1196 results about "Management unit" patented technology

The invention relates to the technical field of safety monitoring, in particular to a bridge safety monitoring system based on sensor data. The method comprises the steps that a sensor measuring unit monitors key physical parameters of a bridge in real time; the data acquisition and transmission unit reads sensor data and transmits the read sensor data; the data processing and analysis unit extracts key features reflecting the health state of the bridge in the sensor data based on a multi-modal physical perception feature fusion method, identifies an abnormal mode in the sensor data through a support vector machine model, and evaluates the remaining life of the bridge based on a carbonization-corrosion-crack closed-loop feedback control rule; and the information management unit stores the analysis result of the data processing and analysis unit and displays the monitored bridge physical parameters. According to the design of the invention, a multi-modal physical perception feature fusion method is introduced, and adversarial learning, graph wavelet transformation and a three-dimensional convolutional neural network are combined, so that high-precision feature extraction of bridge structure response is realized.

The invention provides a BIM intelligent management platform oriented to a whole life cycle of project construction. A building information model, Internet of Things sensing data and a block chain evidence storage mechanism are integrated through a multi-source data fusion technology, and a whole-process data chain of association planning, design, construction, operation and maintenance is associated. The platform adopts space optimization Huffman coding to realize model lightweight, combines a constraint genetic algorithm to optimize a construction path, and applies a bidirectional long-short-term memory network to analyze an equipment state. A three-chain block chain system is reconstructed on the architecture, intelligent association of engineering quantity and payment nodes is realized through cooperation of a main chain, a calculation quantity side chain and an auditing side chain, and mobile terminal offline interaction is supported based on a digital-analog separation technology. The platform covers an intelligent design management unit, a block chain investment management unit, a dynamic correction management unit, a quality safety responsibility tracing unit, an NLP risk management unit and a digital twin operation and maintenance unit. The units achieve cross-system cooperation through a unified data bus, and a closed-loop management architecture covering the whole life cycle of project construction is formed.

A data-driven dynamic energy management system for the adaptive coordination of renewable and conventional energy sources, consisting of: a processing unit configured to perform real-time calculations to optimize the generation, storage, and distribution of electrical energy by continuously analyzing operational data, forecasting future energy demand, and generating control instructions to match available generation resources with forecasted consumption demand; a storage unit connected to the processing unit, configured to store records of historical energy production and consumption, environmental data, operating thresholds and learned model parameters, and to provide said data as input for the forecasting and optimization routines performed by the processing unit; a multitude of IoT-based monitoring units, each comprising at least one sensor configured to measure instantaneous parameters of generation, storage level, consumption rate and environmental conditions, with each monitoring unit being configured to periodically transmit measurement packets to the processing unit via a secure communication network; a forecasting unit implemented in the processing unit, configured to process historical and real-time data to create forecast curves for demand and generation using statistical and probabilistic forecasting techniques, and to dynamically update the weights of the forecasting model in response to observed deviations between forecasted and actual output; an optimization control unit implemented in the processing unit and configured to evaluate the outputs of the forecasting unit together with current operational data to determine a set of optimized control variables representing the target generation contribution of each energy source, and to pass these targets to a lower-level controller for execution; a controller that is communicatively connected to the processing unit and the multiple energy generation sources and is configured to regulate the operation of each source by adjusting the activation state, output level and operating priority based on the control signals received from the processing unit; an energy storage management unit comprising at least one battery array and a power conditioning circuit, configured to receive control instructions from the processing unit, store excess generated energy, release stored energy when forecasted demand exceeds available generation, and report charging and discharging characteristics in real time to the processing unit for continuous recalibration; an alarm and notification control unit connected to the processing unit, configured to continuously compare storage levels and generation reserves with stored operating thresholds, trigger predefined responses when critical or abnormal conditions are detected, and transmit acoustic, visual, and digital remote alerts to designated operators; a user interface terminal connected to the processing unit, configured to display real-time generation statistics, demand forecasts, energy storage status, and system alerts, and to accept operator-defined parameter inputs that are transmitted to the processing unit for recalibration of forecast or optimization parameters; and a secure server interface configured to synchronize operational logs, learning data, and performance indicators with a remote monitoring or analysis server for centralized monitoring, long-term data analysis, and distributed decision support.

