340 results about "Environmental Wind" patented technology

The invention discloses a digital intelligent management method and system for hydraulic engineering construction, particularly relates to the technical field of hydraulic engineering construction management, and is used for solving the problems of regulation lag and insufficient environmental disturbance adaptability of an existing method under the action of multi-physics field coupling. According to the method, a concrete three-dimensional temperature field model is established, initial regulation and control parameters are generated, and a heat conductivity coefficient under the seepage influence is corrected based on space-time relevance of pore water pressure and temperature data; the constraint boundary is dynamically adjusted in combination with the construction progress and the material strength curve, a cooling water pipe coordinated regulation and control matrix is constructed, and target flow instructions of space differentiation are generated through the included angle between the distance and the water flow direction; setting a lag time threshold and optimizing an execution time sequence according to the thermal inertia parameter, splitting the threshold and allocating a weight coefficient when the environmental wind speed suddenly changes, and finally updating the model parameter and the regulation and control instruction; accurate temperature control response and abnormal heat conduction suppression under multi-field coupling are achieved, and the structural safety and construction efficiency under complex working conditions are improved.

The invention relates to the technical field of construction control, and particularly discloses a method and a system for dynamically regulating and controlling the installation precision of an inclined-span steel box arch bridge based on machine learning. Wherein the real-time data comprises real-time stress of the arch rib, real-time deformation of the arch rib, real-time environment wind speed and real-time hoisting parameters; constructing a prediction model capable of analyzing the coupling effect of the wind load and the hoisting unbalance load based on a large amount of historical construction data; inputting real-time data into the prediction model to obtain a real-time coupling effect analysis result; outputting a hoisting sequence optimization instruction based on the decision engine, the coupling effect analysis result and a preset mechanical constraint condition of the obliquely-spanning steel box arch bridge; based on the deviation between the real-time deformation amount of the arch rib and a preset installation precision threshold value, a cable force grading adjustment scheme is generated; construction efficiency of the inclined-span steel box arch bridge is effectively improved, construction safety and installation precision are guaranteed, and stability and reliability of the bridge structure are guaranteed.

The invention discloses a fan blade diagnosis method and system based on voiceprint perception, and relates to the technical field of intelligent monitoring of wind power equipment, and the method comprises the steps: carrying out frequency domain compensation processing, stripping environment wind noise components, and generating a pure voiceprint signal based on a wind flow characteristic parameter set; based on the pure voiceprint signal, identifying a sensitive acoustic frequency band of the fan blade, exciting a sound wave phase synergistic effect in the sensitive acoustic frequency band, and generating an enhanced voiceprint signal; quantifying the internal damage depth of the fan blade material according to the enhanced voiceprint signal, and calculating a sound energy flow disorder degree index; according to the sound energy flow disorder degree index, the blade health state of the fan is judged through a multi-dimensional acoustic characteristic state space mapping mechanism, and a three-dimensional health assessment report is generated; through a physical level wind noise stripping technology, a transfer function matrix is generated based on vortex interference modeling and sound wave-airflow phase offset correction, frequency domain energy reweighted decoupling is realized, and environmental wind noise is accurately stripped in a strong turbulence environment.

The invention discloses a dynamic wind disturbance suppression method for an unmanned aerial vehicle, and belongs to the technical field of power control, and the method comprises the steps: constructing a difference value sequence of an actual moving speed and an expected moving speed of the unmanned aerial vehicle, and collecting and constructing an environment wind speed sequence; secondly, the moving speeds of the unmanned aerial vehicle at multiple moments are processed by calculating change factors and combining a moving speed prediction model, so that the moving speed of the unmanned aerial vehicle at the next moment is accurately predicted; then, on the basis of a double-layer wind disturbance control model, the difference value between the predicted speed and the expected speed and the difference value between the expected speed and the target speed are comprehensively considered, and needed wind disturbance suppression power is obtained through calculation; and finally, after the wind disturbance suppression power is applied, dynamically adjusting the double-layer wind disturbance control model according to the difference between the actual moving speed of the unmanned aerial vehicle and the target speed, thereby realizing accurate suppression of wind disturbance and improving the flight precision of the unmanned aerial vehicle in a complex meteorological environment.

