401 results about "Control measure" patented technology

The invention discloses a distribution cable branch box state monitoring method based on state recognition, and particularly relates to the technical field of power monitoring, and the method comprises the steps: collecting multi-dimensional operation data of a plurality of branch boxes in a continuous time period, and constructing a state evolution sequence; calculating a state offset score and an adjacent equipment state consistency score to judge whether an evaluation process is triggered or not; after triggering, constructing a state influence probability map, identifying an abnormal influence path, extracting a state disturbance diffusion index and a cooperative behavior deviation index, inputting into a pre-trained risk identification model, generating a risk level interval and a cause probability distribution vector, executing an influence regulation and control measure, and updating a state identification logic; according to the method, dynamic perception of the state of the branch box is realized by constructing a state evolution sequence, combined judgment of individual and group behaviors is realized by combining a state offset score and an adjacent equipment state consistency score, and a risk level interval and cause probability distribution vector are used for driving regulation and control strategies and map updating. And the monitoring precision and the self-adaptive capability of the system are improved.

The invention discloses a mine safety risk prevention and control method and system based on multi-source data fusion, and particularly relates to the technical field of mine safety monitoring, and the method comprises the steps: obtaining surface topography, an underground geologic structure and real-time monitoring parameters through remote sensing images, drilling data and dynamic monitoring equipment, and constructing a mining area geologic database with consistent time and space; fusing geologic feature data, integrating earth surface and underground feature data by using a three-dimensional geologic modeling technology, and mapping dynamic monitoring parameters into a model to generate a dynamic geologic feature field; performing clustering analysis on the abnormal feature points based on a spatial clustering algorithm, and calibrating a potential safety hazard region; calculating a regional risk comprehensive index by combining the risk values of the dynamic features, the geological features and the spatial features; early warning is triggered in a graded mode according to the comprehensive index, prevention and control measures are put forward, and the evaluation model is dynamically updated; comprehensive support is provided for mine potential safety hazard area monitoring and safety management decision making, and the method is suitable for risk management scenes of complex mining areas.

The invention discloses a failure chain quantitative analysis and risk assessment method and system based on a multi-level security model, and aims to solve the defects that accident cause analysis of a complex social technology system is inaccurate, and a risk assessment result is lack of effective verification. According to the method, a multi-level causal model is systematically constructed, a multi-dimensional failure chain (MDFC) is extracted, multi-dimensional risk quantification is performed on the MDFC, a directed weighted failure propagation network is constructed based on the multi-dimensional risk quantification, and structural features of the directed weighted failure propagation network are analyzed to identify key risk factors. The core innovation of the method is that reverse accident reason tracing and forward risk propagation path analysis based on the weighted network are fused, mutual verification and iterative optimization are realized by comparing analysis results of the two paths, so that the understanding of an accident evolution mechanism is deepened, and the reliability of evaluation is improved. The system vulnerability can be revealed more comprehensively, powerful support is provided for formulating accurate risk control measures, and the overall safety level of a complex system is improved.

The invention discloses a tension optimization control system and method for a tensioning device of an underground coal mine belt conveyor, and relates to the technical field of tensioning device optimization control. The method comprises the steps that S1, multi-source tensioning data are collected in real time, and data preprocessing is conducted on the multi-source tensioning data; s2, predicting a coal flow load based on historical multi-source tensioning data, and taking a dynamic compensation measure for a tensioning device; s3, in combination with the multi-source tensioning data and the coal flow load prediction result, collaborative distribution is carried out on the hybrid execution mechanism, and automatic regulation and control are carried out based on the collaborative distribution result; s4, abnormity is detected in real time based on the multi-source tensioning data, and early warning is carried out; s5, performing safety risk assessment according to the real-time multi-source tensioning data, and taking adaptive regulation and control measures in combination with a safety risk assessment result and an anomaly detection result; the problem that faults are caused due to the fact that high-frequency pulsation and short-time impact of belt tension are difficult to adjust in time is solved.

