2527 results about "Wind direction" patented technology

The invention discloses a wind power plant generating capacity improving method based on active wake flow yaw control optimization. The method comprises the following steps: 1) acquiring basic information data of a wind power plant; 2) establishing a CFD simulation model of the wind power plant according to the basic information data; 3) optimizing the arrangement scheme of the laser wind finding radar, and obtaining the operation data of the wind turbine generator in real time; 4) constructing a single-machine analysis wake flow model and a multi-machine wake flow superposition model, respectively comparing with the flow field simulation result data and the wind measurement result of the laser wind measurement radar, and correcting a wake flow speed distribution expression to obtain wind speed and wind direction prediction data at the hub center height of each machine site in the wind power plant; and 5) constructing a whole field optimization control model, taking maximum output as an optimization target to obtain an optimal yaw control strategy set of each wind turbine generator, and enabling the related wind turbine generators to execute yaw actions. The invention belongs to the technical field of wind power generation control, and solves the problem that the wake flow loss among wind power units in a wind power plant is difficult to reduce by the existing control strategy.

The invention discloses a tunnel fan energy-saving control method and system, a storage medium and a program product, and relates to the field of general control or regulation systems.The method comprises the steps that historical train flow data are obtained, and the predicted train flow of the next time period is obtained through calculation according to the historical train flow data; collecting real-time gas concentration data and wind speed and direction data; calculating a theoretical gas concentration increment based on an aerodynamic model, the predicted train flow, the real-time gas concentration data and the wind speed and direction data; calculating according to the theoretical gas concentration increment and a pollutant diffusion model to obtain a pollutant diffusion trend; determining a target section according to the pollutant diffusion trend and a preset gas concentration threshold value; according to the position information of the target section and the pollutant diffusion trend, the minimum starting number of tunnel fans and the corresponding minimum rotating speed are obtained through calculation; and generating a fan control instruction according to the minimum number of started fans and the minimum rotating speed. According to the method, the effect of reducing the energy consumption of the tunnel fan while the ventilation effect of the tunnel is maintained is achieved.

The invention discloses a power transmission line icing real-time monitoring method and system based on multi-parameter fusion, and relates to the field of data processing, and the method comprises the steps: receiving conductor physical parameters at the same moment, and simulating an icing track of a target power transmission line section in combination with current environment data; determining a windward side of the icing track based on the current wind direction, and simulating a windward icing layer of the icing track by taking the windward side as a starting surface, taking the current wind speed as a reference wind speed and adopting an icing layer simulation strategy; based on the topographic data of the target power transmission line section, determining a high-risk icing area in the icing track, and determining icing layer data of the high-risk icing area; determining an icing galloping area in the icing track based on the vibration parameter and the strain parameter; and fitting the windward icing layer, the high-risk icing area and the icing galloping area with the icing track, and optimizing the fitted icing track according to the icing layer data to generate a visual interface. According to the invention, the accuracy of icing monitoring of the power transmission line can be effectively improved.

The invention relates to a multi-machine cooperative yaw control method and device considering a dynamic wind direction and a medium. The multi-machine cooperative yaw control method comprises the steps that S1, the dynamic relation between the wind direction and a wake flow area is established based on a Gaussian-curl hybrid model; s2, constructing a single-machine yaw optimization model based on model predictive control, optimizing single-machine yaw by taking maximum generating capacity of a wind power plant and reduction of fatigue load as optimization objectives, and obtaining a single-machine optimal yaw angle through rolling optimization and feedback correction; and S3, a serial optimization method is adopted to carry out multi-round iterative optimization on one fan by one fan, and an optimal multi-fan cooperative yaw control result is obtained. Compared with the prior art, the method has the advantages that higher total generating capacity and more balanced fatigue load can be realized, so that the whole wind power plant reaches the optimal state of power and load in a large range.