The utility model relates to the technical field of photovoltaic power generation panels, and discloses a windproof photovoltaic support which comprises a counterweight base, the upper end of the counterweight base is fixedly connected with a supporting rod, the upper end of the counterweight base is fixedly connected with a wind power sensor, and the upper end of the supporting rod is fixedly connected with a fixing plate. According to the windproof photovoltaic support, the wind power sensor monitors environmental wind power in real time, the wind power sensor transmits wind power data to the processor, the processor presets a safe wind power value, and when the wind power data is larger than the preset wind power value, the second motor is started to enable the clamping assembly to be in a parallel state with the wind direction or enable the mounting plate to be in a windward state, so that the photovoltaic panel is prevented from being scraped by strong wind; the processor is provided with a preset program, the first motor and the second motor are started according to the moving track of the sun to enable the photovoltaic panel to face the sun, the power generation efficiency is ensured, the wind blocking edge of an inclined structure is arranged, when crosswind passes through, the wind blocking edge guides and decomposes the crosswind, the crosswind is decomposed into downward pressure, and the photovoltaic support is prevented from being damaged by strong wind.

The application provides a large-span bridge substructure vehicle-fire wind force real-time hybrid test platform and implementation method, the platform comprises a physical loading and transmission system, a T-shaped wind-fire coupling simulation system, a modularized prying integrated system, an intelligent control and calculation system and a multi-dimensional high-precision monitoring system. The method realizes real-time pre-test of the boundary displacement / force of the test piece through the construction of a numerical substructure fast calculation model based on LSTM and converts the boundary displacement / force into a loading instruction to drive the through core jack to realize thermal force coupling interactive loading; the T-shaped wind-fire coupling simulation system reproduces the real vehicle fire scene under the influence of the environmental wind. The test platform supports independent loading of any component of the cable system, can execute open space self-defined fire test and closed space standard fire test, and accurately analyzes the cable failure mode, critical temperature threshold and damage evolution law under fire through the multi-dimensional high-precision monitoring system, thereby providing a high-fidelity test platform and analysis method for fire resistance design of large-span bridges.

The invention discloses a high-pier large-span extra-large bridge suspended pouring beam hanging basket construction method, and belongs to the field of bridge engineering construction.The method comprises the following steps that hanging basket rails are installed, the precision is controlled, and a hanging basket comprising a double-channel-steel main truss, a manganese steel sling, an arc-shaped flow guide plate and a honeycomb formwork is assembled; grading pre-pressing is carried out according to the specified multiple of the design load, and the pre-camber of the template is corrected by adopting a BP neural network to ensure that the finished bridge linear error meets the requirement; a mechanical-hydraulic-electrical integrated intelligent control system is deployed, and the traveling speed and synchronism of the hanging basket are controlled through double-oil-cylinder driving, a 5G digital twin platform and an edge computing technology, so that rapid alarm is realized when the load is abnormal; segmental circulation construction is carried out, and when the environment wind speed reaches a set value, a hydraulic rail clamping device is automatically locked; a model is established by using ANSYS software, and simulation verification is performed on multiple types of key working conditions to ensure that the safety coefficient of the structure meets the specification requirement. The construction precision and safety are guaranteed, and the method adapts to complex environments.

The invention discloses dust falling equipment for building construction, and relates to the technical field of construction dust falling, the dust falling equipment comprises a support, the support is of a U-shaped plate-shaped structure, vertical plates are arranged on the two sides of the upper end face of the support, rotating shafts are rotatably connected to the vertical plates, atomizing nozzles are installed in the middles of the rotating shafts, and the atomizing nozzles are connected to the upper end face of the support; the end part of the rotating shaft is connected with a wind power driving piece for driving the rotating shaft to rotate; the clamping assembly is mounted on the bracket and is used for fixing the dust falling equipment on the construction coaming; the water mist shielding assemblies are installed on the front side and the rear side of the upper end face of the support; through cooperative arrangement of the wind power driving part, the water mist shielding assembly and the telescopic driving assembly, rotation of an atomization spray head and stretching movement of an auxiliary baffle can be driven through power of environmental wind, so that the shielding area of the corresponding position is increased, and water mist floating to one side of the surrounding plate is reduced; therefore, the influence of water mist drifting caused by environmental wind on the environment on the two sides of the coaming is reduced.