The invention relates to the field of intelligent traffic safety, in particular to a hazardous chemical substance transportation path dynamic risk prevention and control system and method based on space-time fusion, and provides a method for calculating a multi-dimensional risk index matrix through a risk index quantification module and combining a space-time environment sensitivity prediction matrix generated by an environment sensitivity analysis module. According to a risk spreading probability cloud picture of the risk spreading prediction module, accurate evaluation of the dynamic risk of the road section is realized; the system establishes a collaborative risk factor assessment model, adjusts a safety threshold according to historical accident data, and generates a space-time road network risk scoring matrix; the risk prevention and control decision module determines an early warning level, selects prevention and control measures, optimizes a transportation path, formulates an emergency response plan for a high-risk road section, and outputs an intelligent decision instruction set; according to the system, comprehensive quantification of hazardous chemical substance characteristics is realized, and the comprehensiveness of risk assessment and the intelligence of prevention and control decision making are improved.

The invention discloses a dynamic flow control method for a two-phase cold plate liquid cooling system based on multi-modal sensing, and relates to the technical field of equipment cooling. Comprising the following steps: S1, collecting liquid cooling monitoring data in real time, and performing data preprocessing; s2, judging the state risk of the cold plate, carrying out signal cross validation, and taking an abnormal regulation and control measure; s3, cooling liquid flow regulation and control are carried out, and the matching degree of flow regulation and control and chip thermal load is evaluated, so that flow regulation and control correction is carried out; and S4, constructing a big data modeling and simulation feedback platform, evaluating a flow regulation and control self-healing effect, optimizing each parameter and strategy, and carrying out self-learning evolution. The problems that an existing two-phase cold plate liquid cooling system generally only depends on a single temperature signal, lacks a multi-source redundancy check mechanism, has the problems of response lag, weak local reflection capacity, high risk during failure and the like, consequently, the cooling capacity distribution and adjustment precision is insufficient, and the actual requirement of a high-heat-density data center for heat dissipation is difficult to meet are solved.

The invention discloses a coal mine rock burst risk assessment system which comprises a data acquisition module, an energy accumulation rate calculation module, a roadway network modeling module, a risk assessment module and an early warning regulation and control module. The method comprises the following steps of: firstly, calculating an energy accumulation rate of a roadway, then constructing a roadway network diagram, identifying a high stress conduction path, calculating a dynamic risk index and delimiting a risk area by integrating factors such as a historical impact event and an energy index, and automatically triggering corresponding early warning and regulation measures by a system according to a risk level so as to realize accurate early warning and dynamic regulation. And mine operation decision making and accident prevention are assisted.

The invention discloses an engineering construction quality safety risk management system, and belongs to the technical field of safety risks. Comprising a project management module, a quality safety risk management and control module, a compliance review and data analysis module, an integrated project management module, a risk identification and evaluation module, a risk prevention and control strategy module, a dynamic monitoring and early warning module, an accident handling and tracing module, a compliance review auditing module and a data analysis report module. According to the invention, basic information and design parameters of construction projects are collected through the project management module, a BIM model is established, construction simulation, conflict detection and resource optimization are carried out, an actual construction plan and schedule are formulated, multivariate data in the construction process are collected in real time, early recognition, evaluation and positioning of construction safety quality risks are realized by using the model, and the construction safety quality risk is evaluated and positioned. A risk prevention and control strategy is formulated, key parameters are monitored in real time, early warning is given out immediately when data exceed a threshold value, a risk model and prevention and control measures are improved, and efficiency and safety are improved.

