30results about How to "Efficient and Accurate Collection" patented technology

The invention provides a multi-strategy coupled virtual power plant scheduling system and method, and the system comprises a data collection module which is used for collecting the real-time operation data of each data source, carrying out the analysis of the real-time operation data, and obtaining the power prediction demands of a distributed user side energy storage power station; the strategy determination module is used for performing multi-dimensional analysis on the power prediction demand based on the multi-dimensional optimization target to obtain a multi-dimensional scheduling strategy, and performing coupling coordination on the multi-dimensional scheduling strategy to determine an optimal balance point of the multi-dimensional optimization target; and the scheduling management module is used for generating a scheduling plan based on the optimal balance point, carrying out electric energy scheduling on the distributed user side energy storage power station based on the scheduling plan, and carrying out dynamic optimization on the scheduling plan based on an execution result of the electric energy scheduling. The scheduling effect and accuracy are ensured, and the multi-strategy coupling algorithm enables the virtual power plant to utilize the resources of the distributed user side energy storage power station to the greatest extent and optimize the overall operation efficiency while ensuring the economic benefits.

The invention relates to the field of technical data acquisition, and particularly discloses a data acquisition method and device for an industrial Internet of Things and a storage medium, and the method comprises the following steps: S1, constructing a dynamic sensor network, and collecting the operation data of industrial equipment in real time through a multi-modal sensor; s2, dynamically adjusting a data acquisition frequency # imgabs2 # based on an environment noise coefficient # imgabs0 # and an equipment health index # imgabs1 #; s3, performing hierarchical compression and encryption on the acquired data, and allocating a compression rate # imgabs4 # and encryption strength # imgabs5 # according to data type importance # imgabs3 #; s4, executing load balancing through an edge computing node, and distributing a computing task to an optimal node; and S5, storing the processed data into a distributed database according to spatial-temporal correlation, and generating a multi-copy disaster recovery index. Through dynamic acquisition, intelligent processing, optimized storage and adaptive strategy adjustment, accurate and efficient data acquisition is realized, data security and processing performance are flexibly guaranteed, storage query efficiency and disaster tolerance capability are improved, and storage resources are utilized to the maximum extent.

The invention relates to the technical field of Internet of Things data alarm threshold management, and discloses an Internet of Things data alarm threshold management method and system based on a distributed generation mode, and the system comprises a user side alarm threshold application demand identification module, a user side alarm threshold application processing module, and a user side alarm threshold application feedback adjustment module. Internet-of-things distributed client alarm threshold application program object type intelligent identification is carried out based on big data storage Internet-of-things data alarm threshold application program parameters in combination with intelligent identification algorithm client alarm threshold application demand standard keyword translation information; the intelligence and applicability of the Internet of Things data alarm threshold management system are improved; and according to the analysis information of the user-side Internet of Things data alarm threshold application program, the application execution hardware terminal is combined to autonomously and dynamically execute the user-side Internet of Things data alarm threshold application operation, so that the visualization and functional diversity of the Internet of Things data alarm threshold management system are improved.

The invention relates to the technical field of quality management, and discloses a building construction quality supervision system and method based on big data, and the system comprises a construction quality supervision action management module, a construction quality problem evaluation module, and a construction quality problem feedback module. Building main body design entity model parameters in different construction stages are stored on the basis of big data, and precise retrieval of building main body theoretical design entity models in different construction stages is carried out in combination with an intelligent search algorithm and current construction time point parameters; building main body entity model feature abnormal image parameters in the current construction stage are accurately collected through screenshot software, and construction quality problem types of a building main body in the current construction stage are analyzed in combination with an intelligent recognition algorithm and different types of building construction quality problem image parameters; the specific quality problem types of building construction in different construction stages are scientifically and intelligently evaluated, and the reliability of building construction quality supervision is improved.

The invention relates to the technical field of building maintenance management, and discloses a building use process maintenance management system and method based on artificial intelligence, and the system comprises a building maintenance control module, a building maintenance problem recognition processing module, and a building maintenance problem output module. An unmanned aerial vehicle carries a cloud lens to accurately collect an outer wall state image of a real-time inspection position of a building outer wall, and intelligent identification of a damage problem type of the building outer wall is carried out by combining an intelligent search algorithm and scientifically preset image information of different building outer wall damage types; based on an artificial intelligence algorithm, building outer wall damage type identification information and standard stored different building outer wall damage type repair process information are combined to carry out intelligent assessment on a damage repair scheme of the building outer wall, and meanwhile, building outer wall damage position coordinates are searched autonomously; intelligent data analysis of a building outer wall damage repair scheme and a damage position is realized, and intelligence and reliability of building maintenance operation are improved.

