46 results about "Fuzzy membership function" patented technology

The invention discloses a hierarchical optimization scheduling method for deep peak regulation of thermal power generating units, and the method comprises the following steps: system layering: dividing a power system into a plurality of subsystems, each subsystem comprising a thermal power generating unit cluster and differentiated load demands; subsystem-level prediction: generating a basic scheduling plan; dynamic preference-driven multi-target collaborative optimization: receiving multi-target data from each subsystem, carrying out multi-target collaborative optimization, modeling three targets of a power grid company, an environmental protection department and a terminal user as game participants, quantifying the priority of each party by adopting a fuzzy membership function, generating a dynamic game solution through a Nash equilibrium solver, and carrying out multi-target collaborative optimization; screening out a Pareto optimal solution giving consideration to interests of multiple parties; performing online verification on the dynamic security domain; virtual synchronous machine cooperative support: simulating operation characteristics of a synchronous generator; and global coordination and iterative optimization: uploading the optimal scheduling scheme of each subsystem to a scheduling center through a message queue telemetry transmission protocol, and performing global constraint verification.

The invention discloses a 5G base station energy-saving control method and system, relates to the technical field of communication, and provides a 5G base station energy-saving control method for solving the problem that resources are overused or idle in the prior art, and the method comprises the steps: monitoring a real-time load; analyzing business requirements; intelligent decision making; if it is judged that the component meets the dormancy condition, sending a dormancy instruction to the component to enable the component to enter a dormancy state; if it is judged that the component meets the wake-up condition, a wake-up instruction is sent to the component, so that the component returns to the normal working state. According to the method, whether various hardware components in the base station meet the dormancy or awakening condition or not is accurately judged through the intelligent decision algorithm, dynamic optimal configuration of hardware resources is achieved, and overuse or idling of the hardware resources is effectively avoided. According to different types of hardware components and business requirements, the weight coefficient and the fuzzy membership function of each factor are flexibly adjusted, the prediction accuracy and reliability are improved, and the expandability and the flexibility are high.

This invention relates to the field of power system generation scheduling and discloses a method for risk analysis and control of pre-flood energy storage in cascade hydro-wind-solar complementary systems. Taking the pre-flood energy storage as a constraint, a dry-season drawdown model and a flood-season water storage operation rule are established to define simulation criteria. A comprehensive set of indicators, including dry-season power shortages, flood-season water spillage, inadequate year-end energy storage, and wind and solar power curtailment, is constructed to quantify multi-stage, multi-source operational risks. By coupling Monte Carlo simulation with fuzzy membership functions, the method characterizes multidimensional uncertainty scenarios and their probabilities, and analyzes the quantitative relationship between pre-flood energy storage and system benefits, risk probabilities as well as losses. Simulation results demonstrate that precise risk characterization coupled with proper storage control increases annual generation by 580 million kWh while reducing average risk-induced losses by 42%, demonstrating substantial practicality.

The invention discloses a cross-domain HDR image dynamic ghosting removal method fusing statistical offset fuzzy membership, and the method comprises the steps: carrying out the ghosting removal of an LDR image sequence through employing a trained fuzzy statistical cross-domain ghosting removal model, and obtaining a ghosting-free HDR image; according to the model, after an input LDR sequence is subjected to preprocessing and feature extraction, a space context alignment module dynamically aligns non-reference frame and reference frame features through space-channel attention; meanwhile, the LDR image sequence is input into a statistical offset fuzzy membership module, and a membership graph is generated through sliding window statistical analysis and a fuzzy membership function; the aligned features are input into a multi-scale cross-domain cooperative processing module, multi-scale feature extraction and feature fusion are carried out, a frequency attention module is activated through membership graph gating, and global context modeling is introduced into a key region; and finally, outputting a high-quality ghosting-free HDR image. According to the method, fuzzy statistics and cross-domain processing are fused, and accurate ghosting removal and detail reservation in a dynamic scene are realized.

