426results about How to "Accurate data support" patented technology

The invention discloses a bridge damage detection method and system, and belongs to the technical field of bridge engineering.The method comprises the steps that image data, point cloud data and spectral data of a to-be-detected bridge are obtained; inputting the obtained image data, point cloud data and spectrum data of the to-be-detected bridge into an input module of the constructed bridge damage detection model, and determining feature vectors of the image, the point cloud and the spectrum; and a feature fusion module of the constructed bridge damage detection model fuses feature vectors of images, point clouds and spectrums, interacts and fuses obtained fused feature representations of all modals on different levels to obtain fused feature vectors, and outputs a bridge damage detection type through a classifier in a DNN classification layer. The method can improve the accuracy of bridge damage detection.

The invention discloses a test system and method for an artificial heart valve implant, and relates to the technical field of medical instrument detection. The system comprises a ventricle simulator, an atrium simulator, a circulation loop, a high-speed camera and a laser generator, wherein an artificial heart valve is arranged in the high-transparency compliance valve testing cavity, and the circulation loop is composed of a blood vessel compliance simulator and a blood vessel damping simulator. The circulation loop simulates a blood flowing environment for the artificial heart valve, and a flowing medium is added with tracer particle turbid liquid; the ventricle simulator, the atrium simulator, the vascular damper and the vascular compliance simulator respectively provide power, storage space, resistance and pulse pressure for the flowing medium; and the laser generator and the high-speed camera act together to obtain a particle image behind the artificial heart valve. The particle image is uploaded to a computer for heart valve pulsating flow field visualization analysis based on the digital particle image velocity measurement technology, and therefore quantitative analysis of the risk after the heart valve is implanted into the expected position is achieved.

The invention relates to the technical field of building engineering, in particular to a steel structure construction quality monitoring system based on an unmanned aerial vehicle and three-dimensional scanning, which comprises a data acquisition module, a data preprocessing module, a construction defect identification and risk assessment module and a quality assessment module, the data acquisition module acquires quality monitoring data of a construction site in real time; the data preprocessing module is used for preprocessing the acquired quality monitoring data; the construction defect identification and risk assessment module identifies steel structure defects in the construction process and assesses the severity of the steel structure defects; and the quality evaluation module performs comprehensive quality evaluation on the preprocessed quality monitoring data and provides corresponding repair suggestions. According to the method, key problem areas can be quickly identified, a construction resource allocation strategy is optimized, and comprehensive and accurate data support is provided for steel structure quality evaluation in a complex construction environment.

The invention relates to a light control method and system based on a holographic interactive projection technology, and the method comprises the steps: projection region recognition, user interaction detection, light parameter calculation and light real-time regulation and control, the projection region recognition, scanning of a target region through a holographic projection device and a depth induction sensor, and generation of a three-dimensional space model of an environment; a motion capture device and a deep learning algorithm are used for carrying out real-time recognition on gestures or motions of a user, interaction intentions and priority ranking are generated, a holographic projection device is used for generating a three-dimensional environment model, the motion capture device recognizes the intentions of the user, and an illumination optimization model is used for calculating regulation and control parameters; and the output of the light equipment is dynamically adjusted, so that high-precision and intelligent light control is realized, and the problems that a traditional light control method is insufficient in environment perception capability, lacks a user interaction mode, is limited in flexibility and adaptability of light regulation and control, and lacks a multi-module cooperative working mechanism are solved.

