46 results about "Distributed collection" patented technology

The invention discloses an intelligent fireproof electrical control cabinet operation method, and the method comprises the steps: building a multi-source data set in which a physical position is strongly bound with a network topology label through the distributed collection of multiple types of sensors, and achieving the precise normalization, noise suppression and unified feature calibration of original data; and an abnormal resonance identification algorithm and causal inference are further adopted to extract an equipment transaction association mode, a dynamic equipment trust map is constructed based on Bayesian updating and an attention mechanism, and a map neural network is utilized to intelligently predict a risk diffusion path and high-risk node distribution. The system automatically triggers and issues a graded alarm and protection plan according to a risk cascade threshold value to realize active prevention and control of physical isolation, load degradation and the like, and meanwhile, periodically corrects a risk relationship and model parameters by means of an execution feedback mechanism. High-precision, whole-process dynamic optimization and self-adaptive evolution of power distribution network risk identification can be realized, and the group intelligent protection level and the system stability are effectively improved.

The invention discloses a data asset inventory and blood relationship analysis method, and belongs to the technical field of cloud computing and data asset management. The method comprises the following steps: constructing a unified asset information base by deploying a distributed acquisition agent cluster; performing unified semantic modeling on the metadata to generate a standardized data asset description file; analyzing the data processing log to construct a blood relationship map containing time sequence attributes and dynamic relationship strength; performing multi-dimensional anomaly detection and influence propagation analysis based on the atlas; and carrying out value evaluation and classification on the data assets in combination with topological importance, business value and risk level. According to the method, the problems of metadata dispersion, blood relationship static lag, abnormal influence assessment difficulty and the like in the prior art are solved, automatic checking, blood relationship dynamic tracking and asset value intelligent assessment of the data assets are realized, and the accuracy and decision support capability of data asset management are remarkably improved.

The invention provides an Internet of Things equipment energy consumption big data acquisition and threshold early warning analysis method and system, and relates to the field of Internet of Things and energy consumption monitoring and early warning, and the method comprises the steps: obtaining energy consumption data of unified time slices of equipment in a cluster through a distributed acquisition unit, and converging the energy consumption data into an overall energy consumption distribution data set; the method comprises the following steps: constructing a connection graph which takes equipment as nodes and dependencies as edges according to equipment function dependencies, after node energy consumption is updated, determining a node energy efficiency influence relationship through attention calculation, quantifying the node energy efficiency influence relationship into edge weight parameters, and setting deviation degree thresholds for different equipment in combination with a node reference energy consumption deviation degree and the edge weight parameters; according to the method, abnormal propagation is simulated on a connection graph, node abnormal source probability distribution is calculated, when the node deviation degree exceeds a threshold value, the influence range is determined according to the deviation degree, the edge weight and the probability distribution, single-point, regional and system-level grading early warning is started, energy consumption data can be accurately processed, abnormal sources can be positioned, grading early warning is conducted, and it is guaranteed that cluster energy efficiency is stable.

The application discloses a blockchain-based on-chain and off-chain data similarity and difference positioning system and method, belongs to the technical field of blockchains, and synchronously acquires on-chain block data and off-chain business data by deploying distributed collection nodes; a unique on-chain identification address is allocated to each business entity, and a state anchoring contract is deployed, a corresponding business state sequence record chain is constructed on the chain when the entity completes any business link; the latest node hash on the chain is called and recorded before off-chain operation execution, a new node is generated by driving the chain after operation completion, and a feature vector is constructed by extracting on-chain and off-chain multi-dimensional features; by comparing global hash identification, layered analysis is started when the identification is inconsistent: the first layer verifies the continuity of the business link number and the timestamp; the second layer calculates the cosine similarity of the feature vector to locate specific difference fields and generates a verification digest; finally, the digest is submitted to the on-chain evidence contract, the abnormal type is automatically analyzed, and hierarchical alarm is triggered.

