240 results about "Environment management" patented technology

The invention discloses a pigsty environment regulation and control optimization method and system, and belongs to the technical field of breeding environment management. The system comprises an intelligent sensing module, an environment analysis module, a parameter optimization module and a control management module. The intelligent sensing module is used for collecting pig house environment parameters and live pig physiological parameters through a multi-mode sensor; the environment analysis module is used for constructing a behavior recognition model, analyzing behavior characteristics based on physiological parameters and dividing abnormal regions; the parameter optimization module is used for establishing a physiological environment control model and setting an optimal optimization scheme for each abnormal region; and the control management module is used for generating an environment control instruction according to the optimal optimization scheme and controlling equipment execution. The pig house environment and the pig physiological parameters are collected and intelligently analyzed through the multi-mode sensor, automatic and precise environment optimization management is achieved, and the comfort level and the health level of the pigs are improved.

The invention relates to the technical field of soil environment monitoring, and discloses a soil remediation construction site environment monitoring method based on edge computing cloud collaboration. The method comprises the following steps: deploying an edge computing node at a restoration construction site, and collecting real-time data of soil humidity, heavy metal concentration, volatile organic compound content and meteorological parameters through a multi-source sensor; inputting the data into a spatio-temporal feature extraction network, and generating a spatio-temporal fusion feature matrix by means of hierarchical convolution and a cross-channel attention mechanism; on the basis of the matrix, the index anomaly probability is calculated by using a depth probability network, and a risk feature sequence with uncertainty measurement is generated; constructing a dynamic risk field model in combination with repair process parameters, and predicting a pollution diffusion path through a space-time propagation algorithm; and in combination with an equipment operation state, an edge side local regulation and control instruction and a cloud global optimization strategy are generated by a collaborative decision engine, and efficient and accurate environment management requirements of a construction site are met.

The invention provides a computing power center resource centralized self-adaptive control scheduling system and method, and the method comprises the steps: S1, a user submits a computing power training task through an API, and sends the task to a DAG task composer, and forms a task list to be scheduled; s2, the intelligent monitoring analysis module is used for continuously collecting node data and calculating real-time CS and HS scores of each node; s3, analyzing the dependency relationship type data by a task composer, and calling a dynamic programming algorithm in an adaptive scheduler to make a decision; s4, the adaptive scheduler performs dynamic task distribution according to the task list of the DAG task orchestrator and the intelligent monitoring analysis module, and S5, the distributed runtime and environment management module is used for uploading the prepared Docker mirror image to the distributed storage; and S6, through the unified communication adaptation layer, the mirror image is pulled from the distributed storage on the target node and the container is started, the user does not need to concern the difference of the operating system in the whole process, and efficient and intelligent adaptive scheduling is realized.

The invention discloses a thermal comfort monitoring robot system and method based on multi-modal body language feature recognition and fusion, and aims to realize individual thermal comfort monitoring, regulation and control in a dynamic indoor environment. The intelligent mobile platform carries multiple types of environment sensors and visual acquisition equipment, and performs autonomous navigation and acquires environment parameters and human body image data; the multi-modal feature recognition module performs human body detection, posture recognition and identity maintenance on a video stream frame by frame based on a deep learning network, and extracts multi-modal human body features; the data processing and fusion module realizes cross-frame identity consistency through an algorithm and fuses multi-modal human body features and environmental parameters; the thermal comfort calculation module dynamically adjusts a metabolic rate parameter based on a predicted average voting model, incorporates the metabolic rate parameter into a psychological correction factor and calculates an individual thermal comfort index; the three-dimensional visualization and regulation and control module generates a comfort distribution map, is in butt joint with a building environment automatic control system to achieve dynamic regulation and control, and provides support for intelligent building environment management.

The invention relates to the field of environment management, and discloses a watershed digital twinning environment real-time simulation and interaction platform fusing cloud edge collaboration and intelligent modeling, and the platform comprises the steps: carrying out the dynamic collection of the Yangtze River and Yellow River watershed, and generating environment state information organized according to the temporal-spatial resolution; associating the generated environment state information with multi-source environment data to form a multi-source knowledge basis of the drainage basin pollution field; establishing a rule knowledge base covering pollution identification, early warning and prevention and control business processes by utilizing a generative knowledge representation method, and generating a pollution event candidate identification result; carrying out fusion calculation on the pollution event candidate recognition result and multi-source heterogeneous data, constructing a digital twin simulation model, and eliminating data islands between modules and data sources; and executing linkage calculation on the pollution area and the risk node calibrated in the digital twinborn simulation model, generating environment state interaction information and synchronously updating the environment state interaction information to the digital twinborn environment. The method has the advantage that the regional water environment risk prevention and control capability is improved.

