427results about How to "Avoid deficiencies" patented technology

The invention relates to the technical field of big data storage, in particular to a storage control method and device based on big data. The method comprises the following steps: acquiring an original data stream and application demand information; performing data dynamic correlation analysis on the original data flow according to the application demand information to obtain a dynamic update data correlation graph; performing feature vector generation on the dynamic update data association graph to obtain a data feature vector; performing intelligent quality evaluation on the data feature vector to obtain a data quality label; performing timeliness evaluation according to the data feature vector, and performing access popularity evaluation to obtain a timeliness score and an access popularity score; and acquiring system resource load condition information. The storage resource utilization rate, the data access performance and the overall efficiency of the system are improved by solving the limitation of a traditional method in the aspects of static data management and resource allocation.

The invention discloses a crop sowing parameter control optimization method applied to multi-target precise fertilization, and relates to the technical field of agricultural crop sowing, and the method comprises the following steps: collecting a soil sample, carrying out spectrum scanning and analysis, combining with known soil nutrient data, building a soil nutrient content prediction model, and calculating a soil nutrient content prediction model; and combining spectral data to predict the nutrient content in the soil. According to the invention, through accurate evaluation of soil nutrient conditions and deep analysis of crop growth demands, fertilization and sowing parameters are optimized, so that crops can obtain required nutrients in the growth process, the optimized sowing depth, row spacing and plant spacing can effectively promote the development of crop roots, the absorption ability of the crops to moisture and nutrients is enhanced, and the quality of the crops is improved. And through real-time monitoring and adjustment of the intelligent fertilization equipment, the fertilization amount can be dynamically adjusted according to actual demands of crops, and the common problem of excessive or insufficient fertilizer in a traditional fertilization method is avoided.

The invention relates to the technical field of intelligent agriculture, in particular to a mulberry field monitoring method and system based on the Internet of Things. The method comprises the following steps: acquiring environment and soil data of a mulberry field through a sensor network to obtain original sensor data; performing time sequence data integration on the original sensor data to obtain an environment parameter data set; the method comprises the following steps: performing multispectral image acquisition on mulberries in a mulberry field through a multispectral camera, and performing image preprocessing to obtain preprocessed image data; estimating the chlorophyll content according to the preprocessed image data to obtain chlorophyll content data; and performing growth health parameter analysis according to the preprocessed image data and the chlorophyll content data to obtain growth health parameters. By combining the sensor technology, the multispectral imaging technology and the intelligent algorithm, comprehensive, accurate and real-time monitoring of the mulberry field is achieved, and an effective technical means is provided for fine management of the mulberry field.

The invention discloses a patient nursing strategy optimization system for nursing in the department of hepatobiliary and pancreatic, and relates to the technical field of nursing strategy optimization. The nursing strategy optimization platform is in communication connection with a patient information management module, a knowledge base module, a nursing evaluation module, a nursing strategy plan making module, a nursing implementation module, a communication and cooperation module and a nursing effect evaluation module. According to the patient nursing strategy optimization system for nursing in the department of hepatobiliary and pancreatic, data in multiple aspects of physiology, psychology, society and the like of a patient are comprehensively collected and analyzed through the integrated nursing evaluation module, and key indexes such as vital signs, pain degree, nutritional status, sleep quality and the like are monitored and evaluated in real time; in addition, a personalized nursing plan provided by the system is combined with specific requirements and illness state changes of the patient, so that the nursing service better fits the actual condition of the patient.

The invention provides a data transmission optimization method and system based on a satellite channel congestion scene, and belongs to the technical field of satellite communication, and the method comprises the steps: classifying service data, and obtaining different types of data messages; reporting the cache state report to a satellite master station; receiving uplink communication resources distributed by the satellite master station, wherein the uplink communication resources are sent after being distributed by the satellite master station based on the cache state report; determining a channel transmission state of the satellite terminal station based on the uplink communication resources and the service volume in the transmitting cache region; scheduling and sending each type of data messages according to the transmission priorities of the different types of data messages; the transmission priority is determined based on a channel transmission state. According to the invention, in a satellite channel congestion scene, key messages are scheduled preferentially by dynamically adjusting the transmission priorities of different types of data messages, so that the communication efficiency and reliability are improved under limited resources.