This invention relates to the field of financial data processing technology, and more particularly to a financial data processing method and system based on a cloud platform. The method includes the following steps: distributed collection of multi-source raw financial data; data standardization of the multi-source raw financial data to obtain standard multi-source financial data; matching the standard multi-source financial data with financial scenarios and generating financial scenario identifiers; determining the priority ranking of financial scenarios based on the financial scenario identifiers to obtain scenario priority values; and monitoring the communication network status of the financial cloud platform based on the scenario priority values ​​to obtain scenario network status data. This invention, through data processing technology, network status detection technology, and network fault optimization technology, detects server fault risks and optimizes the server-side fault risk management, improving the stability of the cloud platform; and dynamically adjusts the financial task resource allocation data of the cloud platform to ensure the reliability of financial data.

The invention relates to the technical field of data life cycle management, and discloses an insurance coupon life cycle data tracking management system, which comprises a data acquisition module, a data processing module, a tracking monitoring module, a risk assessment module, a report generation module and an optimization management module, multi-source coupon data are collected in real time through a life cycle event recording unit and a distributed collection unit in the data collection module, and a data format is standardized by using a data preprocessing unit, so that the problems of information loss and distortion caused by transmission delay and interface abnormality can be discriminated in real time, the accuracy and integrity of coupon state data are ensured, and the data processing efficiency is improved. According to the method, data acquisition errors are reduced, external environment variables and user behavior data are integrated in combination with a multi-dimensional analysis unit, risk model parameters are dynamically updated by utilizing an adaptive learning unit of an optimization management module, the card and coupon risk levels can be dynamically corrected in real time in combination with change factors, and timeliness and accuracy of risk assessment are guaranteed.

The invention relates to a remote diagnosis method for industrial solid waste treatment equipment, and the method comprises the steps: collecting multi-mode real-time working condition signals of different parts of the equipment in a distributed manner through multiple types of sensors, and building a multi-source original data set of position labeling and working condition mapping in combination with a geographic position and a working condition label; based on statistics, time domain and frequency domain feature mining, generating high-dimensional feature nodes fused with spatio-temporal information; and constructing a spatio-temporal evolution diagram network, introducing a dynamic graph neural network to learn dynamic association between nodes and a working condition evolution rule, realizing high-precision recognition and threatened trajectory extraction of complex anomalies, and finally generating traceable multi-label anomaly early warning.

The invention discloses a distributed storage test acceleration method and device, electronic equipment and a storage medium, and relates to the technical field of distributed storage. Operation semantics and dependency relationship recognition is performed on a test case of a to-be-tested distributed storage system, and the test case is decomposed into test slices capable of being independently executed; and constructing a multi-layer parallel pipeline comprising a test environment preparation layer, a test data management layer, a test operation execution layer and a test result verification layer based on the dependency relationship to realize parallel processing of test slices. In the execution process, system resources and test slice execution states are monitored in real time, dynamic scheduling distribution is carried out according to monitoring results and dependency relationships, distributed collection and consistency verification are carried out on parallel execution results, and a test report is generated. The problems that in the prior art, due to linear execution of test cases, insufficient resource utilization and lack of systematicness of result verification, the test period is long, resource waste is serious, and test reliability is insufficient can be solved.

The utility model relates to a garbage pool deformation monitoring system which is characterized in that a magnetic hydrostatic level is used for measuring the sedimentation of a garbage pool, an embedded strain gauge is used for measuring the stress change of the garbage pool, and an inclinometer is used for measuring the inclination of the garbage pool; the acquisition terminal comprises an acquisition instrument and a distributed acquisition base station; the acquisition instrument is respectively connected with the magnetostrictive hydrostatic level and the inclinometer, and the distributed acquisition base station is connected with the embedded strain gauge; the monitoring cloud platform is respectively connected with the acquisition instrument of the acquisition terminal and the distributed acquisition base station, and the monitoring cloud platform is used for receiving measurement data of the magnetic hydrostatic level gauge, the embedded strain gauge and the inclinometer and carrying out deformation early warning on the garbage pool according to the measurement data. The deformation monitoring points can be arranged according to the characteristics of the household garbage storage partitions in the garbage pool, data are monitored in the whole life cycle of operation of the household garbage incineration power plant, and production management is effectively guided to ensure the structural safety of the garbage pool.

