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The invention provides an on-line quality monitoring method and system based on optical multispectral fusion, and relates to the technical field of multispectral fusion, and the method comprises the steps: collecting visible light and infrared multispectral images of an object to be measured, carrying out the preprocessing and registration, inputting the images into a variational auto-encoder, and carrying out the probability distribution modeling, and obtaining a spectrum basis vector and an initial abundance graph; and constructing a multi-scale morphological feature pyramid, performing graph segmentation in combination with spatial information to obtain a local consistency region, and fusing the local consistency region with the initial abundance graph to obtain an enhanced abundance feature. And fusing the spectrum basis vector and the enhanced abundance feature by adopting a multi-head cross attention mechanism to obtain a multi-spectrum fusion feature. And inputting the fusion features into a dynamic neural network, analyzing a topological connection relationship between nodes, obtaining a structured representation, performing discriminative enhancement, calculating node significance distribution, determining a quality defect area, analyzing a formation mechanism of the quality defect area, and finally generating a quality monitoring report.

The invention provides a vehicle collision risk early warning method, system and device and a medium, and belongs to the technical field of vehicle safety control. The method comprises the steps that surrounding environment information of a vehicle is collected in real time through a vehicle built-in sensor and a GPS module; a multi-sensor fusion device technology is used to carry out comprehensive processing on surrounding environment information of a vehicle, and an environment perception model is generated after data integration; based on the environment perception model, target identification is carried out by using a computer vision technology based on a convolutional neural network so as to identify travelers, vehicles, traffic signs and obstacles; performing behavior prediction based on a deep learning model to predict a behavior track of a front vehicle or pedestrian; evaluating a potential collision risk in the current scene in combination with the target recognition result and the behavior prediction result; when a potential collision risk is detected, an early warning signal is sent to a driver, and when the driver does not take corresponding measures, active safety measures are automatically triggered to avoid collision or reduce accident damage.

The invention relates to the technical field of industrial automation, and discloses a method for detecting abnormal operation of industrial control equipment based on industrial control protocol analysis, which comprises the following steps of: 1, acquiring operation data of the industrial control equipment through at least one industrial control protocol which is a Modbus protocol, an OPC UA protocol or a PROFIBUS protocol, the operation data comprises sensor data, register data and equipment state data of the equipment; and 2, analyzing the collected data packet by using a protocol analyzer, extracting key information related to the equipment operation state, the key information comprising parameters such as equipment working frequency, load, vibration, temperature and pressure, and converting the key information into a uniform data format. By collecting, analyzing and analyzing the operation data of the industrial control equipment in real time, abnormal conditions in operation of the equipment can be found in time, spreading of equipment faults is avoided, and stable operation of the equipment is guaranteed.

The invention provides an intelligent mineral resource exploration and evaluation system, and relates to the technical field of data processing, and the system comprises a data preprocessing module which is used for preprocessing data to obtain preprocessed data; the stress analysis module is used for analyzing the rock physical property and the geological structure stress state of the exploration area according to the preprocessed data so as to obtain the relevance between the rock physical property and the geological structure stress state; calculating a dynamic adjustment coefficient according to the relevance between the rock physical property and the geological structure stress state; the resource reserve estimation module is used for estimating mineral resource reserves according to the dynamic adjustment coefficient; and the resource evaluation module is used for evaluating the mineral resource reserves to obtain a final evaluation result. According to the method, accurate analysis of the rock physical property and the geological structure stress state is realized, so that the accuracy and the reliability of exploration and evaluation of mineral resources are greatly improved.