The invention relates to the field of carbon emission management, energy distribution and optimization regulation and control, in particular to an industrial enterprise carbon emission allocation method based on regional energy and carbon platform supervision data. The method comprises the following steps: step 1, data acquisition and preprocessing, including data acquisition, data preprocessing and data analysis; 2, initial carbon quota distribution, wherein a multi-level decision-making model is established, and the initial carbon quota of an enterprise is calculated; 3, a dynamic adjustment mechanism is provided, wherein the dynamic adjustment mechanism comprises the steps of obtaining power data feedback, calculating a quota adjustment coefficient and dynamically adjusting a quota; step 4, accumulation of double-control index data, including accumulation of the double-control index data and accumulation of carbon emission intensity data; and 5, continuously optimizing the model. According to the method, the flexibility of carbon quota distribution is improved, normal production of enterprises is ensured, meanwhile, the total carbon emission control target is not exceeded, and the overall efficiency of carbon emission management is improved by introducing a multi-level decision model and a feedback mechanism.

The invention relates to the technical field of sowing control, in particular to a precise control system and method for cooperative fertilization and sowing, and the method comprises the following steps: monitoring soil humidity distribution data of a target farmland by using a soil humidity sensor, and calculating a soil permeability coefficient based on the soil humidity distribution data in combination with a three-dimensional terrain model and a soil permeability coefficient; constructing a soil humidity gradient model by adopting a finite element analysis method; based on the soil humidity gradient model and in combination with target fertilizer characteristics, establishing a fertilizer diffusion model, simulating the diffusion range and concentration distribution of the fertilizer under the soil humidity gradient condition, and outputting the fertilizer diffusion radius and the concentration gradient distribution of the fertilizer in soil through multivariate regression analysis; and based on the fertilizer diffusion model, calculating the fertilization amount and the fertilization depth in combination with the crop demand parameters. According to the method, the soil humidity gradient model is established, and fertilizer waste and environmental pollution caused by non-uniform fertilization or excessive fertilization amount are avoided.

The invention relates to the technical field of equipment management, in particular to a medical beauty equipment cloud management system and management method. The method comprises the following steps: acquiring a medical beauty equipment number and medical beauty equipment parameters; carrying out cloud platform data uploading on the medical beauty equipment parameters based on the medical beauty equipment number, and generating medical beauty equipment monitoring data; consumable information digital registration is carried out on the medical beauty equipment monitoring data, and a beauty equipment consumable digital registry is generated; the method comprises the following steps: acquiring beauty equipment consumable data through a beauty equipment consumable digital registry to obtain beauty equipment consumable sensing data; consumable loss influence analysis is carried out on the beauty equipment consumable sensing data, and a consumable state monitoring data set is generated; and performing consumable service life prediction on the consumable state monitoring data set, thereby generating consumable service life early warning data. According to the invention, through real-time monitoring, intelligent analysis and dynamic adjustment of the cloud platform, the accuracy and comprehensiveness of cloud management of the medical beauty equipment are improved.

The invention discloses a network resource optimization method for network slices, which comprises the following steps of: acquiring historical flow data, user behavior data and network topology information of each network slice from each network node in real time by utilizing a distributed data acquisition system, and performing data preprocessing on the historical flow data, the user behavior data and the network topology information to form a feature data set; inputting the feature data set into a prediction model constructed based on an attention mechanism and a mixed density network algorithm, optimizing the network weight through a gradient descent algorithm, and training the prediction model; inputting feature data of the current moment into the trained prediction model, and outputting prediction values of probability distribution of different network slices for future traffic demands; and formulating a resource pre-allocation strategy according to the predicted probability distribution of different network slices for future traffic demands, and dynamically optimizing and adjusting network resources. According to the invention, through accurate resource pre-allocation, network resources are utilized to the maximum extent, the operation cost is reduced, and the resource utilization efficiency is improved.

