3603results about How to "Improve collection efficiency" patented technology

The invention discloses a construction progress detection system and method based on three-dimensional model and field data fusion, and relates to the technical field of power grid construction engineering. The system comprises a data acquisition module, a data preprocessing module, a data matching module, a data fusion module, a progress detection module and a feedback module, the data matching module matches point cloud data with a panoramic image, a clonal selection algorithm is applied to optimize matching parameters, and on-site three-dimensional basic data is constructed; the data fusion module performs deep fusion on the BIM model and on-site three-dimensional basic data, and constructs a three-dimensional fusion model for construction progress detection by using a GeoBIM technology; and the progress detection module compares the real-time acquired panoramic image of the construction site with the three-dimensional fusion model frame by frame, and automatically detects the construction progress, so that efficient acquisition, accurate processing and real-time monitoring of construction site data are realized, and the efficiency and decision ability of construction management are remarkably improved through automatic progress detection and real-time feedback.

The invention discloses a bridge structure detection method based on an unmanned aerial vehicle, a product, a medium and equipment, and relates to the technical field of bridge structure detection, and the method comprises the steps: obtaining the basic data of a bridge structure, and constructing a three-dimensional model according to the basic data; layering the three-dimensional model of the bridge structure according to a preset interval, and calculating an initial path of the unmanned aerial vehicle; optimizing the initial path by adopting a gradient descent method to obtain an optimal path of the unmanned aerial vehicle; acquiring to-be-detected data of the bridge structure based on the optimal path of the unmanned aerial vehicle; preprocessing the to-be-detected data to obtain preprocessed to-be-detected data; and performing crack detection and deformation detection based on the preprocessed to-be-detected data to realize bridge structure detection. According to the bridge structure detection method based on the unmanned aerial vehicle, the product, the medium and the equipment, efficient and accurate detection of the bridge structure can be realized.

The invention provides an integrated metadata management method and system based on data source expandability, and relates to the technical field of data sources, and the method comprises the steps: executing real-time detection on a plurality of heterogeneous data sources through a PF4J plug-in framework, collecting connection information, and establishing a dynamic connection pool; obtaining a table structure, a field attribute and an association relationship list, and assembling the table structure, the field attribute and the association relationship list into JSON format data; performing analysis and standardization processing on the data, and constructing an association degree calculation matrix; generating a standardized data structure description file; establishing a three-layer index directory, and detecting structure change and updating; and calculating a data table reference dependency relationship, and generating a DAG data flow path. According to the method, efficient integration and management of heterogeneous data sources are realized, and the metadata processing efficiency is improved.

The invention provides an industrial Internet of Things data acquisition method based on edge cloud collaboration, and belongs to the technical field of data analysis, and the method comprises the steps: S1, deploying a plurality of edge nodes in an industrial field, collecting original data of industrial equipment, and carrying out the real-time preprocessing; s2, the edge nodes further process the preprocessed data by adopting a hybrid algorithm combined with a deep learning model; s3, in the data processing process, the edge node monitors the operation state of the system through a real-time feedback mechanism, and dynamically adjusts the data acquisition frequency, the data compression rate and the processing strategy through a preset strategy; s4, the cloud performs deep analysis on the received preprocessed data, constructs a multi-dimensional analysis model, and generates an analysis result and an optimization strategy; and S5, the cloud end feeds back the analysis result and the optimization strategy to the edge node, and guides the edge node to adjust the data acquisition and processing strategy. The data acquisition efficiency can be improved, the data security is ensured, and the cloud pressure is relieved.

The invention provides a cross-platform burying-point-free data collection and intelligent circle selection rule generation method and system, and relates to the technical field of intelligent algorithms, and the method comprises the steps: obtaining view hierarchy tree information and interaction event information of page elements through injecting a data collection script, and training a page element recognition model based on a graph neural network. The model is combined with an adaptive feature fusion network to realize cross-platform element alignment and recognition. And classifying the newly added elements by utilizing the element similarity information, and generating and correcting the circle selection rule based on a preset rule template and the context feature vector. And finally, the rule execution engine realizes continuous monitoring and dynamic acquisition of the target element in the cross-platform application program according to the target circle selection rule.

