1888results about How to "Improve the level of" patented technology

The invention discloses a knowledge and data fused chronic disease collaborative management method and system, and relates to the technical field of medical management. Comprising the following steps: generating a feature data set, processing the feature data set by using a feature gain modeling method, and generating an enhanced feature data set; dynamically generating a chronic disease comprehensive knowledge graph, performing node supplementation and weight optimization on the knowledge graph, and generating a specific knowledge sub-graph of the patient; carrying out multi-time sequence prediction by utilizing the specific knowledge sub-graph, and carrying out short-term and long-term trend prediction; a patient health track model is constructed through the state transition probability in combination with the prediction result; according to the dynamic risk labeling result of the health track model, the health state of the patient is comprehensively evaluated in combination with the specific knowledge sub-graph, and personalized management suggestions are generated according to the evaluation result. According to the collaborative management platform, cooperation between different medical institutions and medical staff can be promoted, information sharing and resource integration are realized, and the overall level of medical services is improved.

The invention provides a tunnel quality safety detection system and method based on laser radar data, and the method achieves the fusion and complementation of crack detection based on point cloud density change and crack detection based on curvature change, and achieves the quick recognition and precise detection of a crack region. The potential crack area is rapidly positioned through point cloud density change detection, and the boundary of the crack is further accurately positioned in combination with curvature change detection, so that the accuracy and integrity of crack detection are improved. For tiny deformation which is very tiny in change in point cloud density and curvature and is difficult to directly detect, a projection plane is further determined on the basis of the identified crack, and after point cloud data is projected to a two-dimensional plane, the characteristics of the tiny crack in the image are highlighted through image enhancement, so that the crack is identified. And then an edge detection algorithm is used to identify the micro crack so as to make up for the defects of a previous point cloud density and curvature detection method in the aspect of micro crack detection, and the accuracy and integrity of crack detection are further improved.

The invention relates to the technical field of medicine information management, in particular to a traceability method and system based on a medicine consumable traceability code. The method comprises the following steps: acquiring medicine purchasing information data; generating a unique code for the number of medicine purchasing information so as to generate a medicine warehousing traceability code; performing drug information association on the drug purchase information data according to the drug warehousing traceability code to generate a drug warehousing associated traceability code; storing the medicine warehousing associated traceability code in an information base to generate a medicine warehousing traceability code information base; performing scanning access mode division on the medicine warehousing traceability code, and generating a medicine dispensing scanning request mode and a medicine returning scanning request mode; and performing drug splitting tracing on the drug warehousing tracing code in a drug dispensing scanning request mode to generate drug splitting tracing data. According to the invention, through full-process closed-loop management, data association enhancement, intelligent scheduling optimization and drug return tracing improvement, the efficiency and precision of the drug consumable traceability code tracing method are improved.

The invention belongs to the field of paper products, and particularly relates to a heat-sealing coating composition for paper products and application of the heat-sealing coating composition, the coating composition comprises a component A, a component B, a component C and a component D, the component A is one or two of a biomass material with a dendritic or network structure or a cationized biomass material with a dendritic or network structure; the component B is selected from one, two or more of polyhydroxyalkanoate, alkyl ketene dimer, polyglycolide, polylactide, copolymer of butylene adipate and butylene terephthalate, cellulose ester and cellulose ether; and the component C is selected from one, two or more of thermoplastic cellulose and derivatives thereof, thermoplastic starch, rosin, cardanol-based epoxy resin, epoxidized soybean oil, epoxidized castor oil, tannic acid and malic acid. The coating composition is simple in preparation process and easy to industrialize, a target mixture can be obtained through physical blending, and the coating composition is low in production cost, energy-saving and environment-friendly.