The invention discloses a fingerprint identification method and system based on an optical identification induction technology, and relates to the technical field of fingerprint identification, and the method comprises the steps: collecting a fingerprint surface texture image through the total reflection principle of light; converting the collected fingerprint surface texture image into a fingerprint surface texture grayscale image; determining the main direction and frequency of the fingerprint streaklines, and separating the adhered fingerprint streaklines; smoothing stray point information in the fingerprint image by using an image filtering algorithm; the fluctuation characteristics of the fingerprints are further highlighted by using morphological expansion and corrosion operation; extracting morphological features of fingerprints and local features of streaklines from the preprocessed fingerprint image; and outputting the user information corresponding to the fingerprints in the database higher than the preset similarity value. By arranging the image acquisition module, the image processing module, the feature extraction module and the similarity comparison module, the interference of environmental factors is reduced, the fingerprint image quality is ensured, the fingerprint identification time is shortened, and the real-time performance of the system is improved.

The invention discloses a device and a method for collecting and analyzing gas produced in different thermal runaway stages of a lithium ion battery, and relates to the technical field of thermal runaway of the lithium ion battery, a closed box body for accommodating the lithium ion battery is provided with a plurality of gas collection ports, and the plurality of gas collection ports are located at different positions of the closed box body; the gas collection control part is respectively connected with each gas collection port pipeline of the closed box body, and is used for determining the thermal runaway stage of the lithium ion battery based on the surface temperature and the tab voltage of the lithium ion battery acquired by the sensing part; controlling the gas collection control part to obtain mixed gas at different gas collection ports in different thermal runaway stages to obtain the mixed gas corresponding to the different thermal runaway stages, and subsequently analyzing the mixed gas corresponding to the different thermal runaway stages. Therefore, the gas generated at different thermal runaway stages of the lithium ion battery and at different positions of the closed space can be efficiently and accurately collected and analyzed.

The invention discloses a podophyllotoxin extraction process monitoring system based on data analysis, and particularly relates to the field of medicine. Comprising a podophyllotoxin extraction data acquisition module, a podophyllotoxin extraction parameter monitoring module, an acquired data preprocessing module, an influence data analysis module, an abnormality diagnosis module, a process optimization module and a historical data storage module. The invention discloses a podophyllotoxin extraction process monitoring system based on data analysis. A podophyllotoxin extraction data acquisition module is used for completing acquisition and transmission tasks of first basic data in a podophyllotoxin extraction process, and a solid data basis is provided; a second extraction effect is obtained through an influence data analysis module, the influence degree of each parameter on the final extraction effect in the extraction process is accurately grasped, and a quantitative basis is provided for the extraction effect; the process optimization parameters are obtained through the process optimization module, and the process parameters are rapidly and accurately adjusted according to the actual production condition so as to achieve the optimal production effect.

The invention relates to the technical field of automobile part machining control, and discloses an automobile part production monitoring method and system, and the system comprises an automobile part machining welding spot feature recognition module, an automobile part machining welding spot state analysis module, and an automobile part spot welding process parameter adjustment module. According to actual coordinate parameters and theoretical coordinate parameters of the body-in-white part machining welding spots, coordinate error parameters of the body-in-white part machining welding spots and theoretical position adjusting coordinate parameters of the body-in-white part machining welding spots are accurately measured by combining numerical analysis; digital metering of spot welding machining position errors and spot welding machining theory adjusting coordinates of automobile body-in-white parts is achieved; and the automobile part generation monitoring end performs automobile part machining welding spot position parameter adjustment operation in a self-adaptive manner based on the body-in-white part machining welding spot theoretical position adjustment coordinate parameters in combination with the industrial robot control end and the spot welding machining equipment.

The invention provides an artificial intelligence-based motion capture collection method and system, and the method comprises the steps: carrying out the multi-dimensional collection of the sign representation information of a human body based on a multi-dimensional sensor, and carrying out the preprocessing of the collected sign representation information; training and optimizing a deep learning model based on the preprocessed sign representation information, and performing multi-dimensional application scene interaction adaptation on the trained and optimized deep learning model; and fusing the real-time sign information collected by the multi-dimensional sensor, inputting a fusion result into the adapted deep learning model for analysis, and feeding back an analysis result to a corresponding management terminal based on a multi-dimensional application scene interaction adaption result. The motion capture efficiency and reliability are improved, meanwhile, the motion capture operation is simplified, and the motion capture effect is guaranteed.