The invention discloses a self-adaptive management method and system for intelligent terminal equipment of a distributed power distribution network. According to the method, a self-organizing peer-to-peer communication network covering the whole network is constructed, and neighbor discovery and information sharing among intelligent terminal devices are achieved; the terminal independently completes control instruction calculation based on the local electrical parameters and a preset multi-objective function and optimizes an area control effect through a cooperation mechanism; introducing a self-adaptive adjustment strategy of a control algorithm; when abnormal operation is detected, the terminal can autonomously complete fault positioning and isolation, and power supply recovery is realized based on standby path judgment or micro-grid switching; the central management unit periodically carries out acceptance capacity evaluation, and terminal model parameters are aggregated in a federated learning mode; the terminal has an edge autonomous capability, and can maintain local control and data retention when communication is interrupted. The system has the characteristics of quick response, flexible structure, intelligent cooperation, high adaptability and the like, and is suitable for intelligent operation and management and control scenes of various types of power distribution systems.

The invention relates to the technical field of quantum communication security, and discloses a quantum key distribution secure communication system based on a quantum mechanics principle. The system comprises a quantum state preparation unit which controls a quantum emission device to output a quantum state sequence containing a preset polarization angle and a phase modulation photon group; a quantum channel feature extraction unit captures channel environment interference parameters and constructs a photon polarization distribution matrix; a quantum communication security evaluation unit receives the matrix, and calculates a channel security coefficient threshold through a quantum bit error rate analyzer; the quantum key dynamic optimization unit generates an optimized key segmentation strategy in combination with a security coefficient threshold and a historical key negotiation record; the quantum key rotation control unit switches quantum state modulation parameters according to a segmentation strategy and a time window; and the quantum node synchronization management unit monitors node clock offset and injects a calibration signal to realize key distribution time slot alignment. The system can dynamically cope with environmental interference, and improves the security and adaptability of quantum key distribution.

The invention relates to an AI server cooling water pump vibration quantity self-adaptive calibration test method and system, an intelligent test platform integrates a six-dimensional force sensor and a temperature compensation vibration exciter, the platform rigidity is automatically calibrated, a water pump-pipeline system transfer function is obtained, and a rotating speed-lift-modal frequency three-dimensional mathematical model is established; a three-axis MEMS accelerometer array is arranged at sensitive parts such as a water pump bearing seat and a motor shell, and vibration, current and pressure signals are synchronously collected; carrying out time-frequency domain signal processing by adopting variational mode decomposition in combination with self-adaptive S transformation, and extracting a 128-dimensional full-frequency domain feature vector containing a modulation side frequency band; effective values of vibration acceleration, speed and displacement are calculated through a frequency domain integration algorithm, and current harmonic interference is corrected through an electromagnetic vibration compensation model; and finally, a vibration health degree evaluation model containing 18 characteristic parameters is established based on a support vector machine, the test system comprises an intelligent test platform unit, a multi-source sensing unit, an edge calculation unit and a data management unit, and microsecond-level synchronous acquisition and GB-level data throughput are realized through a time sensitive network. And online incremental learning and automatic generation of a test report are supported. The method has the effect of improving the water pump vibration quantity test precision.

The invention discloses a self-correction structured bid evaluation guide method for public resource transaction, and relates to the field of resource transaction processing, the method is based on a bid evaluation system, and the method comprises a data preprocessing unit, a structured analysis unit, a rule unit, an intelligent evaluation unit, a workflow management unit, a report generation unit and a data filing unit. Historical similar project scoring data is analyzed based on a large language model through an intelligent review unit, a real-time scoring reference interval is generated, expert experience and data driving are combined, professional judgment is reserved, scoring randomness is reduced through data quantification, a workflow management unit adopts an LSTM neural network to construct a review behavior prediction model, and the review behavior prediction model is used for predicting the review behavior. According to the method, the degree of deviation between expert scores and predicted values is compared in real time, meanwhile, multi-party review cases are integrated based on federal learning to form a dynamic knowledge base, review after the event is changed into real-time monitoring and intelligent intervention, the objectivity of bid evaluation is enhanced, and subjective item scores tend to be standardized.

