153results about How to "Easy to grasp" patented technology

The invention discloses an intelligent nursing management system and method for a critical patient, and relates to the technical field of medical health monitoring, and the method comprises the steps: setting a multi-physiological signal collection channel, synchronously collecting multi-dimensional physiological signals of the patient, carrying out the preprocessing of the collected signals, and forming a standardized multi-modal physiological data flow; the preprocessed multi-modal physiological data are input into a deep learning model based on LSTM and a multi-head attention mechanism, intelligent fusion analysis of different physiological signals is achieved in combination with a dynamic weight adaptive algorithm, and a patient individualized physiological system coupling model is established; and based on an analysis result of the deep learning model, calculating an illness state risk assessment value of the patient in real time, and outputting a specific early warning level according to a set multi-level early warning threshold. According to the invention, the multi-stage and multi-dimensional early warning threshold system is constructed, so that the condition of the patient can be monitored and early warned in all directions. The monitoring quality of critically ill patients can be remarkably improved, and the missed judgment rate and the misjudgment rate are reduced.

The invention provides a method for creating a structured document based on a deep learning model, and relates to the technical field of data processing, and the method comprises the steps: obtaining basic text information collected by a user, obtaining text data, fragmenting the text data, obtaining text fragmented data, and creating a structured document according to the text fragmented data. Analyzing the structures of the sentences in the paragraphs, determining keywords in the sentences, analyzing the logical relationship between the sentences in the paragraphs, associating the sentence keywords in the paragraphs, analyzing the association degree between the paragraphs in the chapters, identifying core keywords of the chapters, obtaining a chapter keyword data set, and analyzing the field involved in the text. The method comprises the steps of extracting field information of a text to obtain a text keyword data set, constructing a structured document model based on a graph neural network model, and inputting the text keyword data set and text data into the structured document model to obtain a structured document. According to the method, the structured document can be constructed through the deep learning model.

The invention relates to a radio frequency module electromagnetic compatibility analysis method and system, and the method comprises the steps: obtaining the structure data and electromagnetic parameter information of a radio frequency module, carrying out the electromagnetic simulation of the structure data based on the electromagnetic parameter information, and obtaining the corresponding simulation data of the radio frequency module; acquiring near-field scanning data of the radio frequency module, and performing correlation calculation on the near-field scanning data and the radio frequency module simulation data through a preset fully implicit frequency domain finite volume numerical algorithm to obtain corresponding far-field electromagnetic distribution characteristic data; obtaining interference emission data of the radio frequency module, and performing zero eigenvalue entropy correction to obtain corresponding interference propagation feature data; performing optimization analysis on the far-field electromagnetic distribution characteristic data and the interference propagation characteristic data to obtain corresponding initial optimization information; and performing scheme analysis on the initial optimization information and an EMC performance evaluation result to obtain a corresponding EMC optimization scheme. According to the invention, the electromagnetic characteristics of the radio frequency module can be evaluated more comprehensively, so that the accuracy of electromagnetic compatibility analysis is improved.

The invention discloses a manufacturing industry supply chain optimization method, system and equipment based on a large model, and a medium, belongs to the technical field of large model and supply chain management, and aims to solve the technical problem of how to monitor, predict and optimize a supply chain in real time, improve the efficiency of the supply chain and improve the efficiency of the supply chain. According to the technical scheme, the method comprises the following steps: data acquisition and preprocessing: comprehensively acquiring manufacturing industry supply chain data, and carrying out cleaning, duplicate removal, missing value processing, abnormal value detection and data normalization processing on the acquired manufacturing industry supply chain data to obtain preprocessed manufacturing industry supply chain data; building a large supply chain model: building the large supply chain model by utilizing the preprocessed manufacturing industry supply chain data, and training, optimizing and deploying the supply chain model; real-time monitoring and prediction: monitoring the inventory level and each index of the generation progress in the manufacturing industry supply chain in real time through the trained large model; optimizing the decision; and updating and iterating the model.

