20958 results about "Fan blade" patented technology

A gas turbine engine comprises a fan, a core turbine engine coupled to the fan, a fan case housing the fan and the core turbine engine, a plurality of outlet guide vanes extending between the core turbine engine and the fan case, and an acoustic spacing. The fan comprises a plurality of fan blades that define a fan diameter and a BEAL. The fan case comprises an inlet and an inlet length between the inlet and the fan. The acoustic spacing comprises a distance between the fan and the plurality of outlet guide vanes, and in combination with the BEAL determines an acoustic spacing ratio of the gas turbine engine.

The invention relates to the technical field of fan blade fatigue damage prediction. The invention provides a fan blade fatigue damage prediction method and system. The method comprises the following steps: constructing a coupling finite element model based on blade anisotropy parameters; blade surface three-dimensional strain field data, blade vibration acceleration signals, environment temperature and humidity and wind speed and direction data are obtained in real time, and a multi-dimensional monitoring data set is constructed; based on the multi-dimensional monitoring data set, nonlinear coupling features of all the load components are extracted, a multi-dimensional feature tensor is obtained, and a reference stress field matched with the current working condition is generated; inputting the multi-dimensional feature tensor and the reference stress field into a bidirectional long-short-term memory network, and establishing a data-physics combined driven damage evolution model; and positioning a damage area based on a damage probability distribution diagram output by the damage evolution model. The problems that in the prior art, prediction errors are obvious, sensitivity to early damage is insufficient, the false alarm rate is high, and accurate positioning of the damage position and quantitative prediction of the residual life are difficult to achieve are solved.

The invention relates to the technical field of wind power generation, in particular to a long flexible blade monitoring method and system based on multi-source data fusion, which adopts a multi-source data fusion technology, collects optical fiber strain, vibration, environment and image data by arranging sensor nodes on a fan blade, and generates comprehensive feature data through preprocessing; and extracting potential feature vectors by a multi-modal auto-encoder, and mapping the potential feature vectors into predicted stress data by using a physical information neural network in combination with offline finite element simulation data and physical constraint conditions. Then, a control decision is generated through the multi-modal deep fusion network and hierarchical reinforcement learning, the blade state is adjusted in real time, and the model is optimized through a closed-loop feedback mechanism; according to the invention, precise monitoring and active regulation and control of special working conditions such as blade pollution and icing are realized.

The invention discloses a multi-modal perception-based fan blade defect detection system and method, the system comprises a data fusion module and a depth feature extraction and defect detection module, the data fusion module is used for obtaining data of multiple modals of the surface of a to-be-detected fan blade in the same scene, and the depth feature extraction and defect detection module is used for extracting the data of multiple modals of the surface of the to-be-detected fan blade; preprocessing, feature extraction and feature fusion are carried out on the data of the multiple modes, a fused feature map is obtained, and the data of the multiple modes comprise a visible light image, an infrared image, laser radar data and thermal imaging data; and the depth feature extraction and defect detection module is used for introducing a dynamic multi-scale convolutional network and adaptive context convolution, performing multi-scale feature extraction on the fused feature map to obtain multi-scale feature information, and obtaining a fan blade defect detection result according to the multi-scale feature information. According to the invention, the limitation of a single-mode detection mode is solved, and the defect detection precision and adaptability of the system are improved.

The present invention particularly relates to the field of permanent-magnet electric motors. Disclosed is a permanent-magnet synchronous electric motor with an externally mounted explosion-proof mechanism. The permanent-magnet synchronous electric motor comprises an enclosure, wherein the interior of an explosion-proof housing is divided into a first cavity and a second cavity by means of a first partition plate; auxiliary heat-dissipation fan blades are provided inside the first cavity, and the auxiliary heat-dissipation fan blades are fixedly arranged on a support shaft; the support shaft is in splined connection with an output shaft inside the enclosure; a heat-dissipation explosion-proof mechanism is provided inside the second cavity; and a high temperature display mechanism is provided on a side wall of an outer end of the explosion-proof housing. In the present invention, heat in the explosion-proof housing can be transmitted to sodium bicarbonate particles, and the sodium bicarbonate particles decompose under heat and can absorb heat when decomposing, thereby increasing the heat-dissipation efficiency of the enclosure; when an explosion occurs inside the enclosure, the air pressure and temperature inside the enclosure rapidly increase, and the air pressure can enter the explosion-proof housing and be relieved by means of heat-dissipation holes; in addition, an explosion-proof buffering airbag can play a role in buffering to achieve an explosion buffering function.