The invention discloses a soft network system capable of expanding a transmission mode and an implementation method, and the system comprises an equipment resource mapping management unit which automatically generates a unique channel code based on a native hardware interface and establishes a multi-dimensional mapping relation; the heterogeneous interface data acquisition unit is used for monitoring various hardware interfaces in a kernel space in parallel and realizing zero-copy data transmission through a three-buffer lockless annular buffer area; the transmission abstraction and dynamic expansion unit realizes transmission mode modularization in a plug-in form and supports atomic hot plug during operation; the protocol analysis and service processing unit is used for realizing unified scheduling and fault isolation in a single process through a dynamic link mechanism; and the cross-layer monitoring and self-healing unit realizes automatic switching based on a session state machine and a redundant channel. According to the method, the code complexity is reduced from O (N * M) to O (N + M), and the time lt is extended; fault switching is carried out at 1s; and the hardware cost is reduced by more than 40%, so that the method is particularly suitable for power and environment monitoring scenes with more than 1000 devices and more than 15 protocols, and has high creativity.

The invention relates to the technical field of power transformation equipment state monitoring, in particular to a power transformation equipment multi-parameter intelligent sensing and state monitoring system which comprises a sensing unit, a data processing unit, a state analysis and diagnosis unit and an upper computer monitoring and management unit. Through data collection preprocessing, lightweight AI model anomaly preliminary screening and hierarchical edge cloud cooperative transmission strategies, efficient cleaning of original data, rapid edge end anomaly identification and optimal utilization of network resources are realized, data transmission bandwidth occupation is greatly reduced, monitoring real-time performance is improved, and the method is suitable for large-scale popularization and application. The method integrates technologies such as digital twinning, federated learning and a time-space attention network, realizes equipment cross-time-space fault accurate positioning, fault type reliable identification and residual life dynamic prediction in combination with a quantification algorithm, triggers hierarchical early warning through hierarchical health assessment, and provides scientific and accurate decision support for refined operation and maintenance of power transformation equipment.

The invention provides an intrusion prevention method, a management unit, a system and a storage medium, and relates to the field of network security, and the method comprises the steps: collecting context operation data corresponding to a to-be-tracked asset object in a kernel, and carrying out the security management of the context operation data, and obtaining a first target security control strategy corresponding to the to-be-tracked asset object; and mounting a first target BPF byte code corresponding to the first target security control strategy in a Linux security module so as to monitor and defend the target asset object through the Linux security module. Or in response to the security policy configuration request, extracting a second target security control policy from the security policy configuration request; and when the second target security control strategy is activated, mounting a second target BPF byte code corresponding to the second target security control strategy in the Linux security module. Therefore, through the above intrusion prevention method, the embodiment of the invention can immediately block attacks and improve the convenience of maintenance and deployment.

The invention discloses a vertical retaining structure displacement automatic monitoring device and a monitoring method thereof, and relates to the technical field of displacement automatic monitoring, and the device comprises a data acquisition unit which is used for configuring monitoring nodes, obtaining sensor data monitored at the top of a retaining wall, and preprocessing the sensor data to obtain effective inclination angle data; the displacement conversion unit is used for recognizing and optimizing the attitude angle by using a dynamic Kalman filtering algorithm, and calculating a displacement value of the vertical soil retaining structure by combining the vertical distance from the bottom to the top of the soil retaining wall; the monitoring and early warning unit is used for uploading the displacement value of the vertical retaining structure to a remote data platform, constructing a monitoring network, analyzing and predicting the deformation trend of the retaining wall and triggering early warning according to an analysis result; and the battery management unit is used for providing battery state monitoring and management. The displacement of the top of the retaining wall can be accurately sensed and monitored through the inclination angle data, and comprehensive and accurate monitoring is ensured by adopting an attitude solver and a dynamic Kalman filtering algorithm.

