70results about How to "Realize dynamic matching" patented technology

The invention discloses a rod-pumped well group control method based on a flexible load, and belongs to the technical field of rod-pumped well group control. The method is characterized by comprising the following steps that 1, modeling is conducted on an oil pumping system; step 2, establishing a flexible load model suitable for a rod-pumped well group; 3, taking the minimum difference value between the well group power and the input power as an objective function, considering the power constraint of each pumping unit and the frequency constraint of a motor, and solving the power constraint and the frequency constraint to obtain a pumping adjustment degree scheme between pumping unit well groups; and 4, forming a rod-pumped well group prediction control algorithm. According to the rod-pumped well group control method based on the flexible load, the flexible load characteristic of the rod-pumped well group is fully utilized, and green electric power resources can be efficiently absorbed and utilized. Dynamic matching of load and energy supply is realized by constructing an accurate flexible load model of the rod-pumped well group and performing scheduling optimization control on the system.

The invention discloses a power supply scheduling method and system of a railway traction station based on photovoltaic grid-connected power generation, and relates to the field of photovoltaic power generation. The method comprises the following steps: acquiring load information after traction of a railway in a target area for a preset duration and detection information corresponding to a photovoltaic grid-connected power generation system; according to the load information and the detection information, a power supply mode of each traction station is determined, and the power supply mode comprises that any one of a photovoltaic grid-connected power generation system, an energy storage system and a power grid continuously supplies power to the corresponding traction station within a preset duration; and within the preset duration, supplying power to each traction station according to the power supply mode. By implementing the technical scheme provided by the invention, the fluctuation of photovoltaic power generation can be effectively stabilized, and the stability of overall power supply is improved.

The invention relates to the technical field of power distribution network power dispatching, and discloses a digital twinborn intelligent optimization dispatching system and method, which dynamically and accurately counts real-time power dispatching total power load parameters of a target power distribution network line power distribution end according to real-time demand power load parameters of a power distribution network user end in combination with numerical analysis. The power management platform is combined to efficiently and autonomously execute power dispatching operation of the power distribution end of the power distribution network; and according to the spatial three-dimensional model parameters of the overall line of the power distribution network, the power dispatching parameters and the three-dimensional model combination parameters of the power distribution terminal, and the power load parameters and the three-dimensional model combination parameters of the user terminal, carrying out dynamic matching on the power dispatching electrical variables of the power distribution terminal and the user terminal in the power distribution network line and the power distribution network line. The digital twinborn full-scene accurate matching of the power dispatching parameters and the power dispatching objects of the power distribution network is realized, and the scientificity and the intelligence of the power dispatching operation are improved.

The invention discloses a one-film six-row wide-narrow-row close-planting staggered planting method for cotton, which comprises the following steps: measuring the soil nutrient content of a region to be planted, calculating the comprehensive score of soil fertility, selecting a basic plant spacing according to the tillering coefficient of a cotton variety, fitting an accumulated temperature correction function, calculating a predicted value of the tillering rate, and calculating a dynamic offset in combination with the latitude of a planting field. Determining a narrow row spacing and a sowing depth according to the dynamic offset, extracting a growth picture of the same variety of cotton in the same region after the flowering and boll-setting period, extracting a planting row spacing mean value of the canopy coverage in a preset range as a wide row spacing, planting cotton according to the basic plant spacing, the narrow row spacing, the wide row spacing and the sowing depth, and monitoring the canopy photosynthetically active radiation in real time. And dynamically regulating and controlling a drip irrigation fertilization strategy according to the photosynthetically active radiation of the canopy. By means of the method, the photosynthetic efficiency, the water and fertilizer utilization efficiency and the stress resistance of cotton groups can be improved, a brand new technical path is provided for high-yield and high-quality cultivation of cotton, and the method has important significance in promoting intelligent transformation of the cotton planting industry.