The invention relates to the technical field of micro-grid distributed control, in particular to a micro-grid cluster distributed control method and system based on information interconnection. The method comprises the following steps: identifying a micro-grid cluster in a region, and extracting a plurality of micro-grid nodes; obtaining a plurality of microgrid operation state parameters; performing filtering standardization processing on the plurality of micro-grid operation state parameters, and constructing a micro-grid time sequence load change curve; discrete wavelet transform is carried out on the micro-grid time sequence load change curve, load fluctuation frequency trend mining is carried out, and micro-grid load fluctuation frequency trend characteristics are generated; carrying out data stream encapsulation on the load fluctuation frequency trend characteristics of the micro-grid, and constructing a cloud environment distributed computing framework; carrying out dynamic load demand calculation on the plurality of micro-grid nodes based on a cloud environment distributed calculation framework so as to obtain multi-period load demand prediction data of each micro-grid; according to the invention, high-efficiency microgrid cluster control with high energy utilization rate is realized.

The invention relates to the technical field of police service management, discloses a police service management system and method based on an image recognition technology, and aims to improve the police service management efficiency and accuracy. The system comprises a data receiving module, a data preprocessing module, a target detection module, a behavior analysis module and an information integration module. A monitoring video stream is received, data is preprocessed to form an image data set, and then a specific target is detected by using a deep convolutional neural network and a track sequence is output. And carrying out behavior analysis on the target track by adopting a long-short-term memory network, and identifying an abnormal mode. And finally, integrating the detection result and the behavior analysis data, and generating a police service management report. According to the invention, intelligent processing of monitoring videos is realized, police service departments are assisted to respond to abnormal conditions in time, and urban public security is maintained. Through the deep learning technology, the accuracy of target detection and behavior recognition is improved, and powerful support is provided for modern police service management.

The invention relates to the technical field of heart data analysis, in particular to an AI (artificial intelligence)-based heart disease prediction system, which comprises a feature relationship modeling module for mapping each type of information into a multi-dimensional feature space based on collected heart data, analyzing the condition correlation degree between feature nodes, connecting the feature nodes through correlation information, and establishing a model; and quantifying a linkage effect between the features to obtain a feature condition dependency relationship analysis result. According to the method, various types of heart health data are noded by constructing a multi-dimensional feature space, and a correlation structure is established according to condition correlation among data features. And a synergistic effect and an interdependence relationship among the features are disclosed. By analyzing the joint state probability of the feature nodes, the linkage effect of the feature combination on the overall risk is quantified, and the analysis depth of the disease risk is enhanced. In addition, by comparing the independent state probability of a single feature with the joint state probability of the feature combination, a feature combination that makes a significant contribution to the risk can be identified.

The invention discloses a plant disease and insect pest detection device and method based on unmanned aerial vehicle high-altitude texture imaging, and belongs to the technical field of intelligent agriculture. The plant disease and insect pest detection device comprises an unmanned aerial vehicle body, a holder, a high-altitude texture camera and a small host; the high-altitude texture camera is arranged below the holder, the holder is arranged below the small host, the small host is arranged below the unmanned aerial vehicle main body, the unmanned aerial vehicle main body is provided with a front high-definition camera, a battery and an illumination sensor, and the high-altitude texture camera is wirelessly provided with a handle and a flight remote controller through Bluetooth; according to the plant disease and insect pest detection method, high-precision recognition of disease and insect pests is achieved on the basis of high-altitude texture feature fusion in combination with an environment perception driven data enhancement module, a self-adaptive multi-scale image convolution feature extraction and fusion module and a disease and insect pest area attention fusion module. The technology effectively supports precise detection of diseases and insect pests in agricultural production, and provides a scientific basis for agricultural management and pesticide application.

The invention discloses an anti-direct-current component nanocrystalline current transformer and a using method thereof. The anti-direct-current component nanocrystalline current transformer comprises a current transformer body, and a magnetic core hole penetrating front and back is formed in the middle of the front side of the current transformer body. The device is provided with a secondary side open circuit detection and protection mechanism, so that imbalance of a magnetic field in the mutual inductor caused by disconnection of a secondary loop is effectively prevented, iron core magnetic flux saturation and potential high electromotive force generation are avoided, the safety of the mutual inductor and peripheral equipment is protected, the risk of power system faults such as fire disasters or short circuits is reduced, and meanwhile, the safety of the mutual inductor is improved. A live wire centering fixing mechanism is arranged, so that the stable centering position of a wire in a magnetic core hole of the mutual inductor is ensured, magnetic field distribution is optimized, the magnetic leakage phenomenon is reduced, the accuracy and stability of current measurement are remarkably improved, meanwhile, measurement fluctuation caused by wire shaking is reduced, and the measurement precision is improved. And more accurate data support is provided for harmonic analysis, fault detection and electric energy quality monitoring of a power system.