The invention relates to the technical field of agricultural machinery, in particular to an orchard intelligent all-dimensional mechanical weeding machine which comprises a frame, a controller is fixedly connected to the top of the frame, a camera is fixedly connected to one side of the frame, the controller is used for receiving image information collected by the camera, and an energy supply assembly for supplying energy to the mechanical weeding machine is arranged at the top of the frame. A driving assembly used for driving the mechanical weeding machine to move and a reversing assembly used for controlling the mechanical weeding machine to reverse are arranged at the bottom of the frame, and a monitoring assembly used for monitoring the current environment condition and an adjusting assembly used for adjusting the weeding height are arranged on one side of the frame; and a control system for controlling the mechanical weeding machine to operate is arranged in the controller. Orchard images are collected in real time through the camera and the recognition module, crops and weeds are accurately distinguished on the basis of the database established through data over the years, the weeding accuracy is improved, and meanwhile the possibility that the crops are accidentally damaged by the mechanical weeding machine is greatly reduced.

The invention belongs to the field of network attack detection, and particularly relates to an APT attack detection method based on traceability graph behavior information. The method comprises the following four steps: step 1, data preprocessing; step 2, generating a sub-graph; step 3, behavior feature extraction; performing feature extraction on each sub-graph, wherein the feature extraction comprises node feature extraction and edge feature extraction; 4, designing and training a classification model, and performing anomaly detection; and training and testing the classification model, sequentially classifying the type of each edge by using the trained model, and when a certain edge cannot be correctly classified by any existing sub-model, judging that the edge is abnormal, and outputting a behavior structure diagram of the edge. According to the method, behavior attributes and structural information thereof are introduced into the modeling of the traceability graph, and the category of traditionally paying attention to entity interaction relationships is exceeded; by introducing a pooling method and graph representation learning, the expression ability of the model is improved, important information in a behavior structure is more effectively captured, and continuous optimization is performed on the basis of initial structure information.

The invention discloses pre-hospital emergency medical aid emergency help integrated equipment and system. The method comprises the following steps: S1, acquiring key vital sign data of a patient by using medical equipment; s2, calling basic information and medical history of the patient through equipment; s3, transmitting the collected data to a server of a remote data processing center in real time; s4, performing comprehensive analysis on the received vital sign data and the medical history information of the patient by applying a pre-trained deep learning model on the server, and generating a prediction report; s5, displaying a prediction result on a portable device or a remote monitoring station in real time by using a data visualization technology; s6, based on a visual prediction result and medical history analysis, guiding first-aid personnel to take targeted emergency medical measures; and S7, continuously monitoring the vital sign response of the patient and any health change related to the medical history, and updating the treatment strategy according to the further analysis of the deep learning model.

The invention relates to the technical field of grounding monitoring, and discloses a multipath grounding monitoring method for an intelligent station electrostatic monitor, and the method comprises the steps: carrying out the infrared scanning of a station region, comparing a station layout template, obtaining the station configuration data, and reading an electrostatic monitoring parameter; performing time division multiplexing matrix design on the multiple monitoring channels to obtain a time division multiplexing configuration scheme; performing on-off control time sequence compilation on the high-speed solid-state relay to obtain an on-off control time sequence table, and executing intelligent on-off control to realize monitoring channel switching; inputting the electrostatic signals of the plurality of monitoring channels into a high-precision analog-to-digital converter for parallel sampling and de-noising processing to obtain pre-processed electrostatic data; according to the invention, the monitoring strategy can be dynamically adjusted according to the station characteristics, the efficient collection and processing of multichannel data are realized, and an accurate static risk assessment and early warning mechanism is provided.

The invention discloses a real-time cultural tourism path optimization and adjustment system based on big data analysis, and relates to the technical field of cultural tourism path optimizing.The system comprises an acquisition and analysis module, the acquisition and analysis module is connected with a combination and matching module, the combination and matching module is connected with a path optimization module, and the path optimization module is connected with a data processing module. The path optimization module is connected with an interaction feedback module, and the collection and analysis module is used for collecting tourism behavior characteristic information of tourists in real time by using a big data analysis technology. According to the real-time cultural tourism path optimization and adjustment system based on big data analysis, a personalized model is established, tourism paths can be customized for tourists, unique tourism requirements and preferences of the tourists are met, the satisfaction degree and participation degree of the tourists in the tourism process are improved, the tourism paths can be adjusted in time according to real-time external data, and the tourism efficiency is improved. The tourists are prevented from being caught in unfavorable conditions such as congestion and severe weather, and smooth and efficient travel itinerary is ensured.