The invention discloses a small and micro enterprise loan availability evaluation method, which belongs to the technical field of data processing, and integrates unstructured operation and semi-structured behavior data, establishes a dynamic data confidence evaluation matrix, and starts artificial recheck to guarantee data quality. And constructing a three-layer fuzzy membership function system, and generating a standardized score by using an improved interval type-2 fuzzy set and an alpha-cut algorithm. Defining an interest rate sensitive dimension, generating an initial interest rate hierarchy through an improved spectral clustering algorithm, and predicting operation fluctuation and adjusting parameters by using a double-layer LSTM (Long Short Term Memory). And through IPC cross validation, carrying out residual analysis on the fuzzy data and on-site collected data, generating a joint confidence interval through D-S evidence fusion, and evaluating loan availability and outputting a suggestion report on the basis of the joint confidence interval. According to the method, the existing evaluation data processing problem is effectively solved, evaluation scientificity, accuracy and comprehensiveness are improved, a reliable decision basis is provided for financial institutions, and accurate customer layering and product adaptation are assisted to be achieved.

The invention discloses an NSGA-II-based power grid emergency scheduling method and system under extreme disasters, and relates to the technical field of power grid emergency management and optimization, and the method comprises the steps: collecting power grid data, building power grid side and user side optimization targets, and constructing a multi-target scheduling model; generating an optimal solution set of the multi-target scheduling model through population initialization, genetic crossover mutation operation and non-dominated sorting; and calculating the satisfaction degree of a multi-target scheme by using a fuzzy membership function, and comprehensively evaluating and selecting an optimal scheme. According to the method, the multi-objective optimization model is constructed, the chromosome coding mode is improved, the fuzzy membership function is introduced, and the number of first-aid repair teams, task allocation and path optimization are subjected to comprehensive scheduling, so that the problems of complex power grid first-aid repair scheduling tasks, low response efficiency and insufficient utilization of first-aid repair resources under the flood disaster condition are solved; and the effects of improving the response speed of the first-aid repair task, optimizing the resource utilization rate and realizing optimal balance in time, resources and task completion degree are achieved.

The invention discloses a three-phase transformer winding top deformation diagnosis method based on high-voltage oscillation wave detection, and relates to the field of transformer safety guarantee and fault diagnosis. Firstly, a mechanical device for controlling deformation enables the top of a winding of a transformer to generate deformation of different degrees, and deformation of the winding of the transformer is simulated. And the high-voltage oscillatory wave test device is further used to obtain oscillatory wave test curves under different fault degrees. Finally, according to the diagnosis method based on the high-voltage oscillatory waves, normalization processing is carried out on transformer winding oscillatory wave time sequence signals through a normal cumulative distribution function, a time sequence is mapped to a discrete symbol sequence, then the entropy value of the symbol sequence is calculated through a fuzzy membership function, and the high-voltage oscillatory waves are obtained. The method can effectively reflect the irregularity and complexity of the signal. The deformation fault of the three-phase power transformer can be safely and efficiently detected and diagnosed, and a guarantee is provided for power transmission safety.

The embodiment of the invention provides a decision negotiation method and device based on a depth deterministic policy gradient. The method comprises the following steps: receiving negotiation scene information input by a first negotiation party; wherein the negotiation scene information comprises a plurality of negotiation topics, a preference value interval for each negotiation topics and a preference weight value for each negotiation topics; for each negotiation topic, creating a invention for the negotiation topic according to the preference value interval and the preference weight value of the negotiation topic; wherein the utility model comprises corresponding trapezoidal fuzzy membership functions when negotiation values are in different preference value intervals, and an overall satisfaction function for performing weighted summation on the trapezoidal fuzzy membership functions of all negotiation dimensions; a first reference value of the first negotiation party is predicted through a pre-trained Actor-Critic network; and receiving a first negotiation value input by the first negotiation party according to the first reference value, and sending the first negotiation value to a second negotiation party, thereby facilitating determination of the negotiation value.