The invention relates to the technical field of environment management information systems, in particular to a method and a system for extracting an ecological environment access list rule of an intelligent agent. The method comprises the steps of collecting ecological environment policy and regulation data from a plurality of data sources, and performing data cleaning and labeling to obtain a standardized text data set; training and optimizing the data set to obtain an ecological environment professional knowledge large model; designing a prompt project template including input, instructions, examples and output requirements; inputting the cleaned new policy data into the large model, and automatically extracting a structured access list rule according to a prompt template; and finally outputting and storing the rule. According to the method, automatic conversion from an unstructured policy text to a structured access rule is realized, the problems of low efficiency, poor accuracy and difficulty in updating and maintenance of a traditional manual extraction mode are effectively solved, and the intelligent level and decision support capability of ecological environment partition management and control are remarkably improved.

The invention discloses an urban thermal exposure risk optimization method and system based on carbon emission dynamic regulation and control, and belongs to the technical field of urban climate adaptation and low-carbon planning, and the method comprises the steps: obtaining real-time carbon emission data and a weather short-time forecast result; and inputting the obtained real-time carbon emission data and the weather short-time forecast result into the trained thermal exposure risk transfer model, outputting a future thermal exposure risk level, and combining an early warning threshold value to realize the optimization of the urban thermal exposure risk by adopting differential regulation and control strategy matching. The method solves the problems that a dynamic correlation mechanism of carbon emission and thermal exposure is not clear, a regulation strategy lacks multi-scene adaptability and real-time performance and the like, supports rapid early warning, accurate regulation and effect verification of thermal exposure risks, provides scientific support for urban thermal environment management, low-carbon development planning and resident health guarantee, and is suitable for popularization and application. The method is suitable for climate toughness optimization of multiple scenes such as industrial parks and high-density residential areas.

The invention discloses a metering equipment remote calibration method and device, a medium and equipment. The method comprises the following steps: calculating a loss index according to current characteristics of an extracted current signal in a monitoring period, and determining a phase offset of each harmonic based on the loss index; constructing an environment gain coefficient according to the environment temperature and the environment humidity in the environment management period; constructing a current correction coefficient according to the fundamental wave amplitude of the current signal in the monitoring period and the environment gain coefficient; and correcting each harmonic amplitude in the next monitoring period according to the current correction coefficient, and correcting each harmonic phase in the next monitoring period according to the phase offset of each harmonic to obtain a calibration current in the next monitoring period.

The invention discloses a hotel environment governance intelligent evaluation method integrating ESG indexes, and relates to the technical field of hotel environment monitoring, and the method comprises the following steps: collecting multi-source environment data in real time, and obtaining hotel data and guest room check-in information by deploying Internet of Things sensing equipment and docking with an existing hotel management system; based on the obtained guest room check-in state information, the number of check-in rooms is counted according to set time slices, and the real-time check-in rate of each time slice is calculated; performing standard unit conversion on the acquired environment data, and combining the obtained occupancy rate information to form a total environment load vector; matching a preset parameter according to the hotel type, and if no matching type exists, calculating to obtain an optimal parameter group of the hotel; on the basis of the parameters, the load efficiency of each time slice is calculated firstly, and then a DO-ELE coefficient is obtained through calculation and serves as an evaluation index; and according to the calculated DO-ELE coefficient, determining the ESG governance grade of the hotel by comparing with a preset grade division standard, and generating a visual evaluation report of a related data curve.

The invention discloses an active city cooling method based on a three-dimensional city form and a circuit theory, and belongs to the technical field of city environment regulation and heat island effect governance, and the method comprises the steps: S1, recognizing long-term stable cold and heat source patches through obtaining multi-temporal surface temperature (LST) data and combining mathematical form spatial pattern analysis (MSPA) and a landscape connectivity index; s2, adopting a spatial principal component analysis (SPCA) method to construct a comprehensive resistance surface fused with the three-dimensional urban form factors; s3, connecting a cold and heat source to simulate an airflow conduction path based on a circuit theory, extracting a cooling gallery and identifying key nodes; and S4, finally, through a stable surface-connecting line-key point mode active cooling network, space optimization is carried out. According to the method, accurate identification and efficient communication of cold and heat sources can be realized, the heat island effect relieving efficiency is improved, the long-term adaptability of a cooling network is ensured, and a popularized urban thermal environment governance path is provided.