The invention discloses a memory test system and method, a board card and a server. The memory test system comprises an out-of-band management unit and a target chip, the out-of-band management unit sends a pressure test instruction to the target chip through the preset communication interface, the pressure test instruction comprises dynamically adjusted test strength parameters, and the pressure test instruction is generated based on a preset instruction set; the target chip performs calibration verification on the target memory in response to the pressure test instruction; after the calibration verification is passed, a test load is applied to the target memory according to the test strength parameter, and a cyclic pressure test is executed; the target chip collects test data generated in the pressure test process and transmits the test data back to the out-of-band management unit through the preset communication interface, and the out-of-band management unit generates structured test data according to the test data. Compared with the prior art, the situation that normal services are interrupted due to testing in a traditional testing method can be avoided, and the availability and stability of the system in the testing process are guaranteed.

An offline pre-training and online fine-tuning apparatus based on reinforcement learning includes a data management unit collecting and processing data for offline reinforcement learning in advance; an offline model training unit training an offline policy network and an offline state-action value function network using a previously collected dataset that includes a state, an action, a next state, a reward, and an accumulated reward collected by the data management unit; and an online model training unit performing fine-tuning to update parameters of the offline policy network using an online dataset that includes action information determined based on state information acquired through interaction with the offline policy network and an environment, state information at a next time point according to the action information, and the reward, and the previously collected dataset.

The invention discloses a management system of a server and the server, relates to the technical field of computers, and realizes efficient interconnection and centralized management between a plurality of computing nodes and a management module by introducing an interface module between the computing module and the management module. Specifically, each computing node comprises a computing unit and a programmable logic device, a plurality of computing nodes are connected through the programmable logic device in the interface module, and the first management module obtains the operation data of each computing node through the interface module, so that the design that one management module manages multiple nodes is realized, the management units can be reduced, and the management efficiency is improved. And the cost is reduced, so that the expandability and the management efficiency of the system are improved.

The invention relates to the technical field of electric power asset management, and discloses an electric power equipment full life cycle management system based on a digital twinning technology, and the system comprises a causal knowledge graph construction unit, a strategy rule learning unit, a decision option value quantification unit, a combined decision optimization unit, and a maintenance decision voucher management unit. The method comprises the following steps: constructing a knowledge graph containing a causal relationship among equipment, environment and management activities; carrying out anti-fact deduction based on the atlas to dynamically learn strategy rules; quantizing the value of the potential maintenance decision by adopting a physical option model; performing combination optimization under resource constraints of budget, spare parts and the like to generate an optimal decision combination; and finally, generating a standardized maintenance decision voucher for the decision in the combination. According to the method, decision-making flexibility and environment uncertainty can be quantified into specific economic values, future-oriented and globally optimal resource allocation is realized, and a decision-making process and a decision-making result are solidified into traceable and manageable digital assets.

In a storage device including a plurality of controllers for controlling data reading and writing operations with respect to at least one host computer, each of the controllers includes: a cache region to which a plurality of management units capable of temporarily storing the data are allocated in accordance with the data reading and writing operations; and a control unit for controlling the data reading and writing operations, and when an error occurs, the control unit determines whether or not an occurrence position of the error is in the cache region, and when it is determined that the occurrence position is in the cache region, the control unit excludes, among the plural management units, a specific management unit that contains the occurrence position from an allocation target in the cache region, to control the data reading and writing operations using remaining management units in the plural management units.