A high-speed wind-gathering booster fan is provided. The high-speed wind-gathering booster fan includes a housing. An air duct is arranged inside the housing. A motor base is arranged at an axis of the air duct. Part of a circumferential wall surface of the motor base extends radially outward to form guide vanes. The air guide vane includes a parallel part and a torsional wind cutting part. The parallel part is close to the side of an air outlet. The parallel part is in parallel with an axis of an air outlet. The torsional wind cutting part is close to the side of an air inlet. The torsional wind cutting part is deviated from a plane where the parallel part is. An extension surface of the torsional wind cutting part is axially intersected with a wind-deflecting fan blade set.

Provided are a fan blade and a neck fan. The fan blade comprises a base, a plurality of outer blades, and a plurality of inner blades. The base is generally circular and protrudes in the middle, including an annular outer disc, a connecting cylinder, and a circular inner disc. The outer disc is annularly arranged on the outside of the bottom end of the connecting cylinder, and the inner disc seals the top end of the connecting cylinder. The inner disc is used for connecting the output shaft of the driving mechanism. The outer blades are annularly arranged on the outside of the outer disc, and the inner blades are annularly arranged on the outside of the inner disc, so that both the outer blades and the inner blades are located on the same side of the base, and the outer blades and the inner blades are spaced apart.

The invention relates to the technical field of fan blade detection, and provides a wind power plant fan blade detection method and system based on three-dimensional point clouds, and the method comprises the following steps: carrying out the multi-angle scanning of a fan blade through a laser scanner, and obtaining the three-dimensional point cloud data of the fan blade; performing registration processing on the three-dimensional point cloud data, and unifying the three-dimensional point cloud data into the same coordinate system to obtain registered point cloud data; performing block acceleration processing on the registered point cloud data by adopting an octree partitioning algorithm to obtain block acceleration point cloud data; performing feature extraction and feature segmentation on the block acceleration point cloud data to obtain a key feature region of the fan blade; performing defect identification analysis on the key feature region based on a point cloud network enhancement model to obtain a defect detection result, the defect detection result comprising a defect position and a defect type; and generating a detection report containing the defect position and the defect type, and visually displaying the detection report. According to the invention, the integrity of data acquisition and the precision of defect identification are improved, and the efficiency of fan blade detection is improved.

A sheath is provided. The sheath includes a leading edge portion having pressure and suction sides for respective association with pressure and suction sides of an airfoil and first and second wings respectively extending from the pressure and suction sides of the leading edge portion. The first wing includes a first elongate portion and a first trailing edge disposed at an end of and thinned relative to the first elongate portion. The second wing includes a second elongate portion and a second trailing edge disposed at an end of and thinned relative to the second elongate portion.

The invention belongs to the technical field of robots, and provides a robot joint module which comprises a driving mechanism, a speed reducing mechanism and an output mechanism which are in transmission connection in sequence, the driving mechanism generates torque, and the torque is output through the output mechanism after being increased through the speed reducing mechanism; wherein the driving mechanism is provided with a power cavity, and a stator and a rotor rotating around the periphery of the stator are arranged in the power cavity; the rotor is provided with a rotor magnet yoke with fan blades, and external air can enter the power cavity from the axial direction of the stator through rotation of the rotor magnet yoke and is discharged in the radial direction of the stator so as to take away heat generated in the power cavity to achieve heat dissipation of the stator and the rotor. Through the rotor magnet yoke with the fan blades, air flow in the power cavity can be accelerated, external air is guided to enter the power cavity and is discharged to form an efficient heat dissipation channel to take away heat, the heat dissipation capacity is improved, the heat dissipation effect is enhanced, overheating of the driving mechanism is avoided, the service life of the driving mechanism is prolonged, and the reliability of the joint module is effectively improved; and the stability of the robot during long-time operation is ensured.