The invention relates to the technical field of plastic production, in particular to an intelligent processing method and system for plastic mold process parameters. The method comprises the following steps: carrying out sensor network deployment on a plastic mold to obtain a mold parameter sensing network; operating parameters of the plastic mold are collected in real time through the mold parameter sensing network, and mold operating state data flow is obtained; performing process state feature extraction on the mold operation state data stream to obtain mold process state feature data; performing spatio-temporal data hierarchical analysis on the mold process state feature data to obtain mold state multi-scale feature data; and performing layered thermal field dynamic modeling on the plastic mold based on the mold state multi-scale characteristic data to obtain a mold thermal field evolution model. The key process parameters of the mold can be identified, and the stability and reliability of the mold performance are enhanced.

The invention provides an explosion-proof power distribution cabinet control method and system based on situation awareness, and relates to the technical field of power distribution cabinets, and the method comprises the steps: obtaining the associated power equipment information of a target power distribution cabinet; analyzing the connection relation of the same-level equipment to generate an equipment network topology structure; acquiring use scene information, and generating an operation configuration parameter set; acquiring an operation condition data set; judging whether a running configuration parameter set is met or not; if yes, performing real-time state monitoring to obtain state monitoring information of the target power distribution cabinet; inputting a situation awareness prediction model to carry out abnormal state prediction to obtain an abnormal state prediction coefficient; and judging whether an abnormal state prediction coefficient threshold value is met or not, and if yes, generating a first emergency processing instruction to perform emergency processing. According to the method, the problems of low data acquisition and processing efficiency and poor timeliness and safety of power distribution cabinet control due to lack of accurate prediction of abnormal states in a traditional method are solved.

The invention discloses an unmanned aerial vehicle cluster intelligent formation method, device and equipment based on distributed reinforcement learning, and the method comprises the steps: constructing a reinforcement learning environment of an unmanned aerial vehicle cluster, which comprises a state space, an action space and a reward function, according to a flight task scene of an unmanned aerial vehicle, the flight mission scene comprises execution of air refueling and long-distance formation transportation; building a training framework of a distributed reinforcement learning algorithm based on the reinforcement learning environment, and performing network construction based on the training framework to obtain a neural network including an action decision network and a formation target evaluation network; performing distributed training on the neural network by adjusting hyper-parameters of the neural network and utilizing large-scale distributed data to obtain a formation model; and loading the formation model to an actual unmanned aerial vehicle cluster system, and adjusting a formation strategy according to a real-time flight environment and task requirements to carry out a formation flight task. The cooperative flight capability and the self-adaptability of the unmanned aerial vehicle cluster can be improved.

The invention relates to the technical field of industrial automation, in particular to an industrial equipment self-diagnosis system based on algorithm model prediction, and the system comprises a model building module which comprises a historical fault model; the data acquisition module divides a plurality of to-be-detected point locations and acquires and converts vibration signals; the period judgment module performs periodic judgment on the real-time vibration graph, determines that the vibration period is abnormal according to the judgment result and gives an alarm, or analyzes the abnormal condition of the point location; the data analysis module adjusts a preset frequency based on the point location abnormal conditions, or determines an overall abnormal condition based on a plurality of point location abnormal conditions so as to determine a real-time fault degree, and performs fault early warning on a comparison result of the real-time fault degree and a preset fault degree, or adjusts a preset interval; the model comparison module inputs a plurality of pieces of real-time vibration data into a historical fault model and calculates a fault degree difference value; the model calibration module calibrates the historical fault model based on the fault degree difference. According to the invention, the accuracy of the model fault prediction result is improved.

The invention discloses an AI-based marketing commodity short video generation method and device, a medium and a product, and relates to the field of short video generation. The method comprises the following steps: constructing a short video industry knowledge base; obtaining question information input by a user; searching answers from a short video industry knowledge base according to the question information; obtaining a video selected from the answers by the user as a reference short video, and obtaining commodity information uploaded by the user; the commodity information comprises commodity selling points and commodity materials; retrieving a reference copywriting from the short video industry knowledge base according to the commodity selling point, taking the reference copywriting as knowledge supplementary information, generating a script copywriting according to the reference short video and the knowledge supplementary information, and generating picture information according to the script copywriting and the commodity material; and editing the picture information to obtain a short video of the commodity information. The output efficiency of the running amount materials can be improved.

The invention relates to a fractured coal and rock mass strength intelligent prediction method based on image recognition, and belongs to the technical field of rock mass mechanics prediction. The method comprises the following steps: (1) carrying out an indoor test according to different fracture parameters and lithology, and establishing an initial training data set; (2) introducing numerical simulation data, supplementing laboratory data through the simulation data, integrating the data into a data set, and constructing a sample database of coal and rock mass fractures and strength; (3) training a machine learning model by using the sample database, wherein the machine learning model is trained by adopting a gradient lifting decision tree model; (4) testing the precision of the machine learning model by using test set data; (5) acquiring a working face image; and (6) predicting the strength of the to-be-measured coal rock mass. According to the method, a traditional rock strength measurement method is improved, an accurate prediction model can be constructed by combining the nonlinear relationship between the geometrical characteristics and the strength of the coal-rock mass fractures with different lithology, and efficient prediction is realized.