The invention discloses a precise fertilization method, system and device for a rice transplanter, and relates to the technical field of rice cultivation. Comprising the following steps: dividing a to-be-fertilized field into a plurality of sub-regions, analyzing the concentrations of nitrogen, phosphorus, potassium and organic matters, and taking an average value as the nutrient content of the field; the soil compactness is analyzed, and the nutrient penetration depth index is calculated in combination with environmental parameters such as soil temperature and humidity mean values; acquiring field salinity and alkalinity data, and calculating a soil nutrient effectiveness index in combination with the environmental parameters; correcting the fertilization longitudinal spacing and the fertilization depth according to the nutrient effectiveness index and the penetration depth index to obtain an accurate value; finally, the rice precise fertilization operation is completed through a rice transplanter according to the precise fertilization depth and the longitudinal distance. According to the method, soil nutrients and environmental parameters are dynamically combined, the fertilization precision is optimized, and the fertilizer utilization efficiency is improved.

The invention discloses an advanced power control method suitable for a marine photovoltaic power generation system, and relates to the technical field of photovoltaic power control, and the method comprises the following steps: collecting multi-dimensional data in a ship navigation process, and taking the multi-dimensional data as input information; and on the basis of the collected multi-dimensional data, an ultra-short-term photovoltaic power prediction model of CNN-LSTM-AM is constructed. According to the method, the CNN-LSTM-AM ultra-short-term marine photovoltaic power prediction model is introduced, the photovoltaic power generation power in the next second can be accurately predicted, power distribution is carried out according to the photovoltaic power generation power, accurate prediction and dynamic adjustment of the photovoltaic power are achieved, and the photovoltaic power generation power can be accurately predicted and dynamically adjusted by monitoring the photovoltaic power generation power, the SOC of the storage battery and the direct-current bus voltage key parameters in real time. The system can dynamically adjust the power control strategy, ensures the stable tracking of the output current of the inverter, effectively avoids the problems of power deviation and energy accumulation or insufficiency, and remarkably improves the stability and reliability of the system.

The invention provides an intelligent vehicle type identification and dynamic regulation and control loading system, and compared with the prior art, the intelligent vehicle type identification and dynamic regulation and control loading system comprises an arrangement module, an identification module, a loading control module, a dynamic regulation and control module and a real-time monitoring platform. The arrangement module intelligently dispatches and matches vehicles according to transportation requirements; the identification module accurately identifies vehicle information through an image identification algorithm; the loading control module controls the loading device to automatically complete material loading through a PLC. The dynamic regulation and control module adjusts the loading speed according to the real-time loading state, and overload or too slow loading is avoided; and the real-time monitoring platform provides transportation task progress monitoring and abnormity alarming, so that the loading process is ensured to be carried out smoothly. According to the system, the utilization efficiency of transportation resources can be effectively improved, the transportation cost is reduced, and the automation and intelligence level of loading operation is improved. Through intelligent scheduling and dynamic regulation and control, it is ensured that the material loading process is more efficient and accurate.

The invention belongs to the technical field of mine transportation, and discloses a belt conveyor roller anomaly detection system based on optical fiber auscultation, which comprises a data acquisition unit, a preprocessing unit and a prediction model which are connected in sequence, and an anomaly detection unit and a linear layer which are connected with the prediction model. The data acquisition unit acquires audio data in the running process of the carrier roller, converts the audio data into vibration data and outputs the vibration data to the preprocessing unit, the preprocessing unit segments the input vibration data, the segmented vibration data are input into the trained prediction model, and the prediction model is used for predicting the carrier roller. And the prediction model outputs the characteristics of the potential space corresponding to the current vibration data to an anomaly detection unit, the distance between the characteristics of the current potential space and the characteristic center of the potential space when the carrier roller normally operates is calculated, and if the distance is larger than a set distance threshold value, the current operation of the corresponding section of carrier roller is abnormal. According to the method, automatic detection of the abnormity of the carrier roller is realized, the information contained in the potential spatial features output by the prediction model is richer, and the abnormity detection precision of the carrier roller is improved.