The invention discloses an electroencephalogram head ring interaction control method and device based on concentration level, and the method comprises the steps: collecting multi-band electroencephalogram signals and user interaction parameters, carrying out spectrum decoupling analysis to recognize a concentration feature baseline, exporting an attention stability coefficient, and building a cognitive state mapping relation; tracking a high-response frequency band core to implement frequency band fusion analysis to form a control channel, and collecting concentration fluctuation data to construct an interaction control network; executing multi-task response analysis to identify an intention switching point, extracting cognitive load parameters to divide a low-load area and a high-load area, and extracting a recovery rate to construct an attention toughness index in an identification conversion process; determining an optimal trigger position in a low-load area according to an attention toughness index, constructing a brain wave feature chain, aligning the brain wave feature chain with an attention stability coefficient, determining a low-interference response window, and setting a self-adaptive threshold group; and the coupling identification false triggering area extracts redundant brain wave components to execute false triggering suppression to generate an interaction control instruction, so that accurate matching between teaching intervention and the cognitive state of the student is realized.

This invention discloses an intelligent health education method, device, equipment, and storage medium for gynecological tumor patients. The method acquires the patient's electronic medical record information and patient interaction data. Based on the electronic medical record information, it identifies the gynecological tumor disease type and treatment stage tags. Based on the patient interaction data, it specifically identifies psychological stress signals related to gynecological tumor treatment, generating a profile of the patient's current psychosomatic state. It matches and dynamically generates personalized health education content and psychological counseling plans from a structured knowledge base. Based on the patient's treatment data, it automatically generates reminders for medication and follow-up examinations. It structurally correlates the output records of personalized health education content and the patient's feedback data on the reminders to form a digital pathmap for patient education. This enables dynamic matching and personalized generation of health education content and psychological counseling plans, improving the patient's cognitive adaptability to health information and the effectiveness of psychological support, achieving closed-loop management throughout the entire hospital and inpatient cycle.

The application provides a working condition prediction method and system fusing map and camera information, historical driving data of a time span of a vehicle, and camera data and map navigation data outside the vehicle are collected; a driver personalized feature working condition set is constructed; a multi-modal feature fusion working condition prediction model including an input layer, a multi-modal feature extraction layer, a feature fusion layer and an output layer is established based on a neural network; current real-time driving data of the vehicle, the camera data and the map navigation data outside the vehicle are input, and a real-time working condition feature index matrix is output through the multi-modal feature fusion working condition prediction model; the real-time working condition feature index matrix is input into the driver personalized feature working condition set, and the latest working condition prediction result is obtained. The application fuses historical driving data, vehicle-mounted camera visual information and vehicle-end navigation map information, realizes long-term and short-term time domain cooperation, multi-modal feature adaptive weighted fusion, fully utilizes multi-source information, and improves technical prediction accuracy and scene adaptability.

The application discloses a kind of electric truck super-charging facilities collaborative planning method considering traffic network-power grid interaction, according to the energy consumption heterogeneity characteristics of electric truck multi-type transport task, constructs charging demand space distribution model;Introduce node marginal electricity price mechanism, establish the charging station selection equilibrium model with the minimum total cost as target;Based on the theory of direct current optimal power flow model, construct the power distribution network operation model with the minimum total generation cost as target;Build electric truck super-charging facilities collaborative planning model considering traffic-power two network interaction, and carry out transformation processing to obtain several differentiable barrier sub-problems, and solve several differentiable barrier sub-problems using interior point method, obtain the super-charging facility optimization setting scheme of traffic network-power grid interaction.The application solves the collaborative optimization problem of charging facility deployment and power grid impact in the field of port collection and distribution during electric transformation, provides efficient and stable collaborative decision support for port electric truck charging network planning, and has significant application value.