The invention relates to the technical field of security management and control, in particular to an intelligent security dynamic identification management and control system, which comprises a multi-mode sensing module, a high-definition camera array, a millimeter-wave radar, an infrared sensor, an RFID reader-writer and a data processing module, and is used for receiving data of the multi-mode sensing module, carrying out time-space alignment and data fusion processing, and sending the data to the multi-mode sensing module. And personnel features, article features and environment features are extracted. The system also comprises an artificial intelligence analysis module and a user interaction module. According to the intelligent security dynamic identification management and control system, an artificial intelligence analysis module constructed by using a deep learning algorithm can perform real-time analysis and prediction on personnel behaviors, article states and abnormal events, discover potential safety hazards in advance and take corresponding management and control measures, thereby realizing conversion from passive defense to active prevention and control. For example, the system can give an alarm in time according to multi-dimensional information such as temperature change, smoke concentration and abnormal behaviors of people at the initial stage of a fire, so that precious time is won for people evacuation and fire extinguishment.

The invention discloses an intelligent control system for a high-precision emulsifying pot, relates to the field of intelligent control, and is used for collecting multi-dimensional data such as temperature field distribution, material rheological characteristics, liquid drop behaviors and mechanical states in real time through distributed sensors and monitoring the emulsifying process in real time. The system evaluates the phase stability risk level by adopting a multi-source data fusion technology, and dynamically adjusts the process parameters such as the stirring rotating speed, the emulsifier flow and the heating power according to the risk level. For a high-risk state, by analyzing the correlation between a temperature field and torque fluctuation, an abnormal reason is accurately identified, and a targeted regulation and control measure is triggered. A liquid drop coalescence monitoring mechanism is introduced into the system, and when liquid drop coalescence exceeds the standard, temperature compensation is automatically enhanced. The system has a self-learning capability, dynamically optimizes a risk judgment threshold according to historical data, and improves the control precision.

The invention discloses a liquefied natural gas (LNG) early warning system and method for dynamically monitoring an LNG ship, and the method comprises the steps: collecting the output amount, cabin pressure, environment temperature and pump operation parameters in real time, combining a multi-factor correction model to dynamically calculate the actual evaporation rate, and reversely setting an allowable evaporation rate threshold according to the maximum capability of a BOG processing system; the evaporation rate is ensured to be within a safe range through a grading alarm mechanism and safety regulation and control measures; the problem that in the prior art, static testing cannot reflect evaporation rate changes in real time is solved. Liquefied natural gas whole life cycle monitoring and performance degradation early warning of the LNG ship are achieved.

The invention provides a shale oil gathering and transportation pipeline leakage risk analysis and safety prevention and control method which comprises the following steps: establishing an FTA model to analyze a pipeline leakage accident of a shale oil gathering and transportation pipeline, and defining pipeline erosion as a key risk factor causing the pipeline leakage accident; performing quantitative risk analysis on pipeline leakage by using a Bayesian network, and calculating the probability of pipeline leakage; establishing a pipeline erosion model in Fluent software, and simulating reasons of pipeline leakage risks; establishing a pipeline leakage diffusion model of the shale oil gathering and transportation pipeline in FLACS software; performing grid division on the pipeline leakage diffusion model; setting pipeline leakage output gas components and component proportions in the pipeline leakage diffusion model; setting a pipeline leakage aperture and leakage pressure in the pipeline leakage diffusion model; setting factory environment parameters; analyzing a shale oil and gas leakage diffusion rule by using FLACS software; and formulating pipeline leakage risk safety prevention and control measures based on quantitative analysis of influence factors before and after pipeline leakage.

The invention discloses a quality control and real-time supervision system for pile foundation concrete, which comprises a data storage unit and a man-machine interaction terminal, and is characterized by further comprising a supply and demand matching module, a detection distribution module, a quality monitoring module and a plurality of detection units bound with unique detection numbers. Through automatic supply and demand matching of a pile foundation project and a stirring station and random distribution of the detection units, bidirectional real-time detection of delivery and entry of concrete can be realized to prevent unqualified concrete from flowing into a pile foundation construction site, and meanwhile, automatic judgment and sending of different warning information can be realized, so that the construction efficiency is improved. Therefore, different responsible subjects can be reminded to check the quality safety risk of the concrete in time and take corresponding control measures.

