89results about How to "Rich data support" patented technology

The present disclosure provides a workpiece clamping force monitoring system for a clamp, belonging to the technical field of tooling clamps. The workpiece clamping force monitoring system for the clamp comprises a plurality of sensor modules for monitoring the pressure information of the workpiece when the clamp clamps the workpiece in real time and transmitting the pressure information to a data processing module. The data processing module can transmit the processed pressure data to a central control module through a first communication module. The central control module can transmit the data information to a display module to display the pressure fluctuation curve, and can also intelligently analyze the plurality of pressure information to determine a target adjustment strategy. When the pressure information is abnormal, the first alarm module is triggered, an alarm is given and emergency shutdown measures are taken. The workpiece clamping force monitoring system for the clamp provided by the present disclosure can improve the control accuracy, accuracy and anti-interference of the clamping force of the clamp, and based on the abnormal pressure information, an alarm is given to avoid causing greater losses, ensure the stability of the machining process and improve the production efficiency.

This invention designs a multi-scale star surface impact crater detection method, system, and medium. The method includes the following steps: S1: Acquire star surface images and segment them into image patches of different scales; S2: Construct multiple impact crater detection sub-models; S3: Train each sub-model using star surface image patches of different scales; S4: Input the segmented star surface image to be detected into each pre-trained sub-model to obtain the detection results; S5: Select the bounding boxes with high confidence and large area among all candidate bounding boxes of each impact crater as the final detection result for that impact crater. This invention can simultaneously identify impact craters of different scales in star surface images with high accuracy, especially improving the accuracy and efficiency of identifying small impact craters, providing more accurate and comprehensive data support for lunar science research, and promoting the in-depth development of lunar exploration and geological research.

The invention discloses a distributed optical fiber-grating-based rockburst test system and method, solves the problem that in the prior art, only strain parameters are simply obtained in a rockburst test, and has the beneficial effects of accurately simulating rockburst and obtaining related parameters of the rockburst. According to the specific scheme, the rockburst test system based on the distributed optical fiber-grating comprises a test device, the test device comprises a vibration table, and the vibration table supports a supporting box body; the rock sample is provided with an optical fiber channel, and the distributed optical fiber penetrates into the optical fiber channel; the vibration table, the stress applying component and the drilling disturbance component are respectively connected with the control unit; the monitoring unit is connected with the distributed optical fiber and the grating optical fiber; the monitoring unit sends monitored data to the control unit, and the control unit judges when rockburst is triggered and obtains stress change, elastic strain energy release amount and strain abrupt change time difference at the moment of rockburst when the rockburst occurs.

The application discloses a natural gas hydrate stratum and wellbore working fluid interaction simulation experiment system, and relates to the field of experimental instruments, which comprises a high-pressure kettle, a gas injection unit, a liquid injection unit, a wellbore working fluid circulation unit, a vacuum preparation module and a monitoring unit; the high-pressure kettle is internally provided with a simulated stratum and a vertical simulated wellbore with a liquid permeation hole; the gas injection unit and the liquid injection unit are respectively used for injecting methane gas and working fluid into the high-pressure kettle; the wellbore working fluid circulation unit comprises a magnetic circulation pump and a high-pressure filter and is used for driving the working fluid to circulate in the simulated wellbore; the vacuum preparation module is used for preparing an initial experimental environment; and the monitoring unit comprises temperature, pressure and displacement sensors, an ultrasonic detection system, a resistivity imaging system and a microscopic imaging system and is used for monitoring and collecting parameter changes of the simulated stratum under the action of multiple physical fields in real time. The application can simulate a wellbore working fluid circulation invasion process and comprehensively evaluate the influence of the working fluid on the stability of a natural gas hydrate stratum and the phase change of hydrates.

The invention belongs to the technical field of coal rock mechanical property testing, particularly relates to a mechanical testing device and method for coal rock loading, and solves the problems that an existing device is single in function, fragments splash, cleaning is inconvenient, and protection and cleaning are not linked. The device comprises a supporting mechanism, and a modular loading mechanism is detachably mounted on the supporting mechanism and comprises a static extrusion loading module and a dynamic impact loading module; the linkage type protection mechanism is provided with two protection half barrels, and fragments can be prevented from splashing when the two protection half barrels are closed; the sweeping mechanism is started when the protective half barrels are unfolded, a rotating ring drives a Z-shaped plate to rotate, an annular inclined panel is driven to vibrate, and fragments are swept; the device integrates a static extrusion function and a dynamic impact function, so that the equipment utilization rate and the application range are improved; protection and cleaning are linked, safety is guaranteed, cross contamination is avoided, and the experiment accuracy and efficiency are improved.