The application discloses a device control method and device, equipment, storage medium and computer program product, and is used to solve the problem that the user plane device running state and service load lack dynamic matching ability under the existing device scheduling mechanism, resulting in device idling and high energy consumption at low load. The method comprises the following steps: acquiring energy efficiency index data and service traffic data corresponding to each user plane device in a device pool; determining predicted traffic in a future preset time window based on a pre-trained prediction model according to the service traffic data; determining a control strategy for at least one user plane device in the device pool according to the predicted traffic and the energy efficiency index data, wherein the control strategy is used to control the user plane device to enter a sleep state; generating a control instruction according to the control strategy and sending the control instruction to the user plane device to control the user plane device to perform a corresponding sleep operation.

The application relates to the technical field of intelligent trolley walking mechanisms, in particular to an intelligent trolley walking mechanism for logistics carrying, which comprises a moving chassis mechanism and a supporting bottom plate installed on the top of the moving chassis mechanism, one side of the top of the supporting bottom plate is fixedly provided with a vertical fixing plate, one side of the vertical fixing plate, which faces the center of the supporting bottom plate, is rotationally connected with a closed-loop chain type conveying belt; equidistant through shaft sleeves are fixedly arranged in the closed-loop chain type conveying belt; and supporting shafts are rotationally connected in the shaft sleeves; the closed-loop chain type conveying belt and the multiple material carrying frames arranged on the vertical fixing plate realize dynamic matching of the material carrying stations and the taking and placing points. All the material carrying frames can be circulated to the butt joints of the same height as required, so that the matching clamping mechanism does not need to perform a complex vertical lifting stroke, the motion freedom degree of the clamping mechanism is greatly simplified, and the taking and placing operation cycle period is greatly shortened compared with a traditional multi-layer rack AGV.

The present application relates to the technical field of material performance testing, and discloses a kind of test methods for evaluating the chemical solvent penetration resistance of reinforced plastic, comprising the following steps: constructing inverse transfer function to compensate platform lag, using historical strain data to predict the starting time of microcrack opening in the next cycle, combining platform inherent delay to calculate instruction sending time, based on stiffness attenuation rate calculated in real time to adaptively adjust the best disturbance frequency, using inverse transfer function to generate modified disturbance instruction and superimposed injection, deducting fluid viscous damping work previously calibrated from single cycle data to obtain effective dissipation density, determining failure end point based on the second derivative change of effective dissipation density sequence.The present application realizes the time synchronization of pressure wave and crack opening through prediction feedforward strategy, maintains deep penetration driving force using adaptive disturbance, and eliminates fluid damping interference through energy decoupling mechanism, improving the authenticity and result accuracy of stress-assisted solvent penetration test.

The application discloses a kind of based on multi-mode adaptive switching hydrological section automatic flow measurement control method, it is related to water conservancy and hydrology automatic measurement control technical field;Single threshold value determination is inaccurate, mode switching leads to data breakpoint, scheme fixed is not applicable to dynamic working condition Problem.The application fuses multi-source hydrological perception data calculation section comprehensive working condition abnormality parameter, determines adaptive threshold value based on historical contemporaneous statistical characteristics to execute three-zone switching decision, constructs precision benefit function, safety risk function and time efficiency function to solve pareto optimal scheme set and select optimal scheme to drive truss automatic flow measurement car execution, in double mode parallel transition mode, according to the relative position of the section comprehensive working condition abnormality parameter in transition interval to determine weighting coefficient and to flow data Weighted fusion.The application realizes the adaptive smooth switching of flow measurement mode under all working conditions and the dynamic optimization of flow measurement scheme.