The invention discloses a slope protection structure for mine geological environment governance, and belongs to the technical field of mine geological environment governance, the slope protection structure comprises a slope body, grooves located in the surface of the slope body, anchor rods and a vegetation net, the anchor rods are implanted into the slope body at intervals, the vegetation net is laid on the surfaces of the grooves and preliminarily positioned through the anchor rods, and the vegetation net is in a movable state in the initial state. In order to solve the problems that a traditional vegetation net cannot adapt to an irregular slope of a mine and water and soil loss is caused due to the fact that gaps are easily reserved, the vegetation net is attached in a self-adaptive mode through an outer metal protective net pressure applying-attaching mechanism driving-elastic stainless steel rod deformation linkage mechanism, an outer metal net applies pressure to push a push rod, and the vegetation net is attached to the slope. The elastic stainless steel rods are pertinently deformed according to the concave and convex shapes of the slope surface, the vegetation net is driven to fill gaps and fit the slope, the releasing mechanism releases the steel wire rope, adjustment allowance is provided for the vegetation net, wrinkles and suspension are avoided, stable attachment of soil and a spray-seeding matrix is ensured, and the survival rate of vegetation is greatly increased.

The invention discloses a method for monitoring VOC (Volatile Organic Compounds) unorganized emission by utilizing an ultrasonic imaging technology, and belongs to the technical field of environment monitoring. The method comprises the following steps: acquiring ultrasonic data of a chemical industry park production device through an ultrasonic imaging module; 20-100 kHz leakage ultrasonic signals are separated, and sound pressure is read; positioning a leakage source in combination with coordinate mapping and a digital twinborn model, and marking sound pressure with a color code; a fitting coefficient is obtained through laboratory calibration, the leakage rate is calculated, the total leakage volume is calculated according to the duration, and gas density can be combined to be converted into the total mass. The method has the advantages of wide-area coverage, real-time response, accurate positioning, small monitoring deviation and the like, solves the problems of multiple blind areas and difficulty in quantification of a traditional method, and provides data support for safety and environment management of chemical industrial parks.

The invention discloses a safety and environmental protection management system and method based on multi-pollutant cooperative treatment, and relates to the technical field of environmental management. According to the invention, multi-pollution data is collected in real time through a multi-parameter sensor network; optimizing and constructing an optimized pollutant relevance model by adopting a graph neural network and a Nelder-Mead simplex method, analyzing a collaborative / antagonistic relationship among pollutants, and generating a multi-pollutant processing list; multi-target optimization is carried out on a three-dimensional target function containing the removal rate, the cost and the by-product amount through an improved genetic algorithm, an optimal scheme is selected, balance between the environment and economic benefits is achieved, a dynamic multi-pollution map is constructed, and a pollution migration path is accurately tracked; a by-product material flow network analysis system is established, and resource recycling is achieved through a directional separation and reprocessing technology; according to the method, the combined pollution analysis precision is improved, the treatment cost is reduced, and the occurrence rate of secondary pollution is reduced.

The invention relates to the technical field of intelligent storage environment management, in particular to an intelligent storage environment management method and system based on artificial intelligence, and the method comprises the steps: calculating a theoretical humidity value of an internal cavity of closed power equipment according to an external environment parameter and an equipment sealing grade; obtaining cavity response characteristics including a shell vibration spectrum and microwave dielectric response data; inputting the cavity response features into a pre-trained humidity inversion neural network to obtain an actually measured humidity value of the internal cavity; according to the absolute deviation value of the theoretical humidity value and the actually measured humidity value, a cavity risk index is calculated in combination with the key grade coefficient of the closed power equipment; and when the cavity risk index exceeds a preset risk threshold, generating an active intervention instruction for the closed power equipment. And the risk that the closed power equipment is affected with damp due to humidity change in a storage environment is effectively solved.