The present invention provides a multi-strategy coupled virtual power plant dispatching system and method, including: a data acquisition module, used to collect real-time operation data of each data source, and analyze the real-time operation data to obtain the power forecast demand of the distributed user-side energy storage power station; a strategy determination module, used to perform multi-dimensional analysis of the power forecast demand based on the multi-dimensional optimization target, obtain the multi-dimensional dispatching strategy, and couple and coordinate the multi-dimensional dispatching strategy to determine the optimal balance point of the multi-dimensional optimization target; a dispatching management module, used to generate a dispatching plan based on the optimal balance point, and dispatch the distributed user-side energy storage power station based on the dispatching plan, and dynamically optimize the dispatching plan based on the execution result of the power dispatching. The dispatching effect and accuracy are guaranteed, and the multi-strategy coupling algorithm enables the virtual power plant to maximize the use of distributed user-side energy storage power station resources and optimize the overall operating efficiency while ensuring economic benefits.

The invention relates to the technical field of electricity consumption abnormity monitoring of household AC distribution lines, and discloses a user side electricity consumption abnormity monitoring system and method based on machine learning, and the system comprises a user side electricity consumption abnormity analysis module, a user side electricity consumption abnormity object analysis module, and a user side electricity consumption abnormity feedback module. Based on the instantaneous power consumption parameter of the power consumption object of the power distribution line, combining with an intelligent search algorithm and a scientifically preset instantaneous rated power consumption parameter of the power consumption object of the power distribution line, accurately identifying the power consumption abnormal state of the power consumption object of the power distribution line of the user side; and according to the power consumption abnormal state identification parameters of the power consumption object of the power distribution line, combining a machine learning intelligent algorithm with the standard stored power consumption object identity text information of the power distribution line, carrying out efficient search on the identity information of the power consumption abnormal state object in the power distribution line of the user side, and realizing intelligent monitoring on the power consumption equipment of the power consumption abnormal state of the user side.

The invention belongs to the technical field of fluid mechanics experiments, and relates to a flapping-fan-deformation coupling variable camber flapping wing ground experiment device which comprises a water tunnel frame and a deformation flapping wing movement mechanism, the deformation flapping wing movement mechanism comprises a linear sliding rail, a first motor, a long shaft, a second motor, a short shaft and a deformation flapping wing, and the deformation flapping wing comprises a front wing section and a rear wing section. The front wing section is rotationally connected with the rear wing section through a rotating shaft, the long shaft drives the front wing section, the short shaft drives the rear wing section, and the front wing section is connected with the rear wing section through the rotating shaft; according to the invention, through a force measuring mechanism in a deformation flapping wing movement mechanism, computer assistance and other regulation and control devices are utilized to collect torsional force and moment of force borne by a deformation wing during movement, and a visual image of a flow field vortex during pitching, sinking and floating and compound movement of the deformation wing in water flow is obtained, so that data processing and analysis are facilitated; therefore, a data foundation is laid for improvement of cruising ability, propelling performance, stability and the like of the flapping wing aircraft.

The present invention discloses an offline scene information collection method, platform, system and medium based on an AR terminal, the method comprising: receiving real-scene data collected by an AR terminal; performing scene standard detection on the real-scene data to confirm whether the real-scene data meets the preset collection standard; performing scene image and text recognition on the real-scene data when the real-scene data meets the preset collection standard; extracting and recording the digital scene information in the real-scene data according to the scene image and text recognition result. The AR terminal collects the screen of the offline scene in real time, and performs accurate scene standard detection and efficient scene image and text recognition on the real-time collected real-scene data, extracting the digital scene information in the real-time scene screen, and realizing efficient and accurate offline scene digital information collection.

The invention relates to the technical field of multimedia data retrieval processing, and discloses an earthquake science popularization multimedia content integration system and method, and the system comprises an earthquake science popularization multimedia material collection module, an earthquake science popularization file generation module, and an earthquake science popularization file integration result display module. Based on earthquake science popularization multimedia material editing application software parameters, an intelligent search algorithm and a standard stored multimedia data editing application software operation instruction library are combined to carry out scientific identification on an editing application software operation instruction library object required by target earthquake multimedia material data editing; the speed and reliability of earthquake science popularization multimedia content integration are improved; the editing application software operation instruction information required for editing the target earthquake multimedia material data is accurately identified, and the earthquake science popularization file manufacturing operation is autonomously and accurately executed, so that the intelligent integration of the earthquake science popularization multimedia content is realized, and the functional diversity and applicability of the earthquake science popularization multimedia content integration are improved.