The invention relates to the technical field of logistics intelligent management, and particularly discloses a large logistics cognitive collaborative management system which is constructed based on AI and an industrial internet platform and is provided with an edge layer, a platform layer, an engine layer and an application layer. The edge layer is constructed based on an IT system, OT equipment and manual filling of the logistics transportation industry, and corresponding data acquisition capability is activated according to a received data request; the platform layer starts a corresponding data processing flow according to the received task instruction; the engine layer performs analysis, identification and task planning processing on the received request, and performs intelligent analysis processing on the received data; and the application layer analyzes the received user request and outputs the received data result. According to the invention, the IT system and the OT equipment in the logistics transportation industry are integrated, intuitive and efficient cognitive collaborative management can be formed for large logistics, and a timely, comprehensive and accurate data support basis is provided for business and technical decisions of enterprises.

This invention discloses an adaptive weight-based power load forecasting method. The method includes: constructing a multi-source feature matrix based on pre-collected data of the region to be predicted; calculating an enhanced feature matrix based on the multi-source feature matrix using a preset dual-branch attention module; determining a dynamic weight vector based on real-time feature data of the region to be predicted; calculating a dynamic feature matrix based on the dynamic weight vector and the enhanced feature matrix; training a preset deep learning model using the dynamic feature matrix to obtain a load forecasting model; and forecasting the power load of the region to be predicted at a preset target time using the load forecasting model to obtain predicted load data. This invention can improve the accuracy of power load forecasting.

The invention relates to a three-dimensional heterogeneous formation water control oil extraction multi-parameter synchronous simulation experiment device which comprises a device body, a plug, a production pipe column and a sensor unit. The device body is of a coaxial multi-layer nested structure, a plurality of independent simulation units are constructed in an internal annular sand filling area through replaceable sieve pore partition plates, and heterogeneous stratum reconstruction of fluid communication and sand body isolation is achieved. The production pipe column adopts a modular water control short section series connection structure, a replaceable fluid sensitive valve and a tracer agent storage cabin are integrated, and performance evaluation and fluid traceability of multiple types of water control tools are achieved; the sensor unit synchronously acquires outlet, wall surface and radial gradient pressure through three-dimensional arrangement of mandrels with various lengths, and realizes multi-dimensional data collaborative analysis in combination with flow and water content monitoring. The problems that an existing device is difficult to restore complex fluid channeling physical characteristics and is single in monitoring dimension are solved, full-process high-fidelity simulation from stratum seepage to tool water control is achieved, and key technical support is provided for water control strategy optimization.

The application provides an AI-based eye health management and lens fitting recommendation method and system, which captures eye state information through a collection device, synchronously acquires optometry data and eye detection data and pre-processes; inputs the data into an AI analysis model, identifies eye features and analyzes eye health conditions, and generates a health assessment report; based on the report, matches correction and protection schemes and screens adaptive contact lenses in combination with eye use requirements; through the linkage of intelligent wearable devices and special function contact lenses, eye data is monitored and health management suggestions are generated, visual expansion effect is realized, and the evaluation results and recommended schemes are continuously iterated and optimized, realizing the individualization and intelligentization of eye health management and lens fitting recommendation.

This application discloses a data-processing-based intelligent management method and system for thermal power fuel, comprising the following steps: collecting multi-dimensional data of the entire life cycle of thermal power fuel; cleaning, standardizing, and fusing the collected multi-dimensional data to obtain pre-processed fuel data; constructing a multi-dimensional analysis model to analyze the pre-processed fuel data, comparing the analysis results with preset condition information, generating procurement adjustment instructions, inventory scheduling instructions, coal blending execution instructions, and equipment operation and maintenance early warning instructions, and pushing the instructions to the corresponding execution terminals, collecting feedback data in real time during the instruction execution process; obtaining instruction execution status data based on the feedback data, visualizing the instruction execution status data, fuel data, and analysis results, and generating multi-dimensional statistical reports; this invention establishes a unified data collection and integration mechanism, breaks down data barriers at each stage, and forms a complete data link for the entire fuel life cycle.