The present application relates to the technical field of alfalfa planting, and discloses a phosphorus application quota distribution method for improving alfalfa seed yield, and the specific process is as follows: first, preparing the planting plot, cleaning the plot weeds in advance, leveling the land, installing the underground drip irrigation system, then, sowing and applying base fertilizer, applying the base fertilizer when finishing the land, planting the test variety by using the wide-narrow row mulching sowing method, uniformly dripping seedling water the next day to ensure uniform seedling emergence, setting the total irrigation amount and the total phosphorus application amount per hectare, and through the water and phosphorus management mode of implementing irrigation and phosphorus application quota distribution, the water and phosphorus are proportionally controlled to carry out underground drip irrigation in the growth periods of the branching stage, the squaring stage, the flowering stage and the podding stage of alfalfa, the technical scheme provided by the present application realizes the synergistic effect of differentiated irrigation amount and phosphorus application amount quota distribution in different growth periods through setting different irrigation and phosphorus application quota distribution modes, and thus improves the alfalfa seed yield and the water and phosphorus utilization efficiency.

According to the high-temperature-resistant resin system for dry-method winding of the prepreg tape and the preparation method, dicyclopentadiene phenolic epoxy and polyfunctional naphthalene ring epoxy resin are selected as matrix resin, multiple components are used for adjusting the viscosity of the system, a composite curing agent is selected for adjusting the rheological manufacturability and curing activity of the system, and the high-temperature-resistant resin system for dry-method winding of the prepreg tape is obtained. An organic / inorganic hybrid latent polyphosphazene curing agent is adopted to synergistically improve the high temperature resistance and mechanical properties of the system, and a metal phthalocyanine high-temperature-resistant modified component is adopted to further adjust the high temperature resistance and rheological properties. By adjusting the chemical structures and proportions of the resin matrix, the composite curing agent and the high-temperature-resistant modified component, a resin system with excellent high-temperature resistance and an intelligent adhesion characteristic is obtained, and the prepared prepreg tape has a yarn releasing intelligent adhesion characteristic and a winding intelligent adhesion characteristic which are adaptive to dry winding. According to the technology, the blank of a high-temperature-resistant resin material system for dry-method winding is filled up, and development and application of dry-method winding in lightweight parts in the aerospace field are powerfully promoted.

The present disclosure provides a data migration method, device and equipment and storage medium, and relates to the technical field of data processing. The method comprises the following steps: receiving a first migration request sent by a request node, wherein the first migration request comprises position information of the request node and the size of data to be migrated, and the request node is an edge node; determining a target node from a plurality of edge nodes according to the position information of the request node and the size of data to be migrated in combination with storage resource information of the plurality of edge nodes; sending the position information of the target node to the request node, so that the request node sends a second migration request to the target node based on the position information of the target node; and sending a permission proof to the target node, so that the target node sends a confirmation message of accepting migration to the request node in the case that information carried by the second migration request meets the permission proof.

The invention provides a freight heavy truck driving parameter design method, system and device and a medium, and belongs to the technical field of intelligent driving, and the method comprises the steps: S1, classifying the operation scenes of a freight heavy truck, and collecting the driving parameter data of a driver in each operation scene; s2, preprocessing the collected driving parameter data to obtain a driving parameter sample set; and S3, analyzing the driving parameter sample set by adopting a clustering algorithm, and extracting typical driving parameters in each operation scene. Accurate matching of the driving parameters and the freight scene is achieved, and adaptability, safety and efficiency of the intelligent driving system in a complex freight environment are improved.

The invention relates to the technical field of data processing, in particular to a BIM model-based multi-party cooperative construction management and control method and system, and the method comprises the steps: obtaining the point cloud data of a real-time construction project, and determining the optimal thick side length of a voxel block according to the down-sampling rate of the point cloud data and the unit side length of the spatial distribution of the point cloud data; voxelization is carried out on the point cloud data based on the optimal coarse side length to obtain a plurality of voxel blocks, and the average density of point cloud distribution of the point cloud data in the voxel blocks is determined; determining the optimal side length of the voxel block according to the average density, the down-sampling rate, the optimal coarse side length and the unit side length, and performing down-sampling on the point cloud data based on the optimal side length to obtain a down-sampling project point cloud set of the real-time construction project; and constructing a BIM model of the real-time construction project by using the down-sampling project point cloud set, and managing and controlling the real-time construction project by using the BIM model. Therefore, the construction accuracy of the BIM three-dimensional model is improved.