The invention provides a boiler soot blowing control method and a related device, and relates to the technical field of boiler operation control. Performing image processing on the initial image of the boiler heating surface to obtain a processed image, performing mapping operation on pixel coordinates of the processed image and actual reference coordinates of the boiler heating surface to obtain a mapping result, and obtaining a region image corresponding to the soot blower based on the mapping result, carrying out dust deposition identification operation on the regional image to obtain a dust deposition identification result, calculating regional attribute information of the regional image according to the dust deposition identification result, determining a fuzzy membership function boundary value corresponding to the regional attribute information, constructing a self-adaptive fuzzy membership function by using the fuzzy membership function boundary value, and obtaining a self-adaptive fuzzy membership function; and determining a fuzzy quantity corresponding to the regional attribute information by using an adaptive fuzzy membership function, determining a soot blowing parameter of a soot blower corresponding to the regional image according to the fuzzy quantity corresponding to the regional attribute information and the fuzzy rule base, and controlling the corresponding soot blower to perform soot blowing operation according to the soot blowing parameter.

An active vibration damping control method based on an adaptive neuro-fuzzy inference system, belonging to the technical field of vibration isolation control. The method includes: constructing a system model and collecting data; designing an ANFIS model based on the state variables of the platform; the ANFIS model automatically adjusts the parameters of the fuzzy membership function through training with experimental data; training the ANFIS model based on a hybrid learning algorithm; using sensors to obtain the displacement and velocity of the platform in real time and inputting them into the ANFIS model to achieve real-time active vibration damping control. By collecting the displacement and velocity data of the platform in real time and inputting them into the ANFIS model, the system can dynamically calculate the control signal, quickly respond to vibration changes, effectively suppress vibration and reduce the vibration amplitude of the system, ensuring the stability of the platform. Through the feedback loop of the sensor and the control system, it is ensured that the system can automatically adjust the control signal according to the actual vibration state of the platform at any time.

This invention relates to a vehicle differential lock control method, terminal device, and storage medium. The method includes: S1: constructing a first fuzzy membership function, a second fuzzy membership function, and a fuzzy rule inference table; S2: real-time acquisition of environmental values, road grade, and road curvature values, obtaining the maximum value of road curvature; S3: obtaining all corresponding first fuzzy intervals and fuzzy values ​​from the first fuzzy membership function based on the road curvature ratio; S4: obtaining all corresponding second fuzzy intervals and fuzzy values ​​from the second fuzzy membership function based on the environmental values; S5: matching the first fuzzy intervals with the second fuzzy intervals to obtain a combined fuzzy value of the fuzzy interval combination; S6: taking the fuzzy interval combination corresponding to the maximum value as the fuzzy decision combination, and obtaining the decision result from the fuzzy rule inference table; S7: controlling the differential lock based on the decision result. This invention achieves timely differential locking of the vehicle in weather conditions such as rain and snow when slight slippage occurs during normal driving.

The application discloses a kind of multi-sensor data fusion and online reconfiguration method based on planetary topology structure, including the following steps, construct three-layer multi-sensor data fusion framework based on planetary topology structure, with sensor as outer layer satellite, the subsystem of two two combinations of sensor as middle layer planet, inner layer is main filter;Two-stage fault detection unit is set in satellite and planet layer, sensor fault information is provided by sensor, the effective probability of subsystem is obtained by substituting chi-square test value into fuzzy membership function by subsystem;Filter system reconfiguration table is designed, when fault occurs, the influence brought by fault is reduced online when system reconfiguration is carried out to multi-sensor data fusion system;Finally, global state estimation is completed in inner layer main filter based on the fault information of sensor and subsystem.