The invention relates to a pavement crack monitoring method and system, and belongs to the technical field of pavement state monitoring. According to the method, the problems of insufficient identification reliability, lack of three-dimensional geometric information and incapability of dynamic prediction caused by dependence on single sensing data in the prior art are solved. The method comprises the steps of synchronously collecting multi-modal sensing data containing a two-dimensional image and a three-dimensional point cloud, establishing a mapping relation between two-dimensional pixels and a three-dimensional space through space-time registration, extracting a candidate crack region based on a crack recognition algorithm, and projecting the candidate crack region to the three-dimensional point cloud to generate a candidate point cloud set, according to the method, geometric feature parameters including depth variance and normal vector consistency indexes are calculated, a real crack is judged by comparing the geometric feature parameters with a preset threshold value, three-dimensional form information is output, finally, the same crack is associated through feature matching based on the multi-cycle three-dimensional form information, the expansion rate is calculated, and the remaining service life is predicted according to a material fatigue model. The method and the system are mainly used for crack detection and state evaluation in road maintenance management.

The application discloses a kind of complex lighting conditions underwater artificial crack dataset construction method, it is related to image dataset production technical field, including, collection crack picture and extract crack curve generation coordinate information, based on this, construct crack 3D model and prepare concrete standard test block;The test block is placed in water, and underwater crack image under conventional, dim and uneven illumination is collected, and is classified after pre-processing according to illumination condition;Stable Diffusion model based on LoRA fine-tuning is used, and different illumination condition images are input respectively to train and optimize, and style expansion image is generated, and pre-processing image constitutes unlabeled data together;Through image enhancement algorithm processing the data, after the enhanced image is labeled, the label is corresponded with the original image, and the underwater artificial crack dataset under complex lighting conditions is constructed, the application solves the problem that actual underwater crack disease is difficult to collect, meets the core demand of engineering practice, and provides richer data support for underwater structure crack detection and segmentation model training.

The application relates to the technical field of foundation engineering construction, and discloses a device for detecting the thickness of deposited sediment in foundation engineering construction, which comprises a deposited sediment thickness detector installed on a foundation. The device is characterized in that the rolling assembly, the steel wire rope, the rotating disc and the turnover frame are cooperatively operated, the detection of different positions in a pile hole can be completed without repeated disassembly, and the detection efficiency is greatly improved; the positioning plate increases the contact area, the extrusion arm firmly clamps the side wall of the pile hole, stable support is provided for the probe puncture, the detection data is ensured to be accurate and reliable; the output end for adjusting the probe position acts on the steel wire rope, damage caused by the probe being stuck is avoided, and the service life of the device is effectively prolonged; meanwhile, the turnover frame, the rotating disc and other structures are matched, the flexible movement and multi-angle detection of the probe in the pile hole are realized, the detection range is significantly expanded, and more comprehensive and accurate data support is provided for the quality evaluation of foundation engineering construction.

The application provides a method and system for checking the cross-modal information consistency of a maintenance plan based on a large model, and relates to the technical field of big data analysis. The method comprises the following steps: identifying a target maintenance plan through a power large model, determining key maintenance content, an unstructured proportion, and an attachment type complexity; obtaining a text data complexity and a business risk index based on key maintenance content analysis, as a first checking difficulty coefficient and a second checking difficulty coefficient; determining a third checking difficulty coefficient according to the unstructured proportion and the attachment type complexity evaluation; taking the expected review time limit of the target maintenance plan as a constraint, formulating an adaptive checking depth and an adaptive checking breadth based on the first checking difficulty coefficient, the second checking difficulty coefficient, and the third checking difficulty coefficient; and performing cross-modal information consistency checking on the target maintenance plan according to the adaptive checking depth and the adaptive checking breadth. The dynamic allocation of resources for checking the cross-modal information consistency of a maintenance plan is achieved.

The invention relates to the technical field of image processing, and discloses a landslide surface crack three-dimensional evolution unmanned aerial vehicle image extraction and quantification method and system, and the method comprises the steps: carrying out the bundle adjustment of an ultrahigh overlapping degree aerial image of a landslide surface, and obtaining an image shooting position, an image attitude parameter and a sparse three-dimensional point cloud; constructing a high-precision digital earth surface model; performing digital mosaic on the aerial image with the ultrahigh overlapping degree to obtain an orthoimage; performing semantic segmentation on the orthoimage to obtain a crack binary segmentation map of the orthoimage so as to identify a main crack and a secondary crack; performing three-dimensional geometric parameter analysis on the main crack and the secondary crack to obtain a crack three-dimensional space attribute parameter; carrying out evolution trajectory tracking on the crack three-dimensional space attribute parameters to obtain evolution data so as to construct a visual map of the landslide surface; according to the invention, the efficiency of extracting and quantifying the three-dimensional evolution unmanned aerial vehicle image of the landslide surface crack can be improved.