The invention discloses a mobile self-adaptive charging control and thermal control method and system, and belongs to the technical field of thermoelectric control systems.The method comprises the steps that a charging state sensing matrix is constructed by collecting multi-dimensional data such as electric quantity, battery health, environment temperature and load in real time; a neural network model fusing a space-time attention mechanism and a bidirectional LSTM is adopted to accurately identify a charging demand, and a dynamic strategy library is matched to generate an initial charging parameter; in the charging process, the state of a loop is monitored through double-end synchronous sampling larger than 1 kHz, the current and voltage are dynamically optimized in combination with a battery equivalent circuit model of the self-adaptive order, and efficient power matching and ripple suppression are achieved. And when it is detected that the temperature is abnormal, a multi-mode thermal management mechanism is triggered, and a charging-calculation-heat dissipation cooperative control closed loop is formed. The system also supports security OTA strategy updating based on federated learning and differential privacy; according to the invention, the charging efficiency, the safety and the service life of the battery are remarkably improved, and the environment adaptability in a complex mobile scene is enhanced.

The application discloses a big data-based intelligent education guidance evaluation system and method, belongs to the technical field of intelligent education and big data analysis, and comprises a multi-source heterogeneous education data acquisition module, a data preprocessing and feature fusion module, a multi-dimensional capacity evaluation module, a learning behavior sequence analysis module, an individualized guidance recommendation module and a multi-role visual display module. The method integrates multi-source data through a time sequence self-adaptive alignment algorithm, realizes five-dimensional comprehensive capacity evaluation by adopting a subjective and objective fusion weighting algorithm and a double-flow attention knowledge tracking algorithm, performs learning behavior time sequence modeling by using a key behavior node identification algorithm, and generates an individualized learning path by a cognitive load perception path optimization algorithm. The application solves the problems of single evaluation dimension, fragmented data acquisition and lack of data support for individualized guidance in the existing education evaluation system.

The application relates to a multi-source data fusion battery pack thermal runaway fire control method and system, and relates to the technical field of battery packs, which comprises the following steps: acquiring a battery number and a battery temperature corresponding to the battery number; when the battery temperature is greater than a preset thermal runaway temperature, defining the battery number corresponding to the battery temperature as a thermal runaway number; acquiring a real-time temperature corresponding to the thermal runaway number; when the real-time temperature is greater than a preset ignition temperature, accumulating an ignition time; and when the ignition time is greater than a preset time threshold, controlling an atomizing nozzle to spray the battery corresponding to the thermal runaway number according to a preset spraying mode. The application has the effect of improving the fire control efficiency of the battery pack in a thermal runaway scene.

The present application provides a kind of mine roadway support intelligent design and feedback optimization system and method, it is related to mine support technical field, including rock mass quality classification, support parameter automatic design, knowledge graph case reasoning and AI optimization, agent model quick verification, three-dimensional visual support design and digital twin modeling, BIM / GIS integrated interface, multi-source monitoring and early warning, dynamic feedback optimization and surrounding rock parameter inversion, design report generation and multi-roadway progress board nine big subsystems.The intelligent generation and optimization of support scheme are realized based on machine learning algorithm through multi-source data fusion analysis, the three-dimensional visual model of roadway is established using digital twin technology, the dynamic adjustment of support scheme is driven by real-time monitoring data, the scientificity and economy of support design are effectively improved, the complex geological instability risk is effectively resisted, the intelligent management of support full life cycle is realized, and the safe and efficient production of mine is ensured.