The invention relates to the technical field of environmental engineering, in particular to an intelligent operation management platform and method for a tail water constructed wetland of a large sewage plant, and the operation management platform comprises a monitoring system device which is used for collecting wetland monitoring data in real time, and transmitting the collected wetland monitoring data to an analysis and storage module; the analysis storage module is used for analyzing the wetland monitoring data to obtain structured monitoring parameter data; the operation scheduling management module comprises a scheme management unit used for storing a plurality of regulation and control schemes; the operation control unit is used for regulating and controlling the regulation and control object equipment by adopting preset scheduling logic according to the current monitoring parameter data and the regulation and control scheme; the operation and maintenance management unit is used for sending an inspection work order to a mobile terminal of a corresponding operation and maintenance worker according to a preset inspection plan; and the evaluation module is also used for receiving the inspection result data reported and sent by the mobile terminal of the operation and maintenance personnel and evaluating the inspection result data by adopting a preset rule to obtain an evaluation result.

The invention relates to the technical field of the Internet of Things, in particular to a sewage detection and analysis system based on the Internet of Things, which comprises a data acquisition unit, a data transmission unit, a data processing and analysis unit and a monitoring and management unit. According to the invention, the self-adaptive bionic sensor array integrating self-cleaning and fault self-healing functions and the mobile patrol robot with autonomous navigation, obstacle avoidance and refined retest capabilities are combined with signal optimization and equipment management of the front-end processing and self-maintenance module; continuous and accurate acquisition and stable operation of multi-dimensional parameters in a complex sewage environment are realized, and a high-quality data source is provided for subsequent data processing, so that the coverage range, data quality and pollution abatement decision efficiency of sewage monitoring are remarkably improved, and fine management and rapid emergency response of the complex sewage environment are effectively supported.

This application provides a data processing method and apparatus. The method includes: after a first management unit sends a first request message corresponding to a first write request message, and between receiving a first response message, if other write requests with the same cacheline address as the first write request message are received, then multiple data items with the same cacheline address are written into the cache space corresponding to the first management unit, and then the data is written into the storage space corresponding to the second management unit. This reduces the interaction between the second management unit and the data during multiple data write processes, thereby effectively reducing data processing latency and improving the overall efficiency of data processing.

The invention relates to the technical field of building energy consumption analysis, and discloses a building energy consumption and carbon neutralization analysis system based on big data analysis, which comprises an acquisition unit, an analysis unit, a calculation unit, a deficit unit, a judgment unit and a carbon neutralization management unit, and is used for generating a carbon neutralization management instruction of a target object according to a carbon neutralization urgency index, performance degradation of a target object along with increase of service life is captured, an analysis unit combines real-time carbon emission data of a power grid, generates a dynamic carbon track slope and reflects a carbon emission change trend in real time, a calculation unit performs segment processing on operation duration based on big data, and a complete-cycle carbon track vector is constructed. A healthy deficit degree and a stepped urgency index are generated through big data analysis of the deficit unit and the judgment unit, and finally a management instruction is output by the management unit, so that the problem of insufficient tracking of full-life-cycle energy consumption attenuation and carbon emission increment of a target object by traditional analysis is effectively solved, and the accuracy of long-term carbon neutralization planning is greatly improved.

The invention discloses an irrigation oasis regulation potential quantification and targeted intervention strategy generation method and system, and the method comprises the steps: dividing a target irrigation oasis region into a plurality of management units, obtaining the multi-source data of all management units, and calculating the coupling coordination degree of each management unit; the management unit with the coupling coordination degree smaller than the regulation lower limit serves as a unit needing to be regulated, and the difference value between the coupling coordination degree of the unit needing to be regulated and the corresponding regulation lower limit or regulation upper limit serves as the regulation potential; constructing and training a Bayesian causal network, and calculating mutual information or belief variance of each driving node of the unit needing regulation and control to a target node by adopting the probability output by the trained Bayesian causal network according to the coupling coordination degree and the index of the unit needing regulation and control; and taking the driving node with the highest mutual information or belief variance as a main control factor of the corresponding unit needing to be regulated and controlled, and searching a targeted intervention strategy of the unit needing to be regulated and controlled in the factor-strategy knowledge base by adopting the main control factor.