The invention discloses an environmental protection management system based on big data service integrated management, and the system comprises a data collection layer which is used for collecting multi-source environmental data; the data management layer is used for storing, cleaning and standardizing the collected data and encrypting the data transmission and storage process; the data analysis layer is used for carrying out deep mining and intelligent analysis on the processed data; the application service layer is used for visually displaying the analysis result and realizing query, management and sharing of environment information through a user interface; and the block chain traceability layer is used for recording a source, a timestamp and a processing process of the data, and realizing tampering prevention and traceability of the data through a block chain technology. By integrating various advanced technologies, efficient acquisition, processing, analysis and management of environment data are realized, and comprehensive and scientific technical support is provided for environment management.

The invention discloses a garden environment informatization management system based on diversified analysis, which belongs to the technical field of garden environment management and comprises a management platform, a parameter monitoring module, a vegetation growth evaluation module, an environment influence analysis module, an early warning unit and a decision execution module. According to the method, a partition management mode is adopted, the vegetation growth state of a local area is comprehensively analyzed based on soil data and vegetation apparent images of a single area, the vegetation abnormal growth type of an abnormal management area is obtained through abnormal recognition, and historical data tracing analysis is combined, so that the vegetation abnormal growth state of the abnormal management area is obtained. The method specifically comprises the steps of performing root cause judgment based on historical meteorological data and facility data so as to generate different strategy information according to a root cause judgment result, constructing a closed-loop management system from anomaly recognition to data attribution to decision execution, and performing decision execution by using diversified data and an intelligent analysis technology and taking data as driving. And comprehensive monitoring, multi-dimensional analysis and accurate decision making of environmental elements are realized.

The invention discloses a method for determining industrial soil and underground water preferential management and control pollutants through multistage screening, and belongs to the technical field of environment management and pollutant risk assessment.The method comprises the steps that an industrial pollutant database of an area to be managed and controlled is constructed; forming a specific pollutant list; quantitative indexes are determined, a TOPSIS method is adopted to sort the pollutants, and preferential control pollutants are determined; according to the method, a three-stage progressive screening framework of'suspected pollutant library-particular pollutant-preferential control pollutant 'is carried out, a multi-criterion comprehensive evaluation system of a weight and TOPSIS sorting model is fused, multi-dimensional risk quantitative sorting is carried out on the pollutants, and the pollutants needing preferential control are accurately locked; the defects that a traditional screening technology is high in subjectivity, single in consideration dimension, lack of industry pertinence and the like are overcome, the comprehensiveness, scientificity and accuracy of pollutant screening are remarkably improved, and effective technical support is provided for environmental risk management and control.

The invention relates to the technical field of pollution risk assessment, and provides an AI-based karst region soil-underground water cooperative pollution assessment system. According to the system, multi-source soil and underground water heavy metal time sequence monitoring data are fused, cross-medium collaborative characterization characteristics are constructed, an enhanced time sequence modeling method with a parameter efficient adaptation capability is introduced, and a composite dynamic loss function oriented to non-stationary pollution evolution characteristics is designed; and collaborative prediction and uncertainty description of the heavy metal pollution states of the soil and the underground water are realized. Furthermore, a prediction result is combined with spatial gridding analysis, a collaborative pollution risk index and a risk zoning result are constructed, technical conversion from pollution evolution modeling to spatial risk assessment and early warning output is realized, and reliable technical support is provided for dynamic early warning, graded prevention and control and environment management decision of heavy metal pollution in the karst region.

The invention relates to the technical field of environment management, in particular to an intelligent aquatic plant community optimization system which comprises a community recognition module, an adaptive screening module, a spacing adjustment module, a growth monitoring module and a response regulation and control module. According to the invention, through dynamic monitoring of plant growth states and optimization treatment of spatial configuration, accurate management of aquatic plant communities is realized, the matching degree of plant species and environmental conditions is enhanced, spacing and density configuration of plant planting are improved, resource competition among plants is effectively dealt with, and the yield of aquatic plants is improved. Through multi-dimensional plant growth state feedback and nutrition state monitoring, the plant configuration is adjusted in real time, so that the dynamic management of the community is more flexible, the singleness of the community structure is avoided, and effective intervention is performed aiming at the water eutrophication problem. The adaptability and growth quality of the plants are improved, overgrowth or decline of the plants in an unsuitable environment is avoided, and ecological restoration and water health are promoted.