The invention provides a control method of cleaning equipment and the cleaning equipment. The control method of the cleaning equipment comprises the steps that a force signal of operation force acting on the cleaning equipment is obtained; according to the signal change rate of the force signal, whether the operating force is instantaneous disturbance force is determined, and according to the duration and the fluctuation amplitude of the force signal, whether the operating force reaches a target stable state is determined; under the condition that the operating force is not the instantaneous disturbance force and reaches the target stable state, the magnitude of the operating force is determined according to the force signal; determining a target rotating speed of the motor according to the magnitude of the operating force based on a nonlinear mapping relation; the actual rotating speed of the motor is adjusted to the target rotating speed, and rotating speed control over the rolling brush is achieved.

The application relates to the technical field of plastic processing, and discloses a plastic melting uniformity analysis method and system. The method comprises the following steps: collecting fluctuation of a supply amount and material distribution data, obtaining a temperature deviation fluctuation interval and a material abnormal distribution graph; combining the temperature deviation and a dynamic disturbance frequency to judge a fluctuation type and generate temperature distribution abnormality prediction data; extracting key features from the temperature distribution abnormality prediction data to determine a plastic flow characteristic change trend; integrating dynamic characteristic data to evaluate the influence degree of a melting process on uniformity; quantifying a shear rate mutation response based on the influence degree to adjust a melting time fluctuation interval parameter; generating a uniformity distribution graph through multi-scenario simulation to determine a product quality quantization index; generating an adjustment strategy according to the index and iteratively optimizing the adjustment strategy to finally determine melting process control parameters. The application solves the problems of poor melting uniformity and control lag caused by disturbance coupling, and improves the stability of a plastic melting process and the consistency of product quality.

The invention relates to the technical field of image processing and vehicle safety protection, and discloses a complex industrial scene-oriented vehicle intelligent auxiliary safety protection system and method. The method comprises the steps of collecting video stream data, carrying out obstacle identification and generating space distribution information, dynamically constructing a three-dimensional warning space, analyzing an intrusive obstacle, tracking a motion track, generating a graded brake control signal and sending the graded brake control signal to a brake execution mechanism. The system comprises a video acquisition unit, an obstacle identification unit, a space mapping unit, a warning space construction unit, a space analysis unit, a target tracking unit, a decision unit and an instruction output unit. According to the method, obstacles are accurately recognized through image recognition and space mapping, a self-adaptive three-dimensional warning space is dynamically constructed according to vehicle driving parameters, graded braking signals are generated in combination with obstacle categories and movement tracks, and the accuracy and reliability of vehicle intelligent auxiliary safety protection in a complex industrial scene are achieved.

The present application belongs to copper pyrometallurgy technical field, specifically discloses a kind of dynamic optimization method of double-side blowing copper smelting slag type based on molten pool working condition real-time monitoring and model driving.The method includes: real-time acquisition molten pool temperature, flue gas oxygen content, slag Fe3O4 Content and viscosity and other multiple key working condition parameters;Parameter is input into the preset control model, the expert rule based on metallurgical thermodynamics and production data is embedded in the model, and the dynamic adjustment amount of SiO2, CaO, MgO three kinds of slag forming agent is calculated accordingly;According to the adjustment amount, the proportion of slag forming agent is adjusted in real time;Periodic acquisition of slag sample analysis, compare measured value with model expected value, and feedback correction model parameters, realize closed-loop optimization.The present application can dynamically adjust slag type according to molten pool real-time working condition, reduce the fluctuation of slag fluidity by more than 40%, stabilize the copper content of slag below 1.5%, and improve the direct recovery rate of copper to more than 97.5%, significantly improve the process stability and metal recovery rate.