The invention relates to the technical field of mine potential safety hazard identification, in particular to a mine potential safety hazard identification method and system based on an unmanned aerial vehicle. The method comprises the following steps: acquiring a global image of a mining area by using an unmanned aerial vehicle camera, and constructing a three-dimensional model; thirdly, performing rock-soil landslide probability estimation through weathering erosion mechanism reduction in combination with the three-dimensional model and the global image, and calculating landslide coercing force potential energy increment; then, according to the landslide probability and the coercing force incremental data, carrying out risk grade endowing on the local area of the mining area; and finally, constructing a mine potential safety hazard identification optimization model based on the risk level, and sending the model to a terminal for potential hazard identification. According to the invention, the mine potential safety hazard identification technology is optimized, so that the mine potential safety hazard identification technology is more perfect.

The invention relates to the technical field of piston ring group wear monitoring, in particular to a piston ring group wear life prediction method and system. The method comprises the following steps: collecting working state data of a piston ring group in real time, de-noising by using improved wavelet transform, processing missing data by using a KNN interpolation method, standardizing and normalizing the processed data, adopting a filtering label generation and auditing mechanism to ensure the ordered homogeneity of the data, and constructing an over-limit learning machine model to obtain a piston ring group model; a hidden layer weight and an offset vector are randomly generated to calculate a hidden layer output matrix, a whale optimization algorithm is adopted to optimize model parameters, the prediction precision is improved, then the residual life is predicted, a final prediction result is used for calculating a fault risk coefficient and comparing the fault risk coefficient with a preset threshold value, maintenance suggestions are provided, and real-time data and the prediction result are displayed. And a user is assisted to make a maintenance decision. The advanced signal processing technology and the machine learning algorithm are combined, and the maintenance efficiency of the piston ring set and the reliability of equipment operation are improved.

The invention relates to the technical field of geological ecological monitoring, in particular to a geological ecological monitoring system and method. The method comprises the following steps: acquiring a topographic map of a monitoring area; performing real-time data acquisition by using a sensor network according to the topographic map of the monitored area, and constructing a rock-soil physical characteristic matrix to obtain the rock-soil physical characteristic matrix; performing rock-soil mechanical response spectrum construction according to the rock-soil physical characteristic matrix to obtain a rock-soil mechanical response spectrum; according to the monitored area topographic map, point cloud data processing is utilized to construct a side slope geometric model, and a side slope three-dimensional geometric model is obtained; performing unit stress analysis according to the three-dimensional geometric model of the side slope to obtain unit stress data; and performing strength reduction calculation according to the unit stress data to obtain a reduction strength parameter. The geological ecological system is comprehensively, dynamically and systematically monitored and evaluated, so that geological disaster prevention and control and ecological environment protection are better served.

The invention discloses an urban safety risk assessment method and system based on a digital standard, and the method comprises the steps: obtaining urban safety risk monitoring data and historical data, constructing a risk index event library according to the historical data, carrying out the abnormal screening and classification of the monitoring data, and obtaining risk indexes, matching the risk indicator with the risk indicator event library to determine a first risk event, predicting an uncertain risk event according to the first risk event, and constructing a city safety risk assessment model according to the first risk event, the uncertain risk event and the risk event weight, and inputting to-be-assessed city safety risk monitoring data and historical data into the city safety risk assessment model to obtain a city safety risk assessment result. The method not only can improve the efficiency and accuracy of urban safety risk assessment, but also has good interpretability, and can be directly applied to an urban safety risk assessment system.

The invention discloses a user question answering method and device, equipment and a medium, and relates to the field of artificial intelligence, and the method comprises the steps: obtaining the input information of a user; performing application scene analysis on the input information and semantic intention understanding on the input information by using a multi-level associated scene analysis model, and determining an actual application scene of the input information; calling a core element template preset for the actual business scene, and extracting core element information in the input information according to the core element template; and acquiring scene data, inputting the reference knowledge, the cue word and the scene data into the trained large language model as input data, and obtaining a reasoning result output by the large language model. According to the method, the data correlation problem that knowledge quoted by an existing LLM is inaccurate and incomplete is solved, association matching between the problem and business scene data is perfected, and therefore the reply effect of the LLM on scene related problems of all industries and fields is improved.