The invention discloses a park fused salt energy storage quantitative management system and method based on distributed control, and relates to the technical field of energy management. The system comprises a load perception and classification module, a demand quantitative analysis module, an energy storage configuration rule construction module and a partition configuration and scheduling module. According to the method, park load data is acquired through a distributed acquisition terminal, characteristics are extracted, and load classification is completed; calculating an energy consumption gap based on a classification result, and constructing a three-dimensional quantitative index system; establishing a quantitative mapping relation between the load indexes and the energy storage parameters, and forming a regionalized configuration rule base; and calculating matching parameters according to rules, generating a configuration scheme, and realizing partition quantitative configuration and cooperative scheduling. According to the method, accurate load classification, quantitative demand analysis and automatic energy storage parameter matching are realized, the fused salt energy storage configuration precision and the park energy utilization efficiency are improved, and the method is suitable for park distributed energy management scenes.

The application discloses an intelligent fireproof electrical control cabinet operation method, through multi-type sensor distributed collection, a multi-source data set of strong binding of physical position and network topology label is established, accurate normalization, noise suppression and unified feature calibration of original data are realized, further, an abnormal resonance identification algorithm and a cause-effect inference are adopted, an equipment abnormal motion correlation mode is extracted, a dynamic equipment trust graph is constructed based on a Bayesian update and an attention mechanism, a graph neural network is used to intelligently predict a risk diffusion path and a high-risk node distribution. The system automatically triggers and issues a hierarchical alarm and a protection plan according to a risk cascade threshold, realizes active prevention and control such as physical isolation and load degradation, and periodically corrects risk relations and model parameters with the aid of an execution feedback mechanism, the application has high-dimensional space-time monitoring capability, can realize high-precision, whole-process dynamic optimization and self-adaptive evolution of power distribution network risk identification, and effectively improves group intelligent protection level and system stability.

The invention provides an online dynamic adjustment method, system and device for control parameters and a medium, and the method comprises the steps: collecting storage use data from each processor node, processing state fluctuation in a multi-node environment through employing a distributed collection protocol, and obtaining the current storage occupation proportion of each node; determining high-load state nodes by adopting a threshold comparison method according to the current storage occupation proportion of each node; analyzing a storage state of a processor node adjacent to the high-load state node, and determining a target node of the migration task; and sending a part of data packets of the high-load node to a target node through a transmission path based on an encrypted transmission protocol to complete online dynamic adjustment. According to the method, real-time monitoring of the storage state is realized in a multiprocessor environment, and storage resources are dynamically balanced through a collaboration mechanism among nodes.

According to the distributed collection system and the data processing method, in the distributed collection system, clock synchronization of a management node and a working node is carried out through a time sensitive network (TSN), a clock of the working node in the distributed nodes is used as a main clock, clock synchronization of collection modules in the distributed nodes is carried out, and the data processing efficiency is improved. Global clock synchronization of the distributed acquisition system is realized; uniform time information of clock synchronization is added to the sensor data, clock synchronization of the sensor data collected in the distributed collection system is achieved, the sensor data is transmitted to the upper computer through the TSN, and data support is provided for health and prediction diagnosis of equipment.

The utility model discloses an efficient deoxidizing agent stable feeding device in the technical field of deoxidizing agent processing, which comprises a base installed perpendicular to the ground, a machine frame is arranged on the upper surface of the base, a conveying belt is arranged on the inner side of the machine frame in a transmission mode through a motor, and a discharging opening used for discharging is formed in the position, close to the upstream of the conveying belt, of the machine frame. A conveying belt is arranged on the machine frame, a feeding port used for feeding is formed in the downstream position, close to the conveying belt, of the machine frame, a plurality of material collecting grooves distributed at equal intervals are formed in the outer side of the conveying belt, a blocking frame making contact with the conveying belt is arranged on the inner side of the machine frame, the blocking frame is in a U shape, and a material smoothening plate attached to the conveying belt is arranged on the inner side of the blocking frame. According to the efficient stable feeding device for the deoxidizing agent, when the deoxidizing agent is fed to a certain height, the deoxidizing agent can be smoothly tidied into the material collecting groove to be conveyed, the phenomenon that the deoxidizing agent falls back is avoided, a small part of the deoxidizing agent falling back in the tidying process can also be shielded to be circularly conveyed, and the feeding stability is improved.