The invention discloses an industrial control ring network monitoring system and a monitoring method thereof. The system comprises a data acquisition module which is used for acquiring an industrial control ring network data packet in an industrial control network; the data processing module is used for carrying out data cleaning and data arrangement on the collected data and carrying out protocol matching on a data packet so as to identify an industrial protocol in the data packet; the data identification module is used for carrying out protocol matching on data in the network data packets and identifying communication data of each network packet; through organic cooperation of a plurality of units, the system realizes omnibearing monitoring, analysis and dynamic adjustment of the network, so that the system architecture provides a real-time, intelligent and self-adaptive network security solution, and compared with a traditional intrusion detection system, the system pays more attention to real-time optimization of network performance, and the network security is improved. Under the condition that the bandwidth occupancy rate is relatively high, unnecessary interference to other servers is reduced, so that the problems of lengthy and tedious protocol identification are solved.

The invention relates to an intelligent ventilation system in a tunnel and a control method thereof, and belongs to the technical field of tunnel ventilation. The intelligent ventilation system in the tunnel comprises a data acquisition unit, a ventilation unit, a control unit, a data storage unit and a data analysis unit, wherein the data acquisition units are mounted in detection sections in a tunnel, and each data acquisition unit comprises a COVI detector, a wind speed and direction detector and a traffic flow detection module; when the CO concentration and the VI exceed threshold values, the ventilation unit is controlled to enter a corresponding working mode; the data analysis unit is used for generating an early warning model according to the data of the data storage unit, and the early warning model is used for obtaining CO concentration and VI data in the future # imgabs0 # time according to the wind speed and wind direction data, the traffic flow, the vehicle type, the fuel oil type data, the CO concentration and the VI change. According to the ventilation system, intervention can be conducted before the pollution concentration is increased, the period of insufficient ventilation is effectively avoided, and it is guaranteed that good air quality is always kept in the tunnel.

The invention provides a robot-assisted wound suturing method and system based on artificial intelligence, and relates to the technical field of artificial intelligence, and the robot-assisted wound suturing method comprises the steps: obtaining multi-modal perception data of a wound area, constructing multi-modal three-dimensional representation of a wound, and determining a plurality of suturing points based on the multi-modal three-dimensional representation of the wound; for each suture point, calculating a candidate suture point, and for the adjacent suture points, generating a needle tip track of a needle tip in the wound, and sampling on the needle tip track to obtain a suture scheme adapted to the wound form and the tissue attribute; based on the obtained stitching scheme, an optimal control sequence of the stitching robot is obtained, meanwhile, a robust compensation control law is constructed through coordinate transformation and a feedback control law, and the optimal control sequence and the robust compensation control law are integrated into a stitching robot real-time control system; the output of a real-time control system of the suturing robot is converted into an actuator control instruction, and the suturing robot is controlled to assist in wound suturing.

The invention provides a preparation method and application of casei paracasei IOB413 after-generation powder, and relates to the field of microorganisms. Tartary buckwheat is used as a solid-state fermentation culture medium, and the lactobacillus paracasei IOB413 is fermented and then crushed to prepare the lactobacillus paracasei IOB413 after-generation powder with high flavone content. The flavonoid content of the metagenic powder prepared by the method is far higher than that in tartary buckwheat and casei paracasei IOB413, the levels of tumor necrosis factor alpha (TNF-alpha) and interleukin (IL-6) can be reduced, the level of anti-inflammatory factor interleukin (IL-10) can be increased, the gingival index and the dental plaque index can be reduced, the growth of streptococcus mutans can be inhibited to a certain extent, and the metagenic powder can be used for preventing and treating the dental plaque. The oral micro-ecology is improved.