The invention relates to the technical field of stress detection, in particular to an absolute stress detection method and system for a concrete bridge, and the method comprises the following steps: obtaining stress data of a bridge girder, a support, a box girder and a main tower, collecting wind speed and wind direction sensor data, calculating a wind load gradient value, and extracting wind load primary and secondary influence regions and a transmission buffer region. And generating a wind load area stress data set. According to the method, through environmental factors and stress data, the influence of wind load on structure stress is identified, data comprehensiveness is ensured, through wind load gradient change rate calculation and stress sudden change area extraction, the structure weak point identification capability is improved, the stress fluctuation trend is quantified through time sequence analysis, and the cumulative change rate is deduced, so that fatigue damage prediction is more accurate; abnormal point identification is combined with deviation ratio analysis, measurement data is corrected, analysis reliability is improved, fatigue damage information is extracted based on stress attenuation features, local fatigue evaluation is optimized, a damaged area is accurately locked, and the accuracy of structural health monitoring is improved.

A wind-finding method based on fusion of millimeter wave radar data and laser radar data, comprising: S1, acquiring wind-finding radar parameters; S2, on the basis of the wind-finding radar parameters, acquiring system state flag bits of wind-finding radars, determining whether the wind-finding radars work normally, and executing corresponding behaviors; S3, acquiring measurement data of the wind-finding radars at different heights, and caching related parameters; S4, by determining radial wind speed significant bits, selecting a corresponding wind-finding radar, and performing inversion on the wind speed; S5, fusing the wind speeds inverted by the millimeter wave wind-finding radar and the laser wind-finding radar to obtain a fused output wind speed; and S6, outputting a horizontal wind speed and a wind direction corresponding to each height level. According to the wind-finding method based on fusion of millimeter wave radar data and laser radar data, two types of wind-finding radar measurement data obtained simultaneously are fused, improving the data reliability of wind speed and wind direction measurement; and the advantages of different wind-finding radars are fully utilized, improving the overall measurement precision.

The invention discloses a pollutant diffusion inspection and tracing method based on a U-Net gas diffusion model, and the pollutant diffusion model based on the U-Net can quickly calculate a pollutant diffusion dynamic graph of any release point source and any wind direction, carries out the precision evaluation, predicts the diffusion range and concentration distribution of pollutants under different environment conditions, and improves the accuracy of the pollutant diffusion inspection and tracing. And a reliable basis is provided for subsequent path planning. Through the MPC algorithm, the output change of the process in a period of time in the future is predicted by using the process model, so that the control effect which should be applied to the process at the current moment is determined according to a certain optimization target. Through prediction and optimization of the MPC and a prediction model and feedback correction combined with the MPC, the control strategy can be adjusted at each sampling moment according to the current system state and environment information, and the diffusion trend of pollutants can be predicted more accurately, so that the layout and detection frequency of detection points are optimized, and the detection precision and efficiency are improved.

The invention discloses a hilly slope irrigation control system based on artificial intelligence, and the system comprises a wind speed and wind direction detection module which is used for obtaining wind speed and wind direction data; the sprinkler head adjusting module is used for adjusting the angle and the spraying distance of a sprinkler head based on the wind speed and wind direction data; the soil humidity detection module is used for being connected with a soil humidity sensor and determining irrigation requirements according to data of the soil humidity sensor; the artificial intelligence control module is used for optimizing the irrigation time and the irrigation amount through an artificial intelligence algorithm; the sprinkling irrigation system control module is used for controlling the sprinkling irrigation system to irrigate according to the optimization result; the hilly slope irrigation control system based on artificial intelligence reduces the phenomenon of non-uniform growth of crops, facilitates healthy and uniform growth of the crops, and ensures that the crops can obtain a proper amount of water supply, so that normal growth and development of the crops are promoted, the yield and quality of the crops are improved, and the agricultural production benefits are further improved.

The invention provides a segmental bridge wind vibration performance evaluation method and system, and relates to the technical field of segmental bridge wind vibration performance. Laser scanning is used for obtaining geometric parameters of a segmental bridge and collecting material characteristics, the geometric parameters and the material characteristics are imported into finite element software, a basic model is established, and boundary conditions are set; modal analysis is executed in finite element software, the natural vibration frequency and the vibration mode are calculated through a Lanczos method, and basic data are provided for wind load analysis; simulating a wind load by using a Davenport wind spectrum, setting a wind speed and a wind direction, and then applying the wind speed and the wind direction to the model; finally, the wind load condition is adjusted, the performance of the bridge under different wind loads is tested, and the displacement, acceleration and stress distribution of the bridge are analyzed and calculated through dynamic response to complete the wind vibration performance evaluation of the segmental bridge.