A land to air vehicle with lower extendable wings and upper extendible wings, a body, a front hood fan, a rear fan and wheels. The wheels include wheel bases, exterior tires circumscribing the wheel bases, and a fan wheel assembly within each wheel base. The wheel assembly includes extendible fans, a rotor outer rim with teeth for holding a stator inner rim, a propeller shroud configured to house a variety of fan blades, at least one fan within the propeller shroud, a hinge fixedly attached to the outer rotor rim and the propeller shroud, a wheel motor platform and a wheel motor. The hinge is structured to allow the propeller shroud with fans to extend distally from the wheel base interior to navigate the land to air vehicle.

The invention relates to the technical field of industrial monitoring, in particular to a fan running state comprehensive monitoring system and a noise and current detection method thereof, and the system comprises a noise data acquisition module, a vibration noise correlation analysis module, a running current acquisition module, an abnormal current detection module, an equipment fault diagnosis module and a performance degradation prediction module. According to the method, the sound data are collected, the frequency and amplitude changes are analyzed, the types of various sound sources are recognized, abnormity caused by mechanical parts is found in the early stage, association analysis of vibration data and sound data is combined, understanding of the physical state of the fan is enhanced, and by monitoring current data and the fan blade rotating speed in real time, the fan blade rotating speed can be accurately detected. Abnormal detection of the current data and evaluation of the current stability are realized, a data basis is provided for fault diagnosis, the operation efficiency and the performance degradation trend of the fan are evaluated in combination with the current data, the service life and the maintenance period of equipment are effectively predicted, and the operation strategy and the maintenance plan of the fan are optimized.

A handheld fan comprises a mesh grid assembly, a motor, and fan blades, wherein the mesh grid assembly comprises a front mesh component and a rear mesh component, the front mesh component and the rear mesh component are fixedly combined with each other, at least one portion of the front mesh component extends in a direction away from the rear mesh component, and at least one portion of the rear mesh component extends in a direction away from the front mesh component; the motor is accommodated between the front mesh component and the rear mesh component, and the motor drives the fan blades to rotate between the front mesh component and the rear mesh component.

Disclosed is a multifunctional outdoor fan. The multifunctional outdoor fan includes a fan base, a fan support, and a fan head. The fan head is provided with a rotating shaft, fan blades mounted on the rotating shaft, and a fan grille mounted outside the fan blades. The fan grille is provided with a water tank, the water tank is provided with a water injection port, and the water injection port is connected to a water tank cover. The rotation shaft is provided with an atomization assembly, the atomization assembly is in communication with the water tank through a water tube, the water tank supplies water to the atomization assembly through the water tube, and the atomization assembly is provided with an atomization port.

A fan blade installation structure of a ceiling fan, the ceiling fan has at least one fan blade, at least one socket, and at least one elastic member. The elastic member is fixed to a periphery of the socket. The elastic member has an open end provided with a holding portion corresponding to a blade hole of the fan blade. The holding portion is elastically moved in and out of the socket. The holding portion has a guide surface for guiding the fan blade. The open end of the elastic member further has an operating portion outside the socket for a user to move the elastic member. The fan blade installation structure has the effects of installing and removing the fan blade quickly, easy assembly, and good assembly safety.

The invention discloses an intelligent temperature control type fan blade electric heating deicing control system and method, and relates to the technical field of fan blade deicing. According to the intelligent temperature control type fan blade electric heating deicing control system and method, the icing thickness, temperature, humidity and environmental conditions of the surface of a blade are collected in real time through an icing monitoring unit, a demand degree matrix is generated, and high-demand, medium-demand and low-demand areas of the blade are divided according to the demand degree matrix; only activating modules in a high-demand area under the guidance of the demand degree matrix, and keeping the non-activated modules in a standby state to save energy consumption; meanwhile, the multi-level power adjusting unit dynamically distributes power according to the heating demand quantity of the activated area, matches the icing thicknesses and actual demands of different areas, continuously collects feedback information in each heating period, and generates a feedback report and optimizes a deicing strategy, wherein the feedback information comprises the temperature change of the blade surface, the energy consumption efficiency, the deicing progress and the like.