The invention discloses a soft rock TBM jamming risk intelligent prediction method based on numerical mechanism guidance, and the method comprises the following steps: S01, building an extrusion soft rock stratum TBM dynamic tunneling whole process refined numerical simulation model which comprises a TBM cutterhead, a front, middle and tail step shield, soft rock, a segmental lining and a backfill material behind a wall, and simulating an evolution process; s02, systematically calculating and analyzing surrounding rock geological parameters, TBM tunneling parameters, TBM construction parameters and TBM construction parameters, and constructing a machine blocking index numerical value sample library; s03, predicting the large deformation of the soft rock and the extrusion load of the shield, fusing TBM rock-machine interaction multi-source data in actual engineering, and establishing a soft rock TBM jamming risk intelligent prediction model; and S04, evaluating the TBM jamming risk, and verifying the effectiveness of the prevention and control measures. According to the technical scheme, the whole process of dynamic interaction between the TBM and the soft rock can be comprehensively considered; the TBM jamming disaster occurrence mechanism is explained, and the generalization ability of the machine learning method in practical application is improved.

The invention discloses a real-time emergency prevention and control system and method for an electrochemical energy storage system based on digital twinning, and belongs to the field of energy storage safety. The system comprises a multi-source sensing unit, a digital twin deduction unit and a visual emergency decision unit. The sensing unit collects multi-source data to form a state vector; the deduction unit outputs a future thermal runaway evolution path containing a temperature field, a gas concentration field and a fire blast risk probability and uncertainty measurement thereof in real time through a pre-trained Gaussian process regression agent model; and the decision-making unit performs three-dimensional visual rendering, jointly determines a high-confidence risk area based on the risk level and the uncertainty level, and generates an emergency prevention and control instruction with accurate spatial positioning. The problems that in the prior art, disaster evolution paths cannot be predicted in real time, and prevention and control measures are extensive are solved, millisecond-level online deduction and accurate active prevention and control of the thermal runaway process are achieved, and the safety of an energy storage system is remarkably improved.

The invention provides a petroleum and natural gas station operator labor protection appliance wearing detection method and system, and relates to the technical field of article detection, and the method comprises the steps: collecting the image data of an operator in real time through an image collection device, and calling a deep learning model to detect the wearing state of a labor protection appliance; according to the method, the technical parameters, the equipment state and the hazard source distribution data are combined to evaluate the hazard level and generate a wearable normative score and a risk trend value, a deep reinforcement learning algorithm is adopted to execute management and control measures, and detection parameters and processing strategies are continuously optimized, so that intelligent and dynamic management of safety protection of operators is realized, and the safety operation level of a station yard is improved.

The invention discloses a black soil erosion simulation system with rainfall runoff and snow melting confluence coupling effect. The system comprises a data acquisition system, a rainfall simulation system, a snow melting simulation system, a runoff collection and monitoring system, a black soil simulation area, a data processing and analysis system and a control system. The data acquisition module comprehensively collects various types of data of the black soil area; each simulation subsystem accurately simulates rainfall, snow melting and coupling processes; the runoff collecting and monitoring subsystem monitors runoff in real time; the black soil simulation area simulates the field condition; the data processing and analysis module deeply mines data, establishes a model and predicts a trend; and the control system realizes automatic accurate control. The whole system adopts a modular design and is convenient to maintain and upgrade. The operation, system flow, maintenance upgrading and application cases of each module are elaborated through a specific implementation mode, a powerful tool is provided for black soil erosion research, and a scientific basis is provided for making prevention and control measures.