The invention discloses a rescue training efficiency evaluation system and an optimization method thereof, and belongs to the technical field of efficiency evaluation, the rescue training efficiency evaluation system comprises a data acquisition module used for collecting performance data and situation data of rescue personnel in simulated training; the fuzzy logic processing module is connected to the data acquisition module and is used for fuzzifying the performance data and establishing a fuzzy rule base; according to the method, a fuzzy logic theory is adopted, specific performance data of ambulance personnel in simulation training is converted into a fuzzy set, accurate numerical values are mapped to a fuzzy concept, a fuzzy membership function is defined, a system constructs the fuzzy set for each evaluation index, and therefore the data are allowed to cross traditional classification boundaries, and the accuracy of the ambulance personnel is improved. And the uncertainty and continuity of the performance of the ambulance personnel can be better captured.

The invention relates to the technical field of satellite navigation, and provides a GNSS / INS positioning system fault processing method and system, and the method comprises the following steps: constructing a GNSS / INS positioning system model; judging whether the GNSS observation data is normal data or not based on the GNSS board card information; lateral jump fault detection based on a fuzzy membership function; judging whether the fault in the GNSS observation process is a small lateral jump fault or not according to the fault probability and the lateral jump threshold value; and updating the initial measurement noise into adaptive measurement noise to obtain positioning information. By adopting multi-stage screening and judgment and combining the fuzzy membership function to perform fault detection, the detection accuracy of the small lateral jump fault can be greatly improved, and the reliability and accuracy of the positioning result are improved.

The invention provides a fuzzy analytic hierarchy process-based oil-water well extraction control property judgment method and equipment, and relates to the technical field of oil-gas field development, and the method comprises the following steps: determining multiple indexes influencing an oil well end control decision, including daily oil production, daily liquid production, daily water production, water content, single-layer oil production, oil production intensity and the like; all indexes are weighted through an analytic hierarchy process, and statistical analysis is introduced into weight determination, so that weight calculation is more objective and accurate. And mapping each index value into the membership degree of the oil well end control or the water well end extraction by adopting a fuzzy membership function. And the weighted membership degree of each index is synthesized, comprehensive evaluation values of the single well in the two categories of oil well end control and water well end extraction are calculated, and the extraction control property of the well is judged according to the comprehensive evaluation values. According to the method, information of multiple levels and uncertainty factors can be comprehensively considered, the accuracy and scientificity of liquid extraction and water control decision making are improved, and the method is suitable for comprehensive treatment and development optimization of the high-water-content oil field.

The application provides a kind of pumped storage unit water turbine operating condition starting process performance multi-index fusion calculation method, relating to pumped storage power station technical field. Including Step1, data standardization;Step2, using fuzzy membership function to convert the data after standardization into fuzzy evaluation matrix;Step3, calculate information entropy;Step4, calculate variation coefficient;Step5, determine adaptive weight from information entropy in Step3 and variation coefficient in Step4;Step6, calculate starting process comprehensive performance score;Starting process comprehensive performance score is obtained by weighted summation, while introducing nonlinear adjustment factor to enhance the degree of differentiation. Through fuzzy membership function processing the uncertainty of index, using information entropy theory to determine the index weight objectively, and introducing adaptive mechanism to dynamically adjust weight distribution, so as to realize scientific, objective comprehensive evaluation of multi-index system.

The invention discloses a gas turbine power turbine rotating speed compound control method based on SMC-PID. The method comprises the steps that a cluster of state space models is established at multiple steady-state points of a gas turbine, scheduling parameters are selected, a scheduling method based on a weighted fuzzy membership function is adopted, scheduling weights are determined by calculating the correlation degree of the scheduling parameters and the steady-state points, and an LPV model of the gas turbine is established; performing discretization processing on the classic PID control law by taking the rotating speed as a control target to obtain a PID control model; based on the established LPV model, constructing a dynamic sliding mode surface model fusing a power tracking error and a change trend thereof; the basic fuel quantity is obtained according to the PID control model, the fuel flow compensation value is obtained according to the dynamic sliding mode surface model, the basic fuel quantity and the fuel flow compensation value are added to obtain a final fuel flow control signal, and the rotating speed of the gas turbine is controlled. According to the embodiment, the adjusting time is shortened under the typical working condition, the overshoot is reduced, and sliding mode buffeting is restrained; and the rotating speed deviation is controlled and is fast and steady, and the robustness is better.