The invention discloses an enterprise micro-marketing auxiliary method and system based on a large language model. The efficiency and effect of marketing are improved by using the large language model. According to the method, by integrating a vector database, an embedded model and a context learning technology, the capabilities of real-time understanding of user intentions, personalized reply and quick service change adaptation are realized. The method has the core advantages of accurate user demand analysis, personalized service provision and efficient knowledge retrieval system. By analyzing user behaviors and dialogue records, product recommendation and marketing strategies according with user preferences can be provided. In addition, the method also has a real-time verbal skill updating capability, so that the timeliness and accuracy of information are ensured; the automatic order information extraction technology improves the information processing efficiency, and reduces the time and cost of manual operation. According to the invention, the marketing efficiency is improved, the interactive experience between the user and the customer service is enhanced, and competitive advantages are provided for enterprises in the market with intense competition.

The invention relates to the technical field of big data, in particular to a real-time commodity sales prediction system and method based on edge calculation. The system comprises a data acquisition module, an edge calculation module, a commodity sales prediction module, an optimization feedback module and an intelligent scheduling module. The system collects sales, inventory, customer behaviors and environment data in real time through the Internet of Things, and utilizes a graph embedding technology to construct a dynamic relation graph and enhance features. Modeling is carried out based on a space-time diagram network algorithm, and accurate prediction of commodity sales volume is realized. Model parameters are optimized through reinforcement learning, inventory replenishment, a distribution path, a production schedule and a promotion strategy are dynamically adjusted in combination with a discrete differential evolution algorithm, and a real-time resource scheduling scheme is generated. According to the invention, the accuracy and real-time performance of commodity sales volume prediction are improved, optimal configuration of resources is realized through intelligent scheduling, and the operation efficiency and market competitiveness of enterprises are effectively improved.

The invention provides a wind power plant ultra-short-term power prediction optimization method based on a laser radar, and the method employs the laser radar to scan a wind power plant region, and obtains the wind speed and direction data based on a coherent Doppler wind measurement principle. The wind speed extrapolation prediction is carried out by adopting an algorithm combining EMD and ARCH, the EMD is firstly used for decomposing a wind speed time sequence, then an ARCH model is established for each intrinsic mode function, and finally the ultra-short-term wind speed is obtained by combining prediction results. Then, an algorithm combining SVR and GA is used for power preliminary prediction, the SVR establishes a nonlinear relation between input parameters and power output, and the GA optimizes SVR parameters; then, the preliminary prediction result is processed and corrected based on an FNN algorithm, and the laser radar prediction wind speed and the preliminary power prediction value are input into a fuzzy neural network, so that the prediction accuracy is improved. And performing precision evaluation on the correction result according to specification requirements, and if the result does not reach the standard, adjusting parameters or improving the method. And when the precision reaches the standard, outputting a wind power forecast time sequence power value in the future 3-5 hours.

The invention relates to the technical field of natural language processing, in particular to an enterprise transformation diagnosis report generation method based on a large model. Collecting corpus data by using an enterprise diagnosis questionnaire; constructing a digital transformation diagnosis knowledge base, and storing the knowledge base into a vector database; training a sample model, and constructing a diagnosis report template through fine tuning of Prompt cue words; and taking the fine-tuned cue word as input, automatically generating a diagnosis report by utilizing the trained large model, selecting different file formats by utilizing an agent, generating a diagnosis report and outputting the diagnosis report. Through questionnaires and industry characteristic analysis, diagnosis suggestions are intelligently generated, enterprise transformation pain points are identified, and the efficiency and accuracy of enterprise transformation diagnosis are improved.