The invention provides a solar cell and a photovoltaic module, and belongs to the technical field of solar cells. The solar cell comprises: a semiconductor substrate having a first surface and a second surface opposite to each other, and a plurality of first side surfaces adjacent between the first surface and the second surface; the passivation contact structure is at least located on a part of the first surface of the semiconductor substrate, and the passivation contact structure comprises an interface passivation layer and a first doped semiconductor layer which are stacked in sequence; wherein in the direction from the first surface to the second surface, the first side face comprises a first area and a second area which are adjacent in sequence, and the first area protrudes in the direction away from the first side face compared with the second area; the first doped semiconductor layer is further located on a part of the surface of the first region, and the first doped semiconductor layer located on the first region and the first doped semiconductor layer located on the first surface are integrally continuous; a portion of the surface of the first region adjacent to the second region is not covered with the first doped semiconductor layer.

The invention discloses a light-weight government affair questionnaire intelligent touch and analysis system and method based on a fusion message, and the system comprises an integrated message application platform operation interface which is used for the submission, application, strategy definition and transmission of a customer message; the questionnaire engine is used for generating questionnaires, issuing strategies and performing multi-dimensional statistical analysis on questionnaire results; the intelligent message scheduling engine is used for realizing AI generation of rich media messages, multi-channel intelligent reach distribution, optimal reach mode selection and summary analysis of reach mode results; and the electronic fence data engine is used for processing operator real-time signaling big data and capturing operator numbers and accurate touch short messages in a specified range. An efficient and convenient short message creation and auditing mechanism, flexible and diversified questionnaire construction, intelligent rich media message generation, accurate regional orientation and audience access, intelligent distribution, high interactivity, comprehensive and deep data analysis and report generation can be realized.

The invention provides an electron microscope automatic focusing method and system based on a deep learning model, and relates to the technical field of electron microscope automatic focusing, and the method comprises the steps: collecting a plurality of images at different focusing distances through an electron microscope, and recording the focusing distance of each image; calculating the characteristic value of each collected image, combining the focusing distance and the characteristic value of the image into a characteristic vector, and generating a characteristic sequence according to the characteristic vectors obtained under different focusing distances; training a pre-constructed neural network model by using the feature sequence to obtain a trained neural network model; and inputting a to-be-tested image into the trained neural network model, calculating a difference value between the predicted optimal focusing distance and the focusing distance of the collected image, and judging whether the difference value is within a set range or not. According to the invention, the microscopic image acquisition efficiency and quality are obviously improved.

The invention discloses a centrifugal deep sea rare earth collecting mine car, a deep sea rare earth collecting system and a mining method.The centrifugal deep sea rare earth collecting mine car comprises a mining car body, the mining car body is provided with a centrifugal collecting mechanism, and the centrifugal collecting mechanism comprises a first annular flow channel and a first driving mechanism; and the first driving mechanism is connected with the first annular runner. According to the centrifugal deep-sea rare earth collecting mine car, the centrifugal collecting mechanism is adopted for collecting deep-sea rare earth, negative pressure is formed through the first annular flow channel, the deep-sea rare earth and seawater can be sucked upwards to be collected, deep-sea rare earth slurry can be efficiently collected, the collecting efficiency is improved, and the collecting mode is particularly suitable for collecting the deep-sea rare earth; the defect that a traditional mining vehicle cannot be used for deep-sea rare earth collection is overcome, and development of the deep-sea rare earth collection industry is facilitated.

The invention discloses a supported double perovskite photocatalytic material which is prepared by the following steps: putting copper nanoparticles and double perovskite Cs2NaBiCl6 into a water-absolute ethyl alcohol mixed solution, carrying out ultrasonic dispersion, heating the dispersion solution to 55-65 DEG C, carrying out cooling crystallization at a rate of 1-2 DEG C / min, completing the reaction when the temperature is reduced to 25 DEG C, carrying out solid-liquid separation on the reaction product, and washing and drying the solid, the Cu nanoparticle-loaded double-perovskite photocatalytic material is applied to photocatalytic reduction of CO2, the catalyst has the characteristics of high reduction catalysis efficiency and good selectivity, the performance is stable after repeated cyclic utilization, and the material disclosed by the invention is simple in preparation process, high in efficiency and suitable for large-scale production and market popularization and application.