The invention provides a centrifugal air conditioner gas-liquid separator, and belongs to the technical field of gas-liquid separators, the centrifugal air conditioner gas-liquid separator comprises a cylinder body and a cylinder cover, the cylinder body is connected with a drainage pipe and an air inlet pipe, the cylinder cover is connected with an exhaust pipe, a supporting ring and a fixing ring are arranged in the cylinder body, a drainage plate, a wind shield and a side plate are arranged in the cylinder body, and a backflow pipe is arranged on the outer wall of the cylinder body. The filter assembly comprises a water absorption piece; the extrusion assembly comprises a telescopic air bag and a fixing plate; the guide assembly comprises a drainage cover, an outer tube and an inner tube, and a rotating rod is arranged in the inner tube; the device has the beneficial effects that the wind shield drives the rotating rod to rotate, so that the turbine fan blades rotate to promote gas emission, and meanwhile, the cleaning plate is driven to clean the surface of the lower filter plate, so that the blockage condition is reduced, the filtering effect is improved, timely and effective cleaning is ensured, in addition, the water absorption part can be automatically extruded to drain water, the maintenance and replacement frequency is reduced, and the working efficiency is improved. The use efficiency is improved.

The invention discloses a fan blade inner cavity defect detection method and system based on image recognition and deep learning. The method comprises the following steps: performing multi-angle and multi-position image acquisition on an inner cavity of a fan blade through imaging equipment; the collected fan blade inner cavity image data set is preprocessed; generating a primary defect sample by using the first-layer generative adversarial network model; generating a complex defect image by using the second-layer generative adversarial network model; a convolutional neural network model is used for training; inputting the preprocessed fan blade inner cavity image data set into the trained convolutional neural network model; generating a defect report based on a defect detection result; when a new defect type appears, the recognition capability of the new defect is continuously optimized. Compared with the existing single detection technology, the multi-network combination method disclosed by the invention has the advantage that the defect detection efficiency and the classification capability are remarkably improved.

The invention provides a fan blade tip visual positioning method based on multi-parameter correction, and relates to the technical field of visual localization, and the method comprises the steps: firstly controlling an unmanned aerial vehicle to reach a top view point through the position information of a fan, carrying out the target detection and feature extraction of the fan through an algorithm, and according to the position relation between a hub and a cabin, carrying out the target detection and feature extraction; a redundancy calculation mechanism for acquiring yaw information of the fan is designed; secondly, the unmanned aerial vehicle conducts pose correction based on the top view by means of visual feedback, and therefore calculation is conducted and the unmanned aerial vehicle goes to a fan front view point; then, primary positioning of blade tips is completed through a front view, and three correction parameters of a blade phase angle, a wind wheel elevation angle and a blade taper angle are measured and calculated; and finally, constructing a fan simplified model and combining the corrected parameters to realize accurate positioning. According to the invention, precision guarantee can be provided for fan inspection route planning.

The invention relates to the technical field of ocean engineering and mechanical engineering, in particular to a method and a device for analyzing crack propagation of a fan blade considering a real ocean environment. According to the method, the real marine environment working condition is considered, dynamic simulation analysis is conducted on the fan blade, distribution information of loads borne by the fan blade is determined and loaded on a finite element model of the fan blade, a fatigue hot spot area is determined according to a finite element fatigue damage analysis result, and crack arrangement is conducted. And calculating a stress intensity factor of a crack tip and performing crack propagation simulation according to a finite element analogue simulation result so as to evaluate the fracture damage risk of the fan blade in a real marine environment. The wind turbine blade crack propagation analysis thought under the complex stress condition is provided, equipment faults and risks caused by blade breakage can be prevented, a scientific basis is provided for overhaul and operation and maintenance of a wind turbine, and therefore economic losses caused by failure of the wind turbine blade are reduced.