The invention provides a blood vessel image processing analysis method and system combining magnetic resonance blood vessel and blood vessel wall imaging, and the system comprises a data obtaining module which obtains a blood vessel enhancement image and a blood vessel wall image; the image registration module is used for registering the blood vessel wall image to the blood vessel enhanced image to obtain a registered blood vessel wall image; the segmentation module is used for obtaining a blood vessel lumen segmentation result and a blood vessel wall segmentation result; the fusion module is used for carrying out weighted fusion on the blood vessel enhanced image and the registered blood vessel wall image to obtain a fused image; the analysis module is used for calculating an intersection region of a blood vessel lumen segmentation result and a blood vessel wall segmentation result; and the three-dimensional visualization and curved surface reconstruction module is used for performing three-dimensional skeleton extraction and curved surface reconstruction on the three-dimensional connected domain of the suspected occluded blood vessel. According to the method, the information of the blood vessel lumen and the blood vessel wall can be obtained at the same time, the defect of a traditional imaging means in evaluating the condition of the blood vessel wall at the far end of the occluded blood vessel is overcome, and the time needed by preoperative evaluation is remarkably shortened through automatic processing and analysis.

The invention discloses a dynamic obstacle avoidance control system based on machine vision, and relates to the technical field of machine vision and automatic control, and the main scheme is that an information collection module obtains image information, machine basic operation and task target data in real time; the image processing module calculates obstacle influence factor parameters and ranges, task complexity indexes and operation obstruction indexes according to the images and the operation data, and the data adjusting module judges whether machine transportation is obstructed or not according to a comparison result of the operation obstruction indexes and a threshold value and sets an obstacle avoidance route. The control decision module calculates predicted delay time according to the operation obstruction index and the like, further obtains a self-adaptive task speed value and steering, judges whether normal work is affected by comparing the predicted delay time with a threshold set, adjusts the normal work into a self-adaptive value when the normal work is affected, and controls the task speed value and the steering direction. According to the system, the autonomous obstacle avoidance capability and the task execution efficiency of a machine in a complex environment are improved.

The invention discloses a text matching method and device, and belongs to the technical field of text retrieval. The text matching method comprises the following steps: processing an obtained initial text library to obtain a first vector corresponding to each paragraph text and a second vector corresponding to each sentence text included in the initial text library; processing the obtained problem text to obtain a third vector corresponding to the problem text; obtaining a first similarity between the question text and the paragraph text based on the first vector and the third vector; based on the second vector and the third vector, obtaining a second similarity between the question text and the paragraph text; processing at least one keyword included in the question text to obtain the importance degree of each keyword to the paragraph text; and determining a target paragraph text corresponding to the question text from the plurality of paragraph texts based on the first similarity, the second similarity and the importance degree. According to the text matching method, the precision and the accuracy of a text matching result are improved.

The invention discloses a cable partial discharge identification method and device based on an improved decision tree-rotating forest, and the method comprises the steps: carrying out the wavelet packet decomposition energy feature extraction of a TRPD ultrasonic signal, calculating the zero-crossing rate of the ultrasonic signal, and carrying out the classification of TRPD ultrasonic features through employing an improved decision tree algorithm based on adaptive weighted information adjustment gain. Multi-dimensional information such as occurrence time, phase and energy distribution of partial discharge can be comprehensively described, characteristic information of cable partial discharge can be more comprehensively acquired, and the accuracy of partial discharge detection and identification is improved; the Bayesian fusion algorithm based on multi-stage fusion is adopted, the results of different feature classifiers are fused, the defects of a single classification algorithm are overcome, and the reliability of the partial discharge type recognition result is improved.