The invention discloses an intelligent precise farmland irrigation direction control system based on the Internet of Things, and relates to the technical field related to intelligent irrigation. Comprising a data acquisition module, a data processing and analyzing module, a data labeling and classifying unit, a three-dimensional coordinate model building module, a nozzle angle adjusting device, a nozzle water quantity adjusting unit and a control instruction execution unit. According to the invention, the distance between the nearest nozzle and the water-requiring position is calculated, so that irrigation water can reach the water-requiring area more efficiently, the distance is accurately calculated to ensure that water can be quickly and accurately conveyed to the required area, water loss and energy waste caused by long-distance water conveying are avoided, the water spraying direction is adjusted in combination with the wind direction and the wind speed, and the water spraying efficiency is improved. The device can effectively cope with the influence of natural wind on irrigation, and by monitoring wind direction and wind speed information in real time and combining the wind direction and wind speed information with water spraying parameters of the spray head, the system accurately calculates horizontal and vertical angle adjustment values of the spray head, so that sprayed water flow can accurately reach a water needing position.

The invention discloses a PPI wind shear extraction method and device based on a laser wind finding radar and a storage medium, and the method comprises the following steps: S1, obtaining the radial data of N light beams in a period based on PPI scanning, and carrying out the screening and marking of the radial data; s2, inverting a horizontal wind field based on a light beam sliding window to obtain a horizontal wind speed and a horizontal wind direction of the light beam; s3, grid division is carried out on the horizontal wind field, and interpolation is carried out based on the detection distance; compared with the prior art, the method takes radial data obtained by PPI scanning as a basis, adopts a sliding window method, and takes the horizontal wind speed and the horizontal wind direction calculated by a previous sliding window as initial values of model parameters to be substituted into the gradient descent solving model of the current light beam, so that the horizontal wind speed and the horizontal wind direction of the current light beam are inverted; the wind field inversion error when the wind direction and the light beam direction tend to be perpendicular is reduced, and the inversion precision of the horizontal wind field is improved.

The invention discloses a hoisting task control method and device of a crane and electronic equipment, and relates to the field of mechanical control. The method comprises the following steps: constructing a coupling model of a crane and a wind power blade according to hoisting task parameters; determining first control data of the crane according to the coupling model; obtaining current environment data, wherein the current environment data comprises wind speed and wind direction; determining wind load distribution corresponding to the current environment data in a preset wind load database; calculating position deviation and attitude deviation of a hoisting point of the crane according to the wind load distribution, and calculating a wind load compensation vector; superposing the wind load compensation vector into the first control data to generate second control data; and converting the second control data into a servo control instruction, and driving the crane to run according to the carrying track according to the servo control instruction. According to the technical scheme, the control instruction is dynamically adjusted by calculating the wind load compensation vector, and the accuracy of the hoisting process is improved.

The invention discloses an energy-saving control method based on a building group spatial form, which relates to the technical field of energy-saving control, and comprises the following steps: constructing an airflow track analysis region based on a region with hot pressure difference direction change in a spatial pressure covering sensing matrix, and collecting continuous wind direction and wind speed data; judging whether the airflow direction is abnormal or not according to the change of the flow direction consistency entropy; performing spatial coincidence processing on the spatial pressure shielding sensing matrix and the airflow direction abnormal region, and generating an air outlet ventilation and heat extraction efficiency evaluation index based on the heat conduction rate in the coincidence region and the stability of an airflow output path; and on the basis of the ventilation and heat removal efficiency evaluation index of the exhaust outlet, an exhaust response condition matrix containing a space pressure shielding parameter, an airflow disturbance level and a heat retention level is constructed, and a ventilation control judgment sequence is generated. According to the method, the problem of air exhaust failure under pressure shielding interference is solved, ventilation efficiency accurate judgment and energy-saving regulation and control optimization are achieved, and the ventilation stability and the energy utilization efficiency of the building group are guaranteed.