The invention relates to a non-signaling test-based frequency offset calibration method, system and device and a medium, and the method comprises the steps: carrying out the parallel non-signaling frequency offset test of a plurality of target chips, collecting the output waveforms of the target chips, and determining the frequency offset values of the target chips according to the output waveforms; performing deviation analysis on the frequency deviation value, and calculating a corresponding frequency deviation calibration value based on the frequency deviation value and a preset frequency calibration coefficient under the condition that the frequency deviation value reaches a preset frequency limit range; writing the frequency offset calibration value into a corresponding target chip, and performing parallel frequency offset calibration; and carrying out calibration degree verification on the target chip after frequency offset calibration so as to confirm whether the frequency offset value of the target chip accords with a preset standard frequency. The method and the device have the effect of improving the frequency offset calibration efficiency of the chip.

The invention relates to the technical field of electric wheelchair control, in particular to a multi-mode navigation control method and system of an electric wheelchair controller. The method comprises the following steps: acquiring a real-time environment monitoring video based on an electric wheelchair high-definition camera; video jitter distortion compensation and dynamic object frame-by-frame continuous optical flow tracking are carried out on the real-time environment monitoring video, and a moving track of each dynamic object is generated; performing environment static obstacle accurate identification on the real-time environment monitoring video, and performing dynamic environment perception modeling based on a moving track of each dynamic object so as to generate a dynamic environment map; a navigation mode switching decision is made based on a real-time wheelchair operation instruction of the user to obtain a current navigation mode of the user, and the current navigation mode of the user comprises a rocker control mode and an intelligent navigation mode. According to the invention, efficient and intelligent multi-mode control of the electric wheelchair is realized, so that the electric wheelchair can more flexibly and safely cope with a complex environment.

The invention relates to the technical field of hydraulic engineering operation prediction, in particular to a hydraulic engineering operation trend prediction method and system. The method comprises the following steps: acquiring multi-source hydraulic engineering data, and generating a hydraulic engineering three-dimensional model through multi-source space fusion processing and three-dimensional model simulation; performing geometric complexity identification and stress path analysis on the three-dimensional model to determine key nodes in the water conservancy project; historical water conservancy data are obtained, time sequence conversion and potential mode mining are carried out, and potential modes related to engineering are obtained; performing stress superposition comparison on the key nodes of the water conservancy project and the potential mode to generate stress superposition comparison data, and iteratively adjusting the key nodes according to a result to obtain adjusted stress nodes; constructing a prediction model based on the adjusted stress node and the potential mode, performing operation trend prediction, and generating an operation trend prediction result of the water conservancy project; the high-precision and high-adaptability water conservancy project operation trend prediction method is realized.

The invention provides a geological disaster monitoring multi-dimensional visual early warning system and method based on big data, and relates to the technical field of geological disaster monitoring, and the method comprises the steps: collecting ground surface displacement, slope stability and underground water level in real time; analyzing and processing the collected data to generate a surface risk coefficient, a slope risk coefficient and a water level risk coefficient; establishing a risk level evaluation model of which the input quantity is an earth surface risk coefficient, a slope risk coefficient and a water level risk coefficient and the output quantity is a geological risk level, obtaining historical earth surface displacement parameters, slope stability parameters and underground water level parameters, and defining corresponding geological risk level coefficients; and comparing the risk grade coefficient analyzed by the evaluation model with a threshold value, and sending out a corresponding early warning signal. According to the method, the accuracy of disaster early warning and risk assessment can be improved, model parameters are verified by using historical disaster data in big data, and the accuracy and reliability of a risk grade evaluation model are improved, so that the geological disaster risk is predicted more accurately.