The invention relates to the technical field of detection equipment, and provides a BFS product automatic lamp inspection machine aiming at the problem that the traditional row ampoule bottle detection efficiency is low, and the BFS product automatic lamp inspection machine comprises a control module, a feeding conveying mechanism, an inverted conveying mechanism, an inclined conveying mechanism, an upright conveying mechanism and a discharging conveying mechanism; the inverted conveying mechanism and the feeding conveying mechanism are used for conveying inverted row ampoule bottles; the inclined conveying mechanism is used for conveying the parallel-row ampoule bottles and enabling the parallel-row ampoule bottles to be turned over to be inclined from inverted; the upright conveying mechanism is used for conveying the parallel-row ampoule bottles and turning the parallel-row ampoule bottles from an inclined state to an upright state; the discharge conveying mechanism is used for conveying the ampoule bottles in rows and turning the mounting bottles from upright state to horizontal state; the inverted conveying mechanism, the inclined conveying mechanism and the upright conveying mechanism are each provided with an image obtaining assembly, the discharging conveying mechanism is further provided with a material removing assembly, and the image obtaining assemblies and the material removing assembly are both electrically connected with the control module. The device has the advantage that the row ampoule bottles can be conveniently detected.

The invention discloses a dynamic water affair monitoring system and method based on digital twinning, and belongs to the technical field of water affair monitoring. The method comprises the following steps: acquiring equipment working environment data, performance data of each piece of monitoring equipment and water affair data, wherein the water affair data comprises hydrological data and water quality data; performing comprehensive analysis according to the equipment working environment data to obtain an equipment working environment evaluation value, performing comprehensive analysis according to the performance data of each piece of monitoring equipment to obtain a performance evaluation value of each piece of monitoring equipment, and performing comprehensive analysis according to the equipment working environment evaluation value and the performance evaluation value of each piece of monitoring equipment to obtain a state evaluation value of each piece of monitoring equipment; performing evaluation feedback according to the state evaluation value of each monitoring device; performing comprehensive analysis according to the water quality data to obtain a water quality evaluation value, finally performing comprehensive analysis according to the water quality evaluation value, the equipment working environment evaluation value and the hydrological data to obtain a water affair state evaluation value, and performing evaluation feedback according to the water affair state evaluation value.

The invention discloses an automatic detection method for ocean temperature-salinity-depth profile data, and particularly relates to the technical field of ocean monitoring, comprising the following steps: setting a target profile area of an ocean, placing an ocean temperature-salinity-depth sensor, and then performing data collection, processing and classification operations; the method comprises the following steps: acquiring a first type of profile data set and a second type of profile data set, then drawing a visual graph, acquiring profile closed areas with different gradients, performing volatility analysis and mobility analysis, and then performing comprehensive analysis. The comprehensive disorder value is compared with a preset disorder threshold value of the section closed area of the target gradient, and whether an early warning signal is sent out or not is determined according to a comparison result; according to the method, the dynamic change of the ocean profile can be comprehensively known, quantitative evaluation on the stability of the ocean environment is further provided through calculation of the comprehensive disorder value, an early warning signal can be sent out in time when an early warning mechanism is triggered, and the safety of ocean management is ensured.

The invention discloses an autonomous acousto-optic fusion target detection method and system for an amphibious unmanned platform, relates to the technical field of underwater target detection, and aims to solve the problem that a method for detecting a complex underwater environment target by combining an acoustic sensor and an optical sensor is lacked in the prior art. Comprising the following steps: S1, synchronously acquiring underwater environment information through an optical camera and a foresight sonar of the amphibious unmanned platform; s2, preprocessing the image data and the acoustic data respectively, and then performing segmentation and target identification on the preprocessed image data and acoustic data; s3, respectively converting target identification results under the optical camera coordinate system and the foresight sonar coordinate system to a joint coordinate system; and S4, establishing a support degree matrix between the target identification results of the optical camera and the foresight sonar, rejecting outliers with low support degree according to the obtained comprehensive support degree matrix of each data, and performing optimal weighted fusion on measured values with high support degree to obtain an acousto-optic combined underwater target positioning result.