The invention belongs to the technical field of industrial internet, and particularly relates to an adaptive extension method and system for SaaS (Software as a Service) application based on the industrial internet. According to the method, intelligent resource scheduling and self-adaptive extension are realized when a SaaS application platform processes a user uploading service, the resource demand in a service period is predicted at first, the remaining resource state is monitored, and then resource scheduling is carried out on the basis of resource demand prediction, remaining completion time and resource distribution change. According to the method, resource allocation is optimized and missing resources are supplemented through distributed enhanced scheduling at the minimum total cost, and finally, resource allocation parameters are adjusted through continuous testing and evaluation, so that efficient service processing and optimal cost are ensured; through dynamic monitoring and intelligent scheduling, adaptive expansion of SaaS application resources is realized, the response speed and the resource utilization rate of the system are improved, and the operation and maintenance cost is reduced.

The invention discloses an agency bookkeeping intelligent auditing system and method based on an AI algorithm, and belongs to the technical field of agency bookkeeping intelligent auditing. The agency bookkeeping intelligent auditing system based on the AI algorithm comprises a data acquisition module, a risk assessment module, a resource allocation module and a self-adaptive adjustment module; the data acquisition module is used for collecting enterprise financial historical data, obtaining a historical trend chart of financial indexes, analyzing a historical trend of financial data and determining a financial auditing period; the risk assessment module is used for assessing the risk of the financial data, calculating a deviation index of a financial index, and performing risk grade division on the financial data according to the calculated deviation index of the financial index; the resource allocation module is used for allocating auditing resources; according to the agency bookkeeping auditing system and method, the agency bookkeeping auditing process is analyzed through the AI algorithm, and the problem that the auditing resources are distributed unevenly is solved.

The invention discloses a load demand-based cross-period dynamic hydrogen storage planning method, which relates to the technical field of energy utilization and comprises the following steps of cross-period hydrogen storage system modeling, typical day selection and feature extraction, comprehensive energy system planning model establishment, random-robust two-stage optimization method solving and objective function design. By designing the introduction and modeling of the IHS, the energy transfer function is realized, the problem that energy storage equipment in a traditional power system cannot store energy across seasons is solved, the technical challenge of unbalanced power supply and demand is overcome, the permeability of renewable energy sources is improved, wind and light abandoning phenomena are reduced, and carbon emission is reduced. And the realization of low-carbon and green energy targets is promoted.

The invention discloses a novel high-ground-temperature tunnel local ventilation cooling system, and relates to the technical field of high-ground-temperature tunnel ventilation, and the novel high-ground-temperature tunnel local ventilation cooling system comprises a temperature monitoring module, a cold air conveying starting module, a cold air output adjusting module, a regional cold air distribution module, an energy efficiency optimization module and a real-time monitoring and emergency response module; and the temperature monitoring module is used for arranging a temperature sensor network in the tunnel. The tunnel temperature is monitored in real time through the temperature sensor network and the model, cold air output is dynamically adjusted, and accurate cooling is ensured. The vortex tube array directly produces cold air by introducing high-pressure air, the cold air is conveyed to a cooling area through an air pipe, and exhausted hot air is subjected to energy recovery through a phase change heat absorption material or a hot air power generation system. The intelligent algorithm predicts the temperature trend, adjusts cold air in advance, and prevents potential safety hazards. And the real-time monitoring platform tracks the temperature and the equipment state, automatically alarms and executes emergency measures to ensure that the system operates in a safe range.