The invention discloses a real-time laser coal checking system and method, and relates to the technical field of material management and inventory checking, and the system comprises the following components: a laser detection module, a data processing module, a communication module, a monitoring module and a server module. The laser detection module is adopted to perform high-frequency scanning on the coal pile to obtain the three-dimensional point cloud data of the coal pile, the crown block displacement data measured by the laser range finder and the material and density information of the material pile are combined, the volume and weight of the coal pile are calculated through an algorithm, the outer contour of the coal pile can be determined more accurately, and the accuracy of the coal pile is improved. According to the shape characteristics and the density distribution condition of the coal pile, the coal pile is divided into a plurality of small geometries for volume calculation, and compared with traditional manual measurement or simple geometric shape approximation, the method has the advantages that the measurement precision of the volume and the weight of the coal pile can be remarkably improved; and more accurate data support is provided for material management and inventory checking of enterprises.

The invention provides a wound nursing intelligent decision-making method and system based on high-precision image recognition. The method comprises the following steps: in response to a received wound monitoring request, extracting a patient identifier, wound image information corresponding to a multi-angle high-precision image, wound background information and multi-modal sensor information from the wound monitoring request; a pre-trained three-dimensional convolutional neural network model is used for automatically recognizing the wound state, and a wound recognition result is obtained; based on the wound image information and the wound background information, assisting in positioning through an augmented reality technology; performing wound healing environment assessment based on the information of the multi-modal sensor; retrieving matched nursing strategy information from a preset nursing scheme database based on patient historical information and personalized treatment preference information corresponding to the patient identifier, the wound identification result, the wound positioning information and the wound healing environment evaluation information; and pushing the nursing strategy information. According to the scheme, the wound nursing quality is improved.

The invention relates to the field of data acquisition, in particular to a multi-sensor array type equipment acoustic fingerprint self-adaptive acquisition device and method, and the device comprises a track which is arranged around a transformer body and is provided with a plurality of acoustic sensors; the controller is responsible for receiving operation state information and environment parameters of the transformer equipment and acquiring the operation state information and the environment parameters through an interface of the transformer equipment monitoring system and the environment monitoring sensor; the controller is provided with a communication module, sends an instruction to the acoustic sensor array through the communication module, and adjusts the layout and parameters of the acoustic sensor; and the server is used for monitoring, analyzing and storing the acoustic fingerprint signals in real time. When the device is used, the layout and parameters of the acoustic sensor are automatically adjusted, so that accurate acquisition of acoustic fingerprint signals of the transformer equipment is realized. Meanwhile, the advanced signal fusion technology is utilized to improve the signal strength and reliability, and more accurate and more reliable data support is provided for state monitoring and fault diagnosis of transformer equipment.

The invention belongs to the technical field of environmental health risk identification and supervision, and discloses an environmental health risk assessment method and system for combined pollution of a metal smelting area, and the method comprises the following steps: S1, constructing an environmental health risk assessment system; s2, acquiring and inputting data; s3, heavy metal environmental health hazard identification; s4, evaluating receptors of heavy metal environmental health; s5, heavy metal environmental health hazard assessment; s6, evaluating the exposure of the heavy metal environment health; s7, comprehensive evaluation of heavy metal environment health; and S8, judging the supervision priority. Aiming at various heavy metal environmental health risks under multiple exposure media in the production activity of the metal smelting area, based on multiple steps, multiple models and graded evaluation, the method considers comprehensiveness and differentiation of evaluation results, determines a preferential supervision area, carries out targeted differential supervision, and improves the safety of the production activity of the metal smelting area. The efficiency of identifying and supervising the environmental health risk of the metal smelting area is improved.