The present invention relates to the field of satellite navigation technology, and provides a GNSS / INS positioning system fault handling method and system, including the following steps: constructing a GNSS / INS positioning system model; judging whether GNSS observation data is normal data based on GNSS board card information; lateral jump fault detection based on a fuzzy membership function; judging whether the fault in the GNSS observation process is a small lateral jump fault according to the fault probability and the lateral jump threshold; updating the initial measurement noise to an adaptive measurement noise to obtain positioning information. By adopting multi-level screening and judgment and combining a fuzzy membership function for fault detection, the detection accuracy rate for small lateral jump faults can be greatly improved, and the reliability and accuracy of the positioning result can be enhanced.

The invention discloses an intelligent resource scheduling method and system based on water affair data, and the method comprises the steps: achieving the real-time collection and preprocessing of multi-modal water affair data through an edge calculation node, guaranteeing the data quality and safety through an adaptive sampling strategy and differential privacy protection, and achieving the non-tampering evidence storage of the water quality data; a demand prediction model based on a space-time diagram neural network is adopted, accurate prediction of partitioned water consumption is achieved through space-time convolution and a gating attention mechanism, an improved multi-target particle swarm algorithm is adopted, water supply stability, energy consumption minimization and leakage suppression are taken as targets, and an optimal scheduling scheme is screened in combination with a dynamic inertia weight and a fuzzy membership function; virtual deduction is carried out through a digital twin system, pressure abnormity is visualized, an intervention strategy is recommended, pump set operation is optimized in combination with a time-of-use electricity price strategy, and agent adding is dynamically adjusted based on water quality prediction. According to the method, the water supply stability can be improved, the energy consumption and the leakage rate are reduced, and the reliability and economy of a water affair system are remarkably improved.

The application relates to a daily power consumption prediction method based on a fuzzy membership function, which comprises the following steps: step S1: constructing a time sequence of historical daily power consumption and historical air temperature by taking date as an index; step S2: establishing a fuzzy membership function; step S3: taking the maximum Pearson correlation coefficient as an objective function, and optimizing the parameters of the fuzzy membership function through a meta-heuristic algorithm; step S4: converting the historical air temperature and the predicted air temperature into relevant factors based on the optimized fuzzy membership function, and marking the relevant factors as covariates; and step S5: establishing a time sequence prediction model, training the model by using the historical daily power consumption and the historical covariates, and finally inputting the predicted covariates to calculate the daily power consumption prediction value. The application fully utilizes weather forecast data, and effectively improves the accuracy of daily power consumption prediction of a power grid.

This invention discloses a method for constructing a trust mechanism for electricity market transactions based on blockchain, relating to the field of electricity market transaction technology. The specific steps of this construction method are as follows: S100, data collection and feature fusion: collecting electricity user equipment operation data, electricity consumption behavior pattern data, power grid interaction data, as well as electricity market transaction price fluctuation data, historical default records, and power grid operation status data. By utilizing the distributed ledger characteristics of blockchain, this invention achieves encrypted storage and tamper-proofing of multi-dimensional information such as electricity user equipment operation data, electricity consumption behavior pattern data, power grid interaction data, and electricity market transaction price fluctuation data, effectively preventing data forgery and tampering. At the same time, by using fuzzy membership functions to create an initial credit scoring model and combining it with a real-time monitoring and scoring update mechanism, this invention can dynamically adjust the credit scores of trading entities, ensuring the accuracy and timeliness of credit assessment.

The invention discloses a damming river fish migration habitat reconstruction method based on fuzzy interval planning. The method comprises the following steps: step 1, constructing a multi-target ecological scheduling model; the objective function of the multi-objective ecological scheduling model is to minimize the supersaturated TDG level and maximize the generating capacity; step 2, constructing constraint conditions of the target function; the constraint conditions comprise a water level balance constraint, an upstream and downstream water level constraint, a flow constraint, a power generation limitation, a supersaturated TDG horizontal constraint and a reservoir area flow velocity constraint; wherein the reservoir area flow velocity constraint is constrained by adopting a fuzzy membership function; and step 3, based on the constraint condition, solving the objective function, and according to the obtained solution, completing the reconstruction of the fish migration habitat of the damming river. According to the method, the cascade reservoir area flow velocity uncertainty multi-target ecological scheduling model considering fish migration safety is constructed, and the fish migration safety requirement and the power generation requirement can be considered.