The invention discloses a coarse cereal quality evaluation method and system based on a characteristic spectrum, and relates to the technical field of coarse cereal quality evaluation.The coarse cereal quality evaluation method comprises the following steps that light of a specific wave band is emitted to the surface of quinoa through a hyperspectral imager, and spectral data reflected by the surface of the quinoa are collected; the chenopodium quinoa willd surface spectrum change is captured through the spectrum extreme value attenuation index and the spectrum width index, the spectrum characteristic change coefficient is generated in combination with the machine learning model, and accurate judgment of mildewing of different degrees is achieved. Aiming at insufficient reflection caused by an oxide layer, the light emission duration is dynamically adjusted based on a Bayesian optimization algorithm, reliable spectral information is ensured to be obtained, and the adaptability and the detection precision are improved. In a complex environment, the system can stably and accurately identify mildew, delay is avoided, and high-quality data is provided for coarse cereal quality evaluation.

The invention discloses a state awareness scheduling method based on ECRH system and EPICS integration, belongs to the technical field of control of nuclear fusion devices, and solves the problem that a traditional ECRH system is slow in scheduling response when the equipment state changes. According to the invention, through the IOC module and the Channel Access protocol of the EPICS system, the equipment state data can be collected and transmitted to the central control system in real time, so that the rapid feedback of the equipment state is ensured; by monitoring and analyzing real-time state data, the detection precision of the system on equipment abnormity is improved, and it is ensured that the system can be rapidly adjusted when the state of the equipment changes; by dynamically adjusting the priority of the control signals, resource allocation can be optimized in real time according to changes of equipment states and experiment requirements; the overall efficiency of the system is improved; by dynamically adjusting the transmission frequency of the control signal, adaptive adjustment can be performed according to the actual load condition of the equipment, and resource waste or insufficiency caused by fixed frequency scheduling is avoided.

The invention provides a preparation method of spherical iron phosphate, and relates to the technical field of lithium ion batteries, and the preparation method comprises the following steps: S1, one-step reaction: carrying out parallel flow on an iron salt solution, a phosphorus salt solution and ammonia water according to a molar ratio of 1: (0.8-1.2): (0.8-1.1) to generate amorphous iron phosphate slurry; adding ammonia water into the iron phosphate slurry to adjust the pH value to 1.5-2.5; s2, membrane washing; s3, a second-step reaction: adding pure water into the washed iron phosphate slurry, adjusting the iron concentration to 0.5-1.2 mol / L, adding a phosphoric acid solution, heating to 90-120 DEG C, and controlling the heat preservation time for 30-90 minutes after the material is converted into a white material, so as to obtain white slurry; s4, washing: taking a filter cake; s5, drying: generating iron phosphate dihydrate; s6, calcining: spherical iron phosphate is generated, and the iron phosphate is successfully converted from a traditional olive type, peanut type or honeycomb type to a spherical type through the preparation method provided by the invention.

The invention provides an elastic training method and device. The method comprises the following steps: determining an idle execution module and issuing a training task; if the number of the idle execution modules is larger than or equal to the data parallelism degree of the issued training tasks, target execution modules are determined from the idle execution modules based on the data parallelism degree of the issued training tasks, and the number of the target execution modules is integer multiples of the data parallelism degree corresponding to the issued training tasks; and executing the issued training task on the target execution module. According to the elastic training method and device provided by the invention, idle resources can be utilized to the maximum extent, the execution efficiency of the training task is improved, and the stability and accurate execution of the training task can be ensured.

The invention relates to the technical field of colorectal image analysis, in particular to a colorectal cancer diagnosis auxiliary method and system based on deep learning. The method comprises the following steps: acquiring colorectum endoscope image data, and performing region-of-interest positioning on the colorectum endoscope image data to obtain colorectum region-of-interest data; performing multi-stage image segmentation on the colorectal endoscope image data to obtain colorectal image multi-stage segmentation data; performing depth feature extraction on the first colorectal image segmentation data to obtain colorectal image depth feature data, and performing three-dimensional network construction on the second colorectal image segmentation data to obtain colorectal image three-dimensional network data; and carrying out cell relation feature extraction on the colorectal image three-dimensional network data to obtain colorectal image cell relation feature data so as to carry out colorectal cancer diagnosis auxiliary operation. According to the invention, the early diagnosis rate and diagnosis precision of colorectal cancer are improved.