The invention discloses a wind power generation abnormal data analysis method and system, and relates to the technical field of data analysis, and the method comprises the following steps: constructing a wind direction change rate enhanced perception model, analyzing the potential omen of wind direction abrupt change based on an ultra-short time scale wind direction change trend curve and a wind speed fluctuation coupling index collected at multiple measurement points, and determining the wind direction abrupt change. Generating a risk early warning label of wind wheel pointing deviation; and based on the risk early warning label, executing a high-frequency yaw disturbance prediction mechanism, and predicting an inflow angle continuous offset window caused by yaw response lag by using a nonlinear time sequence evolution trend and a short-term wind direction reversal probability curve. The wind direction sudden change early warning is realized through multi-measuring-point wind direction enhanced perception and wind speed coupling analysis, the response precision is improved and the energy consumption is reduced in combination with predictive yaw compensation and torque balance, the yaw parameters are dynamically optimized by using adaptive closed loop and reinforcement learning, the inflow angle is kept stable for a long time, and the power generation efficiency and the structural safety are improved.

The invention discloses a wind generating set load dynamic prediction method and device based on wind direction change, and belongs to the technical field of wind power generation. The method comprises the following steps: collecting historical load, historical wind direction and historical wind speed data of a wind generating set of a target wind power plant to construct a historical data set; performing correlation analysis on the historical wind direction, the historical wind speed and the historical load to obtain a correlation analysis result of the historical wind direction, the historical wind speed and the historical load; inputting the correlation analysis result into a preset initial model to train and optimize the initial model, and generating a load prediction model for predicting the future load of the wind generating set; and inputting the real-time wind direction, the real-time wind speed and the unit operation state parameters into a load prediction model, and generating predicted real-time load change of the wind generating set through the load prediction model so as to adjust operation parameters of the wind generating set. The method improves the prediction precision of the load influence caused by wind speed and wind direction changes, and achieves the quick response and control of the fan load.

Systems and techniques for wind estimation are presented herein, such as using Uncrewed Aircraft (UA). No on-board flow sensor is required, and the present subject matter does not require estimation of thrust or drag forces. For example, using only GPS (or another indicium of groundspeed) and orientation sensors, wind vectors in the Earth-fixed frame can be estimated during turning maneuvers. The “Wind-Arc” technique described herein was verified using simulation. Also, when applied to experimental flight test data, the technique works and follows both airspeed and wind speed trends.

The invention discloses a mobile intelligent control spraying and dust-settling system, and particularly relates to the technical field of compensation or utilization of an external environment of a spraying and dust-settling spraying vehicle under a wind field disturbance condition, which comprises a plurality of wind speed and wind direction sensing nodes mounted on a lifting rod in the advancing process of the spraying and dust-settling spraying vehicle, acquiring a plurality of local wind field parameters in different heights and directions, and constructing a wind speed gradient data set based on the local wind field parameters; and performing normalization and disturbance feature extraction processing on the wind speed gradient data set to generate a wind disturbance time sequence and a spatial disturbance distribution map. By constructing a time-space coupling control mechanism fusing wind disturbance feature extraction, trend prediction and path calibration, advanced sensing of non-steady-state wind field disturbance and dynamic correction of spray response parameters are achieved, and therefore the problems of sensing-control coupling lag and spray offset errors are solved.

The invention relates to the technical field of environment modeling, in particular to a carbon accounting method and system based on artificial intelligence, and the method comprises the following steps: obtaining a carbon emission source rate, a wind direction and airflow intensity, setting a time step length, calculating the spatial distribution of a carbon diffusion trajectory, and calling an airflow influence range to calculate a diffusion path of carbon molecules. According to the method, through multi-source data fusion and dynamic calculation, a carbon emission diffusion path is accurately simulated, the joint calculation of the wind direction, the airflow intensity and the emission rate ensures the accuracy of diffusion trend depiction, the extraction of carbon concentration data is combined with the dominant emission direction, the data pertinence is enhanced, a missing region is filled through gradient difference calculation, and the accuracy of the carbon emission diffusion path is improved. Data integrity is improved, a diffusion path is optimized through error calculation and threshold judgment, the emission rate and airflow intensity are dynamically adjusted, the carbon concentration trend prediction precision is improved, space correlation factors are combined with a region adjustment mechanism, the accounting range is adjusted in a self-adaptive mode, errors are prevented from being divided, and time sequence calculation of carbon emission is optimized.