The invention discloses a continuous rigid frame aqueduct cantilever casting hanging basket stress monitoring and early warning method and system, and relates to the technical field of hydraulic engineering construction.The method comprises the steps that stress monitoring points and displacement monitoring points are arranged, and a stress-displacement double-system collaborative sensing model is constructed; carrying out double-channel vibration noise separation on the stress signal and the displacement signal which are collected in real time; respectively calculating wet weight values based on a stress-wet weight nonlinear mapping relation and a displacement-wet weight geometric inversion model, and verifying the consistency of wet weight value measurement results through a residual checking mechanism; constructing a multi-source driving safety threshold model, and generating a dynamic safety threshold in real time; and when the monitored wet weight value exceeds the dynamic safety threshold value, triggering graded early warning and executing risk control measures. According to the stress-displacement dual-system independent measurement and cross checking method, through a vibration frequency domain compensation algorithm, vibration interference is suppressed, a multi-source driving safety threshold model is constructed, and high-precision monitoring of the stress of a continuous rigid frame aqueduct cantilever casting hanging basket is achieved.

The invention discloses a ship ballast water tank water level real-time monitoring and remote control device, and relates to the field of ship ballast water tank water level control. According to the real-time monitoring and remote control device for the water level of the ship ballast water tank, a first data acquisition and analysis unit is used for acquiring water level monitoring data of each ballast water tank of a ship to be controlled in real time and analyzing the water level monitoring data to obtain an adjusted water level value; the second data acquisition and analysis unit is used for acquiring the ship state monitoring data and the sea condition monitoring data, analyzing to obtain a ship state water level regulation factor and a sea condition water level regulation factor, and analyzing to obtain a corresponding comprehensive water level regulation factor; the water level monitoring value of the corresponding ballast water tank is obtained through the comparison control unit, the water level monitoring value and the water level control interval are analyzed, and control measures are taken based on the analysis result so as to ensure that the water level of the ballast water tank can be corrected in time under the severe sea condition. Therefore, the sailing safety of the ship is enhanced.

The invention provides a subway tunnel water disaster risk evaluation method under extreme rainfall based on multi-source data, and belongs to the technical field of urban rail transit disaster prevention. The method comprises the following steps: establishing a grading evaluation system on the basis of field rainstorm monitoring data, hydrogeological parameters, field geological exploration, rock-soil physical and mechanical parameters, monitoring data of a tunnel lining structure and material strength parameters of a tunnel site area in combination with a plurality of developed tests, dividing corresponding grades and determining an influence index-; and S4, respectively carrying out weight calculation on the influence index-by adopting an analytic hierarchy process and an entropy weight method, then calculating a dynamic weight of the influence index-, correcting an abnormal dynamic weight, generating a comprehensive score, dividing risk grades, matching graded prevention and control measures, and optimizing and adjusting the prevention and control measures in real time through a parameter risk grade dynamic judgment and construction method matching mechanism. According to the method, minute-level accurate interpretation of a disaster evolution mechanism and dynamic optimization adaptation of a prevention and control scheme are realized.

The embodiment of the invention provides an online evaluation method and device applied to a product. The method comprises the steps of obtaining a to-be-admitted product; for the to-be-admitted product, determining a plurality of first indexes of the to-be-admitted product under the inherent risk assessment dimension and a plurality of second indexes of the to-be-admitted product under the control measure effectiveness dimension; determining a first evaluation result according to the plurality of first indexes and the corresponding first risk attribute information, and determining a second evaluation result according to the plurality of second indexes and the corresponding second risk attribute information; determining a target risk level of the to-be-accessed product according to the first assessment result, the second assessment result and a predetermined risk assessment table; and determining an online evaluation result of the to-be-admitted product according to the target risk level. According to the technical scheme of the embodiment of the invention, the online evaluation result of the to-be-admitted product is obtained according to the inherent risk evaluation dimension and the control measure effectiveness dimension, whether the product has non-compliant transactions or not is evaluated more comprehensively, and the supervision efficiency and accuracy are improved.