The invention discloses an array server configuration method suitable for AIPC and a server, and relates to the field of server configuration.The method comprises the steps that calculation demand characteristics of a target application scene are obtained, and the calculation demand characteristics comprise the single-machine calculation power demand, the network interconnection demand and the storage capacity demand; calculating the number of target computing power modules according to the single-machine computing power demand, and calculating the number of target storage modules according to the storage capacity demand; constructing a server topology model according to the calculation demand characteristics, and calculating an estimated flow of data transmission between modules in the server topology model according to the server topology model; according to the number of the target computing power modules, the number of the target storage modules and the estimated flow, a server layout mode comprising the computing power modules, the storage modules and the network switching module is determined in a server topology model, and by implementing the method, the resource allocation balance of the array server can be improved.

The invention discloses a single-layer spherical reticulated shell steel structure construction method based on a BIM technology, relates to the technical field of steel structure construction, and aims to solve the problem that construction data cannot be obtained in time in the construction process of a single-layer spherical reticulated shell steel structure. Therefore, real-time acquisition and analysis of resource configuration, structural performance data and quality control data are optimized, quality problems in the construction process can be found and processed in time, when the risk threshold value of target real-time construction data is higher than a preset risk threshold value critical point, an early warning mechanism can be started quickly, and the early warning efficiency is improved. The construction risk is effectively prevented from being further expanded, the safety of the construction equipment in the operation process can be ensured by carrying out collision and overload detection on the construction equipment, the time line of each construction stage can be clearly displayed through the BIM technology, and project management personnel can reasonably arrange the construction sequence.

The invention discloses a drying device and a drying process for silicon carbide micro powder, and relates to the technical field of silicon carbide processing, the drying device comprises a drying box and further comprises scattering equipment, a discharging hole is formed in the front side of the drying box, a discharging plate is slidably mounted on the front side of the drying box, a first spring is arranged between the discharging plate and the drying box, and a second spring is arranged between the first spring and the scattering equipment; a feeding frame is fixedly mounted at the top of the drying box and communicates with the interior of the drying box, drying equipment fixedly penetrates through the rear side of the drying box, and the scattering equipment comprises a servo motor, a rotating rod, a hollow rod, a scattering rod, an extrusion rod and a cambered surface block; the scattering rod longitudinally moves in a reciprocating mode and rotates to scatter the to-be-dried materials entering the drying box, the phenomenon that the materials are gathered or caked can be avoided through scattering of the materials, it is guaranteed that the particle materials can be evenly heated by the drying equipment, local overheating or insufficient heating is avoided, and therefore the uniformity of the materials during drying is improved.

The invention discloses a pressure control method, device, equipment and medium for semi-combination points of double clutches. The method comprises the following steps: acquiring a first pressure of a historical round in a self-learning process of a semi-combination point of the double clutch; when the system main oil pressure is set to the maximum value, the pressure of the double clutch is adjusted with the first pressure as the target; with the second pressure as the target, the pressure of the double clutches is adjusted, and the target current when the double clutches are maintained at the second pressure is obtained; with the first pressure as a target, the pressure of the double clutches is adjusted, and the initial current when the double clutches are maintained at the first pressure is obtained; the double clutches are adjusted to reach the target current from the initial current, and real-time pressure change data of the double clutches in the adjusting process are obtained; according to the real-time pressure change data of the double clutches, the maximum pressure slope is determined; according to the maximum pressure slope, whether the first pressure of the half-combination point of the double clutches is adjusted or not is detected. According to the embodiment of the invention, the accuracy of self-learning of the half-joint points of the double clutches can be improved.