The invention discloses a deep learning model multi-NPU end-side one-button deployment system and method.The system comprises a front-end interaction module, a service-side control module, an end-side execution module and a result integration module.The method comprises the steps that front-end configuration is carried out on a user side, the front-end configuration is received on a service side, a unified version container environment is called to execute model conversion, and a unified version container environment is called to execute model conversion; pushing to the end side; receiving a file pushed by the service side at the end side, starting a reasoning script, and obtaining a reasoning result and NPU performance data; and receiving a side deployment report at a user side, and feeding back the report to the user through a front-end interface. By integrating the front-end interaction module, the service-side control module, the container environment management unit, the end-side execution module and the result integration module, automatic model deployment on various NPU devices is realized. One-stop automatic deployment is realized, from front-end configuration to end-side execution, the whole process of result analysis does not need manual intervention, and the efficiency is greatly improved.

The invention relates to the technical field of green building environment monitoring, and discloses a green building environment monitoring system and method and a storage medium. The method comprises the steps that environmental parameters such as thermodynamic parameters, humidity parameters and gas concentration parameters are continuously collected through intelligent sensing nodes at multiple positions in a green building; the environment parameters are transmitted to a central processing unit, and the central processing unit combines a pre-stored environment standard value and a real-time data stream and generates an environment control command by adopting a self-adaptive learning algorithm; the environment execution device carries out an environment regulation activity according to the command; and monitoring and adjusting an activity execution sequence in real time, calculating a performance evaluation index, generating a normal or abnormal performance state signal, and automatically triggering an alarm process when the performance state signal is abnormal. According to the method, a complete environment management and control closed loop is constructed, all-directional dynamic monitoring and accurate adjustment of the environment of the green building are achieved, the core requirements for environment protection and comfort of the green building are met, and it is guaranteed that the internal environment of the building is in a proper state.

The invention relates to the technical field of software testing, in particular to an AI-based low-code intelligent test generation system which comprises a demand analysis module, a test path generation module, a test script conversion module, an execution environment management module and a result analysis module. A test path of the test path generation module is supplied to the test script conversion module and the result analysis module, a test script generated by the test script conversion module is sent to the execution environment management module, and an execution result of the execution environment management module is fed back to the result analysis module; and an optimization suggestion generated by the result analysis module is sent to the test path generation module and the test script conversion module. Through cooperation of multiple modules, full-process automation of low-code testing is achieved, testing paths and scripts are dynamically optimized, testing efficiency and coverage pertinence are improved, manual intervention and the error rate are reduced, and dynamic adaptation and execution stability of a testing scheme are ensured.

The invention discloses an agricultural whole industrial chain operation management system comprising an operation management platform which is supervised and managed by a Chinese agricultural and agricultural service agricultural socialization service and reports to the same. The system further comprises a planting module used for forming a planting combined platform, a breeding module used for forming a breeding combined platform, a service module used for forming a service combined platform and a treatment module used for forming an environment treatment platform, and the planting module, the breeding module, the service module and the treatment module all adopt a multi-enterprise combined cycle system. The beneficial effects of the invention are that an agricultural whole industry chain operation mode is created through the management system, and production management can be carried out on all levels of agricultural industries, so that all links involved in the agricultural production process are managed and operated as a whole, four-level logistics transportation is established, agricultural products can be scheduled and operated according to purchase demands, and the management efficiency is improved. Therefore, the food safety problem is solved, a socialized service employment platform is constructed, and the social employment problem can be solved.

To provide a highly versatile movement management system and movement management method that can flexibly adapt to an environment change in a range where a mobile body moves.SOLUTION: A movement environment management device (70) includes: a storage unit (74) that stores environment marker data (74b) in which identification information of a marker (40) provided in a movement range of a mobile body (10), which operates autonomously, and control required in accordance with surrounding environment of the marker are associated with each other; and a control unit (71) that receives the identification information of the marker from the mobile body, specifies corresponding control with reference to the environment marker data, and transmits information related to the control specified for the mobile body.SELECTED DRAWING: Figure 1

The invention provides an enterprise environment influence assessment method, device and equipment and a computer storage medium, and relates to the technical field of environment assessment, and the method comprises the steps: collecting environment index original data with a timestamp, and constructing a multi-source environment data set in combination with enterprise resource consumption data and emission factor data; carrying out credibility evaluation and weighted fusion on the data set, inputting the fused data into a pre-training evaluation model, and outputting a comprehensive environmental impact evaluation value; the contribution degree of each input feature is analyzed and calculated through model attribution, key factors are identified based on metadata, and a customized improvement measure list of priority ranking is generated in combination with a measure knowledge base and a multi-objective optimization algorithm; the invention further provides a matched portable detection device, electronic equipment and a storage medium, dynamic quantification, accurate attribution and closed-loop optimization of enterprise environment influences are achieved, and the method is suitable for intelligent environment management of high-emission industrial enterprises.