The invention provides a water quality multi-parameter detection method and system based on ultraviolet-visible light section spectroscopy, which are used for detecting turbidity, chemical oxygen demand and nitrate nitrogen concentration in a water sample. The method comprises the following steps: firstly, acquiring spectral data of a water sample, converting the spectral data into absorbance, then calculating influence factors of turbidity, chemical oxygen demand and nitrate nitrogen on a mixed sample spectrum, and dividing a spectral range into three characteristic spectral sections according to the influence factors, which correspond to the turbidity, the chemical oxygen demand and the nitrate nitrogen respectively. And finally, establishing a multi-parameter detection model by using a partial least squares PLS method for predicting turbidity, chemical oxygen demand and nitrate nitrogen concentration. According to the method, the interference of serious overlapping of multi-parameter spectral lines is avoided through segmented analysis of the spectrum, the detection precision is improved by utilizing a method of fusing the first-order derivative spectrum, and particularly, the effect in the aspect of nitrate nitrogen detection is remarkable. The method is easy and convenient to operate and low in cost, and a more effective technical means is provided for water quality monitoring and water environment protection.

The invention provides a method for measuring the object positions of gold ores above the medium fraction in heavy sand and application of the method, and belongs to the field of mineral processing.The method for measuring the object positions of the gold ores above the medium fraction in the heavy sand comprises the following steps that gold ores above the medium fraction in a heavy sand sample to be measured are selected, and the length, width and thickness of each gold ore are measured; calculating the observation volume of each gold mineral; a volume correction coefficient and color are introduced to calculate the mass of each gold mineral; and calculating the grade of the gold minerals above the medium grade. According to the method, the observed volume of the gold mineral is corrected by introducing the volume correction coefficient, so that the real volume closer to the reality is obtained, the density of the gold mineral is corrected through color formation, so that the real density closer to the reality is obtained, and the mass of the gold mineral obtained through volume and density calculation is more accurate; therefore, the calculated grade is more accurate.

The invention provides an electric vehicle charging load analysis system based on deep learning and real-time traffic simulation. The system comprises an offline simulation deduction module, a deep neural network training module and an online simulation deduction module. An energy consumption model is constructed by collecting an electric vehicle starting toll station record, ETC door frame vehicle passing information and service area charging station data in an expressway, and offline simulation deduction is achieved. The deep neural network adopts a self-attention mechanism model, and combines a multi-head attention mechanism and time sequence coding to predict the EV charging load. The on-line simulation deduction module collects vehicle data in real time and carries out prediction based on real-time traffic simulation software. And performing weighted analysis and dynamic adjustment on simulation and deep learning prediction results through a feedback mechanism so as to improve the prediction precision. Through the distributed calculation and real-time data processing technology, mass data can be efficiently processed, accurate charging demand prediction is provided, and the method adapts to dynamic changes in different scenes.

The invention discloses a digital construction organization 4D analogue simulation method, which comprises the following steps of S1, determining an integral construction group; s2, simulating a construction scheme; s3, optimizing a construction scheme; s4, performing field tracking and iterative updating; and S5, progress optimization. The method has the advantages that the BIM three-dimensional construction model of the key control engineering of the expressway is created by utilizing a three-dimensional simulation technology, comprehensive performance evaluation is carried out on the model, construction organization design is carried out on the model, a reasonable construction procedure and a reasonable component movement relation are constructed, and 4D visual dynamic simulation of the whole construction process is realized.