The invention relates to the technical field of tunnel engineering safety prevention and control, and provides a gypsum rock tunnel water disaster risk evaluation and prevention and control scheme selection method which comprises the following steps: step 1-3, based on parameters such as rock mass structural integrity, stratum karst development degree, water yield property, groundwater corrosivity, gypsum rock mineral composition, expansibility and corrosion property, establishing a grading evaluation system, dividing corresponding grades and determining influence indexes R1-R8; 4, adopting an AHP method, an entropy weight method and a CRITIC method to perform multi-dimensional weight calculation on the subjectivity, objectivity and conflict influence indexes, correcting abnormal weights in combination with expert experience and verification rules, generating a comprehensive score, dividing risk grades, and matching graded prevention and control measures; and 5, optimizing and adjusting prevention and control measures in real time through a parameter risk level dynamic judgment and construction method matching mechanism. According to the method, multi-source parameter dynamic empowerment can be fused, and a full-life-cycle prevention and control method with accuracy, timeliness and self-adaptability is provided for tunnel engineering.

The invention relates to an ultra-deep well perforation test combined operation tubular column safety evaluation method. The method comprises the following steps that S1, a packer lower portion perforation detonation annulus pressure evolution finite element model and a dynamic negative pressure evolution numerical model after perforation detonation are established; s2, establishing a perforation instant tubular column coupling impact vibration evolution model, and determining main control factors; s3, establishing a dynamic evolution numerical model of the shock absorber at the moment of perforation, and obtaining a dynamic evolution model of the lower oil pipe of the packer, the shock absorber and the perforating gun at the moment of perforation; and S4, evaluating the safety of the pipe column at the lower part of the packer by taking the Mises yield criterion as an evaluation standard. The influence of perforation detonation transient wellbore pressure and dynamic negative pressure on a lower tubular column system of the packer is fully considered, the dynamic response rule of the tubular column is disclosed through numerical simulation and theoretical analysis, risk control measures are put forward, and the safety of the packer is improved. Theoretical basis and technical support are provided for optimal design of an ultra-deep well perforation test combined operation scheme and safety of an oil testing process.

The invention relates to the technical field of tunnels and underground engineering, and discloses a water inrush and mud inrush dynamic variable weight risk assessment and active regulation and control method. The method comprises the following steps: determining a water inrush and mud inrush disaster type of each paragraph in a tunnel and a corresponding risk disaster-inducing factor; establishing a risk assessment index system of each water inrush and mud inrush disaster type; establishing a preliminary risk assessment model, a secondary risk assessment model and a dynamic risk assessment model according to the variable weight strategy and the constant weight vector in combination with the risk assessment index system; and sequentially evaluating the tunnel by using the preliminary risk evaluation model and the secondary risk evaluation model, taking active risk regulation measures, and dynamically evaluating each section after regulation by using a dynamic risk evaluation model to obtain a dynamic risk evaluation level. Through dynamic variable weight risk assessment and active regulation and control measures, the risk assessment accuracy and the risk regulation and control effectiveness of water inrush and mud inrush disasters in tunnel construction are improved, and a powerful guarantee is provided for safe and efficient construction of tunnel engineering.

The invention provides a bridge health monitoring and intelligent control method and system based on machine learning, and the method comprises the steps: carrying out the distributed sensing data collection of a bridge structure, generating a structure monitoring data set, carrying out the spatial-temporal feature extraction, and obtaining a vibration response feature sequence and a traffic load feature sequence of the bridge structure; performing correlation analysis on the two sequences, generating a structural damage sensitive feature matrix, performing damage evolution trend prediction based on the structural damage sensitive feature matrix, generating damage development probability distribution of the bridge key component, and generating a dynamic traffic control instruction according to the damage development probability distribution. The dynamic traffic control instruction comprises a vehicle passing parameter dynamically adjusted based on a damage degree quantitative index, and sending the dynamic traffic control instruction to a traffic management system. According to the invention, the accuracy of bridge health monitoring and the dynamic adaptability of control measures can be improved.