The application discloses a ball and link system control method based on fuzzy sliding mode and periodic event triggering, first constructs a state space equation of the system and carries out regular transformation to obtain a standard system model; then, a fuzzy sliding mode switching function is established in combination with a fuzzy membership function, and a periodic event triggering mechanism is designed; on the basis, a periodic event triggering fuzzy sliding mode controller is constructed, an actual sliding mode band is constructed by analyzing a periodic sampling error, state trajectory is ensured to enter the band in a limited time and remain in the band, and the reachability of the sliding mode surface is ensured; then, a controller gain matrix is solved based on stability analysis of the sliding mode, is brought into the controller to complete closed-loop control on the ball and link system, and a system sampling period is established. The application uses the fuzzy membership function to design the sliding mode surface, has lower conservativeness, and uses the periodic sampling to design the event triggering mechanism, theoretically eliminates the Zeno phenomenon, and provides an efficient control scheme for a system with limited network and communication resources.

The invention discloses a land surface remote sensing virtual constellation selection method and device, a medium and equipment. The land surface remote sensing virtual constellation selection method comprises the following steps: retrieving a candidate satellite list meeting requirements from a pre-constructed virtual constellation domain knowledge graph according to an input query demand; generating a plurality of groups of candidate virtual constellations according to the candidate satellite list, and calculating an observation capability index of each candidate virtual constellation; constructing a fuzzy membership function according to a preset fuzzy comprehensive evaluation requirement, and calculating a single-factor evaluation matrix according to the fuzzy membership function; calculating a total score of each candidate virtual constellation according to the single-factor evaluation matrix and the observation capability index of each candidate virtual constellation; and determining a final target virtual constellation according to the total score of each candidate virtual constellation. According to the method, the adaptation degree of the satellite combination and land surface task parameters can be improved, and the satellite resource utilization rate and the observation task planning efficiency are improved.

The invention provides a gas field gathering and transportation pipe network system energy efficiency evaluation method based on a secondary station distribution strategy, and belongs to the field of natural gas gathering and transportation. In order to solve the problems that gas field development enters a later stage and the technological adaptability of a gathering and transportation pipe network system becomes poor, according to the technological process of the gas field gathering and transportation pipe network system adopting a secondary station distribution strategy, main energy efficiency influence factors are selected, an energy efficiency evaluation system is constructed, and on the basis of researching an analytic hierarchy process, an entropy weight method, a fuzzy membership function method and a linear weighting method, the energy efficiency evaluation system is established. And a set of complete gas field gathering and transportation pipe network system energy efficiency evaluation algorithm model adopting a secondary station distribution strategy is constructed. The invention provides a more scientific and systematic method for energy efficiency evaluation of a gas field gathering and transportation pipe network system for realizing a secondary station distribution strategy.

The invention discloses a method for designing an asynchronous controller of a type-2 switching fuzzy system, which comprises the following steps of: through an IT2 fuzzy set of a prerequisite variable and an emission intensity interval set of a fuzzy rule under an If-Then rule based on an interval type-2 discrete switching fuzzy system of a local nonlinear model; based on a fuzzy reasoning method, constructing a global fuzzy model of the discrete switching nonlinear system; assuming that a switching signal of the global fuzzy model meets the minimum residence time constraint, defining a system timer, and constructing an interval type-2 fuzzy controller dependent on a type-one prerequisite variable division domain; and based on the gain of the interval type-2 fuzzy controller, a closed-loop type-2 switching fuzzy system model with guaranteed cost generalized dissipative performance is obtained. According to the method, different controller structure frameworks are adopted in the asynchronous time period and the synchronous time period, fuzzy member function information of the system is fully utilized to improve the control effect, and the stability and the guaranteed cost generalized dissipation performance of the closed-loop system can be guaranteed.