The invention discloses a sand source resistance and control dynamic configuration method for a hole-to-wind sand area, and relates to the technical field of wind and sand protection, and the method comprises the following steps: collecting meteorological data, wind and sand data and historical sand source change data of the hole-to-wind sand area, and obtaining geographic information and vegetation coverage conditions of the sand source area through a remote sensing technology and ground monitoring equipment; by monitoring key parameters such as wind speed, wind direction and dust concentration in real time and combining high-resolution ground image data acquired by an unmanned aerial vehicle and a satellite remote sensing technology, real-time sensing and accurate analysis of sand source changes are realized, the efficiency and accuracy of data collection are improved, and the detection accuracy is improved. In addition, the prevention and control measures can be dynamically and accurately arranged according to the specific sand source, and by dynamically adjusting the arrangement and density of prevention and control facilities and optimizing the type and area of vegetation coverage, sand storm invasion can be more effectively prevented, the occurrence frequency and intensity of sand storm are reduced, and the efficiency and accuracy of sand source prevention and control are remarkably improved.

The invention relates to the field of integrated optical fiber microscopic endoscopy, in particular to an all-optical-fiber light beam modulation and collection system based on double super lenses and a design method of the all-optical-fiber light beam modulation and collection system. The system comprises a single-mode optical fiber, a coreless optical fiber for beam expansion and two super lenses (a super lens 1 and a super lens 2) with different functions. The super lens 1 is arranged on the end face of the fiber core of the single-mode optical fiber and focuses output exciting light to form extremely small waist spots, and the divergence angle of light beams is increased. The super lens 2 is arranged on the end face of the coreless optical fiber beam expanding area and used for refocusing the exciting light and focusing the collected fluorescence to the focus position of the super lens 1 at the same time, and the fluorescence is incident to the fiber core in parallel through the super lens 1. According to the invention, a double-super-lens system based on a high numerical aperture (NA) is fully utilized, wavefront modulation is carried out, the length of a beam expanding area is adjusted, and the loss of fluorescence in the beam expanding area is reduced, so that the collection efficiency of the fluorescence is remarkably improved, and an innovative solution is provided for the design of a super-lens-based optical fiber optical system.

The invention provides an enzyme activity parameter extraction method and system based on a large language model, and belongs to the field of text information processing and data mining. According to the method, the document in the PDF format is converted into the Markdown format through the OCR technology, and then key data are automatically extracted by combining a large language model with an optimized cue word; the accuracy and consistency of data are ensured through strict cue word optimization and post-processing operation in the automatic extraction process; and verifying the effectiveness of automatic extraction through accuracy and recall rate, wherein the finally generated enzyme database can be used for subsequent research and analysis. By combining the OCR technology and the large language model, the limitation of existing manual data extraction is broken through, and the automation degree of literature analysis and data extraction is remarkably improved; through cue word engineering and optimized cue word design, automatic extraction of structured data in complex literatures is achieved, and especially accurate recognition and extraction of enzyme kinetic parameters are achieved.

The invention provides a concentrator efficient data acquisition optimization method and system. The method belongs to the technical field of electric power communication, and comprises the following steps: setting each reading task as an exclusive task or a parallel task, performing priority distribution on the reading tasks, and introducing a state machine for executing a first reading task, namely a to-be-read data task configured by a main station; after a system is started, whether exclusive tasks exist in a task pool or not is judged firstly, and if yes, all the exclusive tasks are executed according to a priority sequence; and after the execution of the exclusive task is completed, obtaining all parallel first copying and reading tasks in the task pool, performing parallel execution through a task scheduling mode of the state machine, and obtaining corresponding to-be-copied data items. By setting the reading task as the exclusive task or the parallel task and performing priority allocation, system resources can be utilized more efficiently, and the data acquisition efficiency is improved.

The invention relates to the technical field of roller machining, and provides a roller forming device and method.The roller forming device comprises a base which serves as a basic mounting part and is used for providing a basic mounting face and providing space for treatment of metal chippings; the fixing frame is fixedly connected to the top end of the base and used for providing a machining platform for forming treatment of the roller; the compression mechanism is arranged in the base and used for compressing and quantitatively transferring the concentrated metal chippings; the blowing mechanism is arranged in the middle of the top end of the base and used for assisting in collection of metal scraps; and the fixing mechanism is arranged in the fixing frame and used for supporting and fixing the roller. Through the arrangement of the fixing mechanism, the swing amplitude of the roller can be limited, the situation that the roller cannot be effectively fixed or collides with other parts due to swing is prevented, meanwhile, the position of the roller can be actively adjusted when the roller deviates to one side, the working process is simplified, and the placing and fixing efficiency is improved.