The invention discloses a digital twin model evolution method and system based on constructional engineering. The invention relates to the technical field of constructional engineering. Related data of the long-distance water conveyance project are collected, wherein the related data comprise BIM model data, oblique photography three-dimensional model data and GIS data; meanwhile, the data are preprocessed, including format conversion, coordinate unification and denoising, so that the quality and consistency of the data are ensured. A three-dimensional BIM model of the engineering facility is constructed based on Autodesk Revit according to a design drawing and collected data, the facility and equipment in the BIM model are coded according to a KKS coding rule, and a coding database is updated; according to the method, the BIM model data, the oblique photography three-dimensional model data, the GIS data and other multi-source data are fused, a refined three-dimensional scene model is constructed, and comprehensive integration of engineering facility information is achieved. Therefore, data sharing and collaboration among different departments and professions are facilitated, and the overall working efficiency is improved.

The invention belongs to the technical field of airborne atmospheric detector equipment, and particularly relates to an airborne cloud water content detection system, which comprises a constant-temperature hot wire sensor, a cloud water content detection module, a cloud water content detection module and a cloud water content detection module, the pressure sensor is used for measuring atmospheric pressure; the temperature sensor is used for measuring the temperature in the cloud; the humidity sensor is used for measuring the humidity in the cloud; the data processing module is used for receiving the data of the sensor and processing and analyzing the data through a specific algorithm to determine the cloud water content; the data communication module is used for outputting the measured data and the calculated cloud water content data to a computer or other acquisition detector equipment through the Ethernet or a serial port; and the heating control module is used for keeping the detector in a preset standard working temperature range so as to ensure the measurement accuracy and the reliability of detector equipment, and has the effect of finely detecting the airborne cloud water content.

The invention discloses a plug-in-based real-time acquisition and manual analysis method for webpage data without a fixed format. Real-time integrated operation of data acquisition, labeling and uploading is realized through a browser plug-in. A user selects target data through a floating window interface, and a plug-in automatically extracts content, identifies a platform source, performs quick labeling in combination with a preset analysis label and uploads the data to a background. According to the method, the flexibility of manual judgment and the high efficiency of an automation technology are fused, and the method can adapt to multiple platforms including high-protection dynamic webpages without developing a customized tool for a target website. The floating window supports operations such as dragging and zooming, so that the user experience is improved; the labeling is completed by data acquisition, so that the processing chain is effectively shortened, and the efficiency and accuracy are remarkably improved. The system supports authority management, encrypted transmission and real-time statistical analysis, and ensures data security and efficient utilization.

The invention relates to a calculation method for concentration ratios of rainfall in different forms, and the method comprises the steps: obtaining meteorological data and elevation data of a to-be-measured time period of a research region, and generating a wet bulb temperature and a threshold temperature according to the meteorological data and the elevation data; wherein the threshold temperature comprises a critical high temperature and a critical low temperature; performing temperature judgment on the wet bulb temperature based on the threshold temperature, acquiring different rainfall types of the research area, and acquiring rainfall amounts of different types of rainfall in combination with rainfall data; calculating the cumulative rainfall days and the cumulative rainfall amount of different types of rainfall through the rainfall amount, calculating the concentration ratio of different rainfall types by using the regression coefficient, and further calculating the concentration ratio and the rainfall concentration period of the rainfall in the region by combining the vector azimuth angle. The method can solve the problem that the spatial and temporal distribution of the concentration ratio of different rainfall types cannot be effectively quantified, and makes up for the defect that the existing index cannot accurately reflect the change of different rainfall types and the influence of the concentration degree on regional water resource management and weather prediction.

The invention relates to the technical field of pump body structure design and optimization, in particular to a method for acquiring a centrifugal pump blade load distribution curve, which comprises the following steps of: recording the stress distribution condition of a blade under the action of alternating load in real time through a high-precision multi-channel strain gauge and a laser interference measurement technology; a scanning electron microscope, a transmission electron microscope and an X-ray diffraction technology are combined to analyze microstructure characteristics of a composite material and metal bonding interface; through comparison of experimental data and finite element analysis results, deviation is quantified, error analysis is carried out, and key microstructure parameters influencing load distribution are identified. According to the analysis result, experimental conditions and a finite element model are optimized, a design scheme for adjusting the interlayer thickness of the composite material and optimizing the metal treatment process is provided, and the load bearing capacity and durability of the blade are improved. The method can be widely applied to design and optimization of high-performance centrifugal pump blades.