The invention relates to the technical field of unmanned crown block control, and discloses an anti-swing control method and system for an unmanned crown block, and the method comprises the steps: preliminarily determining the initial transportation speed and the initial length of a steel wire rope of the unmanned crown block according to to-be-loaded mass information, to-be-transported distance information and historical information; the initial transportation speed is adjusted according to the load swing angle and the load swing angular speed, and the adjusted transportation speed is obtained; adjusting the initial length of the steel wire rope according to the environmental wind speed and the environmental wind speed change value to obtain the adjusted length of the steel wire rope; and the to-be-loaded mass information, the to-be-transported distance information, the transportation initial speed, the steel wire rope initial length, the load swing angle, the load swing angular speed, the environment wind speed, the environment wind speed change value, the transportation adjusted speed and the steel wire rope adjusted length are stored. Through multi-parameter collaborative optimization, the transportation efficiency is ensured, the anti-swing effect is improved, and the problems of response lag and poor adaptability in traditional crown block control are solved.

The invention discloses an air pollution intelligent early warning method and system based on machine learning, and the method comprises the steps: obtaining the multi-source data of environment, wind direction, geography, traffic, emission, population and the like, carrying out the multi-scale decomposition of the environment data, extracting the short-term fluctuation and long-term trend, and achieving the time series prediction in combination with a historical mode; constructing a regional association graph by using a graph convolutional network, identifying cross-regional diffusion features, and fusing wind direction and space information to determine a high-risk region and a potential diffusion path; carrying out weighted calculation in combination with traffic and emission data to obtain a comprehensive risk score, and completing region division and early warning level determination; and finally, generating a regional visual early warning report. According to the invention, pollution trend accurate prediction and diffusion path identification can be realized.

The invention relates to a wind power blade hoisting load simulation analysis method which comprises the following steps: defining a plurality of simulation working conditions corresponding to a plurality of hoisting scenes according to a blade hoisting scheme of a wind generating set and the plurality of hoisting scenes; a multi-body coupling model established on the basis of a blade hoisting system is adopted, hoisting load simulation analysis is conducted on the basis of the multiple simulation working conditions, hoisting load data of the multiple simulation working conditions are obtained, and the multi-body coupling model comprises blades, a draught fan main engine, a hoisting tool and environment wind conditions. The invention further provides a wind power blade hoisting load simulation analysis device and a storage medium. The simulation analysis of the hoisting load of the wind power blade is realized, the load level of the blade and the whole machine in the hoisting process of the wind power blade can be evaluated, physical tests can be reduced, and the hoisting safety of the wind power blade can be enhanced.

The invention relates to a photovoltaic power station cleaning method and device. The method comprises the steps that infrared steam image information, the spraying height and the steam amount are obtained below an unmanned aerial vehicle; determining the hovering buoyancy of the steam fire balloon from a preset buoyancy model according to the steam quantity, and determining the hovering power of the unmanned aerial vehicle according to the hovering buoyancy; identifying and determining an environment wind direction and a steam offset distance according to the infrared steam image information, and determining a wind-resistant paddle according to the environment wind direction; determining the environment wind speed according to the jet height, the preset jet speed and the steam offset distance, and determining the wind-resistant power of the wind-resistant paddle according to the environment wind speed; and controlling the unmanned aerial vehicle to suspend according to the suspension power and adjusting the anti-wind paddles according to the anti-wind power so as to enable the unmanned aerial vehicle to suspend when wind exists and adjust the unmanned aerial vehicle to clean the photovoltaic panel when the wind direction changes. The unmanned aerial vehicle is controlled in the mode, so that the unmanned aerial vehicle can stably hover in the air when running under the windy condition, and the photovoltaic panel is convenient to clean.