This invention discloses a method for testing the epitaxial structure performance of gallium oxide-based diodes, relating to the field of transistors. It solves the problem of detection effectiveness in existing epitaxial structure performance testing methods. The method includes the following steps: Step S1: Obtaining the luminous efficiency values ​​of the target diode under test at each preset power, and plotting a power-luminous efficiency coordinate graph accordingly. Based on the power-luminous efficiency coordinate graph, the qualified luminous efficiency power range corresponding to the target diode under test is obtained. Step S2: Obtaining the color rendering index values ​​of the target diode under test at each characteristic power, and plotting a color rendering index coordinate graph accordingly. Based on the color rendering index coordinate graph, the qualified color rendering power range corresponding to the target diode under test is obtained. Step S3: Performing performance testing on the sample gallium oxide-based diodes based on the qualified color rendering power range and the qualified luminous efficiency power range, and issuing performance warnings based on the test results. This invention can improve the accuracy of diode performance testing results.

The application belongs to the technical field of network attack and defense simulation, and discloses a network attack and defense simulation engine system based on discrete event driving, which comprises an event scheduling module, a simulation network construction module, an attack and defense simulation module, a simulation kernel module and a panoramic situation awareness module; the event scheduling module is constructed based on MITRE ATT&CK as a theoretical base and is used for converting all network activities into a schedulable discrete event sequence; the network activities comprise packet sending, protocol timeout and attack triggering; the simulation network construction module can construct a simulation network containing complete business logic. The application can convert the MITRE ATT&CK tactical intention into an ordered event stream through the event scheduling module, and can simultaneously perform dynamic decomposition and re-planning on a high-level target through a hierarchical task network planner in the attack and defense simulation module, and can also reconfigure an attack chain in real time by using an ATT&CK technology ID.

This invention provides a lithium carbonate price prediction method based on multimodal data collaborative driving, comprising the following steps: multimodal data source identification and data acquisition; multimodal data classification and standardization; personalized noise filtering and outlier correction of multimodal data; extraction of trend and correlation features from structured data; extraction of semantic and visual / speech features from unstructured data; extraction of key information and feature quantification from semi-structured data; weighted collaborative fusion and feature optimization of multimodal features; construction and training of a two-branch collaborative prediction model; model prediction and preliminary verification of prediction results; optimization and dynamic correction of prediction results; interpretability analysis and visualization of prediction results; and method effectiveness verification and continuous improvement. This method, based on multimodal data collaborative driving, addresses the pain points of existing lithium carbonate price prediction technologies, forming a comprehensive, high-precision, and highly practical prediction solution.

The application discloses a kind of power grid intelligent scheduling system and method based on digital twinning and deep learning, it is related to power grid intelligent scheduling technical field, a kind of power grid intelligent scheduling method based on digital twinning and deep learning, specific steps include: step one, by fusing multi-source heterogeneous data and dynamic parameter updating mechanism, construct and physical power grid synchronous mapping power grid digital twinning, step two, adopt federal learning framework aggregation multi-area power grid data, establish equipment degradation model, perfect priority data channel mechanism, step three, based on power grid digital twinning determines real-time power grid state and equipment risk coefficient, designs deep reinforcement learning dynamic decision-making framework, realizes the load scheduling optimization of multi-objective cooperation, the application is based on power grid digital twinning determines real-time power grid state and equipment risk coefficient, designs deep reinforcement learning dynamic decision-making framework, can realize the load scheduling optimization of multi-objective cooperation.

This invention provides a collaborative control system and method for urban lake stormwater and flood control, relating to the field of flood management. The system and method utilize a multi-source heterogeneous information fusion system, collecting and standardizing multi-dimensional data such as quantitative precipitation forecasts, hydrology, urban flooding, and water quality to construct a unified data lake. This achieves high-precision, multi-dimensional information perception, providing comprehensive and high-quality data support for control decisions. It addresses the problems of incomplete information perception and inconsistent data standards in existing technologies. Furthermore, it establishes a dynamic risk assessment model integrating flood control, ecological water quality, social, and water resource utilization risks. Risk indicators serve as both hard constraints and soft costs in scheme comparison, enabling quantitative assessment and control of multiple risks. This allows decision-makers to clearly understand the potential risks of different schemes, significantly reducing the blindness of decision-making and improving the safety of control schemes.