The invention relates to the technical field of food monitoring, in particular to a nutritious food freshness monitoring and early warning method and system, overcomes the limitation of a traditional method, and improves the level of nutritious food freshness monitoring. The method comprises the following steps: collecting freshness influence factors in the process from production to distribution of the nutritious food; carrying out attribute marking on the collected freshness influence factors to generate a freshness characterization data set; classifying the freshness characterization data set by using a pre-constructed freshness characterization classification model to generate a plurality of freshness characterization type sets; performing freshness evaluation on each freshness characterization type set, and sorting the multiple freshness characterization type sets based on an evaluation result to generate a freshness risk sequence; each freshness characterization type set in the freshness risk sequence corresponds to a freshness risk value; on the basis of a preset freshness requirement threshold value, all freshness characterization type sets in the freshness risk sequence are compared.

The invention provides lactobacillus reuteri HNU872 and application of the lactobacillus reuteri HNU872 in preparation of intestinal inflammation related products. The invention discloses how the Lactobacillus reuteri HNU872 effectively alleviates the phenotype of DSS-induced mouse enteritis. The invention also discloses a preparation method of the Lactobacillus reuteri HNU872. Research results show that the Lactobacillus reuteri HNU872 can significantly relieve weight loss caused by enteritis, improve colon length, significantly improve the level of anti-inflammatory cytokines in serum and reduce the concentration of pro-inflammatory cytokines. In addition, the expression of the intestinal tight junction protein ZO-1 is obviously promoted. The lactobacillus reuteri HNU872 can regulate diversity and structure of intestinal microbiota of mice, inhibit enrichment of pathogenic bacteria and relieve inflammatory response. According to the invention, the action mechanism of the lactobacillus reuteri HNU872 in improving enteritis is clarified, and a solid scientific basis is provided for developing a microbial product based on probiotics as an alternative treatment strategy for ulcerative colitis.

The invention relates to the technical field of lubricating coatings, in particular to a low-temperature curing lubricating coating for a fan bearing and a preparation method of the low-temperature curing lubricating coating. The lubricating coating is prepared from the following components in parts by weight: 55 to 65 parts of mixed solvent, 10 to 15 parts of composite bonding resin, 10 to 15 parts of modified lubricating filler, 8 to 12 parts of wear-resistant filler, 0.5 to 3 parts of dispersing agent, 0.5 to 1 part of micronized dicyandiamide, 0.5 to 2 parts of flatting agent, 0.5 to 2 parts of defoaming agent and 0.5 to 1 part of anti-settling agent, wherein the composite bonding resin is prepared from the following components in parts by weight: 10 to 20 parts of organic silicon resin, 15 to 30 parts of novolac epoxy resin, 15 to 30 parts of urethane acrylate and 35 to 45 parts of polyhydroxy polyether resin; the modified lubricating filler is obtained by modifying mixed powder containing molybdenum disulfide and polytetrafluoroethylene. The adhesive force, the wear resistance and the lubricating property of the lubricating coating can be improved, and the curing temperature can be reduced.

The invention relates to a method for automatically correcting and updating the route of an electric power inspection unmanned aerial vehicle, which comprises the following steps of: S1, collecting and integrating geographic information system (GIS) data of an inspection area, and constructing a topological graph; s2, obtaining detailed point cloud data of the ground and the power grid facilities, and constructing a 3D model according to the obtained point cloud data; s3, based on the topological graph and the 3D model, extracting a key position from the 3D model by using an algorithm, determining an initial waypoint, extracting waypoints from the key position of the power grid equipment, connecting all the extracted waypoints by using a path planning algorithm, and generating an initial inspection route; s4, correcting the initial inspection route in combination with real-time weather, equipment priority and historical data; and S5, combining the combination degree RTK GPS and an environment adaptive VIO algorithm to realize sub-meter positioning precision, and after the key position centralization is successful, automatically updating the waypoint and immediately uploading the waypoint to a control center to realize automatic updating of the route. The accuracy and efficiency of unmanned aerial vehicle inspection are effectively improved.