The invention discloses an energy-saving air conditioning system and a control method of the energy-saving air conditioning system, and relates to the field of energy-saving air conditioning systems.The energy-saving air conditioning system comprises an outdoor unit shell, a compressor, a condenser, a cooling fan and a drying filter are arranged in the outdoor unit shell, the compressor compresses a refrigerant into a high-temperature and high-pressure gas state, then the refrigerant is fed into the condenser, the cooling fan is started, and the drying filter is started; the condenser is condensed, the refrigerant becomes liquid after being cooled, and the liquid refrigerant is conveyed to the drying filter through a pipeline; in the refrigeration mode, when the temperature monitored by one temperature sensor correspondingly arranged on the outdoor unit shell is lower than the temperature monitored by other temperature sensors, the information is fed back to the controller, the controller controls the driving mechanism to drive the air inlet end to move to the position corresponding to the temperature sensor, and at the moment, the air inlet end is driven by the driving mechanism to move to the position corresponding to the temperature sensor. The air supplied to the cooling fan is low-temperature air near the outdoor unit shell, so that the condensation efficiency of the condenser is improved, and the operation energy consumption of the air conditioning system is reduced.

The invention discloses a method and a device for rapidly and intelligently testing the water absorption rate of concrete. The device is mainly composed of a display screen, a test grid, a test box cover plate, a test box, a stainless steel mesh, a temperature sensor, an infrared distance measuring sensor, a pressurizing hole, a water injection hole, a temperature control device, a pressurizing device, a computer host and a water storage device. And the water absorption rate of the concrete can be tested under the pressure of 0-2MPa and the water temperature of 0-80 DEG C. The test piece can be a cube with the size of 100 mm * 100 mm * 100 mm or a cylinder with the size of phi 100 mm * 100 mm. The device has the characteristics of controllable and adjustable pressure and temperature, automatic measurement of liquid level change, real-time display of water absorption and synchronous implementation of multiple groups of tests, and the accuracy, reliability and automation degree of concrete water absorption testing are remarkably improved.

The invention relates to the technical field of communication, and discloses a network slice resource optimization method, device, system and product. The method comprises the following steps: collecting flow data of each edge node in a target network in a current time step according to the size of the time step; the traffic data comprises short-time traffic data and long-time traffic data of all network slices in the edge node; predicting predicted flow data of each edge node in the next time step based on the flow data of each current edge node; determining a target distribution strategy based on the predicted traffic data of each edge node in the next time step; determining target resource configuration in each edge node in the next time step according to a target allocation strategy and the predicted traffic data of each edge node in the next time step; and allocating network resources to each edge node according to the target resource configuration. By adopting the method, the accurate and efficient dynamic network resource allocation of the whole target network can be realized, and the overall performance of the network is improved.

The invention provides an automatic dangerous rock identification method and system based on a machine vision system, and relates to the technical field of engineering mechanics, and the method comprises the steps: obtaining dangerous rock region image data containing disturbance amplitude and frequency, obtaining disturbance stress data, and carrying out the comprehensive analysis to calculate a rockburst failure load; the method comprises the following steps: establishing a relationship among a dynamic disturbance load, a stress gradient, a rockburst failure load and rockburst strength, calculating a stress-strength ratio and establishing a relationship between the stress-strength ratio and rockburst intensity, then extracting deformation and debris granularity characteristics, comprehensively generating a dangerous rock index, setting a safety threshold, and finally comparing the dangerous rock index with the safety threshold and sending out an early warning. According to the method, the image data, the high-resolution imaging equipment, the stress sensor and the numerical simulation method are utilized, automatic dangerous rock identification is achieved, the rockburst risk is effectively predicted, and regional safety is ensured.