This invention relates to the field of pickle technology, specifically to a modular intelligent pickle racket monitor, comprising a racket and a wristband; the wristband includes a body and a flexible wristband; a first sensor module is disposed within the body; the racket includes a racket body and a handle; a second sensor module is disposed within the racket body; the handle has a storage groove; a receiving cavity is disposed within the handle; a strip-shaped groove runs through the storage groove and the receiving cavity; a locking block is movably disposed within the receiving cavity; the locking block has a locking pin; the locking pin is telescopically disposed within the strip-shaped groove; one end of the flexible wristband is connected to the body; the flexible wristband has a locking hole. This invention, through the modular combination design of the racket and wristband, achieves multi-dimensional acquisition of motion data, while utilizing the storage and locking structure of the handle to achieve convenient storage and fixation of the wristband, solving the problems of single data acquisition and easy loss of wristbands in traditional pickle monitoring devices, thus improving the ease of use and monitoring accuracy of the device.

The invention discloses a self-diagnosis high-voltage fuse and a running state online monitoring method thereof, and belongs to the technical field of high-voltage power equipment.The method comprises the following steps that S1, running parameters and environmental parameters of a fuse body are collected, and collected data are corrected in real time based on calibration factors; s2, filtering and denoising the calibrated data, and extracting core feature parameters; s3, calculating a state evaluation index based on a multi-parameter coupling state evaluation formula, constructing a dynamic threshold self-optimization model in combination with a simulation result of the digital twin model, adjusting a state judgment threshold in real time, and adaptively matching a typical fault mode; s4, calculating the residual life of the fuse link body through a dynamic aging prediction formula, and quantifying the fault risk level; and S5, performing graded response and self-diagnosis feedback based on a calculation result. According to the invention, the technical defects of single monitoring parameter, low diagnosis precision and lack of self-repairing linkage in the prior art are overcome, and the operation safety and reliability of a power system are improved.

The invention discloses a multi-dimensional intelligent monitoring device for a cluster fire spreading test of a lithium ion battery. The multi-dimensional intelligent monitoring device comprises a temperature monitoring module, an electrical parameter monitoring module, a flame multi-parameter monitoring module, a data synchronous acquisition module and a data processing and analyzing module, the signal output ends of the temperature monitoring module, the electrical parameter monitoring module and the flame multi-parameter monitoring module are all connected with the signal input end of the data synchronous acquisition module, and the signal output end of the data synchronous acquisition module is connected with the signal input end of the data processing and analyzing module; and the temperature monitoring module is used for acquiring temperature data of the interior and exterior of the battery pack and the space of the test cabin. The problem that an existing device is single in monitoring dimension is solved; a reliable basis is provided for multi-dimensional data comparison; comprehensive data support is provided for thermal runaway spreading mechanism research; the safety of the test process is further improved through the arrangement of the early warning module, and remarkable practicability and creativity are achieved.

The application discloses a high-fidelity single-sample DOM particle-fluorescent component synchronous characterization system and method, and belongs to the field of water environment monitoring.The system comprises a gradient ultrafiltration enrichment unit, an intelligent FlFFF separation unit, a time sequence-particle size linkage collection unit, a multi-parameter collaborative correction EEM detection unit and a multi-dimensional data fusion analysis module, and realizes synchronous characterization through the steps of gradient ultrafiltration enrichment, intelligent separation, differential collection, collaborative correction detection and multi-dimensional analysis.The application has the advantages of high fidelity and high precision through the technical improvements of double-stage ultrafiltration pressure control and concentration self-adaptive flow field regulation, is suitable for various water environment samples, can output a DOM biological activity score, and provides support for ecological function research.

The application discloses a video behavior detection method and device, equipment and a storage medium. The application obtains video features of a current video segment, obtains character information in the current video segment based on the video features, and obtains multi-scale context information representing different background information in the current video segment. The application obtains a current bidirectional interaction relationship feature between the character and the multi-scale context information based on the character information and the multi-scale context information. The current bidirectional interaction relationship feature fully considers the interaction relationship between the character and the context information in the background in complex interaction, and thus can accurately predict the behavior category of the character in the current video segment based on the current bidirectional interaction relationship feature. The current bidirectional interaction relationship feature obtained in the application can perceive the context information associated with the character through the character information, and can perceive the character information associated with the context information through the context information, thereby providing more abundant data support for behavior detection and further improving the detection accuracy.