An air inlet sealing shutter capable of minimizing ventilation resistance during opening belongs to the technical field of ventilation and air conditioning, and comprises a window frame and a vertical wide shutter group capable of minimizing ventilation resistance during opening, the vertical wide shutter group consists of M vertical wide shutters with rotating shafts, and M is greater than or equal to 2; the width W of the vertical wide shutter meets 0.5 m < = W < = 2.6 m, the ratio F of the thickness to the width of the vertical wide shutter meets 1 / 50 < = F < = 1 / 10, the vertical wide shutter with the ratio F of the thickness to the width is used for reducing ventilation resistance caused by the shielding area corresponding to the thickness of the vertical wide shutter when the shutter is opened, and meanwhile the wind resistance strength of the vertical wide shutter is maintained; the vertical wide shutter comprises an air inlet lap joint area, a solid shutter area and an air outlet lap joint area. When environmental wind exists and the shutter is opened, flow guide and vortex elimination are carried out through the vertical wide shutter blades with the width W and the air inlet lap joint area of the vertical wide shutter blades, so that the ventilation resistance of the shutter during inclined air inlet is minimized; when the louver is closed, air inlet sealing of the louver is achieved through alternate lap joint of the air inlet lap joint areas and the air outlet lap joint areas of the adjacent louvers.

The invention relates to the technical field of forging, in particular to a heat treatment and vibration aging comprehensive optimization method for a wind power annular forge piece, which comprises the following steps: acquiring a final-forged annular forge piece; the surface temperature of the annular forge piece is monitored after finish forging, after the surface temperature of the annular forge piece is reduced to be below the target surface temperature, furnace charging and residual temperature annealing are conducted, and rolling residual stress of a plurality of detection points of the annular forge piece is determined; reheating the annealed annular forge piece, preserving heat, transferring into a quenching tank, determining target transferring time of the annular forge piece according to the wall thickness of the forge piece, the real-time forge piece temperature and the environment wind speed, and determining optimal transferring time by combining the target transferring time and the wall thickness of the forge piece; tempering is conducted after quenching, vibration aging parameters are determined according to the tempering residual stress of the annular forge piece, and vibration aging treatment is conducted; and after processing, determining correction parameters and correction values according to a comparison result of the vibration residual stress and preset residual stress. Residual stress is effectively eliminated, and the deformation rate of the annular forge piece is reduced.

The invention discloses a power distribution cabinet intelligent early warning system and method based on multi-modal data, and relates to the technical field of power distribution cabinet intelligent early warning, and the method comprises the steps: carrying out the recognition of environment parameters of a position where a power distribution cabinet is located, and obtaining macroscopic environment data, including environment wind power data, environment humidity data, environment temperature data and environment pollutant data; constructing a three-dimensional coordinate system, and performing grid unit division on the surface of the power distribution cabinet to obtain grid units of the power distribution cabinet; performing data collection on the grid units of the electric cabinet to obtain grid unit parameters; constructing an electrolytic layer prediction model, identifying the macroscopic environment data and the grid unit parameters, and predicting to obtain an electrolyte film risk index of the grid unit of the power distribution cabinet based on coupling analysis of environmental dirt retention and condensation infiltration on the outer surface of the power distribution cabinet; and performing abnormal early warning on the power distribution cabinet based on the spatial distribution of the grid units of the power distribution cabinet and the corresponding electrolyte film risk index.

The invention relates to the technical field of power construction, discloses a multi-system coupling control crossing frame erection collaborative operation method and system, and aims to improve the stability and collaborative efficiency of an erection process. The method comprises the following steps: establishing a three-dimensional digital model of a spanning structure body, synchronously accessing a plurality of sensor acquisition systems, and acquiring space coordinates of key nodes of the spanning structure body, environmental wind load and operation state information of construction equipment in real time; dynamically generating an anti-overturning constraint condition based on space coordinates and wind load information, and generating a cooperative scheduling strategy in combination with an equipment state; and constructing a space pose matching model to output deviation correction parameters. The stability of the frame body is evaluated through the dynamic analysis model, a load early warning index is generated, and an equipment action instruction is generated through the path optimization model. And adjusting the operation priority according to the early warning index, and synchronously sending the updated priority and the action instruction to the terminal to realize multi-system closed-loop control.

The invention relates to the field of digital twin driving, and discloses an electric actuator energy consumption optimization method and system based on digital twin driving, and the method comprises the steps: collecting the current, torque, rotating speed, temperature, vibration and environment wind speed data of an electric actuator in real time, carrying out the online recognition of the thermal-friction coupling parameters of the actuator through a multi-scale sliding window method, and carrying out the online recognition of the thermal-friction coupling parameters of the actuator; the operation state of the actuator is dynamically updated in combination with the load damping change and the long-term health condition; the load evolution trajectory of the actuator is extracted, transient fluctuation and long-term degradation trend analysis are combined, and the energy consumption deviation and the performance bottleneck existing in the operation process of the actuator are recognized; according to the method, related actuator components and mutual influences thereof are comprehensively analyzed, parameters, feature weights and updating frequencies of the digital twin model are dynamically adjusted, and a real-time energy consumption optimization control strategy is generated. The method has the advantage that the real-time response capability and the long-term self-adaptive precision are improved.