The invention belongs to the technical field of dynamic defense, and particularly relates to a dynamic defense method and system fused with water conservancy network security situation awareness, so as to solve the technical problems that data isomerism is difficult to process, model static state lacks timeliness, threat prediction is incomplete, and defense decisions are not balanced in an existing attitude awareness method. The defense method comprises the following steps: constructing a multi-layer attack tree model of the water conservancy network; obtaining heterogeneous security data collected by monitoring nodes in a network, quantifying the heterogeneous security data into normalized threat values in one-to-one correspondence with leaf nodes in the model based on an asset vulnerability incidence matrix and a situation element fuzzy membership function, and taking the normalized threat values as conditional occurrence probabilities of the leaf nodes; and traversing all attack paths in the multi-layer attack tree model, and executing an operation on any path. According to the defense method, interference to normal operation of the water conservancy core business is reduced, and balance between safety and business is achieved.

The application belongs to the technical field of power quality analysis and evaluation in power systems, and provides a sensitive equipment voltage sag tolerance evaluation method and system considering aging effect. Firstly, a fuzzy membership function of sensitive equipment tolerance is constructed. Then, the equivalent mean and equivalent variance of the equivalent random variable are determined. A state function of the sensitive equipment under voltage sag is constructed. Finally, according to the equivalent mean and equivalent variance, the reliability index of the state function is determined based on the first order second moment, the sensitive equipment failure probability is obtained, and the sensitive equipment voltage sag tolerance evaluation is realized. Wherein, the aging time-varying model of equipment tolerance is established based on Weibull distribution, which is used to describe the change law of the key parameters of tolerance in the fuzzy membership function with the running time. By considering the aging effect, the problems such as serious overestimation of the actual voltage sag tolerance level of old equipment are avoided, and the tolerance of the equipment at a certain time point in the future can be predicted.

The invention discloses a coulomb ecosystem health evaluation method and system based on multi-dimensional data, and relates to the technical field of ecosystem health evaluation, and the method comprises the steps: obtaining multi-dimensional monitoring data of a target ecological region, and carrying out the time-space alignment processing, and obtaining the deep features of all dimensions; establishing a causal inference network of deep features, and performing anti-factual inference in combination with time-delay response characteristics to generate a causal association structure; dividing features of a driving layer and a response layer according to a causal conduction path, and calculating a dynamic weight; performing knowledge verification by adopting a priority reconciliation strategy, and establishing a health state reference benchmark; constructing an adaptive fuzzy membership function to obtain a membership function set; and constructing an evaluation model by using the dynamic weight and the membership function set, inputting deep features to obtain a comprehensive health evaluation index, and determining a health level. The method can accurately evaluate the health condition of the coulomb ecosystem.

The invention discloses an intelligent evaluation and measurement integrated system of measurement and control equipment based on a digital twinborn body, and relates to the technical field of industrial automation and digital twinborn. The technical key points are as follows: the system comprises a data acquisition module, a digital twin modeling module, an intelligent index evaluation module, a weight fusion calculation module, a grade scoring reasoning module and a feedback regulation module. The system collects operation parameters of measurement and control equipment through a multi-source heterogeneous sensor, constructs digital twin models in one-to-one correspondence with the operation parameters, and achieves virtual synchronous mapping of equipment states; an index grade evaluation system is constructed based on a fuzzy membership function, subjective and objective weight fusion is carried out in combination with an analytic hierarchy process and an entropy weight method, a comprehensive weight vector is generated, and quantitative evaluation of the equipment intelligence grade is completed through a fuzzy reasoning algorithm. According to the system, parameter adjustment suggestions are further output through an error feedback mechanism, and model closed-loop correction and performance self-adaptive optimization are achieved.