The utility model relates to a manipulator for geological ore sampling, which comprises a base component, a movable component and a sampling component which are arranged on a vehicle body, the base component is positioned at the front end of the vehicle body, the movable component is mounted above the base component, and the sampling component is mounted at the tail end of the movable component. The ore sampling device is scientific and reasonable in design and ingenious in structural design, changes of different angles of the components can be achieved through linkage matching of the multiple components, meanwhile, large ore can be crushed and sampled, and efficient collection of the ore is guaranteed.

This invention relates to the technical field of substance detection, and discloses an intelligent detection method and system for seabuckthorn vinegar flavor substances based on gas chromatography-mass spectrometry. By dynamically acquiring chromatographic and mass spectrometric combination images of seabuckthorn vinegar flavor substance detection points in the fermentation tank based on the coordinate information of the detection points, combined with sampling equipment, a gas chromatography system, and a mass spectrometry system, the system adaptively acquires chromatographic and mass spectrometric combination images of seabuckthorn vinegar flavor substances at different spatial locations within the fermentation tank. Based on the chromatographic and mass spectrometric combination image information of the seabuckthorn vinegar flavor substance detection points in the fermentation tank, and combined with intelligent image recognition algorithms and chromatographic and mass spectrometric combination information of different substance characteristic standards based on big data storage, the system intelligently detects the types and concentrations of flavor substances at the detection points in the fermentation tank, achieving intelligent, comprehensive, and scientific detection of seabuckthorn vinegar flavor substances based on chromatographic and mass spectrometry.

This invention discloses a cable production identification and monitoring system and method based on cable images, belonging to the field of image recognition technology. The system includes: acquiring a sequence of cable surface depth images to construct a grayscale surface map along the cable surface depth direction; using the central ridge of the grayscale surface map as a dynamic axis of symmetry, detecting candidate pixels through multi-scale morphological top-hat transformation to form a symmetrical residual distribution map; combining the eight-neighbor gradient direction field and Hessian matrix curvature to remove false defect points, obtaining an effective image, and inputting it into a pre-trained multi-task neural network to simultaneously output a defect segmentation mask and category label; generating a three-dimensional mesh model with dimensional accuracy through Poisson surface reconstruction; and finally, using the physical coordinates of the defect center to drive a laser marking machine to mark a QR code containing key information, which is then associated and stored in a blockchain database. This application improves the accuracy and efficiency of defect identification, realizing the quantitative characterization and full lifecycle management of defects.

The present invention relates to the technical field of spinning and cotton plucking fault risk detection, and specifically to a spinning and cotton plucking fault risk intelligent detection and analysis system, comprising a data acquisition module, a server, a cotton knot state analysis module, a pathological state analysis module, a bag discharge state analysis module, an influence factor analysis module, an equipment operation analysis module, a fault risk analysis module and a display terminal; the present invention obtains corresponding influence indexes by analyzing and processing cotton knot state information, pathological state information and bag discharge state information in the spinning and cotton plucking process, and obtains influence factor coefficients by comprehensive analysis of the influence indexes, and monitors and analyzes the equipment operation state information at the same time, and then combines the influence factor coefficients to evaluate the equipment operation state, accurately determine the fault risk of the spinning and cotton plucking equipment, and give the fault risk level, so that the enterprise can take preventive measures in time to ensure the continuous and stable operation of the production line, thereby improving production efficiency and product quality.

This invention relates to the field of road construction technology, specifically disclosing a road construction surveying device and method, comprising: a surveying frame; a sleeve mounted on the surveying frame, the bottom of the sleeve being in contact with the surveyed ground, and an end cap on the top of the sleeve; a drilling mechanism, including a power component mounted on the surveying frame, a main shaft driven by the power component to rotate and slide vertically along the end cap, and a drill rod located at one end of the main shaft inside the sleeve; and a sampling pipe mounted on the end cap and communicating with the inside of the sleeve. This invention solves the problem in traditional rock and soil surveying processes where dust generated during drilling directly disperses into the air, causing pollution to the surrounding environment.