The invention discloses an offshore wind power blade defect detection method, and belongs to the technical field of wind power blade detection. The detection method comprises the following steps: S01, offshore wind power blade defect detection: identifying the position of a blade defect, outputting a positioning mark frame of the defect on an original image, and providing the coordinate of the center position of the mark frame and the corresponding length and width; s02, leaf image splicing: carrying out step-by-step shooting; splicing each detected image by means of an image splicing technology to form a complete fan blade image; and S03, determining the actual physical position of the blade defect in the single image: in the spliced total image, determining the actual physical coordinate of the blade defect in the original single image corresponding to the fan blade. According to the detection method, multiple detection means such as computer vision, feature extraction, image splicing and edge detection technologies are fused, blade surface defect information can be comprehensively obtained, and the detection precision and accuracy are greatly improved.

A turbomachine includes an annular casing and a fan disposed inside the annular casing and mounted for rotation about an axial centerline. The fan includes fan blades that extend radially outwardly toward the annular casing. The fan has an average chord fan width according to a first performance factor. The fan has a quantity of fan blades according to a second performance factor.

The invention relates to the technical field of new energy, in particular to a fan blade composite deicing system and method.The fan blade composite deicing system comprises a sensing layer, a decision-making layer, an execution layer and a feedback layer, and the decision-making layer comprises a graph neural network ice type recognition module, a CFD-icing coupling simulation module, a health management module and an energy consumption scheduling algorithm unit; the execution layer comprises a control unit and an execution unit, the control unit comprises a dynamic partition heating controller and a self-adaptive vibration controller, and the execution unit comprises an electric heating system and a vibration deicing system; compared with the prior art that a single deicing mode is usually adopted, and the adaptability to different ice type physical characteristics is poor, the scheme adopts a differential execution strategy, and partition electric heating control is carried out on different chord length areas of the blade based on the ice type recognition result; and high-frequency piezoelectric standing wave vibration is adopted for glaze ice, low-frequency eccentric wheel vibration is adopted for glaze ice, and the beneficial effects that the deicing efficiency is remarkably improved, invalid energy consumption is reduced, and damage to blades is reduced are achieved.

A gas turbine has a core turbine engine, and a fan having a plurality of fan blades. A nacelle surrounds the fan and at least a portion of the core turbine engine. The nacelle defines an inlet arranged upstream of the fan, and a bypass flow passage downstream of the fan defined between the nacelle and the core turbine engine. The gas turbine also includes a bypass flow passage water injection system that includes (a) at least one water injection nozzle assembly arranged to inject water into at least one of the inlet of the nacelle, or into the bypass flow passage, and (b) a water injection supply system arranged to supply water from a storage tank to the at least one water injection nozzle assembly. Water is provided by the bypass flow passage water injection system during a high power operating states of the gas turbine to augment thrust.

The invention discloses a high-integration-level and efficient-cooling external rotor motor ducted fan system, which belongs to the technical field of ducted fans and comprises a motor stator winding and a fan external rotor integrated part integrally formed by fan blades and a motor external rotor turntable, the integrated shell is integrally formed by a motor inner stator sleeve, a ducted nacelle, a motor controller main shell and a plurality of groups of ducted stationary blades; a cooling structure is mounted on the integrated shell; a motor stator winding is fixedly connected to the outer wall of one end of the integrated shell, the front flow guide cover is fixedly connected to the fan outer rotor integrated part, and the rear flow guide cover is installed at the other end of the integrated shell. And the integrated shell is rotationally connected with the fan outer rotor integrated piece. The system is low in noise, high in integration level, high in system reliability, high in system cooling efficiency, high in power level compatibility and high in expandability.