The invention provides an Internet of Things data acquisition method capable of automatically identifying medical equipment, and the medical equipment is IP-based medical equipment. The distributed acquisition terminals are located on the edge side of the Internet of Things; the method comprises the following steps: an acquisition terminal polls an IP of each medical device in the Internet of Things by using an IP scanning tool, and synchronously polls an MAC to obtain an MAC address corresponding to the IP; the acquisition terminal finds the model of the medical equipment corresponding to the MAC address through a pre-established MAC mapping table stored in an upper computer of the Internet of Things; wherein the corresponding relationship between each MAC address and the model of the medical equipment is registered in the MAC mapping table in a one-to-one correspondence manner; binding the IP with the model of the medical equipment; and the acquisition terminal guides the data stream of the medical equipment to a correct driver so as to carry out data analysis.

The present application relates to a kind of industrial solid waste treatment equipment remote diagnosis method, comprising: by the distributed collection equipment of multiple types of sensors different parts of multimodal real-time working condition signal, in combination with geographical position and working condition label, establish position annotation, working condition mapping multi-source original data set;Based on statistical, time domain and frequency domain feature mining, generate high-dimensional feature node that fuses space-time information;Accordingly, construct space-time evolution graph network, and introduce dynamic graph neural network to learn the dynamic association between nodes and working condition evolution law, realize the high-precision identification of complex anomaly and precursor track extraction, finally generate traceable multi-label anomaly early warning.

The present application relates to the field of agricultural waste resource utilization, biochemical process kinetics control and intelligent agricultural equipment, and particularly relates to an integrated treatment method and system suitable for under-forest free-range chicken manure collection and groove type aerobic fermentation, which breaks through the limitation of traditional mechanical active cleaning, and innovatively utilizes the biological habit of poultry phototaxis and night lodging to construct a distributed collection system of "biological induction gathering + shaftless screw conveying + visual target connection". On the premise of not damaging the original ecological landscape under the forest, unmanned and closed fixed-point extraction of high-dispersion chicken manure is realized, and the artificial transportation cost and secondary pollution caused by scattering are greatly reduced.

This utility model discloses a surface waste sorting device, relating to the technical field of surface waste sorting devices. It includes a body, floats, and a conveyor belt. Floats are installed on both sides of the body, and a conveyor belt is installed at one end of the body. A discharge plate is installed at one end of the conveyor belt, and symmetrically distributed collection plates are installed at the end of the conveyor belt away from the discharge plate. This surface waste sorting device, by starting a drive motor, causes a rotating shaft to rotate via a first gear, which in turn rotates a second gear and a push plate. The rotating push plate vibrates the filter plates, thus screening the falling waste. The sorted waste is then collected inside the collection box. Activating a water pump installed inside the filter box allows spray nozzles to spray water, further cleaning waste adhering to the conveyor belt surface and preventing it from sticking.

The invention relates to the technical field of aquaculture, and discloses a growth information acquisition system for aquaculture, which comprises distributed acquisition node modules deployed in a plurality of key areas of a farm and used for acquiring data through a water quality information acquisition module, a biological information acquisition module and an external environment information acquisition module; the data processing module is used for carrying out denoising, time synchronization and regionalization integration on the acquired data; the data transmission module is used for uploading data of the acquisition nodes to the central data processing unit; the central data processing unit is used for integrating and storing the uploaded data and monitoring the running state of the uploaded data; the water quality information acquisition module comprises a multi-parameter water quality sensor and is used for acquiring temperature, salinity, pH value, dissolved oxygen and ammonia nitrogen. According to the invention, through the reasonable deployment of the distributed acquisition nodes, the key areas, including the center, corners and different depth positions of the water body, of the farm are covered, so that the spatial comprehensiveness and regional representativeness of data acquisition are ensured.