The invention discloses a whole-process intelligent disposal management method based on an alarm signal, and relates to the technical field of XX. The method comprises the following steps: monitoring a transmission folder in real time by adopting a Kettle data processing tool, and importing an alarm signal data file transmitted by an OCS system into a database once the alarm signal data file is found; executing a cleaning program on the warehousing data, and extracting core information of the alarm signal; constructing and continuously updating an expert knowledge base, performing matching in the expert knowledge base according to the extracted core information, and correspondingly generating an expert knowledge model; according to the generated expert knowledge model, processing steps of the alarm signals are automatically split according to stages to generate sub-processes; and judging whether an automatic disposal criterion is met or not according to a matching result, if yes, automatically executing, and if not, executing after field personnel confirms. According to the invention, the alarm signal data file transmitted by the power grid monitoring system is automatically sensed and monitored in real time, and the timeliness and accuracy of abnormity monitoring are improved.

The invention relates to the technical field of water quality tracking and monitoring, and discloses a water environment water quality tracking and monitoring system and a method thereof.The water environment water quality tracking and monitoring system comprises a data acquisition unit, a preprocessing unit, a data analysis unit, a pollution analysis unit and an early warning display unit. The water environment condition can be reflected comprehensively and accurately; abnormal value judgment and replacement are performed on the water quality data of the acquisition points and the time points, so that the reliability and the stability of the data are improved; by constructing a regional water quality vector matrix and a fixed-point water quality vector matrix, indexes such as variable coefficients are calculated from space and time dimensions, and acquisition points with local pollution or abnormal fluctuation are accurately found out; according to the invention, the system determines the pollution level, displays the abnormal collection point and the pollution level to related personnel in time, facilitates the related personnel to take countermeasures rapidly, improves the efficiency and level of water environment management, and provides powerful support for the protection and treatment of the water environment.

The invention discloses a gas outburst monitoring and early warning method and system based on an improved ConvLSTM model, and relates to the technical field of gas monitoring, and the key points of the technical scheme are that the method comprises the following steps: constructing a mine gas data set; cleaning the gas data set, converting unstructured data into structured data, and performing data cleaning, denoising and standardization on the structured data; performing high-order derived feature extraction on the preprocessed gas data set; an improved ConvLSTM model is constructed; using a historical gas data set to train the improved ConvLSTM model; identifying a potential gas high-risk area; based on an analysis result of the improved ConvLSTM model, identifying a potential gas outburst ignition risk area; and constructing a monitoring platform. By improving the ConvLSTM model, efficient collection and processing of gas data are achieved, monitoring accuracy and real-time performance are improved, and powerful support is provided for mine safety management.

The invention discloses a regional mouse prevention and control system based on an intelligent mouse poisoning station, and relates to the technical field of mouse prevention and control. Mouse activities and poison bait feeding conditions are monitored and recorded in real time, the deviation degree of poison bait consumption is judged, and the correlation between the poison bait consumption and the mouse activities is evaluated; the abnormal degree of the mouse activity range area is judged, and the interference on mouse activities after poison bait throwing is evaluated; then, the correlation between poison bait feeding and mouse activities and the interference on the mouse activities after poison bait feeding are comprehensively analyzed, and the poison bait feeding accuracy of the mouse poison station is evaluated; the poison bait feeding accuracy of the mouse poisoning station is divided, and the poison bait feeding strategy of the mouse poisoning station is intelligently optimized; after corresponding improvement measures are taken, the accuracy of poison bait throwing of the rat poison station is continuously evaluated, early warning is carried out in time when the accuracy of poison bait throwing is abnormal, the overall effect of regional rat prevention and control is improved, and meanwhile the adverse effect on an ecological system is reduced.