The invention discloses a hydraulic engineering scheduling simulation system based on digital twinning, and relates to the technical field of hydraulic engineering scheduling, the hydraulic engineering scheduling simulation system comprises an acquisition component, a processing component, an analysis component and a scheduling simulation component, the analysis component comprises an ecological analysis unit, a collaborative scheduling unit and a dynamic scheduling management unit, and the scheduling simulation component performs linkage simulation, simulation scene setting, multi-dimensional verification and an exception handling mechanism. Multi-dimensional ecological parameters are integrated through the ecological analysis unit, ecological health is comprehensively and quantitatively evaluated to fill up the limitation of a single index, and multi-target parameters such as flood control and power generation are integrated through the collaborative scheduling unit and converted into unified priority to solve the problem of fuzzy scheduling targets. And the dynamic scheduling management unit integrates multiple detail parameters to generate an accurate and adaptive instruction, so that the execution effect is ensured, and the hydraulic engineering scheduling simulation system has excellent practicability.

The invention relates to the technical field of ground disaster prevention and control report generation, in particular to an intelligent ground disaster prevention and control report generation method and system based on indoor and outdoor work integration. Retrieving geological information of the associated area, and determining the type of a hidden danger point; matching a target template; generating a target template directory structure; calling a workflow agent module according to a directory structure sequence to generate a first draft text; inserting chart data into the first draft text to obtain a complete report; and performing compliance examination and optimization on the complete report, and outputting a final report. The generation system comprises a data acquisition module, an intelligent retrieval engine, a template management unit, a workflow scheduling center and an examination optimization module. The data acquisition module, the intelligent retrieval engine, the template management unit, the workflow scheduling center and the review optimization module are connected in sequence and realize data transmission; synchronous real-time updating of indoor and outdoor data is met, data dispersion and information omission are avoided, and the generation efficiency and accuracy of a ground disaster prevention and control report are improved.

The invention discloses a yaw collecting ring temperature intelligent control system, method and device, a medium and a product, and relates to the field of wind power generation, and the method comprises a temperature collection unit which is used for collecting temperature information of the surface of a collecting ring in real time; the temperature characteristic analysis unit is used for processing the temperature information to obtain a multi-dimensional temperature characteristic value; the data management unit is used for collecting multi-dimensional temperature characteristic values to construct a historical database; the temperature prediction and abnormality diagnosis unit is used for obtaining a temperature prediction result and an abnormality judgment result based on historical data in the historical database and the real-time multi-dimensional temperature characteristic value; the temperature control unit is used for adjusting the working temperature of the collecting ring on the basis of the real-time temperature information when the temperature prediction result exceeds a preset safety threshold value or the abnormity judgment result shows an abnormal condition; according to the method and the device, the crossing from passive control to active prediction can be realized, so that the problem that predictive maintenance is difficult to realize in the traditional technology is effectively solved.

The invention discloses an intelligent memory chip high and low temperature test device and a test tuning method, and relates to the technical field of memory chip testing, the device comprises a test unit used for constructing a cold and hot test environment for a to-be-tested memory chip; the power supply unit is used for providing direct current for each unit; the management unit is used for detecting environment data in real time and uploading the environment data to the data acquisition and analysis server, and regulating and controlling the environment data in a closed-loop manner by combining a test instruction; the excitation generator is used for generating and sending test excitation for the to-be-tested storage chip according to the test instruction, recording test data and feeding back the test data to the data acquisition and analysis server; and the data acquisition and analysis server is used for pre-judging faults of the to-be-tested storage chip based on an AI model according to the real-time environment data and the test data, optimizing test instruction parameters or storage chip FTL algorithm parameters, generating a dynamic regulation and control test instruction and issuing the dynamic regulation and control test instruction. According to the invention, accurate test and optimization of the memory chip in an extreme temperature environment can be realized.