The embodiment of the invention discloses a lock control terminal data analysis method and system applied to intelligent management of a transformer substation, and the method comprises the steps: collecting the historical operation interaction data of each lock control terminal of a target transformer substation through a current distributed collection node, and adjusting the weight of the collection node according to the current state label of the lock control terminal, obtaining a target distributed collection node, collecting current operation interaction data, and determining target operation interaction data; performing feature extraction on the target operation interaction data by using a deep reinforcement learning algorithm in combination with a substation operation rule and a lock control logic, and adaptively adjusting a feature extraction strategy of the algorithm; then inputting the extracted lock control interaction characteristics into an anomaly discrimination model to obtain a lock control state anomaly discrimination result, and generating early warning push information containing a causal derivation knowledge graph and an early warning decision keyword based on the result; therefore, the accuracy and the efficiency of data analysis are improved, and the safety and the reliability of the transformer substation are enhanced.

The invention discloses a mobile network situation data dynamic convergence method based on bandwidth awareness, and belongs to the technical field of mobile communication network operation and maintenance. The method comprises the following steps: acquiring running state data of equipment, links, subnets and services in the maneuvering network through distributed acquisition nodes; measuring and predicting the available bandwidth of each communication link in real time; dynamically adjusting the acquisition frequency, the transmission priority and the aggregation node of the data to realize the aggregation of the situation data; and performing fusion processing on the converged situation data to generate a maneuvering communication comprehensive situation view. According to the method, real-time acquisition, dynamic convergence and visual presentation of multi-dimensional situation data of equipment, links, subnets, services and the like in a maneuvering network can be realized, the acquisition frequency and the data priority are dynamically adjusted based on a real-time bandwidth sensing result, key data transmission is ensured when the bandwidth is insufficient, the data granularity is improved when the bandwidth is sufficient, and the data transmission efficiency is improved. And efficient utilization of resources and dynamic adjustment of comprehensive situation views are realized, and network situation support is provided for command decision making.

This utility model relates to the field of sorting machine technology, specifically disclosing an agricultural product sorting machine, including a base, on which symmetrical supports are fixedly installed. A conveying pipe is fixedly installed between the two sets of supports. Both the supports and the conveying pipe are inclined. A feeding hopper is fixedly connected to the top of the conveying pipe. A sorting port is opened on the bottom surface of the conveying pipe. Symmetrical arc plates are slidably arranged on the conveying pipe. Damping is provided between the arc plates and the conveying pipe. The bottom edges of the two sets of arc plates are both located inside the sorting port, and the distance between the bottom edges of the two sets of arc plates gradually increases from top to bottom. The bottom end of the conveying pipe is provided with graduations on the sides of the two sets of arc plates. Evenly distributed collection boxes are provided on the base, and the collection boxes are all located below the sorting port. This agricultural product sorting machine can easily adjust the sorting size standard according to the size of different types of agricultural products, effectively enhancing the versatility and practicality of the device.

The invention discloses a cluster credibility verification method and device, equipment, a storage medium and a program product, and belongs to the technical field of cluster security. The method comprises the following steps: acquiring starting information of a first network node, wherein the first network node refers to any one network node which is located at the topmost layer in at least one layer and is connected with a management node; starting information of a first sub-cluster is obtained, the first sub-cluster is a sub-cluster corresponding to the first network node, and the first sub-cluster comprises all downstream nodes connected with the first network node; and generating cluster starting information based on the starting information of the first network node and the starting information of the first sub-cluster, wherein the cluster starting information is used for verifying credible starting conditions of all nodes in the cluster by verification equipment. It can be seen that the top network node serves as the information convergent point, distributed collection of the starting information is achieved, the efficiency of the management node for collecting the starting information of all the nodes in the cluster is improved, and then the efficiency of verifying the trusted starting condition of the cluster is improved.

The application relates to the technical field of information collection in the security field, and discloses a vertical information intelligent collection system in the security field, which comprises a data collection module, a data security module, a data classification module and an intelligent analysis module. The data collection module collects global internet open data through distributed collection technology. The data security module adopts anti-collection and anti-tracing technology in the collection process to prevent external tracking and data tracing. The data classification module automatically classifies and structurally processes the collected multi-source information and stores the information in a preset vertical database. The intelligent analysis module analyzes, judges and aggregates the classified information based on an artificial intelligence big model. Through the whole-process closed-loop processing from the collection of vertical information in the security field to the generation of a report, the vertical information intelligent collection system in the security field deeply adapts to the special requirements of regional security events, specific types of public security events, policy and regulation change information and the like in the security field, and prevents the generalization of collection, the shallow analysis and the insufficient report pertinence of a general information collection system in the security field.