The invention relates to the technical field of aerostat control, and discloses an aerostat control method and system, and the method comprises the steps: S1, collecting the internal state data, external environment data and environment parameters of an aerostat through a multi-source sensor; s2, processing the data acquired in the S1, and constructing a state and disturbance observer to obtain an aerostat state estimation value and an environmental wind disturbance estimation value; s3, based on the state estimation value and the wind disturbance estimation value of the aerostat, a self-adaptive control algorithm is adopted, a control instruction used for controlling the height and the horizontal position of the aerostat is generated, and the control instruction comprises a feedforward component used for actively compensating wind disturbance; and S4, distributing the control instruction to a channel power system of the aerostat and executing the control instruction. An integrated control architecture with state estimation, disturbance observation and adaptive control capabilities is constructed, three technical bottlenecks of weak control robustness, poor anti-interference capability and low intelligent level of a traditional aerostat in outdoor application are effectively solved, and the positioning precision and stability are improved.

The invention relates to the technical field of hoisting load unmanned aerial vehicles, in particular to a hoisting load unmanned aerial vehicle load distribution algorithm, which comprises the following steps: acquiring attitude data, load position coordinates and quality of an unmanned aerial vehicle body in real time, and detecting environment wind field distribution; constructing a dynamic graph structure including the unmanned aerial vehicle attitude data, the load position coordinates and quality and the environmental wind field nodes; calculating a current total gravity center deviation, a physical residual error and a compensation weight matrix of each execution mechanism; generating a compensation instruction by using a space-time fusion prediction network, inputting historical wind field data and a current node state, and predicting a load offset in a future time window through a space-time fusion neural network; calculating a target displacement of a balancing weight and a flexible tentacle joint angle sequence; the balancing weight is controlled to move to the target displacement along the linear guide rail, and the flexible tentacle joint is driven to reach the target angle; incremental compensation is carried out based on the adjusted total gravity center position; vibration energy at a main resonant frequency is suppressed.

The invention relates to the technical field of intelligent fan control, and particularly discloses an energy-saving fan applied to an inflatable model and a control method of the energy-saving fan applied to the inflatable model. And performing time sequence analysis on external wind speed and internal pressure data by using an artificial intelligence technology based on deep learning to capture a time sequence change mode of the external wind speed and the internal pressure, and further performing time sequence response analysis on the external wind speed and the internal pressure to excavate the associated influence of the external environment wind speed on the internal pressure of the inflation model. Therefore, the rotating speed of the fan is intelligently controlled by combining the external environment condition and the internal pressure state of the inflatable model, so that the stability of the inflatable model is maintained. In this way, energy consumption can be effectively reduced, meanwhile, the stability and safety of the inflation model under various environmental conditions are ensured, and therefore the energy efficiency of the inflation model is improved.

The invention provides a downscaling bridge wind temperature coupling numerical simulation method considering a real terrain, and belongs to the technical field of bridge structure design. Comprising the steps of determining a calculation area of a mesoscale model according to a bridge geographic position, and adopting multi-layer grid nesting to improve calculation precision; obtaining terrain static data and initial meteorological field data, and configuring a physical scheme; establishing a geometric model of the small-scale model through three-dimensional modeling software; according to a small-scale model, calculating a domain inlet surface form, and performing fitting block division and extraction point planning; extracting inlet wind speed and temperature data by adopting a Cressman interpolation method through the mesoscale model, and fitting by adopting a least square method to obtain a small-scale model inlet surface wind speed and temperature function; according to the material characteristics of the bridge structure, loading a geometric model and an inlet surface wind speed and temperature function, establishing a small-scale model by using a CFD method, and solving environmental wind, a temperature field and structural response; the simulation authenticity is improved, and the redundancy of simulation work is reduced.