The invention provides a single-point mooring floating type fan platform capable of actively yawing, and belongs to the technical field of offshore wind power. The problem that the aerodynamic efficiency of an impeller is reduced due to the fact that a fan platform needs to bear multiple coupling effects of ocean currents and waves and the fan platform deviates from the best windward direction due to the hydrodynamic force coupling effect when an included angle is formed between the ocean current direction and the wind direction under the action of the complex ocean environment is solved. The system comprises a wind turbine generator, a mast type tower, a platform foundation, a single-point mooring device and a flow guide device, the edge of the platform foundation is connected with the single-point mooring device and can rotate by 360 degrees around the single-point mooring device. The flow guiding device is installed at the edge position of the platform foundation and arranged opposite to the single-point mooring device, the horizontal section of the flow guiding device is in a symmetrical streamline shape, and the flow guiding device is provided with a driving device which drives the flow guiding device to rotate in the horizontal direction and adjusts the acting force of ocean current on the fan platform. The power generation device is mainly used for improving the power generation efficiency of the mast type tower offshore wind turbine platform.

The invention discloses a risk monitoring and control method for offshore construction, and particularly relates to the technical field of collision control for offshore construction, and the method comprises the steps: obtaining the real-time position, the navigational speed, the course, the tonnage, the wind speed, the wind direction, the wave height, the wave direction, the flow speed, the ship type, the ship historical track and the ship behavior mode of a ship, and carrying out the preprocessing; and inputting the processed multi-source data into the constructed ship trajectory prediction model, outputting a plurality of possible trajectories and trajectory probabilities of a future time window, and then calculating a collision probability and a dynamic safety distance, thereby improving the degree of closeness between the collision probability and a real collision probability, improving the accuracy of collision probability analysis, and improving the accuracy of ship trajectory prediction. The safety boundary of the ship and the construction area is quantified in real time, the failure of a fixed threshold value in a complex environment is avoided, a dynamic judgment reference is provided for risk level classification, the risk identification precision is improved, a response instruction is matched more accurately, and the collision harm is further reduced.

The invention relates to the technical field of environment monitoring, in particular to an environment monitoring method and system based on multi-source data, and the method comprises the steps: dividing a to-be-monitored region into a plurality of environment monitoring regions, and determining the pore dynamic parameters of the environment monitoring regions to screen pore-enriched regions; constructing a feature vector set according to the pointing similarity of the plurality of wind direction characterization vectors, judging whether an interactive influence region exists, extracting wind power parameters of each feature vector in the feature vector set, and determining a region range of the interactive influence region, and obtaining a water-soil ecological coupling value of the interactive influence area to determine whether to send out an early warning prompt of environment abnormity of the interactive influence area, thereby dynamically adjusting the monitoring key point according to the specific condition of the soil quality in the area in combination with the actual environment influence factor. And the capturing accuracy of the collapse phenomenon in the monitoring area and the reliability of environment monitoring are improved.

The invention discloses a wind vibration actual measurement analysis method for a large-span steel structure roof, and belongs to the field of steel structure engineering monitoring, and the actual measurement analysis method comprises the following specific steps: I, based on the geometric and dynamic characteristics of a large-span steel structure roof structure, optimizing the arrangement of each sensor, and constructing a multi-modal heterogeneous sensing network; iI, acquiring wind speed and wind direction time sequence data according to the multi-mode heterogeneous sensing network, establishing a reconstruction model of a non-stationary wind field, and predicting time-varying distribution of wind pressure on the surface of the structure; according to the method, high-fidelity dynamic reconstruction of the wind field is realized, the authenticity of wind load input is improved, the data quality and information diversity are improved, the prediction precision and timeliness of the wind pressure field are improved, and the scientificity and the monitoring effect of an overall layout strategy are enhanced; according to the method, the accuracy of long-term performance evaluation can be improved, environment coupling simulation of structural response is achieved, the dynamic adaptive capacity of analysis is enhanced, the structural rigidity evolution rule is depicted finely, and the robustness and local recognition capacity of the model under uncertain data are enhanced.

