whether the number of sampling points of the compared curves is the same, whether there is a delay, and whether the horizontal coordinates are consistent.

The invention provides an article identification method, an embedded terminal and a storage medium, and the method comprises the steps: obtaining an article image in response to an article identification instruction, and displaying at least one to-be-identified article in the article image; and identifying the at least one to-be-identified article by using a preset lightweight article identification model, and determining the type to which the at least one to-be-identified article belongs. Wherein a feature map output module in the lightweight article recognition model performs output through an attention mechanism module; the attention mechanism module comprises a channel attention module and a space attention module which are parallel, and the channel attention module comprises a pooling layer, a one-dimensional convolutional network and a connection layer which are connected in sequence. Compared with the prior art in which an intelligent shelf realizes AI identification of article types through a server, the embedded terminal is endowed with an article identification capability, so that the intelligent shelf can still carry out article identification in an off-network state, and the reliability is improved.

The invention discloses a diversified interaction agent construction method and system based on off-line learning, the system comprises an off-line circulation system and an agent interaction system, the off-line circulation system comprises a process splitting unit, a self-evolution unit, a storage processing unit and a model calling unit, the intelligent agent interaction system comprises an information sharing unit and a cooperation unit. The offline circulating system processes basic functions of the intelligent agent under the independent condition of the single intelligent agent by using an offline strengthening algorithm, and the basic functions comprise a thinking function, a sensing function and an execution function; the intelligent agent interaction system uses an interaction adjustment learning algorithm to enhance information in an offline circulation system, uses a distance contraction adjustment algorithm to improve the cooperation efficiency of the intelligent agent interaction system, and performs information interaction with other single intelligent agents to effectively complete complex tasks. According to the method, efficient learning of the intelligent agent in the offline state is realized, and the data processing efficiency of the diversified intelligent agents for completing complex tasks is improved.

The invention discloses a double-shaft multi-angle wind tunnel test supporting device, and relates to the technical field of wind tunnel tests. The device comprises a stand column, the bottom of the stand column is connected with a test section pivotal bearing, the top of the stand column is connected with a bearing seat, the bearing seat is rotatably connected with a transmission supporting rod, one end of the transmission supporting rod is connected with a driving mechanism, and the other end of the transmission supporting rod is connected with a fixed base. The mounting seat interface is mounted at the end part of the transmission support rod, the spherical hinge is arranged on the mounting seat interface, and the central round hole of the model mounting seat is matched and connected with the spherical part of the spherical hinge. The supporting device provided by the invention adopts a structural form of the main support and the axial extension rod, and the possibility of resonance with a wind tunnel foundation is avoided due to fixed bottom, stable structure and relatively high frequency; and the structural design is small and light, and each part is provided with a hoisting hole, so that transfer transportation and test installation are facilitated, and compared with a traditional supporting structure, the adaptability is wider.

The present invention provides a fire monitoring system based on GNSS-R, including a GNSS satellite that transmits a direct signal and a temperature sensing device, a GNSS-R receiver, a data storage system, a data discrimination system and an alarm system that are connected in sequence; the temperature sensing device receives a first reflected signal and obtains the peak value and signal-to-noise ratio data of a delayed Doppler waveform; the GNSS-R receiver receives the data, the direct signal and the second reflected signal; the data storage system extracts position information and time information from the direct signal; the data discrimination system receives the above data and information, and makes a judgment based on the peak value and signal-to-noise ratio data of the delayed Doppler waveform; the alarm system sounds an alarm in the area judged to be a fire occurrence area based on the judgment result. The present invention also provides a monitoring method. The present invention utilizes the direct signal and reflected signal of GNSS and adopts a temperature sensing device that is extremely sensitive to forest temperature, so that forest fires can be judged in real time.

The embodiment of the invention discloses an intelligent content production method and system based on user requirements. The method comprises the steps that a case judgment document file is processed through a Seq2Seq model, and then a corresponding case abstract is generated; different intelligent content production sub-modules, namely a first content production sub-module based on a twin neural network model or a second content production sub-module based on a recurrent neural network (RNN) model, are selected based on different lengths of case and fact description files input by a user; and finally, intelligently matched law articles and corresponding case abstracts and case judgment document files are output, so that the user experience and the content generation accuracy are improved.

The invention provides a grabbing control method, system and device for a dexterous hand, and the method comprises the steps: controlling the dexterous hand to move to a target object, and obtaining the pressure information between the dexterous hand and the target object; acquiring forward pressure data based on the pressure information; the forward pressure data is compared with preset grabbing force data, and the stress change state of the dexterous hand when the target object is grabbed is determined; the stress change state of the dexterous hand comprises a deformation state, an offset state and a sliding state; and a control instruction is generated based on the stress change state of the dexterous hand, and the grabbing force of the dexterous hand on the target object is adjusted according to the control instruction. The pressure sensing precision and the response speed can be improved, and the dexterous hand can more accurately sense the contact force and make corresponding adjustment.