The invention discloses an intelligent management system for a geological specimen storehouse, and relates to the field of storehouse environment management, and the system comprises a filing module which is used for collecting the type, number, storage position and adaptive environment parameter information of geological specimens, and building a specimen-environment-position association database; the comparison module is used for collecting temperature and humidity, gas components and illumination intensity in the storehouse in real time, and performing targeted comparison with specimen adaptive environment parameters; according to the invention, geological specimen related information and storehouse environment parameters are collected, multi-dimensional association is established, storage environment suitability is judged in real time through targeted comparison, key information is pushed in time through graded early warning, a regulation and control assembly is linked to directionally correct unmatched parameters, and an inspection path is intelligently planned and high-risk specimens are preferentially covered. Stable adaptation of a specimen storage environment is guaranteed, weathering damage is reduced, the storage life is prolonged, blindness of manual inspection and regulation is reduced, and management efficiency and accuracy are improved.

The invention relates to a global land comprehensive improvement monitoring method based on artificial intelligence and remote sensing images, and belongs to the technical field of environment management. According to the method, multi-band high-resolution remote sensing images of a target area in two time phases before and after improvement are obtained for radiation and atmospheric correction to ensure data quality, and land coverage classification maps of the two time phases are generated respectively by using a pre-trained deep convolutional neural network land coverage classification model. Through pixel-level change detection and confidence analysis, a reliable land coverage change area is identified, vectorization and spatial filtering are carried out, multi-dimensional change features are extracted, ecological influence and a spatial distribution mode of the multi-dimensional change features are comprehensively evaluated, and a comprehensive monitoring result including a spatial distribution diagram, a statistical report and trend prediction is generated. And the information is integrated to an interactive geographic information system platform for visual display and early warning. According to the invention, automatic, precise and systematic monitoring and evaluation of the global land comprehensive remediation process are realized.

A method for managing virtual desktop management placement comprises obtaining, by a virtual desktop management placement service, a request for assigning a virtual desktop management service to one of a plurality of management environments based on an end-user experience (EUE), in response to the request: sending an EUE form to an administrator of a front-end environment, obtaining a response to the EUE form, wherein the response comprises EUE requirements, performing a management environment analysis on the plurality of management environments based on the response to assign a management environment to implement the virtual desktop management service, and initiating a deployment of the virtual desktop management service on the management environment based on the management environment analysis.

The invention is suitable for the technical field of environment management, and provides a rural environment data block chain evidence storage method based on multi-source verification, and the method comprises the following steps: determining an unmanned plane inspection plan and a grid member inspection plan based on historical evidence storage data; monitoring station data are received and analyzed in real time, and when the monitoring station is abnormal, an abnormality detection order sending announcement is sent, so that grid members or villagers can carry out detection; receiving unmanned aerial vehicle inspection data, grid member inspection data and villager uploading data, wherein each source data is marked with an environment project, acquisition time and place; performing cross validation on the monitoring station data of each time window based on the unmanned aerial vehicle inspection data, the grid member inspection data and the villager uploading data, and determining the data credibility; and determining block evidence storage data according to the data credibility and the corresponding multi-source environment data, and performing uplink evidence storage on the block evidence storage data. According to the invention, multi-source cross validation is carried out, and the accuracy and reliability of environmental data are improved.

The utility model discloses a portable water quality sampler, which relates to the technical field of environment management and comprises a moving mechanism, and a sampling mechanism is arranged on the top surface of the moving mechanism. The rotating handle is rotated to drive the double-end lead screw to rotate, the double-end lead screw rotates to drive the two moving blocks to move on the sliding rod and get away from each other, when the moving blocks move, the lifting plate is driven by the connecting rod to slide downwards on the surface of the fixing column, and when the lifting plate descends, the idler wheels are driven to descend. Rollers extend out of the base box through roller holes to lift and support the base box, a pull ring is pulled according to the height of a user to adjust the length of a telescopic rod, and after the telescopic rod is adjusted to the proper length, a limiting nut is rotated to fix the length of the telescopic rod; the pull ring is pulled to drive the rollers to rotate through the telescopic rod, the rotating buckle and the base box to move the base box to a sampling position, and the base box is connected with the sampling device to drive the sampling device to move to a working position.