The invention discloses an SAR sea surface flow velocity inversion method based on physical guidance and data driving fusion, and relates to the field of flow velocity inversion, and the method comprises the steps: carrying out the non-geophysical Doppler frequency shift correction of the Doppler frequency shift observed by a spaceborne synthetic aperture radar, and obtaining the geophysical Doppler frequency shift; predicting based on a wave-induced Doppler frequency shift model according to a radar incident angle, reanalyzed wind direction data, a sea surface 10-meter height wind speed inverted by an SAR (Synthetic Aperture Radar), a simulated wind wave parameter, a simulated surge parameter and a simulated maximum wave parameter to obtain a wave-induced Doppler frequency shift; the wave-induced Doppler frequency shift model is obtained based on physical guidance and data-driven modeling; doppler frequency shift generated by sea surface flow is determined according to the geophysical Doppler frequency shift and the wave-induced Doppler frequency shift; according to the method, the Doppler frequency shift generated based on the sea surface flow is converted to obtain the sea surface radial flow velocity, the wave-induced Doppler frequency shift is accurately removed, and reliable inversion of the sea surface flow velocity is realized.

A direct air capture (DAC) facility for capturing carbon dioxide (CO2) from atmospheric air is disposed on a plot of land having a prevailing wind direction and includes at least one contactor wall formed from a plurality of gas-sorbent contactors positioned side by side and a regeneration facility in communication with the plurality of gas-sorbent contactors The at least one contactor wall is disposed on the plot of land and extends along a wall axis parallel to the prevailing wind direction. Each gas-sorbent contactor of the plurality of gas-sorbent contactors includes a housing including a plurality of structural members; at least one air inlet and at least one air outlet;  a gas-sorbent interface; and at least one fan. The regeneration facility is configured to process the CO2-rich sorbent and to regenerate the CO2-rich sorbent to form a regenerated sorbent for the plurality of gas-sorbent contactors.

The invention discloses a photovoltaic support structural member strength analysis method and system based on a wind load, and relates to the technical field of photovoltaic equipment detection, the method improves the accuracy and economy of photovoltaic support wind resistance design through multi-modal data fusion and intelligent algorithm iteration, and improves the photovoltaic support structural member strength analysis efficiency. Firstly, wind speed / wind direction separation modeling based on machine learning breaks through the limitation of traditional static wind pressure calculation, and the extreme wind condition prediction accuracy is effectively improved; secondly, non-dominant dangerous working conditions such as a 52-degree inclination angle can be automatically positioned through linkage of a parameterized model and a global optimization algorithm, and the efficiency is obviously improved compared with manual trial calculation; and finally, a stress threshold dynamic early warning mechanism realizes conversion from passive checking calculation to active defense.

The invention relates to an offshore wind power plant micro-siting strategy based on an improved wake flow model, and the strategy comprises the steps: collecting, statistically analyzing the long-term wind speed and wind direction data of a target region, and constructing a corresponding probability density function model; based on a Jensen wake flow model and Gaussian distribution, an improved Jensen wake flow model and an improved Gaussian wake flow model are provided, a mathematical model of the wake flow effect of the wind turbine is established, the influence of wake flow on the output power of the wind turbine is quantified, and mutual interference between units is simulated; the wake flow modeling precision is improved, the turbulence intensity is introduced, the influence of the turbulence intensity is quantified, and a Reynolds average Navier-Stokes equation model is adopted to more accurately describe the wake flow effect between the wind turbine generators; and the probability density function model of the wind speed and the wind direction and the wake flow model are integrated, a wind turbine power curve is calculated, the total output power of the wind power plant is obtained, and the overall optimal wind turbine layout is obtained. The method can provide theoretical support and an optimization strategy for micro-siting of the wind power plant.