The invention discloses a monitoring and strength measuring system for welding cracks, which comprises a monitoring unit, a data processing unit, a strength evaluation unit, a control unit and an output unit, and is characterized in that the monitoring unit is used for acquiring various physical parameters of crack formation and expansion of a welding joint in an operation process; the data processing unit preprocesses and analyzes the received physical parameters to generate crack state monitoring data; the strength evaluation unit dynamically evaluates the residual strength of the welding joint in combination with the mechanical property of the material; the control unit automatically adjusts welding process parameters, such as welding heat input, welding speed and cooling rate, according to crack monitoring data and strength evaluation information; the real-time monitoring and dynamic adjustment in the welding process are achieved by comprehensively monitoring crack propagation and evaluating the structural strength, the service life of a welding structure can be effectively prolonged, and the safety and reliability of the welding structure can be ensured.

The invention provides a concrete internal scanning defect 3D imaging algorithm, and belongs to the technical field of concrete detection, and the algorithm comprises the following steps: 1, installing a detection device; an acceleration sensor matrix is pre-laid on a to-be-detected concrete structure, and impact equipment is moved to a to-be-detected area; step 2, data acquisition; according to the method, an impact echo method is adopted, impact equipment is used for impacting a concrete structure, elastic waves are generated, elastic wave signals are received through a pre-laid acceleration sensor matrix, and original data in concrete are obtained; 3, preprocessing the original data; 4, data analysis; calculating and analyzing the preprocessed data; 5, constructing a model; the position, size and shape information of the defect is determined according to the analysis result, a three-dimensional visualization technology is adopted, a three-dimensional model in the concrete is constructed, the structure in the concrete and the defect distribution condition are displayed, and the problem that a traditional detection method lacks visualization is solved.

The invention discloses a wearable device, and relates to the technical field of intelligent electronic products, the wearable device comprises a shell, a signal transmission assembly and a biological sound sensor, the signal transmission assembly comprises a signal transmitting piece and a signal receiving piece, and the signal transmitting piece and the signal receiving piece are arranged on the two sides, away from each other, of the shell; the biological sound sensor and the signal transmitting piece are arranged on the same side of the shell, and the biological sound sensor is electrically connected to the signal transmitting piece; the signal transmitting part receives a vibration signal collected by the biological sound sensor, converts the vibration signal into an electromagnetic signal and sends the electromagnetic signal to the signal receiving part. According to the wearable device, FPC physical connection lines are omitted, interference on biological sound signal collection due to wire vibration is avoided, and the signal-to-noise ratio of biological sound sensor vibration signal collection is increased.

The invention provides a method for controlling multi-scale fracture extension at different positions of a main fracture and a fracturing method, and belongs to the field of oil and gas exploitation, the method comprises the steps that fracturing fluid is injected to conduct segmented fracture forming construction on the main fracture, and each fracture forming stage expands to generate the main fracture with the preset length; temporarily plugging the end part of the main crack by adopting a temporary plugging agent, and opening the multi-scale crack in the length direction of the main crack through a temporary plugging effect; a propping agent is continuously injected to fill the multi-scale crack; the blocking of the end of the main crack is relieved, the process from the main crack segmented crack forming construction to the multi-scale crack filling is repeated till the crack length of the main crack reaches the maximum value, and a multi-scale crack network is formed in the length direction of the main crack; and a proppant is continuously injected to fill the main crack. According to the fracturing method provided by the invention, the main crack and the branch cracks can be fully extended, and effective support of the main crack and the branch cracks is ensured.

The embodiment of the invention discloses a three-dimensional modeling method and device based on a panoramic vision laser scanner, and the method comprises the steps: carrying out the comprehensive scanning of a target scene based on the panoramic vision laser scanner according to a preset scanning path, so as to collect scene data, wherein the scene data comprises three-dimensional coordinate information, RGB color information, and texture information; preprocessing the scene data, generating point cloud data, and generating ellipsoid distribution data of a three-dimensional space based on the point cloud data; and establishing a three-dimensional model of the target scene based on the ellipsoid distribution data. According to the embodiment, the defects of a traditional method in the aspects of visual effect, precision and automation degree are overcome, a brand new solution is provided for rapid modeling of a large-scale scene with lower cost and higher efficiency, the centimeter-level precision standard is achieved, and a user can experience immersive feeling in a virtual space. Meanwhile, the high-precision point cloud data can also be widely applied to a plurality of fields such as topographic surveying and mapping, geological survey and forestry survey.