The invention discloses an intelligent commodity management method, and relates to the technical field of commodity management. Through the design of the whole method, the efficiency can be improved, the intelligent system can automatically manage a plurality of goods management tasks such as inventory management, purchase decision making and demand prediction, manual intervention is reduced, the management efficiency is improved, inventory optimization is facilitated, the intelligent system can accurately predict demands through data analysis and prediction algorithms, and the management efficiency is improved. The inventory level is optimized according to the prediction result, the inventory overstock or stockout phenomenon is avoided, the inventory turnover rate is improved, the cost is reduced conveniently, the intelligent system can help enterprises to optimize purchasing strategies and reduce the inventory cost, the purchasing cost is reduced through price optimization and other modes, and therefore the overall cost of the enterprises is reduced, and the enterprise experience is improved. The customer satisfaction can be improved conveniently under the overall application, and the customer satisfaction can be improved and the customer loyalty can be enhanced by meeting customer requirements in time, accurately predicting the market trend and providing personalized services and intelligent commodity management.

The invention discloses a spoken English man-machine conversation interaction training method and system, and relates to the technical field of spoken English training, spoken English audio signals of a user are monitored in real time through a microphone, and the frequency spectrum information of the audio signals is refined into each frame of spectrogram and cepstrum coefficient feature vectors by using Fourier transform and feature extraction technologies; therefore, the voice signal characteristics of the user can be completely captured; three core dimensions of semantic similarity, grammatical structure similarity and fluency are incorporated into an evaluation model, a comprehensive oral English training evaluation system is formed, a text sequence is generated by analyzing a time sequence dependency relationship through a convolutional neural network, and the oral English training evaluation model of a deep learning technology is combined, so that the oral English training evaluation accuracy is improved. According to the method, the expressions of the user in the aspects of semantics, grammar and fluency can be accurately measured, the oral training level of the user can be comprehensively judged by the system by comparing the comprehensive evaluation coefficient with the preset qualified threshold value, and a personalized learning guide is provided according to a result.

The invention discloses a three-dimensional BIM (Building Information Modeling) and GIS (Geographic Information System) model-based integrated city district-level data management platform and method, and the platform forms a three-dimensional information integrated data management platform, collects geographic information data and basic data through an information data collection module, and converts the geographic information data and basic data into a BIM model file; the BIM model building module is used for making a BIM model based on three-dimensional software; the GIS model building module is used for building a GIS model and integrating a development environment and a database environment at the same time; the BIM model lightweight processing module is used for optimizing the BIM model and performing lightweight processing on the BIM model; the platform management module is used for constructing a BIM model management platform based on the cloud GIS, the BIM model management platform based on the cloud GIS is constructed in combination with the cloud GIS technology, visual display and automatic integration of the BIM model can be carried out, and centralized collection and analysis of more related data are achieved.

The invention relates to the technical field of power grid risk prediction, and discloses a power grid risk monitoring method and system based on meteorological early warning, and the method comprises the steps: dividing a power grid monitoring region into a plurality of monitoring regions; defining a power grid risk fault type, obtaining a risk type set of different monitoring region types, and calculating a risk assessment index and a region influence index; generating a risk meteorological feature set, and calculating a meteorological influence index of the risk meteorological feature set on the risk type; and constructing a risk prediction model, performing risk prediction, and issuing meteorological risk early warning information. Through the risk monitoring method of the system, from data collection, risk assessment and meteorological influence analysis to risk prediction and early warning, the level of power grid risk management is comprehensively improved, the risk is monitored and predicted in real time, early warning information is issued in time, the response speed and efficiency for responding to the risk are improved, the occurrence probability and the influence degree of risk events are reduced, and the risk management efficiency is improved. The economic loss is reduced.