The application discloses a kind of pretreatment method and system for water environment heavy metal on-line monitoring, belong to water environment monitoring technical field.It includes the real-time water quality data of acquisition inlet pipeline constructs water quality characteristic vector;Call preset enrichment strategy mapping model to determine basic enrichment mode and pH adjustment target value, combined with pressure data to carry out safety limiting correction, generate control parameter set;pH value is adjusted by double closed loop cascade and cooperates temperature control, simultaneously determines the stage of blockage, and generates preventive control instruction;According to the cumulative sample volume, determine the adsorption termination;In elution process, according to the fluctuation characteristics of conductivity data sequence to determine the elution end point.The application improves the self-adaptive ability and safety of the system to water quality fluctuation through model decision and safety limiting double regulation, realizes the prospective prevention of blockage using nonlinear trend prediction, combined with double closed loop regulation and objective end point determination significantly improves the accuracy of monitoring data and the stability of system operation.

The invention discloses an intelligent processing speed control method and belongs to the technical field of cutting tool cutting. According to the technical scheme, slow sawing speed reduction is executed, wherein fixed speed reduction is conducted at the set fixed position length; and intelligent speed reduction is executed, specifically, speed reduction is conducted by referring to the threshold value or presetting the fixed position and speed in real time in the machining process. The method has the beneficial effects that the current value is collected and analyzed in real time, the feeding speed is dynamically adjusted according to the change of the current value, and intelligent control over the machining process is achieved; the processing problem caused by large hardness difference of wood in the traditional process is solved, and it is ensured that the optimal processing effect can be achieved on the wood with different hardness; production efficiency and product quality are effectively improved, and the service life of the cutting tool is prolonged; the system can be easily integrated with other automatic equipment and control systems, the flexibility and expandability of the system are improved, real-time monitoring and fault early warning can be achieved, machining errors caused by human factors or equipment performance fluctuation are reduced, and the overall quality and consistency of products are improved.

The invention provides a heterogeneous model task scheduling method and system based on parallel strategy metadata. The method comprises the steps that a central scheduler receives a calculation task request containing a model identifier and a task parameter set; querying model metadata according to the model identifier, and obtaining a task strategy predefined corresponding to the model version; scheduling decision making is carried out based on a task strategy, and tasks are distributed to computing nodes; the computing node queries a model-environment mapping table according to the model identifier to obtain an environment identifier and loads an isolation runtime environment; acquiring data and executing a task through the data service layer in the isolated runtime environment; the computing nodes report task states and log information, and the central scheduler provides a monitoring interface queried according to model identifiers after aggregation. According to the method, the task strategy is predefined for the model version, so that the scheduling system has the service semantic perception capability, and the parallel processing efficiency is improved while the data consistency is guaranteed.

The application discloses a kind of based on the high-efficiency operation method and system of sewage plant water inlet characteristics, solve the problem that sewage plant operation uses static single processing scheme, cannot adapt to different water inlet characteristics, including steps: setting water inlet classification standard, establish the parameter control database of sewage plant operation;Collect sewage plant water inlet data, according to water inlet data carries out water inlet characteristic analysis, and according to water inlet characteristic carries out classification;According to the type of water inlet characteristic at current time, from parameter control database corresponding sewage plant operation strategy is retrieved, water inlet characteristic is matched with sewage plant operation process parameter, then according to effluent target, the process parameter is fine-tuned;The effluent quality of sewage plant is predicted, according to the feedback regulation of predicted result to sewage plant operation process parameter.It realizes that sewage plant high-efficiency operation is strong in adaptability, energy-efficient, improves the operation efficiency of sewage plant and the treatment effect to sewage, reduces energy consumption and operating cost.

The invention discloses an equipment vacuum degree detection method and device based on current signal analysis, and relates to the technical field of intelligent sensors, and the method comprises the steps: obtaining the feature information of a vacuum generation device, obtaining the predicted vacuum degree based on the feature information, and obtaining the current collection frequency based on the predicted vacuum degree; acquiring an original current signal by adopting the current acquisition frequency, and preprocessing to acquire a current signal; performing feature extraction on the current signal to obtain a current feature parameter; and performing vacuum degree analysis based on the current characteristic parameters to obtain a vacuum degree classification result. According to the invention, the technical problem of poor non-intrusive vacuum degree detection effect in the prior art is solved.