The invention relates to the technical field of biological detection and freeze-drying application, in particular to an air pathogen, biological and chemical component enrichment detection system. The detection system comprises a sample enrichment device, an inactivation cracking device and a detection device. An enrichment device of the sample enrichment device is used for attaching a pathogen sample in the air to the hydrophobic breathable film. And the inactivation detection device is used for inactivating and cracking pathogens on the hydrophobic breathable film in the lysate reagent tube. And the detection device is used for detecting the content of pathogens in the lysis solution reagent tube after the lysis is completed. According to the invention, the enricher can be flexibly installed and can be dispersedly installed at a specific position, so that the collected sample is more representative and can reflect the pathogen distribution condition of a space environment; meanwhile, the enrichment cap is disposable, no pollution risk exists in the operation process, and biosafety and cross contamination risks can be effectively shielded through inactivation splitting decomposition and shell disinfection. Therefore, the method has the effects of simplicity in operation, high efficiency and accuracy in the process of detecting air pathogens.

The invention relates to the technical field of enzymology or microbiology devices, and discloses wine brewing fermentation equipment and a fermentation method for simultaneous fermentation of grains and medicinal materials. The wine brewing fermentation equipment comprises a pit, and a mounting frame, a vertical driving assembly, a cleaning brush and a cleaning brush driving assembly are mounted at the top of the pit; the cleaning brush is further provided with a telescopic abrasive disc and an abrasive disc driving assembly. The cleaning brush driving assembly drives the cleaning brush to rotate and move along the inner wall of the cellar at the same time, so that residual fermented grains attached to the inner wall of the cellar are cleaned, loss of the fermented grains is reduced, the situation that the subsequent fermentation effect of the cellar is affected after infectious microbes are generated by the residual fermented grains is avoided, and when mildew spots appear on the inner wall of the cellar in the fermentation process, the fermentation quality is improved. The telescopic abrasive disc on the cleaning brush extends and rotates along with the cleaning brush, a mildew spot area can be polished, then the situation that mildew spots affect follow-up fermentation is avoided, the automation degree is high, the cleaning effect is good, and the cleaning efficiency is high.

The invention relates to the technical field of multimedia data retrieval and processing, and discloses an earthquake science popularization multimedia content integration system and method. The system comprises an earthquake science popularization multimedia material acquisition module, an earthquake science popularization file generation module, and an earthquake science popularization file integration result display module; based on earthquake science popularization multimedia material editing application software parameters combined with an intelligent search algorithm and a standard stored multimedia data editing application software operation instruction library, scientific identification of editing application software operation instruction library objects required for target earthquake multimedia material data editing is performed, thereby improving the speed and reliability of earthquake science popularization multimedia content integration; accurately identifying editing application software operation instruction information required for target earthquake multimedia material data editing and autonomously and accurately executing earthquake science popularization file production operations, thereby realizing intelligent integration of earthquake science popularization multimedia content and improving the functional diversity and applicability of earthquake science popularization multimedia content integration.

The invention discloses a rail transit vehicle bottom image acquisition method, an image is quickly acquired through a quick-scanning acquisition system, the quick-scanning acquisition system comprises a quick-scanning camera, an acquisition machine and an industrial personal computer, the quick-scanning camera is mounted on an inspection robot, and the acquisition machine is mounted on the inspection robot. The process of fast image acquisition of the fast-scanning acquisition system is as follows: the inspection robot forwards and continuously moves at the bottom of the rail transit vehicle based on an inspection path to inspect, in the inspection process, the industrial personal computer sends a fast-scanning acquisition instruction to the fast-scanning camera through the acquisition machine, a first folder path for fast-scanning image storage is generated in the acquisition machine, and a second folder path for fast-scanning image storage is generated in the acquisition machine; and the fast scanning camera collects a vehicle bottom image and stores the vehicle bottom image in the first folder path until the inspection robot reaches the end point of the forward inspection path, and fast image collection is completed. Through automatic inspection and high-precision image acquisition, the inspection efficiency and the data quality are remarkably improved.

The invention relates to the technical field of magnetic defect detectors, in particular to a magnetic defect detector with an intelligent defect recognition function, which comprises the following steps: acquiring different-scale output characteristics of a to-be-detected piece; constructing a feature model based on the global overall features and the local crack detail features; designing a convolutional neural network based on the feature model, performing feature extraction on the feature model, sampling the extracted features, and pooling sampling information according to different scales of the detection model through a spatial pooling pyramid to perform feature extraction and reaggregation; based on the aggregation information, calling a database to carry out state judgment on the to-be-detected part, and carrying out frame selection and alarm on the identified crack position on the to-be-detected part; and constructing a learning model based on the state of the to-be-detected part and the feature model, and importing the learning model into a database to construct a rapid judgment model. The invention aims to quickly and stably process data and improve the detection precision and robustness of cracks on the to-be-detected piece.