The invention discloses an endoscope state detection system and method. The endoscope state detection system comprises a first form detection unit used for detecting the bending form of a bending part, a second form detection unit used for detecting the form of a flexible part of the endoscope, and a detection unit used for performing form integration and alignment on a first form and a second form to obtain shape data of an insertion part, the integration unit is used for acquiring the shape data of the bent part and the flexible part and identifying the overall shape of the insertion part inserted into the lumen by using the shape data, the overall shape of the insertion part is acquired by respectively acquiring the postures of the bent part and the flexible part and performing segmented reconstruction, and a display picture is generated according to the shape data synthesized by the integration unit. According to the scheme, an extra shape obtaining related sensor does not need to be placed at the bending part of the endoscope, the overall shape of the whole endoscope insertion part is provided for a doctor while the diameter of the end part of the endoscope head is not increased to influence the bending performance and the instrument channel size, the operability of the endoscope is improved, and the burden of the doctor and a patient is reduced.

The middle tire surface glue brushing device for basketball processing comprises a base, a mounting support, an electric sliding rail, a sliding block, a clamping device and a glue solution box, the mounting support is fixedly connected to the top of the base, the electric sliding rail is fixedly connected to the top of the mounting support, the sliding block is in transmission connection to the surface of the electric sliding rail, and the clamping device is arranged on the surface of the electric sliding rail. The clamping device is fixedly connected to the bottom of the sliding block, the glue solution box is fixedly connected to the front side of the top of the base, a rotating motor is fixedly connected to the rear side of the top of the base, and a rotating disc is fixedly connected to the output end of the rotating motor. By arranging the heating rod, the rotating disc can drive the heating rod to rotate and heat the surface of a basketball middle tire, and the problem that a drying structure is not arranged in the using process, so that a dry glue solution on the surface of the basketball middle tire still has certain flowability and flows downwards is solved; therefore, the uniformity of the glue solution on the surface of the basketball middle tire is influenced, and certain limitation exists.

The invention relates to the field of electrophysiological catheters, in particular to a mapping and ablation system capable of detecting injury depth, which is characterized in that a tail end functional area is arranged at the far end of a catheter, and an electrode, a positioning sensor and an optical probe are arranged in the tail end functional area; the electrode is used for mapping and ablation; the positioning sensor comprises a coil structure; the optical probe is used for performing optical scanning on the contacted tissue. The ablation unit is communicated with the electrode and provides ablation energy for the electrode; the positioning unit is communicated with the catheter and is used for displaying the position and form of the tail end functional area and recognizing the deviation and rotation direction of the tail end functional area; the electrophysiology mapping unit is communicated with the electrode and acquires an electrophysiology signal through the electrode; the optical detection unit is connected with the optical probe through an optical fiber and used for optical coherence tomography; the impedance detection unit is communicated with the electrodes, impedance information of surrounding tissue under different frequencies is collected through the electrodes, and then the frequency response coefficient of the position where each electrode is located is solved and used for recognizing whether the electrodes make contact with the tissue or not.

The utility model discloses equipment for screening building materials in the technical field of building materials, which comprises a screening box, a screen mesh, a feed port, a first discharge port, a second discharge port, a supporting seat, a scraper mechanism and a vibrating mechanism, the feed port is arranged at the top of the screening box, the first discharge port is arranged on the side wall of the screening box, and the second discharge port is arranged on the side wall of the screening box. The second discharging port is formed in the bottom wall of the screening box, a cavity is formed in the screening box, the screen is arranged in the cavity, the feeding port, the first discharging port and the second discharging port are communicated through the cavity, the scraper mechanism comprises a scraper, a push rod and a power mechanism, and the power mechanism drives the scraper to move back and forth on the upper surface of the screen towards the first discharging port. Supporting legs are arranged at the bottom of the supporting seat, a cavity structure sleeved with the supporting legs is arranged at the top of the vibration mechanism body, the vibration mechanism is arranged at the bottom of the supporting seat, and a convex block of the vibration mechanism rotates to drive the screening box to vibrate up and down. The technical problems that a screen of an existing device is prone to being blocked, and the screening efficiency is low are solved.