The invention discloses a metal ball anti-swing method for metal ball calibration of a meteorological radar, and relates to the field of meteorological radars, comprising the following steps: S1, acquiring related information of a metal ball, a flying position and a radar; s2, determining a second rope length between the metal ball and the damping object according to the first rope length and the radar; s3, the mass of a damping object is determined according to the mass of the metal ball, and the shape of the damping object is determined; s4, the two ends of a connecting rope with the second rope length are connected with the metal ball and the damping object correspondingly; s5, the unmanned aerial vehicle is released at the releasing position, and at the beginning of releasing, the overall shaking amplitude of the metal ball and the damping object is reduced; according to the method, the influence of environmental wind and unmanned aerial vehicle movement on the stability of the metal ball is reduced to the greatest extent, the swing amplitude of the metal ball in the air is reduced, the time spent on aligning the antenna to the metal ball is shortened, and the accuracy of a calibration result is improved.

The invention relates to the technical field of wind power generation. The invention provides an emergency yaw and automatic crosswind method and system for a wind turbine generator. The method comprises the following steps: monitoring the on-off state of a safety chain in real time, and activating an emergency power supply switching module when detecting that the safety chain is disconnected; synchronously acquiring unit vibration spectrum, impeller rotating speed, environment wind speed and cabin load distribution data, and generating dynamic risk assessment parameters based on a multi-source signal fusion algorithm; inputting a hierarchical control instruction to a yaw driver according to a comparison result of the risk assessment parameter and a preset threshold value; and in the automatic crosswind control stage, the yaw rate and the angle offset are dynamically adjusted based on the blade root bending moment real-time feedback and the wind speed change rate, so that the unit maintains the aerodynamic load balance in the non-windward state. The problems that after a safety chain of an existing wind turbine generator is disconnected, yaw capacity is completely lost, emergency crosswind protection or fault recovery cannot be achieved, and a traditional emergency yaw scheme is high in cost, complex in maintenance, slow in response, difficult to adapt to complex working conditions and the like are solved.

The invention provides a buoy marine safety automatic monitoring method, and belongs to the technical field of monitoring methods. The buoy marine safety automatic monitoring method comprises the following steps: receiving buoy message data, the buoy message data comprises buoy longitude and latitude data, buoy voltage data, buoy anchor lamp data, buoy cabin door data, buoy cabin water inlet data and buoy sensor data; performing multivariate decomposition operation on the longitude and latitude data of the buoy, and establishing a displacement relation function between a buoy displacement variation component and an environment wind speed variation component; constructing a buoy shift matrix based on the shift relation function, calculating a buoy public safety value, a buoy self-safety value and a buoy function safety value, and performing weighted calculation on the buoy public safety value, the buoy self-safety value and the buoy function safety value to obtain a buoy safety evaluation value; and determining the buoy risk level according to the buoy safety evaluation value. The method solves the problem of how to realize accurate identification and evaluation of the offshore safety state of the buoy.

The invention provides an anti-freezing and energy-saving control method and device for an indirect air cooling system of a thermal power plant. The method comprises the steps that meteorological information and unit working conditions of the environment where the thermal power plant is located are obtained; the meteorological information comprises environment temperature and environment wind speed, and the unit working conditions comprise load and back pressure; determining a heat transfer relationship of the circulating water system by utilizing a pre-constructed heat exchange balance equation; based on the meteorological information, the unit working condition and the heat transfer relation, the temperature deviation between the actual temperature of the circulating return water and the preset freezing damage point temperature is obtained; based on the temperature deviation, the circulating water flow and the cooling air flow are adjusted, so that the actual temperature of the circulating water is larger than or equal to the preset freezing damage point temperature; the preset freezing damage point temperature represents the lowest allowable value of the return water temperature of the circulating water, and the preset freezing damage point temperature is an arbitrary value between 14 DEG C and 18 DEG C. Under the condition that the energy consumption is reduced to the maximum extent, the actual temperature of the circulating water is accurately controlled, and freezing damage of the circulating water system is avoided.

