23results about How to "Quick Disposal" patented technology

This invention relates to a vacuum extractor that improves extraction performance through a vacuum treatment unit, which improves extraction performance by recovering extracts contained in the air drawn in when a vacuum is generated. The vacuum extractor includes: an extraction chamber for extracting extracts from a raw material using a solvent; a chamber heating unit for heating the extraction chamber with a heat medium to improve extraction performance by heating the raw material; and a vacuum treatment unit for generating a vacuum in the extraction chamber to facilitate extraction of the extract from the raw material, while simultaneously recovering the extracts contained in the drawn-in air using a vacuum pump. The vacuum treatment unit includes: a first cooler for cooling the air and recovering the extracts when a vacuum is generated in the extraction chamber using a vacuum pump; a cyclone tank for generating a cyclone and recovering the extracts contained in the air passing through the first cooler; a second cooler for further cooling the extracts contained in the air passing through the cyclone tank and recovering the extracts; and a recovery tank for storing the extracts recovered from the second cooler.

The application provides a method, system, device, equipment and program product for predicting the progression of tension pneumothorax, the method is based on computer and comprises the following steps: obtaining POCUS affected partition count data of a to-be-tested sample; performing classification prediction based on the POCUS affected partition count data to obtain a classification result of the risk level of the to-be-tested sample in terms of the occurrence of cycle collapse of tension pneumothorax; if the POCUS affected partition count data of the to-be-tested sample is greater than or equal to 4, the classification result of the high risk of the to-be-tested sample in terms of the occurrence of cycle collapse of tension pneumothorax is obtained; and if the POCUS affected partition count data of the to-be-tested sample is less than 4, the classification result of the low risk of the to-be-tested sample in terms of the occurrence of cycle collapse of tension pneumothorax is obtained.

The invention discloses a transmitter system based on multi-sensor fusion and edge AI and a self-diagnosis method, and belongs to the technical field of industrial process control instruments, and an industrial intelligent transmitter system comprises a multi-sensor unit, a signal acquisition unit, a microcontroller, an AI coprocessor and a dual-mode communication unit. The multiple sensing units are used for synchronously collecting original data; the signal acquisition unit is used for converting original data into digital signals; the microcontroller is used for processing the digital signal and carrying out environment adaptive compensation to obtain compensated sensor data; the AI coprocessor is used for performing feature extraction and fault probability reasoning on the compensated sensor data to realize real-time self-diagnosis; and the dual-mode communication unit is used for transmitting the compensated process control signal and diagnosis information in different channels. The system has the functions of environment adaptive compensation, real-time self-diagnosis and the like, and the problems of parameter drift and fault response delay in an industrial environment are remarkably improved.

The invention belongs to the technical field of wind power equipment operation and maintenance, and discloses a wind power equipment fault early warning method based on edge calculation. The method comprises the following steps: acquiring vibration, temperature and current parameter operation data through a wind power equipment sensor, generating an original data sequence, and preprocessing to obtain a preliminary feature set; the time sequence gradient of each parameter is analyzed and calculated through a time sequence, and a parameter change rate sequence is obtained through optimization of a gradient descent algorithm. When the sequence exceeds a threshold value, a stable change trend is obtained through sliding window smoothing, and anomaly classification and risk grading are completed in combination with a historical working condition database and a support vector machine. And starting deep analysis according to an edge node resource state, constructing a fine prediction model to generate an early warning signal containing a fault probability and occurrence time, matching a risk level to activate a local response, and outputting an alarm. According to the invention, through edge localization processing and multi-algorithm cooperation, accurate pre-judgment of faults is realized, and the operation and maintenance response efficiency and early warning accuracy of wind power equipment are improved.

The application provides a green, low-carbon and rapid chromium-containing wastewater treatment method, which is improved on the basis of traditional biogas residue and ferrous sulfate treatment of chromium-containing wastewater, introduces short-term micro-aeration technology, and produces unexpected results, which not only treats the chromium-containing wastewater in a green and low-carbon way, but also greatly speeds up the reaction progress. In the process, a certain thickness of biogas residue sediment layer is formed in the biochemical reaction tank, then ferrous sulfate is added, then chromium-containing wastewater and biogas liquid are added, and after standing for a period of time, micro-aeration is carried out, which accelerates the biochemical reduction of Cr(VI) in the chromium-containing wastewater, promotes the activity of microorganisms, and saves resources.