The invention relates to the field of solid state disk data encryption, in particular to a solid state disk data encryption method and system. The method comprises the following steps: performing partition table structure analysis on the solid state disk, and performing hard disk capacity distribution analysis to obtain hard disk capacity distribution data; acquiring to-be-written hard disk data; performing data partitioning processing on to-be-written hard disk data, and performing confusion encryption processing so as to construct a confusion encrypted data sequence; obtaining a pre-stored random picture; pixel channel decomposition is carried out on a pre-stored random picture one by one, and maximum data steganography distribution density calculation is carried out, so that the maximum data steganography distribution density is obtained; and based on the maximum data steganography distribution density, carrying out data distribution encryption steganography on a pre-stored random picture by using the confused encrypted data sequence, and carrying out visual deviation fine tuning so as to generate a visual fine tuning steganography picture. According to the invention, efficient and safe solid state disk data encryption is realized.

The invention relates to the field of cell biology, and particularly discloses an exosome as well as a preparation method and application thereof. The method for preparing the exosome comprises the following steps: (1) introducing nucleotide sequences for coding a signal peptide TPA and an epidermal growth factor into an AAVS1 region of a host cell, such as a sequence shown in SEQ ID No.9 and a sequence shown in SEQ ID No.10, so as to obtain a modified host cell; and (2) collecting the exosome secreted by the modified host cell. The expression level of EGF mRNA in the exosome can be remarkably improved, so that the obtained exosome has a better effect in skin wound treatment.

The invention relates to the technical field of air detection, in particular to a multi-point in-situ detection device for nitrous acid and nitric oxide, which comprises a split-flow collection pipeline, a multi-section extractor, an aspirator pump, a cleaning circulation pipeline and circulating cleaning equipment, the split-flow collection pipeline is mounted in a collection area, and is provided with a plurality of collection ends distributed in different collection areas; the multi-section extractor is installed at the output end of the split-flow collection pipeline, the interior of the multi-section extractor is connected with the nitrous acid detector and the nitric oxide detector, and the gas suction pump is connected with the split-flow collection pipeline and used for sucking gas in the split-flow collection pipeline; the cleaning circulation pipeline is installed above the flow dividing and collecting pipeline, the cleaning circulation pipeline is provided with a plurality of liquid outlet ends, and the liquid outlet ends of the cleaning circulation pipeline are communicated with the flow dividing and collecting pipeline; the input end of the circulating cleaning equipment is communicated with the split-flow collection pipeline, and the output end of the circulating cleaning equipment is connected with the cleaning circulation pipeline. The detection efficiency can be effectively improved, and meanwhile, the detection cost is reduced.

The invention relates to the field of aquatic product safety monitoring and early warning, in particular to an aquatic product safety monitoring and early warning system and method, which comprises a data acquisition module, a data transportation module, a data analysis module, a data early warning processing module and an information management module, through real-time acquisition of related data in links of aquatic product production, processing, storage, transportation and the like, water quality parameters, temperature and humidity are analyzed, the safety condition of aquatic products and a potential risk early warning processing module are evaluated, and when a data analysis result shows that potential safety hazards exist or exceed a set standard, early warning signals of different levels are sent out. Therefore, equipment and related personnel can take measures in time. And the information management module effectively manages and stores various data, thereby facilitating query and tracing. And related reports are generated to provide a basis for decision making.

The utility model discloses a multi-size compatible wafer loading disc, which comprises a bearing disc, a plurality of supporting mechanisms capable of adjusting the balance of the bearing disc are installed at the lower end of the bearing disc at equal angles, and a sensor fixing piece is installed on one side of the bearing disc. A plurality of limiting guide nails for guiding and limiting wafers are detachably mounted on the upper surface of the bearing disc; according to the utility model, the limiting guide nails are matched with the guide nail grooves in the coarse positioning scribed lines, so that the limiting guide nails can be mounted in the guide nail grooves in the corresponding coarse positioning scribed lines according to the bearing requirements of wafers with different sizes, and the multi-size compatibility is realized by arranging the limiting guide nails at different positions of the guide nail grooves; according to the method, whether the position of the wafer has large deviation or not is confirmed through routing inspection of the coarse positioning scribed line, the process switching time is effectively shortened, the risk in the compatible switching and dismounting process is effectively reduced, and better guarantee is provided for the stability in the wafer bearing field.