The utility model provides a cheese whey squeezing device, relates to the technical field of cheese squeezing, and solves the problems that a mechanism for squeezing cheese is lacked, the separation time of whey is long, the squeezing efficiency is low, the cheese is inconvenient to squeeze and form, the cheese is inconvenient to be cut into small blocks with regular shapes for storage and packaging in the next step, and the production cost is low. Meanwhile, cheese is stacked on the surface of a filter screen and cannot be collected at a time, and the cheese collecting efficiency is low. The device comprises a pressing table, the pressing table is hollow, an extrusion assembly is installed at the upper end of the side face of the pressing table, a jacking assembly is installed in the pressing table, a through hole is formed in the upper surface of the pressing table, and the upper portion of the jacking assembly penetrates through the through hole. Through the arrangement of the squeezing assembly, the squeezing efficiency is improved, cheese is squeezed and formed, the cheese can be conveniently cut in the next step, through the arrangement of the jacking assembly, the cheese can be conveniently collected at a time, and the collection efficiency is improved.

The invention discloses an intelligent and automatic transformer substation information acquisition system, which relates to the technical field of information acquisition, and is characterized in that an information change coefficient and an information priority coefficient are acquired and substituted into a logistic regression model to obtain an information potential evaluation coefficient, the information potential evaluation coefficient is analyzed with a preset potential threshold to obtain a comparison result, and the transformer substation information is acquired according to the comparison result. Dividing to obtain a real-time acquisition potential information set and a non-real-time acquisition potential information set, substituting into a default score combination mechanism, determining an actual classification acquisition result of each piece of information, obtaining a network state when each piece of information is uploaded, obtaining a network delay degree and a bandwidth utilization rate from the network state, and substituting into fuzzy logic for fuzzy reasoning to obtain a real-time acquisition potential information set and a non-real-time acquisition potential information set; according to the method, the reasonability result of the default score combination mechanism is determined, then the network delay degree and the bandwidth utilization rate when each piece of information is uploaded are substituted into set parameters in the default score combination mechanism, the score combination mechanism is determined and adjusted, and the information redundancy and the system burden are reduced.

The invention relates to a wavenumber domain compressed sensing damage detection method suitable for a plate-shaped structure. The method comprises the following steps: S1, constructing a compressed sensing equation; s2, solving the compressed sensing equation, and reconstructing to obtain a wave number domain signal of a full wave field; and S3, selecting a threshold value for the reconstructed wavenumber domain data for filtering, returning to a spatial domain through inverse Fourier transform, and carrying out merging processing on results by adopting a root mean square method to obtain a damage morphology graph. According to the method, the sparse basis matrix meeting the compressed sensing requirement is constructed by optimizing the sparse representation of the signal, so that the precision of full-wave field signal reconstruction is remarkably improved; the number of sampling points is greatly reduced, the full-wave-field data acquisition efficiency is improved, and the potential of breaking through the limitation of the Nyquist sampling law is achieved; the position and the shape of the damage are detected, the detection effect is good, and the detection efficiency is high.

The invention discloses a solar cell which comprises a silicon substrate, the surface of at least one side of the silicon substrate is provided with a micro-suede of a sand dune-like structure, and a tunneling oxide layer is laminated on the micro-suede; the sand dune-like structure is provided with at least one vertex, and 3-6 curved side edges pass through each vertex; and the side edges are sunken towards the inner part of the sand dune-like structure. The invention also provides a preparation method of the solar cell. According to the solar cell, the surface reflectivity of the solar cell can be effectively reduced, and the characteristics of surface passivation, surface contact and the like are improved, so that the transmission efficiency and the collection efficiency of carriers are improved, and the short-circuit current density and the conversion efficiency of the solar cell are further improved.