The invention relates to the technical field of monitoring, in particular to an intelligent monitoring method and system for residential area security. According to the technical scheme, the method comprises the following steps that identity information of a visitor is obtained and verified, a visitor information file is established after verification is passed, and an activity permission area is distributed; monitoring data are collected and preprocessed, and monitoring information data and visitor position information are obtained. Dangerous action recognition is performed on the monitoring information data, and danger recognition factors are obtained in combination with the position information of the visitor. And judging whether the danger identification factor is greater than a preset standard factor, if so, sending an alarm signal, and if not, not sending the alarm signal. The dangerous action recognition precision is high, the recognition accuracy is higher, the response speed is higher, and potential safety hazards can be found in time. Excessive manual intervention is not needed, the labor cost is effectively reduced, careless omission of manual guarding is avoided, and the intelligent level of security work of the residential area is improved.

The application relates to the technical field of electric digital data processing, and particularly discloses a product information risk assessment method and system based on a large model, which comprises the following steps: simultaneously scanning source code and products by a scanner to generate a source dependency list and a product component list, performing main name normalization and alignment through a large model, locking a warehouse and a version according to the source dependency list, analyzing original code by a parser to generate a cross-language path logic group, combining the product component list to correct a real package version, converging into a unified intermediate representation, performing reachability and joint analysis on the unified intermediate representation to obtain a risk candidate path set and complete path scoring, finally, according to a preset weight and a running period evidence, modifying the score, screening out a risk path, matching a disposal strategy, and generating executable strategy code by the large model for risk control of a gateway or a service side.

The application discloses a kind of industrial production safety early warning analysis methods for multi-modal data, belong to industrial production safety monitoring technical field.S1, numerical text, audio and video, time series multi-modal data in industrial production are preprocessed, and unified format multi-modal feature data are obtained;S2, the data obtained in S1 are executed time, space, semantic alignment processing, and the fusion multi-modal feature data of space-time semantic consistency are obtained;S3, the data obtained in S2 are integrated processing of neural symbolization data, and integrated feature vector is output;S4, multi-model collaborative early warning analysis is carried out based on integrated feature vector, and the final early warning conclusion is generated;S5, four-level early warning grading response operation is executed;S6, dynamic optimization is carried out by comparing early warning result and actual disposal effect, and model parameters and strategy are updated.The above method is used, multi-modal data are fused, early warning is accurate, response is fast, adaptability is strong, can be dynamically optimized, and industrial production safety is comprehensively guaranteed.

The application relates to the technical field of pressure reducing valves, and discloses a pressure reducer for natural gas, which comprises a valve body, a visual warning mechanism fixedly connected to the low-pressure end of the valve body, a locking mechanism arranged on the outer portion of the valve body, and sound warning mechanisms arranged on the upper and lower sides of the visual warning mechanism. The visual warning mechanism is used for issuing a visual alarm when the temperature is too high or too low, the locking mechanism is used for keeping the visual alarm state and needs to be manually released, and the sound warning mechanisms can issue sound alarms when the temperature is too high or too low and can be released along with the manual release of the locking mechanism. Through the linkage of the visual warning mechanism and the sound warning mechanisms, visual and sound warnings can be issued when the temperature of the pressure reducer is too high or too low, timely warnings can be issued before low-temperature ice blocking occurs and high-temperature tempering risks appear, operation and maintenance personnel can quickly dispose, and the safety hidden danger during the use of the natural gas pressure reducer is reduced.