The invention discloses a fan blade state monitoring method based on multi-sensor fusion, relates to the technical field of wind power, and is suitable for wind energy prime mover equipment manufacturing and blade state monitoring technologies of onshore and offshore wind generating sets. The method comprises the following steps: acquiring operation data, a vibration signal, an acoustic signal and a pulse signal of a fan; the current working condition state of the fan is recognized, common-mode fault verification, local damage positioning and transient stress damage analysis are carried out on the vibration signals and the acoustic signals, and a fault analysis result and a first damage analysis result are obtained; performing phase-locked amplification analysis on the vibration signal and the acoustic signal through active excitation to obtain a second damage analysis result; and finally, a comprehensive state monitoring report of the fan blade is generated, so that the problems of difficulty in identification of weak damage and high false alarm rate of blades of land and offshore wind generating sets in wind energy prime mover equipment manufacturing under a non-stable working condition are solved, and the equipment operation and maintenance intelligent level in the wind energy prime mover equipment manufacturing industry is effectively improved.

The present invention relates to the technical field of small household electrical appliances and discloses a fan module, a main drive module and a foldable handheld fan using the same, wherein the fan module comprises a motor shell assembly, a fan blade assembly and a motor; and the motor is accommodated in the motor shell assembly, a rotating shaft of the motor penetrates from the motor shell assembly, and the fan blade assembly is sleeved on the rotating shaft of the motor, so that the motor drives the fan blade assembly to rotate, and a low-noise air inlet space is formed between the fan blade assembly and the motor shell assembly.

The invention relates to the technical field of fan defect detection, in particular to a fan blade inspection method based on an unmanned aerial vehicle, which comprises the following steps: acquiring static basic data of a fan; constructing a blade reference model based on the static basic data of the fan, and collecting dynamic vibration response data according to a preset short-time dynamic vibration excitation rule; identifying a blade high-risk area according to the dynamic vibration response data, and generating a layered surrounding route in combination with a blade reference model; the unmanned aerial vehicle is controlled to collect blade multi-angle images according to the layered surrounding route, the blade multi-angle images are processed to recognize surface defects, and visual confidence is generated; and mapping the dynamic vibration response data to a blade reference model by using a space-time alignment model, extracting power spectral density characteristics of corresponding positions, calculating a damage index by fusing visual confidence, and outputting an inspection report. The objective of the invention is to solve the technical problem that blade internal damage is difficult to identify in a static inspection mode.

The invention relates to the technical field of wind turbine generators, particularly provides an aeroelasticity analysis method, system and equipment of a fan blade and a medium, and aims to solve the aeroelasticity analysis problem of a flexible fan blade. Therefore, the aeroelasticity analysis method for the fan blade comprises the following steps: acquiring blade parameters and wind speed data of a to-be-analyzed blade; determining the aerodynamic load of the to-be-analyzed blade based on an aerodynamic model, the blade parameters and the wind speed data; based on the blade parameters and the aerodynamic load of the to-be-analyzed blade, determining the structural response of the to-be-analyzed blade; and carrying out aeroelasticity analysis on the to-be-analyzed blade based on the aerodynamic load and the structural response of the to-be-analyzed blade. The method is suitable for aeroelasticity analysis of the flexible blade of the wind turbine generator, and provides reliable reference for aeroelasticity stability evaluation of the flexible blade of the wind turbine generator.

The invention discloses a fan blade icing monitoring system and method, and relates to the technical field of wind power generation, and the system collects temperature, humidity and vibration signals in real time through a multi-sensor module installed on a fan blade, fuses multi-parameter data through an edge calculation unit, and calculates a blade icing risk factor # imgabs0 #. The risk factors are calculated by adopting a dynamic weighting model, and the icing state of the blade is accurately evaluated in combination with normalized characteristic values # imgabs1 #, # imgabs2 # and # imgabs3 #. And when the risk factor exceeds a set threshold value, the system triggers an alarm and transmits data to the cloud through the wireless communication module. The cloud platform predicts the future icing risk based on a long-short term memory (LSTM) neural network model in combination with historical data and real-time monitoring data, the accuracy and real-time performance of icing monitoring are improved, the method is suitable for operation in cold regions and high-altitude wind fields, and reliable guarantee is provided for safe and efficient operation of fans.