The present invention discloses a method for realizing interconnection and intercommunication between devices, which is applied to a housekeeper program on a terminal device in an Internet of Things platform. The method comprises: detecting whether a housekeeper program login instruction issued by a user is received, and if so, logging in; issuing an application login instruction to each application respectively, so that each application logs in; obtaining the user's personalized information from a database of a corresponding server, and storing the obtained personalized information in its own shared storage file; when the application in the terminal device receives an application startup instruction issued by the user, the application can obtain the personalized information from the shared storage file, and provide personalized services to the user according to the personalized information; according to a preset time node, uploading the user's personalized information recorded by the application in the shared storage file to the corresponding server, so as to update the personalized information stored in the database.

The invention provides a data governance robot real-time monitoring method and system based on an automation technology, and is applied to the technical field of data processing. The method comprises the following steps: determining a plurality of to-be-monitored data sources and a to-be-monitored power grid operation parameter list according to monitoring requirements of a power system; merging the data meeting the requirements of the power grid operation parameter list in the plurality of data sources to obtain power grid operation data corresponding to the monitoring requirements; the data is collected by the data management robot; inputting the power grid operation data into an anomaly prediction model to obtain anomaly data in the power grid operation data; according to the method, the corresponding data treatment strategy is executed according to the abnormal data in the power grid operation data, the data treatment result is obtained, the power grid operation parameters can be more comprehensively obtained, the operation state of the power system can be more comprehensively reflected, and the accuracy and the real-time performance can be improved by combining and utilizing the abnormal prediction model instead of human experience judgment.

The invention discloses a hawthorn medicine wastewater treatment device and a comprehensive treatment method thereof, and relates to the technical field of wastewater treatment.The hawthorn medicine wastewater treatment device comprises a wastewater treatment pond, and a flocculation impact mechanism is arranged at the top of the wastewater treatment pond; by arranging a flocculation impact mechanism and adopting an inclined and inclined lower columnar high-pressure spraying mode, when a large amount of flocculating agent is flushed into wastewater in a wastewater treatment tank, the wastewater is fully scattered and rapidly flows by utilizing high pressure, and meanwhile, the wastewater is rapidly diffused in a mode of flushing away from the center of the wastewater treatment tank to the periphery of the wastewater treatment tank; the waste water diffused to the periphery of the waste water treatment tank is turned over to the upper layer and flows back to the center of the waste water treatment tank through the upper layer, so that a flocculating agent is automatically sprayed, the mixing effect in the waste water treatment tank is completed, and the function of turning over and circulating is achieved through spraying in the inclined lower direction; the problem that part of wastewater dirt deposited at the bottom cannot be in full contact with the flocculating agent is effectively prevented.

The invention discloses a test and evaluation method for live-action modeling of a nerve radiation field, and the method comprises the following steps: S10, carrying out data set preparation: collecting a public data set, carrying out the live-action shooting of a forward data set and a reverse data set with a designed place, carrying out the targeted enhancement of a data set, and generating a data set through employing AIGC; the data set is used for training a modeling model or a test model of the system; s20, based on the situation that a user may use different functions of applications in parallel in an actual user scene, policy task issuing is carried out in an interface calling mode; s30, carrying out system equipment performance monitoring and modeling duration recording, analyzing state data and a trend thereof, analyzing whether a task is abnormal or not and whether performance consumption and task duration are reasonable or not, and carrying out targeted optimization based on a target; and S40, after task operation is completed and operation data is recorded, the modeling success rate and the modeling effect are evaluated.