The invention provides an electric power engineering acceptance quality gate and construction progress plan association management system and method and electronic equipment, and the method comprises the steps: building a unified data model to get through a data source of a quality gate and a progress plan, and achieving the structural association of two types of data; automatically generating a three-level progress plan based on the quality gate division data, and establishing a dynamic mapping rule of the quality gate and a progress key node; monitoring a quality acceptance status and progress execution data in real time, and dynamically adjusting an association relationship and a progress plan through a built-in algorithm; when early warning is triggered, an analysis report containing cost estimation and rectification suggestions is generated, and rectification closed-loop management of cross-terminal collaboration and block chain evidence storage is supported. According to the method, the problems of independence of quality and progress systems, non-communication of information and low collaboration efficiency in traditional electric power engineering are solved, collaborative management of quality data driven progress and progress change linkage quality is realized, and project management efficiency and risk predictability are improved.

The invention discloses an explosion-proof grounding resistance on-line monitoring system and device, and relates to the technical field of grounding resistance monitoring. Comprising a grounding loop, a resistance monitoring device and an intelligent control platform, wherein the grounding loop is formed by a metal grounding electrode, a connecting conductor and to-be-protected equipment; the resistance monitoring device obtains a real-time resistance value of the loop, so that the resistance fluctuation state in unit time is monitored on line in a full-dimension manner; and the intelligent control platform communicates with the resistance monitoring device through a local area network, and transmits the resistance value of the grounding loop to the intelligent control platform for monitoring and displaying. According to the invention, a full-chain digital intelligent lightning safety protection comprehensive solution covering sensing, transmission, analysis, decision making and disposal is created, grounding system detection normalization is realized, a traditional lightning protection grounding system monitoring mode is promoted to be transformed and upgraded to be intelligent, the lightning protection and disaster reduction working level is improved, and lightning protection is transformed from passive protection to active defense.

The application discloses a method for tracking and detecting abnormality of secret-involved carriers based on deep learning, and belongs to the technical field of information security, and comprises the following steps: periodically acquiring trajectories corresponding to each secret-involved carrier, comparing the trajectories with secret-keeping rules in a rule base, and determining abnormal operation; calculating and acquiring a comprehensive risk level corresponding to each trajectory, and determining whether the operation corresponding to the trajectory is abnormal operation, and marking abnormal operation samples and normal operation samples; according to the type of the secret-involved carrier, statistically grouping each abnormal operation sample and normal operation sample, and updating the secret-keeping rules in the rule base based on the comparison result; the application automatically identifies new attack trajectories by analyzing the similarity between the abnormal operation samples and the secret-keeping rules, and expands or adds rules based on the output target, so that the rule base dynamically evolves, and the system protection coverage range and adaptability are continuously improved.

The invention relates to the technical field of traffic control, in particular to a second-hand car market mixed flow traffic control method and system based on multi-target recognition. The method comprises the following steps: in response to an activation signal of a barrier gate triggering device, collecting multi-dimensional identification original data of vehicles passing through a barrier gate of a second-hand vehicle market through a multi-source identification device; performing cross-device data calibration processing on the multi-dimensional recognition original data, performing feature matching, and generating a vehicle identity recognition result and an identity confidence coefficient parameter; according to the vehicle identity recognition result and the identity confidence coefficient parameter, a dynamic passing strategy engine is called to generate a vehicle passing permission evaluation result and a strategy adaptation coefficient; and generating vehicle passing state record data according to the passing authority evaluation result and the strategy adaptation coefficient, performing classification analysis, generating an intervention processing work order, and feeding back the intervention processing work order to the system optimization module for iteratively updating the identification model and the passing strategy. The barrier gate passing efficiency of the second-hand car market can be greatly improved.

The present invention belongs to the technical field of industrial automation. The present invention discloses an intelligent control method for double closed-loop of paste filling concentration and flow rate of iron tailings, including: determining the reference resistance characteristic parameters according to pipeline parameters and paste physical properties, and setting the target intervals of concentration and flow rate; collecting the real-time concentration and flow rate values, comparing with the target intervals to determine the coupling interference level; selecting the main and secondary adjustment parameters according to the coupling interference level, determining the adjustment priority order and following time sequence, and generating a cooperative adjustment instruction; inputting the instruction into the closed-loop control channels of concentration and flow rate to execute the adjustment, setting an interlock protection to limit simultaneous large-scale adjustment; monitoring the pipeline pressure and the end flow rate, switching to an emergency dredging mode in case of abnormality, and entering a new round of control cycle after recovery; ensuring the continuous and stable operation of the filling system.