The invention provides an electricity market spot electricity price prediction method and system, and the method comprises the steps: collecting electricity market data from a multi-dimensional data source based on a data collection requirement, and carrying out the preprocessing of the electricity market data, and obtaining unified input data; constructing a multi-class spot electricity price prediction model, inputting the unified input data into the multi-class spot electricity price prediction model to carry out synchronous spot electricity price prediction, and carrying out integrated processing on spot electricity price prediction results of the multi-class spot electricity price prediction model to obtain a target spot electricity price prediction result; and constructing a graphic visual interface, carrying out differential permission configuration on different users based on roles, and carrying out differential display on a target spot price prediction result and related data according to the graphic visual interface based on the differential permission configuration. Support can be provided for stable operation of the electricity market, and meanwhile, the accuracy of spot electricity price prediction under different conditions is improved.

The invention relates to the technical field of road construction, and particularly discloses a road construction surveying device and method. The sleeve is arranged on the surveying frame, the bottom of the sleeve is attached to the surveying ground, and an end cover is arranged at the top of the sleeve; the drilling mechanism comprises a power part arranged on the surveying frame, a main shaft which is driven by the power part to rotate and vertically slides along the end cover, and a drill rod which is arranged at one end, positioned in the sleeve, of the main shaft; the sampling pipeline is arranged on the end cover and is communicated with the interior of the sleeve, and the problem that in the traditional geotechnical survey process, dust generated in the drilling process directly drifts into the air when geotechnical sampling is conducted, and the surrounding environment is polluted is solved.

The invention relates to the technical field of oil equipment state feedback alarm, and discloses an intelligent monitoring system and method for off-network oil equipment, and the system comprises a target oil pumping unit monitoring position searching module, a target oil pumping unit operation state monitoring module, and a target oil pumping unit abnormal operation state alarm module. Performing mechanism appearance abnormal state intelligent analysis on the target oil pumping unit by combining the target oil pumping unit mechanism appearance image parameters with an intelligent search algorithm and scientifically preset oil pumping unit mechanism fault appearance image parameters so as to realize reliable and real analysis on the appearance state of each mechanism of the target oil pumping unit; based on the abnormal operation state identification result of the target pumping unit mechanism and the abnormal appearance analysis result of the target pumping unit mechanism, the operation state of the oil field target pumping unit is scientifically, comprehensively and accurately analyzed, and the authenticity and reliability of the monitoring result of the operation state of the oil field pumping unit are improved.

The invention relates to the technical field of petroleum equipment status feedback alarm, and discloses an off-grid petroleum equipment intelligent monitoring system and method, wherein the system comprises a target pumping unit monitoring position search module, a target pumping unit operating status monitoring module, and a target pumping unit abnormal operating status alarm module; the target pumping unit mechanism appearance image parameters are combined with an intelligent search algorithm and scientifically preset pumping unit mechanism fault appearance image parameters to perform intelligent analysis of the target pumping unit mechanism appearance abnormal status, thereby realizing reliable and true analysis of the appearance status of each mechanism of the target pumping unit; based on the target pumping unit mechanism operation abnormal status recognition result and the target pumping unit mechanism appearance abnormality analysis result, a scientific, comprehensive and accurate analysis of the operating status of the target pumping unit in the oil field is realized, thereby improving the authenticity and reliability of the oil field pumping unit operating status monitoring result.

The invention provides a heterogeneous hardware accelerated supply chain enterprise carbon emission intelligent terminal. Comprising an acquisition module, a storage module, an analysis module and a network module. The acquisition module collects carbon emission data of each link on a power grid supply chain in production, storage, maintenance and scrapping processes in real time through a carbon emission gas sensor deployed on an end side; the storage module adopts an optimally designed time sequence database system, constructs a programmable network hardware read-write request processing sub-module, a query optimization sub-module based on a hardware increment materialized view and a time sequence data compression storage sub-module based on hardware, and realizes storage and management of a large amount of carbon emission time sequence data uploaded by the acquisition module; the analysis module cleans and preprocesses the data stored in the database; and the network module is responsible for safely and quickly transmitting the processed data to a cloud end or other terminal equipment. The effects of accurately and efficiently collecting carbon emission data and efficiently processing large-scale carbon emission data are achieved.