The invention relates to the technical field of internet application, and particularly discloses a page update data processing method, system and equipment based on RN and H5, the method comprises the steps that page update data is acquired, and the page update data comprises page historical access data and page loading data; processing the page historical access data to obtain an access frequency index of each page, processing the page loading data to obtain a data generation complexity index of each page, and performing comprehensive analysis to obtain a cache demand evaluation value of each page; and performing caching processing on each content module of each to-be-cached page according to the content updating period of each content module of each to-be-cached page. By evaluating the page cache demand evaluation value, the overall response speed of the system can be increased, the response time of data access can be shortened, cache resources can be reasonably distributed according to actual demands, resource waste is avoided, the competitiveness of the page can be improved, and sustainable development can be achieved.

The invention relates to the technical field of flat wire stator head twisting equipment control, and discloses a process calculation method and system of flat wire stator head twisting equipment and the head twisting equipment, and the method comprises the steps: obtaining a plurality of setting parameters of a head twisting process input by a user; calculating according to the plurality of setting parameters to obtain an operation result; inputting an operation result into a point set formula of each layer of the torsion head module to obtain a data set, wherein the point set formula comprises a parameter equation and a compensation equation of spatial displacement; and writing the data set into a control file of a preset path, and performing a head turning process on the flat copper wire after the flaring process based on the control file. According to the invention, the motion trail of the equipment is approximate to the motion trail of the copper wire bending point, the copper wire is prevented from being scratched due to large relative displacement between the head twisting die and the copper wire bending point, the process trail of the product equipment and the model changing calculation can be quickly carried out, the device can adapt to the production of flat wire products with different specifications, the production efficiency is improved, and the production cost is reduced. The processing time is reduced.

The utility model discloses a fire-fighting construction pipeline rapid installation platform which comprises a bottom vehicle body, the top of the bottom vehicle body is movably connected with a shear shank, a first electric cylinder is obliquely installed in the shear shank, the top of the shear shank is movably connected with an installation bearing table, and a pipeline lifting mechanism is arranged at the bottom of a pipe supporting plate. According to the rapid installation platform for the fire-fighting construction pipeline, by arranging a second electric cylinder, a guide pipe, an extension rod, a stress plate and a pipe supporting plate, when the rapid installation platform is used, the to-be-installed pipeline is horizontally placed on the pipe supporting plate and limited through a clamping plate, along with the installation bearing table in place, when the pipeline is installed, the second electric cylinder extends upwards, and the stress plate pushes the pipe supporting plate to rise slowly; the pipe supporting plate is used for supporting the pipeline to be high, a worker can conveniently conduct operations such as connection and fixation, the guiding pipe and the extending rod are matched with each other, the pipe supporting plate can be stably lifted, the function of automatically lifting the pipeline is achieved, and the problem that the device does not have the function of automatically lifting the pipeline is solved.

The invention provides a virtual reality urban environment design system based on an AR technology, and relates to the technical field of urban planning design, and the system comprises a data collection module, a modeling module, a rendering module, an interaction module, a display module, a physical simulation module and a real-time updating module. The system provides a visual and immersive design environment for city planners. Through high-precision data acquisition and vivid modeling rendering, a plan can clearly observe details and overall layout of a city. And the real-time updating module ensures that the planner obtains the latest city change information and adjusts the planning scheme in time. The optimization module ensures smooth operation of the system and improves the working efficiency. The physical simulation module can predict the effects of different planning schemes under the influence of various natural and human factors, so that the schemes are optimized, the scientificity and feasibility of urban planning are improved, and planning errors and resource waste are reduced.