The invention discloses an electric vertical take-off and landing aircraft flight abnormal state diagnosis method, and belongs to the technical field of electric vertical take-off and landing aircraft flight management. In order to detect and process the abnormal state of the electric vertical take-off and landing aircraft, the method comprises the following steps: constructing a flight monitoring index of the electric vertical take-off and landing aircraft; constructing influence factors of flight monitoring indexes of the electric vertical take-off and landing aircraft, wherein the influence factors comprise environment temperature, wind speed, wind direction, load, flight time, battery voltage and battery current; constructing an abnormal flight state diagnosis data set of the electric vertical take-off and landing aircraft, wherein the data set comprises a training set, a verification set and a test set; constructing a flight monitoring index prediction model of the electric vertical take-off and landing aircraft based on the improved LSTM neural network; training a flight monitoring index prediction model of the electric vertical take-off and landing aircraft by using the training set to obtain a trained flight monitoring index prediction model of the electric vertical take-off and landing aircraft; and diagnosing the abnormal flight state of the electric vertical take-off and landing aircraft based on the prediction data.

The invention provides a method for monitoring and controlling cable-stayed buckling construction of a concrete-filled steel tube arch bridge based on a digital twin system, and the method comprises the steps: collecting the monitoring data, such as wind speed and wind direction, arch rib stress displacement, tower bottom stress, tower deviation and cable force, through a sensor; establishing a concrete filled steel tube arch bridge construction digital twinning system based on a three-dimensional model, real-time monitoring, data analysis and a visual platform; time sequence data is decomposed into different frequency components through variational mode decomposition (VMD), a bridge construction stage prediction model is established through a long short-term memory network (LSTM), and real-time accurate prediction of the construction progress and state is achieved. And secondly, based on the prediction model and on-site real-time monitoring conditions, an intelligent load adjustment construction control method based on a digital twin system is provided, and high-precision control over automatic load adjustment of cable hoisting and real-time rectification of tower displacement is achieved. The problems that in a traditional monitoring and control method, early warning is not timely, the assembling precision is insufficient, and the arch axis shape control difficulty is large are solved.

The invention provides a solar cell panel inclination angle orientation adjusting device, relates to the field of photovoltaic equipment, and aims to solve the problem of poor stability of a current solar cell panel in an outdoor environment, the inclination angle of the solar cell panel is adjusted relative to a support frame through an inclination angle adjusting mechanism, and the support frame is connected with a base through an orientation adjusting mechanism. The orientation of the solar cell panel is adjusted, the wind speed and the wind direction are measured, and the inclination angle and the orientation of the solar cell panel can be changed when the wind speed exceeds a set value, so that the solar cell panel complies with the wind direction to reduce overturning and damage caused by airflow, the stability is improved, the safety is ensured, and the sunlight receiving efficiency of the solar cell panel is improved.

The invention provides a wind speed and wind direction determination method for a complex scene of a helicopter, the helicopter is equipped with a single-shaft atmospheric engine, and the wind speed and wind direction determination method comprises the following steps: step 1, extracting a course angle psi, an east direction speed VE and a north direction speed VN of the helicopter based on an inertial navigation system; 2, extracting the comprehensive vacuum speed Vt of the single-axis atmospheric engine based on an inertial navigation system; 3, determining the wind speed and the wind direction according to the course angle psi, the east speed VE, the north speed VN and the comprehensive vacuum speed Vt; and 4, dynamically adjusting the course angle psi, the east wind speed VWE and the north wind speed VWN according to the errors of the wind speed and the wind direction determined in the step 3, and re-determining the wind speed and the wind direction until the wind speed and the wind direction are determined accurately. The east speed, north speed and course angle of the integrated navigation system and the vacuum speed of the single-axis atmospheric engine are comprehensively utilized, the wind speed and direction are determined through calculation, the problem of inaccurate wind speed and direction calculation in the prior art is solved, and the wind speed and direction output accuracy is effectively improved.