This utility model discloses an in-situ testing system for battery thermal characteristics, comprising: a battery clamping module including two clamping plates, one fixed and the other adjustable; a thickness measurement sensor assembly for measuring the thickness change of the battery during charging and discharging; an expansion force measurement assembly for measuring the expansion force generated by the battery during charging and discharging; and a temperature measurement module for monitoring the heat generation changes of the battery during charging and discharging. This utility model can simultaneously monitor the thickness change, expansion force change, and temperature change of the battery during charging and discharging, improving the comprehensiveness and accuracy of the test. It is applicable to testing batteries of different sizes and types, and has wide applicability. It solves the problems of limited functionality and cumbersome testing processes in existing battery testing devices, providing comprehensive and accurate data support for battery performance evaluation, and has broad market application prospects.

This invention discloses a dynamic erosion experimental system and method for single-hole perforation in extreme flow-limited fracturing. The system includes a fracturing fluid supply unit, a transparent fluid supply unit, a valve switching unit, an experimental section, a perforation morphology monitoring unit, and a jet pressure field mapping unit. The valve switching unit controls the connection between the fracturing fluid supply unit or the transparent fluid supply unit and the experimental section. The perforation morphology monitoring unit images the perforated sample. The jet pressure field mapping unit measures the pressure distribution of the jet ejected from the perforated sample during the connection between the fracturing fluid supply unit and the experimental section. This invention solves the problem of direct observation in opaque fluids through a "scouring-imaging" method. Combining sacrificial coating technology with direct measurement of jet performance, it can accurately and synchronously quantify the erosion process and its impact on jet performance, providing comprehensive and accurate data support for fracturing technology research.

This invention discloses an intelligent grain silo sampling method and robot based on multi-point automatic planning, belonging to the field of grain silo sampling technology. The method involves a main control unit calculating and planning a compliant sampling point sequence and a global navigation path, supporting dynamic adjustment of the point sequence and replanning of the remaining path. Multimodal perception and obstacle avoidance algorithms enable autonomous robot navigation, obstacle detour, and path regression. Subsequently, grain surface perception, main control parameter adjustment, and resistance feedback complete adaptive sampling of the grain surface, and a unique identifier is generated for each grain sample. Finally, multi-dimensional data from the equipment and environment are collected throughout the process, and the main control unit determines anomalies, issues graded warnings, and responds to remote emergency commands, achieving full-process safety monitoring and emergency intervention. Using the above method and structure, precise sampling point planning, autonomous robot navigation and obstacle avoidance, adaptive grain surface sampling, traceable grain sample information, and full-process safety monitoring, early warning, and emergency intervention are achieved.

The invention discloses a cross-modal knowledge collaboration blast furnace condition evaluation method, and belongs to the technical field of blast furnace production. The method comprises the following steps: a data acquisition module for acquiring sensor data, process parameters and historical data in blast furnace production; the data preprocessing module is used for cleaning, standardizing and extracting features of the acquired data; the cross-modal knowledge cooperation module comprises knowledge extraction, knowledge fusion and knowledge graph construction, and is used for extracting feature and semantic information from multi-modal data, realizing association and complementation among modals and forming a comprehensive knowledge system; the model training module is used for training a LightGBM model by utilizing the marked historical data and learning a mapping relation between the data and the furnace condition; and the evaluation and feedback module is used for inputting multi-modal data in real time, outputting a furnace condition evaluation result and dynamically adjusting a production control strategy. According to the method, through cross-modal knowledge cooperation, high-precision, high-adaptability and real-time evaluation of the furnace condition of the blast furnace is achieved, the production efficiency can be remarkably improved, energy consumption and accident risks can be reduced, and blast furnace production intellectualization is promoted.

This application discloses a portable autofocus hyperspectral imaging system and method. The system includes a spectral data acquisition module, a spectral analysis module, a displacement platform, an inertial measurement module, and a control module. The spectral data acquisition module includes an adjustable focus lens, a beam splitter, a first collimating lens group, and an image sensor. The spectral analysis module is equipped with an electronic shutter, a slit, a second collimating lens group, a grating, a third collimating lens group, and an imaging element along the optical path. The displacement platform drives the spectral analysis module to perform internal scanning motion. The control module executes the autofocus algorithm, automatic exposure control, and multi-source data fusion and preprocessing. This application can improve focusing accuracy and spatial registration accuracy of spectral data in complex depth-of-field scenes, intelligently and adaptively adjust exposure parameters, compensate for geometric distortion, support unattended continuous operation, reduce the cost of ineffective operations, and improve the reliability and usability of hyperspectral data.