The invention discloses a garden landscape simulation method based on a virtual reality technology and three-dimensional visualization, and the method comprises the steps: obtaining the three-dimensional point cloud data of a garden terrain, and generating a three-dimensional grid model; calculating a gradient value of each block grid of the three-dimensional grid model, generating a gradient matrix of the three-dimensional grid model, and clustering the block grids belonging to the same gradient value interval into similar sub-blocks; sorting from small to large based on the terrain slope intervals corresponding to the subblocks of the same type, selecting adaptive plant species according to the illumination conditions of the sorted terrains, and predicting the photosynthetic rate values of the plant species based on a photosynthetic rate prediction model; calculating the number of plants planted in the terrain according to the area of the terrain corresponding to each sub-block and the photosynthetic rate value of the plants in the terrain; and carrying out simulation planting on the three-dimensional grid model, and carrying out garden landscape virtual reality display on the three-dimensional grid model based on a virtual reality technology. According to the method, targeted design can be carried out on different slope areas of the garden landscape.

The invention discloses an automatic labeling method combined with multi-source log data. The method comprises the following steps: 1) preprocessing an application and a tool: generating a corresponding application program log by using related information in a target application program; meanwhile, modifying an attack plan and an attack tool of an attacker; 2) attack execution: executing the attack by using the preprocessed attack tool and the designed attacked application program, and generating an attack log at the same time; 3) data marking: constructing a provenance graph by using an audit log; positioning attack injection points of different types of logs; all system calls in the thread are divided into different processing programs, processing program IDs are recorded, and a tree structure of a processing program derivation relation is constructed; and 4) marking malicious sub-graphs. According to the method, the auditing log, the traffic log and the application program log are integrated, so that the full view of the network attack can be captured from different dimensions, and the accuracy of attack behavior recognition is improved.

The invention provides a network computing power energy sensing network, a resource measurement method, a resource measurement device and a program product. The method comprises the following steps: determining a current available resource corresponding to an infrastructure through a resource sensing unit; before the calculation task is executed, resources needed for executing the calculation task are measured through a measurement device based on the task type, the task scene and the task load corresponding to the calculation task, target resources are obtained, and resource configuration is carried out according to the target resources and resources corresponding to the infrastructure; in the execution process of the calculation task, generating predicted available resources corresponding to the infrastructure in the target period through a measurement device based on the current time feature and the task feature corresponding to the calculation task; performing resource configuration according to the predicted available resource, the current available resource and the target resource; the problem that a single resource measurement index is difficult to meet the requirements of task types and task scene complexity can be solved; and the requirements of task type and task scene complication can be comprehensively and accurately met.

The invention relates to the technical field of data processing, and discloses a BIM-based intelligent weekly progress visual display system and method, and the system comprises a weekly report management module which is used for uploading and storing weekly report progress data of a target project; the model management module is used for uploading and storing the building information model of the target project; the model association module is used for associating the weekly report progress data with the building information model; the coloring module is used for setting colors of different components in the building information model according to the construction progress in the weekly report progress data to obtain a construction progress three-dimensional model; and the display window module is used for displaying the building information model and the construction progress three-dimensional model. According to the method, the weekly report progress data and the building information model are automatically associated and dynamically updated in real time, the weekly progress of the target project is visualized, fine management of the project construction progress is assisted, the project management level is improved, predictable management and control correction is achieved, and it is guaranteed that the project construction period is achieved as much as possible.

The invention relates to the field of tomato planting decision making, in particular to a tomato planting decision making method based on a double-branch network and a computer device. The scheme comprises the following steps: acquiring and fusing multi-modal data; enhancing the fusion data through a self-attention generative adversarial network; feature extraction is carried out through a Transform-CNN (Convolutional Neural Network) dual-branch network; and reinforcement learning and decision making are carried out through DDPG. When the method is used for processing a complex structure and texture image, the self-attention layer can better grasp an image region relation, more accurate natural data are generated, a self-attention mechanism is fully utilized to capture global semantic information and a long-distance dependency relation, a CNN is utilized to extract local features and spatial information, effective fusion and feature extraction of multi-modal data are realized, and the method has the advantages of being high in robustness and high in robustness. And then a DDPG algorithm is used to solve a continuous action space problem, a deterministic strategy and an experience playback mechanism are combined, the accuracy of tomato planting decision making is greatly improved, and the tomato planting decision making method is suitable for tomato planting decision making.