The invention provides a visual monitoring method and device for power transmission line inspection, and relates to the technical field of power transmission line detection, and the method comprises the steps: controlling a preset crawling visual device to detect a preset power transmission line, and obtaining the environment wind parameters of the power transmission line; the environment wind parameters comprise environment wind direction parameters and environment wind speed parameters; analyzing the environmental wind parameters to determine actual influence wind parameters and reference critical wind parameters; judging whether the actual influence wind parameters meet the requirements of the reference critical wind parameters or not; if yes, continuing to control the crawling visualization device to detect the power transmission line, and continuing to obtain the environmental wind parameters of the power transmission line for cyclic judgment; if not, acquiring equipment wind receiving parameters of the crawling visualization device; analyzing the equipment wind receiving parameters to determine equipment adjustment parameters; and controlling the crawling visualization device to adjust the attitude according to the equipment adjustment parameters. The method has the effect of improving the detection accuracy of the power transmission line.

The invention relates to an AIoT-based fan tower inclination on-line monitoring and early warning method and system, and belongs to the technical field of intelligent operation and maintenance of wind power equipment, and the system comprises an end side sensing layer which is used for collecting inclination, settlement, vibration and environment data in real time through multi-point arrangement of inclination angle, vibration and wind speed sensor groups; the edge calculation layer is used for executing space-time consistency processing, dynamic weight fusion and vibration data compression sensing on the multi-source heterogeneous data; the cloud analysis layer is used for establishing a mapping relation among wind speed, vibration and inclination amount based on an LSTM neural network, inputting a time serialization wind speed mean value, vibration spectrum energy and an inclination angle difference value, outputting an inclination trend prediction value, adaptively adjusting a dynamic threshold according to the environment wind speed intensity, and generating an early warning instruction when the threshold is exceeded; and the IoT transmission network is used for converging edge data through ZigBee-Mesh and uploading the edge data to the cloud through 4G / 5G. Through an end-edge-cloud cooperative intelligent architecture, core technical support is provided for safe and efficient operation of the wind power plant.

The invention relates to the technical field of generators, and discloses an efficient heat dissipation piston generator which comprises a power generation body mechanism, wind collection and flow guide mechanisms are arranged on the two sides of the power generation body mechanism, and an air inlet and flow guide mechanism is arranged on one side of each wind collection and flow guide mechanism. According to the piston generator with the efficient heat dissipation function, through the arrangement of the power generation body mechanism, the air collection flow guide mechanism, the air inlet flow guide mechanism, the water mist spraying cooling mechanism and the seepage water collection mechanism, an active spraying cooling technology can be adopted in the using process, and micron-sized water mist is evenly sprayed to the surface of a power generation unit through the water mist spraying mechanism; and meanwhile, directional airflow is formed in combination with an air inlet flow guide structure to accelerate evaporation of liquid drops, so that heat is efficiently taken away, and compared with a traditional passive heat dissipation mode, the scheme remarkably improves the heat dissipation efficiency and reduces dependence on the environment wind speed.

The present invention discloses an offshore wind farm field-level control strategy based on distributed rolling optimization, including: obtaining the wind farm flow field distribution information in real time and using it as the environmental input of the wind farm prediction proxy model, and predicting the dynamic operation characteristics of the wind farm under different control strategies by using the prediction proxy model; in closed-loop control, decomposing the centralized optimization problem of the large-scale wind farm system into multiple distributed local optimization sub-problems according to the unit spatial arrangement rule, establishing a multi-objective optimization function considering power optimization scheduling and fatigue load, and sequentially solving the local control optimal solutions of each wind farm subsystem within the unit optimization time domain period; repeating the above process in the next rolling optimization time domain period, and finally realizing the multi-objective rolling optimal control of the large-scale wind farm under the changing dynamic environmental wind conditions. The present invention can solve the problems of difficult optimization and high calculation cost of large-scale offshore wind farms under changing wind conditions, and realize active power optimization scheduling and load reduction.

According to a wind-driven bubble generating device. The device requires no external power supply and is driven only by environmental wind. By setting a user-interactive linear regulating mechanism, the core advantage of accurately controlling air inlet volume and bubble output volume based on wind power is realized, significantly enhancing energy efficiency ratio and user experience. The movement of the device adopts a quickly detachable and assemblable modular design, which simplifies cleaning, replacement and maintenance, greatly prolonging the service life of products and ensuring hygiene. Various mounting and fixing methods allow the device to be flexibly adapted to various wind-energy-utilizing places including inflatable castles and tents, greatly expanding its application scenarios. The device has the advantages of reasonable overall structural design, good sealing performance, liquid and air leakage prevention, simple and intuitive operation, safety and reliability, and has a huge market application prospect.