The present application provides a smart power plant network security monitoring method and system, an electronic device, and a storage medium. Distributed collection probes are arranged in the production monitoring network, the management information network, and the external network access area in the smart power plant. The collected data is uniformly gathered to a security analysis platform. The security analysis platform calculates the risk index of each communication session in real time. The present application realizes comprehensive collection of multiple network areas and multiple types of data in the smart power plant through the distributed collection probes. The risk index is dynamically calculated through a quantitative formula. The weight factor can be flexibly adjusted according to the scene of key control instruction transmission, so as to realize accurate classification of risks. Meanwhile, the linkage strategy execution unit realizes rapid disposal of security events. The whole system architecture is simple and has strong scalability, which is suitable for the digital transformation needs of the smart power plant. The configuration of the electronic device and the storage medium ensures the landing execution of the monitoring method.

The application discloses a police shield based on a composite material metal laying bonding technology and a design method. In view of the problems of uneven bonding strength between homogeneous layers, easy debonding of a heterogeneous interface and difficult balance between protection and light weight of an existing thermoplastic CFRP / metal heterogeneous fusion shield, the application establishes a thermal load gradient interlayer bonding strength model and a heterogeneous fusion interface bonding mechanism model, combines a genetic algorithm to optimize a laying process and realizes accurate regulation and control of bonding strength. A six-layer composite layered structure is optimized, a PPS-based thermoplastic CFRP is used as a core protection layer, an aluminum alloy force-bearing matrix is matched, and a double protection system is formed. The application effectively solves the bonding failure technical bottleneck, improves the shield protection performance and structural stability, realizes the balance between light weight and high protection, reduces the burden of police officers, and is controllable in process, convenient for large-scale production, suitable for complex police service combat requirements and has important practical value.

The invention belongs to the field of enterprise digital network security, and relates to an access method, system and device based on a zero-trust security model and a medium, and the method comprises the steps: building a secure communication channel; performing access authentication based on the user identity attribute and the access environment attribute; after the user identity attribute and the access environment attribute pass access authentication, an encrypted data transmission channel is established, and the unified access agent forwards all access traffic through the encrypted data transmission channel and collects multi-source security data in real time in the access process; dynamic trust evaluation is performed through the multi-source security data to calculate a trust score, and a hierarchical response strategy is adopted to dynamically adjust the resource access permission of the user according to the trust score. By constructing a complete zero-trust security closed loop of continuous authentication, dynamic evaluation, hierarchical response and active fusing, refined, intelligent and adaptive control of user access behaviors in a complex network environment is realized, and the security protection capability of intranet resources is remarkably improved.

The invention relates to the technical field of gas pipe network monitoring, and discloses a natural gas pipeline full-life-cycle risk early warning method based on data fusion, which comprises the following steps: step 1, full-life-cycle multi-source data acquisition; 2, preprocessing edge node data; 3, cloud multi-modal data fusion is carried out; step 4, AI intelligent analysis and risk identification; step 5, risk grading and early warning generation; step 6, early warning pushing and work order dispatching; according to the method, through the full-chain design of full-cycle data penetration, edge, cloud collaboration, AI dynamic analysis and closed-loop optimization, the core pain points of lagging, low efficiency and insufficient precision of traditional natural gas pipeline risk early warning are solved, and real-time identification, accurate judgment, rapid disposal and continuous optimization of risks are achieved; and the intelligent level and the operation and maintenance efficiency of safety management of the natural gas pipeline are greatly improved.