The utility model provides an infant touch sense training device which comprises a training device body which is in a cartoon animal shape. The body of the trainer main body is made of a sponge body material; the head part of the trainer main body is made of a hard material, the head part is provided with tentacles, and the end parts of the tentacles are plush balls; the eyes on the head of the trainer body are hollow bodies made of hard materials, and movable particles capable of shaking are placed in the hollow bodies. Tactile salient points are arranged on the front side surface of the neck of the training main body, and tactile brushes are arranged on the rear side surface; the colors of the legs of the training body are different, and each leg is detachably connected with the body. The training device is convenient for carrying out various sense and perception training on infants, such as touch, hearing and vision, so that the physical and psychological healthy growth of the infants is promoted.

The invention discloses a connection method suitable for green electricity transaction and an electric energy market, and relates to the technical field of green electricity transaction, and the method specifically comprises the steps: 1, determining a green electricity transaction point, and carrying out the real-time monitoring of green electricity and electric energy transaction data in the green electricity transaction point; step 2, determining a supply-demand relationship balance index of the electric energy market, determining an electric energy basic price and an electric energy price error interval based on the supply-demand relationship balance index of the electric energy market, and determining a theoretical electric energy price formula by integrating the electric energy basic price and the supply-demand relationship balance index of the electric energy market; step 2, determining a supply-demand relationship balance index of green electricity transaction, and determining a unit green electricity average transaction price formula by adding a green electricity added value based on an electric energy basic price and a theoretical electric energy price formula, and step 4, constructing a green electricity transaction platform of a green electricity transaction point, and providing a transaction service for a green electricity power supplier and an electricity purchaser.

The invention relates to the field of electrophysiology catheters, in particular to a mapping and ablation catheter capable of detecting injury depth, which comprises a head end, and at least one electrode for mapping and ablation is arranged on the head end; the positioning sensor assembly comprises at least two positioning sensors, each positioning sensor comprises a coil structure, the at least two coil structures are arranged at a certain included angle, and the positioning sensor assembly is used for displaying the position and form of the head end and recognizing the deviation and rotation direction of the head end; the pressure sensing assembly comprises strain gauges and an elastic body, the strain gauges are arranged on the periphery of the elastic body, and the pressure sensing assembly is used for detecting the pressure magnitude and direction of the head end; the at least one optical probe is used for performing optical scanning on the contacted tissue, and the optical probe, the positioning sensor assembly and the electrode have a fixed position relationship. Through the mutual cooperation of the optical probe, the positioning sensor assembly and the pressure sensing assembly, the detection result is more accurate, the detection depth is deeper, the range is larger, and the use is more convenient.

The invention relates to a power load prediction method and device based on causal characteristics and a medium, and the method comprises the steps: obtaining actual power load influence factor data, inputting the actual power load influence factor data into a trained power load prediction model, and outputting an actual power load prediction result; wherein the training process of the power load prediction model comprises the following steps: S1, acquiring historical power load data, and S2, preprocessing the historical power load data; s3, calculating a normalized causal entropy; and S4, constructing a causal analysis neural network, multiplying the cause sequence by the corresponding causal intensity in the causal analysis neural network, and optimizing the causal analysis neural network based on a loss function to obtain a power load prediction model. Compared with the prior art, the method has the advantages of improving the interpretability and accuracy of a load prediction result and the like.

The invention discloses an investment optimization system based on artificial intelligence investment research, and relates to the technical field of financial investment, and the system comprises the following components: a data collection module which is responsible for collecting data related to an investment portfolio, including historical transaction data, market trend data and company financial data, and carrying out the preprocessing and storage, the risk analysis module is used for analyzing the collected data, evaluating the risk level of the investment portfolio and constructing a risk measurement prediction model, and the module can identify potential risk factors such as market fluctuation and industry risks and give corresponding risk scores and probability distribution, so that the risk level of the investment portfolio is evaluated; according to the invention, rapid processing and accurate analysis of mass financial data are realized through an unsupervised learning algorithm of the data collection module, related information is efficiently captured and integrated from a plurality of data sources, the efficiency and accuracy of investment decision making are greatly improved, investors can better grasp market opportunities, the investment risk is reduced, and the economic benefit is improved. And higher investment return is realized.