The embodiment of the invention relates to the photovoltaic field, and provides a back contact photovoltaic module, which comprises a battery body of which the back surface comprises a plurality of positioning areas which are arranged at intervals along a first direction, and first fine grids and second fine grids which are alternately arranged along a second direction are arranged on the back surface; each interconnection structure is electrically connected with one of the plurality of first fine grids and the plurality of second fine grids; a single interconnection structure electrically connected with the fine grids is used as a target interconnection structure, any fine grid electrically connected with the target interconnection structure comprises a first branch and a second branch, each of the first branch and the second branch comprises an end part close to the target interconnection structure, and the first branch and the second branch are arranged along the direction close to the target interconnection structure. The widths of the end parts of the first branch and the second branch in the second direction are gradually reduced, and the fine grid is one of the first fine grid and the second fine grid; and the insulating strip is positioned on any fine grid which is electrically insulated from the target interconnection structure, and is at least beneficial to improving the photoelectric conversion efficiency of the back contact photovoltaic module.

The invention belongs to the technical field of ground unmanned platforms, and particularly relates to a sky-air-ground integrated cross-country environment high-precision map construction method. Comprising the following steps: 1, acquiring a cross-country environment high-precision map; and 2, making a cross-country environment high-precision map. According to the invention, automatic extraction of elements is realized by combining an automatic extraction technology; in the aspect of map making, making specifications are provided, and the running efficiency of a high-precision geographic information system is improved while it is guaranteed that the cross-country maneuvering requirement of a ground unmanned platform in the cross-country environment is met; incremental data updating is carried out on the high-precision map based on a real-time mobile environment perception result of the ground unmanned platform so as to ensure the timeliness of the high-precision map. Through the method, the blank of a high-precision map technology in the field of automatic driving in the cross-country environment is filled up, and support is provided for improving the cross-country maneuverability of a ground unmanned platform.

The invention relates to a sweat real-time detection device and a preparation method thereof, the sweat real-time detection device sequentially comprises a collection layer and a detection layer from bottom to top, the collection layer comprises a fitting area, a fan-shaped flow guide area and a collection area, the fitting area is used for fitting skin, and the flow guide area is used for guiding sweat into the collection area; a plurality of guide vanes facing the collecting area are arranged in the guide area, and the guide vanes are triangular; the collecting area is connected into the fan-shaped included angle of the flow guide area and penetrates through the collecting layer; the detection layer is internally provided with a drainage area, a detection area and a micro-channel, the drainage area corresponds to the collection area and is used for draining sweat in the collection area to the detection area, and the detection area is provided with a sweat detection chip; the micro-channel is emitted from the drainage area, penetrates through the detection area and extends to the outermost side of the detection layer. The sweat collection device has the characteristics of high sweat collection efficiency, sufficient sweat collection amount, timely sweat detection after collection, rapid sweat analysis and detection process, reliable detection result and the like.

The invention discloses a dust collecting device for producing protective clothing and treating dust, and relates to the technical field of dust collecting devices, the dust collecting device comprises a pre-dust-collecting chamber shell and a second combined flow guiding piece, the upper end of the left side of the pre-dust-collecting chamber shell is connected with an air inlet pipeline, and the lower end of the right side of the pre-dust-collecting chamber shell is connected with an air outlet pipeline; the second combined flow guide part is arranged between the air inlet pipeline and the air outlet pipeline, and the second combined flow guide part is composed of a rectangular outer frame, four second flow guide plates, an angle and distance adjusting mechanism and the like; the dust collector has multiple advantages, the burden of the filter bag can be relieved through the dust pre-collection chamber shell, the first combined flow guide part can flexibly change the included angle between the first flow guide plate and the center axis of the air inlet pipeline by means of the first electric push cylinder according to the flow and concentration of dust-containing air, and the second combined flow guide part can flexibly change the included angle between the first flow guide plate and the center axis of the air inlet pipeline according to the size and concentration of dust particles. The inclination angles of the four second flow guide plates are synchronously adjusted through the angle adjusting mechanism, and the distance between the second flow guide plates is adjusted in a self-adaptive mode through the distance adjusting mechanism.

The invention discloses a large-scale topographic map surveying and mapping method based on oblique photography and airborne LiDAR. The large-scale topographic map surveying and mapping method comprises the following steps: S1, data acquisition; s2, carrying out three-dimensional modeling; s3, collecting ground features and landforms; s4, carrying out LiDAR point cloud classification and contour line data production; s5, data fusion; and S6, field annotation and data editing. According to the scheme, on the basis of oblique photography and airborne LiDAR topographic map surveying and mapping, ground feature and landform data (except contour lines) collected on a three-dimensional model are fused, contour line data are produced on the basis of LiDAR point cloud, large-scale topographic map surveying and mapping can be completed in combination with field plotting, and surveying and mapping efficiency and accuracy can be improved.