The invention discloses an early warning grade evaluation method based on an urban pollution industrial site, relates to the technical field of industrial site early warning evaluation, and solves the technical problems of incomplete overall evaluation and lack of systematic analysis process and data processing correction caused by analysis of a single evaluation index. According to the method, pollution factor indexes are integrated in a three-dimensional mode through the pollutant standard exceeding multiple mean value, the specific pollutant toxicity coefficient and the pollution plume diffusion area proportion, the pollution intensity is reflected, toxicity hazards and spatial diffusion risks are considered, the soil pollution area is calculated through the Kriging interpolation method, the groundwater pollution plume area is predicted through the MODFLOW model, and the groundwater pollution plume area is predicted through the MODFLOW model. The overlapping area is processed through a maximum area method, repeated statistics is avoided, the accuracy of pollution range data is improved, different threshold values are set, standardized matching of comprehensive indexes and early warning levels is achieved, corresponding management and control measures are defined for all the early warning levels, abstract comprehensive indexes are converted into specific practical operation guidance, and hierarchical management and control can be conveniently carried out.

The invention discloses an electric power subsynchronous resonance suppression system and method, and relates to the technical field of electric power, and the system comprises a monitoring unit which collects the operation data of an electric power system in real time; the analysis unit is used for evaluating the subsynchronous resonance risk of the power system by applying an algorithm and an analysis tool based on the acquired data; the execution unit is used for adopting corresponding control measures to suppress the subsynchronous resonance according to the analysis result; the communication and interface unit is used for realizing data communication and interface connection among the unit modules; and the protection and fault processing unit is used for monitoring the running state of the system and detecting and processing faults. According to the invention, analysis results and decisions from the analysis unit are received, and corresponding control instructions are quickly executed, so that subsynchronous resonance can be inhibited in time, and further damage to a power system is prevented; through precise control of the series capacitance compensation device control module and the power system operation mode adjustment module, flexible adjustment of the electrical characteristics and the operation mode of the power system can be realized.

The invention provides a train forward operation risk assessment method based on an operation risk domain, and the method proposes the concept of the operation risk domain based on a field theory, constructs a train forward operation risk assessment model based on the risk domain, and constructs operation risk domain models in two scenes of train tracking and foreign matter invasion. And the forward operation risk of the train is evaluated in real time, and management and control measures are given, so that the real-time and quantitative evaluation of the forward operation of the train is realized, and the construction of an autonomous safety guarantee system of rail transit is promoted.

This invention discloses a state monitoring method for distribution cable branch boxes based on state recognition, specifically relating to the field of power monitoring technology. It involves collecting multi-dimensional operational data from multiple branch boxes over a continuous time period to construct a state evolution sequence; calculating state deviation scores and adjacent equipment state consistency scores to determine whether an assessment process is triggered; after triggering, constructing a state influence probability map, identifying abnormal influence paths, extracting state disturbance diffusion indices and cooperative behavior deviation indices, inputting these into a pre-trained risk identification model, generating risk level intervals and causal probability distribution vectors, executing influence control measures, and updating the state recognition logic. This invention achieves dynamic perception of branch box states by constructing a state evolution sequence, combines state deviation scores and adjacent equipment state consistency scores to achieve joint judgment of individual and group behaviors, and drives control strategies and map updates using risk level intervals and causal probability distribution vectors, thereby improving monitoring accuracy and system adaptability.

The invention discloses a transient stability control method and system for a power system with equilibrium point continuation after disturbance, and the method comprises the steps: firstly building a steady-state mathematical expression of each dynamic element, and constructing a solving model of a system equilibrium point in combination with a power network equation; then, a homotopy method is introduced, homotopy parameter values at saddle node bifurcation points are solved, and whether balance points still exist in the system or not is judged; and for the condition of system instability, further deriving the sensitivity of the fault parameter of the homotopy curve at the saddle node bifurcation point to each control variable, and optimizing the adjustment strategy of the adjustable parameter in combination with the sensitivity and the control cost. Through a systematic search method, the optimal control scheme with the lowest cost is determined on the premise that the stability margin is met, and therefore the economical efficiency and effectiveness of control measures are improved. The optimization adjustment direction of each adjustable parameter can be accurately identified, the effectiveness of a control scheme is ensured, and accurate operation is provided for stability recovery of a power system.