The utility model belongs to the technical field of fire fighting apparatus, especially is involved in an improved fire fighting hook structure for electric vehicle. The combined hook lance is composed of hollow metal conical seat, sliding rail, tow hook, injection hole seat and penetrating cone. The sliding rail is welded to the outer surface of the hollow metal conical seat, the tow hook is connected to the sliding rail through bolts, the hollow metal conical seat is provided with the injection hole seat which is in communication with the hollow, and the penetrating cone is screwed to the upper end of the injection hole seat. The fire fighting hook is designed with hollow pipeline, which can quickly inject special fire extinguishing agent after piercing the battery pack shell, accurately extinguish the fire source and prevent the fire from rekindling. The hollow structure is integrated with an insulation layer, effectively preventing electric shock risk and significantly improving rescue safety and efficiency.

A radioactive nuclide 137 A rapid remediation device and method for Cs-contaminated soil includes an inlet for adding an activator and raw materials, a power supply, a microwave device, an auxiliary extrusion rod, a pressure plate containing a spray head, and a solid pressure plate. The solid pressure plate is located above the pressure plate containing the spray head, and the power supply and microwave device are positioned above the solid pressure plate. A spray head is provided on the pressure plate containing the spray head, and the auxiliary extrusion rod passes through the solid pressure plate and enters the spray head to extrude it. The spray head contains the activator and raw materials, and the auxiliary extrusion rod pushes the activator and raw materials into the soil. This application's solution combines microwave and solidification technologies to achieve remediation of soil containing radioactive nuclides. 137 Advantages of Cs in soil remediation.

This invention relates to the field of fresh food supply chain management technology, and more particularly to a digital management system for the entire fresh food supply chain process. The system includes: a data acquisition module for real-time acquisition of status data of fresh products throughout the entire supply chain process; a model building module for iterative training of a fusion prediction network framework to output a fresh product demand prediction model; an inventory control scheme generation module for dynamically adjusting inventory turnover parameters of fresh products to obtain an inventory control scheme; a route optimization scheme generation module for collaborative analysis of transportation route planning parameters to obtain a transportation route optimization scheme; and an anomaly monitoring module for monitoring and analyzing the flow status of fresh products, generating anomaly handling information when the monitoring results meet preset anomaly conditions. This invention enables real-time dynamic monitoring and collaborative optimization of the entire fresh food supply chain process, improving the overall operational efficiency of the supply chain.

The utility model relates to a movable charging pile fire extinguishing system, and belongs to the technical field of fire extinguishing devices. Comprising a charging pile end fire fighting unit arranged in the mobile charging pile and used for fire detection and fire extinguishing of the mobile charging pile; comprising a composite detector; the thermosensitive wire is arranged along a battery module and a circuit in the mobile charging pile, and the charging pile fire extinguishing device is communicated with the interior of the mobile charging pile through a charging pile fire extinguishing device nozzle; the station end fire fighting unit is arranged in the charging station; comprising a pump set type fire extinguishing system connected with a plurality of sprayers through pipelines; the multi-type detector combination is arranged in the charging station for detection; the pump set type fire extinguishing system is electrically connected with the multi-type detector combination; and the Internet of Things monitoring terminal is in communication connection with the charging pile end fire-fighting unit and the station end fire-fighting unit. Through the multi-layer collaborative design of'equipment-level protection-station-level protection-remote supervision ', the problems that fire safety facilities of an existing mobile charging pile and charging station are lacked, early warning is lagged, and fire extinguishing measures are insufficient are effectively solved.

This invention provides a dynamic risk assessment method for vehicle transportation based on a closed-loop coupling of FTA and the exponential method. It employs a multi-subjective and multi-objective weighting method to eliminate reliance on subjective experience and utilizes an exponential decay model to dynamically adjust static weights, thereby driving the construction of a dynamic risk quantification system. Simultaneously, it overcomes the static limitations of traditional fault trees by adding real-time data-driven dynamic risk perception capabilities through the exponential method. Furthermore, it combines the time-varying analysis capabilities of the Cox proportional hazards model with the logical structure of fault trees to construct a novel dynamic failure rate update framework. Finally, it introduces an adaptive threshold function to dynamically classify warning levels, analyze the contribution of each event in real time, accurately locate key risk transmission paths, and ultimately achieve a complete closed loop from real-time monitoring and accurate assessment to rapid tracing and handling.