The present invention provides a battery SOC evaluation method, system, storage medium and electronic device. The method comprises: obtaining a battery charge and discharge data set, supplementing missing values ​​and performing sliding window processing on the charge and discharge data set to obtain a training feature target set; embedding and position encoding the training feature target set to obtain an embedding tensor; calculating the embedding tensor to obtain a spliced ​​tensor; mapping the spliced ​​tensor to obtain a first output tensor set, performing global flat pooling layer and shaping layer processing on the first output tensor set to obtain a shape output set that can be processed by an LSTM network; inputting the shape output set to an LSTM network to perform data update on a time series to obtain a second output tensor set; inputting the second output tensor set to a linear regression fully connected layer to perform linear regression prediction to obtain a predicted value of the battery SOC. The present invention can evaluate the SOC parameters of the battery.

The invention discloses a garden landscape simulation method based on virtual reality technology and three-dimensional visualization, which obtains three-dimensional point cloud data of garden terrain and generates a three-dimensional grid model; calculates the slope value of each block grid of the three-dimensional grid model, generates a slope matrix of the three-dimensional grid model, clusters the block grids belonging to the same slope value interval into similar sub-blocks; sorts the terrain slope interval corresponding to each similar sub-block from small to large, selects the adapted plant species according to the illumination condition of the sorted terrain, and predicts the photosynthetic rate value of the plant species based on the photosynthetic rate prediction model; calculates the number of plants planted in the terrain according to the area of ​​the terrain corresponding to each sub-block and the photosynthetic rate value of the plant in the terrain; simulates planting on the three-dimensional grid model, and performs garden landscape virtual reality display on the three-dimensional grid model based on virtual reality technology. The invention can carry out targeted design of different slope areas of garden landscape.

A laboratory mouse subcutaneous injection fixing device comprises a workbench, a fixed housing, a positioning support rod, a movable plate, a positioning lock sleeve, a threaded support rod and a fastening retaining ring, an injection opening is formed in the upper portion of the fixed housing, a bearing plate is arranged on the lower portion of the fixed housing, a plurality of supporting legs are connected to the lower portion of the bearing plate, the supporting legs are connected with balancing weights, and a limiting baffle is arranged on the upper portion of the bearing plate. The limiting baffle is connected with the workbench, the lower portion of the workbench is connected with the bearing plate, the bearing plate is provided with sliding blocks, the two sides of the workbench are provided with sliding ways, the sliding blocks are matched with the sliding ways, the sliding blocks are connected with the sliding ways, the sliding blocks slide on the sliding ways, the sliding ways are provided with sliding grooves, the sliding grooves are matched with the rollers, the rollers are connected with the sliding grooves, and the rollers slide on the sliding grooves and are connected with the sliding blocks through shaft rods. The shaft rod is sequentially connected with the sliding block and the roller.

The invention discloses a citrus orchard image data acquisition and annotation method, which relates to the technical field of image acquisition, and further comprises a factor analysis module, a default module, an image data standardization module, an image database module, an abnormal image analysis module, an abnormal root analysis module and a correction module. The system has the advantages that the quality of the acquired citrus orchard image can be obviously improved through the default module, the state and details of the fruit tree can be observed more clearly, the weather state information at the current acquisition time can be acquired by using the image data standardization module, the data is adjusted according to the image definition, and parameter adjustment data is generated, so that the accuracy of the system is improved. The reliability and the stability of image acquisition are improved, excessive influence of external factors such as weather change is avoided, the reason of the abnormal condition of the fruit tree can be analyzed according to the abnormal condition information of the fruit tree by utilizing the abnormal root analysis module, and the efficiency and the effect of problem solving are improved.