The invention discloses an image processing system based on artificial intelligence, and relates to the technical field of image processing, a user inputs an original image into the system by using an image input module, the system receives original image data and displays the image by using a display module, and the image processing module adjusts the original image based on the original image data by using an image adjustment processing module. After brightness and contrast adjustment, noise suppression, edge enhancement and histogram equalization are carried out, the quality of an image displayed on a display module is gradually improved, the defects of a traditional method are overcome, a more intelligent, efficient and high-quality image processing effect is achieved, and particularly, when complex and changeable images are processed, the image quality is improved. The system can automatically analyze the image content and dynamically adjust the processing parameters so as to achieve the optimal processing effect, the image processing system based on artificial intelligence brings a new thought and method for the image processing field, and the system has wide application prospects and important research value.

The invention discloses a method for culturing seawater rotifers by using prawn shell leavening, which comprises the following steps: S1, cleaning prawn shells to obtain a fermentation substrate; s2, dynamically optimizing fermentation conditions by adopting a multi-agent collaborative reinforcement learning algorithm; s3, predicting the optimal completion time of fermentation by adopting a mixed graph convolutional neural network and an adaptive genetic algorithm, and providing dilution suggestions through a spectral analysis technology; s4, dynamically calculating the dilution ratio, and mixing the fermentation liquor with seawater; s5, pouring the diluent into a rotifer culture pond, predicting the health state of the rotifer by adopting a Vision Transform model, and automatically adjusting a nutrition formula or environmental conditions; s6, monitoring the density of the rotifers in real time through a YOLOv5 target detection model and a camera, and keeping the rotifers within a preset density range; and S7, performing intelligent management on waste treatment based on a multi-objective evolutionary algorithm of non-dominated sorting. According to the method, a multi-agent collaborative algorithm and a deep learning technology are adopted, and intelligent culture of seawater rotifers and optimized treatment of wastes are realized.

The invention relates to the technical field of bearing outer ring polishing, and discloses a polishing device for bearing outer ring machining, which comprises a supporting mechanism, the supporting mechanism comprises a supporting frame, supporting legs are fixedly connected to the outer wall of the bottom of the supporting frame, and a connecting rod is fixedly connected to the outer wall of one side, close to the supporting legs, of the supporting frame. When the bearing outer rings are polished, the supporting mechanism and the adjusting mechanism can clamp and fix the bearing outer rings with different diameters and thicknesses, a third motor drives a driving roller so as to drive the bearing outer rings to rotate, and meanwhile balls rolling in supporting rods support the bottoms of the bearing outer rings, so that the bearing outer rings are polished. The bearing outer ring is prevented from shaking in the polishing process, the polishing mechanism positions the bearing outer ring and then machines and polishes the bearing outer ring, in this way, the problem that local polishing is excessive or insufficient can be avoided, and therefore the finished product yield of the bearing outer ring in the polishing link is increased, the product quality is guaranteed, the defective rate is reduced, and the production benefit is improved.

The invention is applicable to the technical field of hydroponic plants, and provides an offshore hydroponic device utilizing wave energy, wind energy and solar energy, which comprises a floating hydroponic frame, a power supply energy storage unit, a nutrition supply unit and a control unit, the floating hydroponic frame comprises a floating box floating on the water surface and a hydroponic plant frame arranged above the floating box, and a plurality of hydroponic grooves used for planting hydroponic plants are vertically distributed in the hydroponic plant frame side by side. The nutrition supply unit comprises a nutrient solution storage tank, a nutrient solution pump and a purifying and conditioning unit which are arranged in the floating box, the nutrition supply unit is arranged, through cooperation of the nutrient solution storage tank, the nutrient solution pump and the purifying and conditioning unit, the nutrient solution pump pumps a nutrient solution from the nutrient solution storage tank, and the nutrient solution is conveyed to the roots of the hydroponic plants after being purified and conditioned; the concentration and supply amount of the nutrient solution can be more accurately controlled, the requirements of plant growth are met, the uniformity of plant growth can be effectively improved, and overnutrition or insufficient nutrition is prevented.