The invention belongs to the field of new energy power generation systems, and discloses a forced circulation steam generation system variable load operation optimization method and related equipment.The method includes the steps that a tube shell type evaporator numerical calculation model and a forced circulation system hydrodynamic balance model are established, and high evaporation capacity, evaporator efficiency and minimum cost serve as optimization targets; a multi-objective optimization model is constructed by combining the change of the flow of the fused salt and the flow of the circulating water; the model is solved by adopting a Pareto dominating method, and a Pareto optimal solution set can be output, so that optimized operation schemes of the forced circulation system under different loads can be formulated according to the optimal solutions; by the adoption of the method, high evaporator efficiency and evaporation capacity can be achieved, meanwhile, pump work loss can be effectively reduced, the key target in operation of the photo-thermal power station is achieved, namely, balance of high efficiency and low loss is achieved, and powerful support is provided for stable operation and economic benefits of the photo-thermal power station.

The invention discloses a navigation method and system for an inspection robot in a breeding house, and relates to the technical field of intelligent agriculture. The method comprises the following steps: dividing the breeding house into a plurality of areas, and preliminarily planning an inspection path of the inspection robot in combination with a shortest path algorithm and a depth-first search algorithm; environment data and animal data are collected in real time through an internal sensor group and an intelligent ear tag, a health data group is obtained through preprocessing, an environment health state index and an animal health state index are calculated, a comprehensive health index is further obtained, and the comprehensive health index and a preset first comprehensive health threshold value and a preset second comprehensive health threshold value are evaluated. And when path planning is triggered by health assessment, a dynamic path optimization model is adopted to adjust an inspection path, and an area with relatively high health risk is preferentially covered until the health assessment of the inspection task area reaches a good state. According to the method, the breeding environment and animal health monitoring efficiency can be effectively improved, and health management and risk control in the breeding process are ensured.

The invention discloses a mining dust concentration monitoring and early warning method, and belongs to the technical field of coal mining, and the method comprises the following steps: data acquisition; a mine respirable dust concentration wireless sensor and a mine intrinsic safety type holder type infrared camera are used for collecting the dust concentration and the environment visibility in a mine respectively; processing and analyzing data; the mining intrinsic safety type wireless monitoring host processes the received data to obtain the dust concentration, and whether the dust falling device needs to be started or not is judged based on the dust concentration; if the dust concentration exceeds the preset range, the dust falling device is started until the obtained dust concentration is within the preset range; compared with the existing dust concentration monitoring means, the mine dust disaster monitoring system can realize dynamic perception, accurate early warning and intelligent management and control of mine dust disasters, introduces a real-time monitoring technology in order to timely discover and solve the problem that the dust concentration exceeds the standard by introducing intelligent and automatic technologies, and can also realize remote monitoring at the same time.

The invention, which relates to the technical field of travel big data evaluation, discloses a travel big data evaluation system comprising a tourist attraction supporting facility evaluation module, a social media big data evaluation module, a miraculous degree module and a comprehensive scoring module. The invention also discloses a travel big data evaluation method. The method comprises the following steps: collecting scenic spot data; cleaning and standardizing the collected data, and performing hierarchical scoring; analyzing the processed data to generate a comprehensive score; and the generated score and analysis result are fed back to the scenic spot and the travel management department, and optimization suggestions and improvement schemes are provided. According to the invention, on the basis of social media data, the service quality, environmental protection and tourist experience of tourist attractions and cultural projects can be monitored in real time, dynamic feedback is provided through a scientific evaluation system and a big data analysis model, the tourist service quality is improved, the international competitiveness of cultural tourist resources is enhanced, and support is provided for the development of the cultural industry.