The invention relates to the technical field of artificial intelligence and automatic driving, and discloses a space-time constraint end-to-end automatic driving system and method based on a unified VLA model, and the system comprises a unified encoder, a computing power management unit, a core neural network and an output decoder. A gating operator embedded into a core neural network is used for calculating characteristic information entropy and computing power consumption in real time, and through topology reconstruction logic based on entropy and computing power joint constraint, computational graph collapse operation is dynamically triggered at an instruction level, so that network reasoning depth is adaptively expanded along with physical time constraint, and the network reasoning accuracy is improved. According to the method, isomorphic mapping of the topological structure of the calculation model and the physical time constraint is established, the deterministic delay upper limit under the extreme working condition is determined, the problem of dimension mismatching of an existing static calculation graph under the hard real-time constraint is solved, and optimal bit allocation of calculation resources in the time dimension is achieved.

The invention provides a PLC integrated digital twinning control enhancement system and method, and relates to the technical field of cloud PLC control, a PLC integrated development environment module comprises an instruction set generation unit, a digital twinning function plug-in library and a PLC compiler unit which are connected in sequence, the instruction set generation unit comprises an FB library, a PLC control instruction generation unit, a control instruction mapping form and a server intermediate variable set which are connected in sequence; the PLC operating environment module comprises a protocol processing unit, a PLC main control logic unit and a server driving program which are connected in sequence, the PLC main control logic unit comprises a DT decision triggering subunit, and the server driving program comprises a strategy control subprogram and a virtual control instruction sending subprogram; the DT decision triggering subunit is connected with the server driving program; and the PLC virtual space module comprises a client driving unit, a virtual IO management unit and a data analysis unit which are connected with one another.

The invention discloses a high-frequency and power-frequency data processing method and system of a double-core electric energy meter and the electric energy meter, and belongs to the field of electric power systems.The method comprises the steps that the double-core electric energy meter comprises a metering unit and a management unit, the metering unit obtains a first power-frequency analog signal through a first processing link, and the management unit obtains a second power-frequency analog signal through a second processing link; a first power frequency digital signal is obtained through filtering, analog-to-digital conversion and numerical calculation, a first high-frequency current analog signal is obtained through a second processing link, a second high-frequency current analog signal is obtained through filtering, the two kinds of signals are transmitted to a management unit through analog and digital signal channels respectively, and time alignment is carried out based on a time synchronization method. Therefore, by means of the electric energy meter, the problems that in the prior art, the sensing frequency band of an electric energy meter is narrow, and the legal function and illegal function coupling degree is high can be solved.

The invention discloses a swimming pool water quality management system and method based on intelligent regulation and control of residual chlorine concentration, and belongs to the technical field of swimming pool water quality management. According to the system, water quality parameters are monitored in real time at the frequency of one second through residual chlorine, pH, turbidity and water temperature sensors, after filtering processing is conducted through a data acquisition module, the adding amount is dynamically calculated through an intelligent adding algorithm in combination with a preset residual chlorine target range, and then accurate adding is conducted through a high-precision metering pump. Meanwhile, the water quality comprehensive management unit automatically adjusts the pH value to a preset range, and a flocculating agent is regularly added to reduce the content of organic matters. When the residual chlorine concentration is lower than 0.3 mg / L or higher than 1.0 mg / L, early warning is triggered, and all monitoring data, adding records and early warning information are synchronously stored in a local server and a cloud database; water quality real-time monitoring and dynamic accurate regulation can be realized, and safety and stability of water quality of the swimming pool are guaranteed.

The invention relates to the technical field of computer system simulation, in particular to a simulation system based on a hierarchical transaction-level modeling protocol. The simulation system based on the hierarchical transaction-level modeling protocol comprises a control module, a data module and an adaptation module, the control module is a central management unit, is connected with the data module and the adaptive module through a control bus, and is used for managing load information of each node and realizing a time sequence management mechanism; the data module is a core communication hub, comprises a transaction-level modeling protocol stack and is connected with the adaptation module through a transaction bus; and the adaptive module is an equipment interaction layer, comprises a protocol conversion unit, is connected with the external simulation module or equipment through the corresponding protocol conversion unit, and is used for converting a signal connected with the physical bus into a transaction bus signal. According to the simulation system based on the hierarchical transaction-level modeling protocol, the simulation time precision is improved, the expansibility is improved, and the development and maintenance cost is reduced while the simulation efficiency is effectively improved.