This utility model relates to the field of engineering waste gas collection and treatment technology, specifically disclosing an engineering waste gas collection and treatment device, including a treatment box. The treatment box has a cleaning mechanism inside, and multiple left-right distributed collection slots are opened through the upper surface of the treatment box. Each collection slot has a notch at its lower end. Multiple striking balls that move left-right and up-down repeatedly strike the filter screen, thereby promptly cleaning the dust particles adsorbed on the filter screen surface and preventing dust particles from affecting the working efficiency of the waste gas collection and treatment device. When disassembling, maintaining, or replacing the filter screen, the fixing mechanism is released from the mounting plate, and then the filter screen is pulled through the notch from the limiting slot via the mounting plate, allowing for quick disassembly. Installation is done by reversing the operation, thus quickly disassembling and installing the filter screen, effectively improving the efficiency of filter screen disassembly and installation, and facilitating use.

The embodiment of the application discloses a lock control terminal data analysis method and system applied to intelligent management of a transformer substation, the method comprising: collecting historical operation interaction data of each lock control terminal of the target transformer substation through a current distributed collection node, then adjusting the weight of the collection node according to the current state label of the lock control terminal, obtaining a target distributed collection node and collecting current operation interaction data, and then determining target operation interaction data; then, combining the operation rules of the transformer substation and the lock control logic, a deep reinforcement learning algorithm is used to extract features from the target operation interaction data, and the feature extraction strategy of the algorithm can be adaptively adjusted; then, the extracted lock control interaction features are input into an abnormality discrimination model to obtain a lock control state abnormality discrimination result, and based on this, early warning push information containing a cause-effect deduction knowledge graph and early warning decision keywords is generated; in this way, the accuracy and efficiency of data analysis are improved, and the safety and reliability of the transformer substation are enhanced.

Distributed muster includes distributing to different mobile devices an identity of an assigned muster location of an ocean-going vessel, and associating each mobile device both with a corresponding passenger of the ocean-going vessel, and also with the assigned muster location. Thereafter, a timer initiates that defines a period during which a muster drill must be completed by all of the passengers and, in response, a message is transmitted to each mobile device that the muster drill has commenced. During the period, as each mobile device is sensed within a geographically defined area of a correspondingly assigned muster location, a record of the completion of the muster drill by the passenger associated with the sensed mobile device is recorded in the memory. As well, subsequent to a lapsing of the timer, a listing is displayed of any passenger not recorded as having completed the muster drill.

The application provides a distributed excrement intelligent processing system, comprising a distributed collection unit, a processing station unit and a mobile transfer unit. The distributed collection unit is used for collecting excrement of people in each sickbed; the processing station unit is used for connecting an external water source and an external sewage pipeline and receiving excrement of each collection subunit; the mobile transfer unit is used for moving to a position of each collection subunit, connecting an interface module of each collection subunit, providing gas and liquid for cleaning for each collection subunit, receiving excrement discharged by a toilet bowl and transferring the excrement to the processing station unit in response to an instruction of each collection subunit, and the mobile transfer unit comprises a transfer host and a self-checking module, a second control module and a second communication module arranged on the transfer host. The application improves the excrement processing efficiency for disabled and paralyzed people and reduces the work burden of nursing staff.

The embodiment of the invention provides a data acquisition and analysis method, system and equipment of stamping equipment and a medium, and belongs to the field of industrial automation control and industrial Internet of Things. The method comprises the following steps: controlling an IO-Link master station to identify and initialize IO-Link equipment connected with the IO-Link master station; operation data of the stamping equipment are collected through a distributed collection network and transmitted to the PLC, so that mold process parameter matching, sliding block position closed-loop control and clamping device control are executed; and performing real-time analysis and health state evaluation on the operation data, and triggering alarm and safety interlocking control when the evaluation is abnormal. Full-process automation from automatic mold identification and parameter matching, high-precision position closed-loop control of the sliding block to intelligent interlocking of the clamping device is realized; and the production efficiency and the intelligent management level of the stamping equipment are improved while the system cost and complexity are reduced.