3408 results about "Turbine blade" patented technology

The invention relates to the technical field of aero-engines, and discloses an automatic design method for aero-engine turbine blades, which analyzes design requirements through a language large model, combines a retrieval enhancement technology and a turbine blade expert knowledge base, performs interdisciplinary coupling verification by utilizing a step-by-step reasoning template, and generates and optimizes part design schemes and parameters. And then calling parametric modeling and an AI simulation agent model to carry out multi-physics field prediction, comparing a result with a requirement, if the result meets the requirement, outputting design, otherwise, automatically iterating and adjusting parameters until the parameters reach the standard or reach the maximum number of iterations. According to the method, end-to-end intelligent closed-loop design from design requirements to design results can be realized, manual intervention is reduced, a design scheme meeting performance requirements can be quickly generated, the design efficiency can be improved, the design cost can be reduced, and the design quality can be improved.

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 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 provides a turbine blade design method which comprises the following steps: S1, dividing a turbine blade profile into four sections at equal intervals along the radial direction according to the size of a turbine, and calculating section parameters of a middle-section turbine blade profile; s2, connecting the four sections by adopting a third-order Bezier curve, defining a blade front edge angle theta as an included angle between the Bezier curve and a blade front edge radial inlet angle alpha, and generating a three-dimensional blade model by changing the inclination angle theta of each section; s3, performing optimization to obtain an optimized theta parameter; and S4, according to the optimized theta parameter, fitting each section blade profile by using a third-order Bezier curve to generate a turbine stator and rotor three-dimensional model. According to the method, the machine learning method is applied to design of the turbine blade, the three-order Bezier curve, the CFD numerical simulation method and the particle swarm optimization are utilized, the blade parameters are given, the geometric parameters can be quickly and accurately predicted, the calculated amount is reduced, the cost is reduced, the design efficiency is improved, and the quality of the designed blade is guaranteed.

The invention provides a multi-angle cutting laser pipe cutting machine, and belongs to the technical field of laser cutting equipment, the multi-angle cutting laser pipe cutting machine comprises a machining module, a feeding module is arranged at one end of the machining module, a discharging module is arranged at the other end of the machining module, and the multi-angle cutting laser pipe cutting machine further comprises a cutting assembly connected with the machining module and used for cutting pipes; the device has the advantages that flexible adjustment of the position of the focus lens is achieved through cooperation of air cylinder driving and telescopic spring buffering, focus requirements of pipes with different thicknesses are met, flexible connection of a cooling channel is achieved through the telescopic pipe, continuous and stable heat dissipation of the focus lens is guaranteed, and the service life of the lens is prolonged; the electromagnetically-driven rotating cylinder drives the turbine blades to rotate to form negative-pressure airflow, an air curtain is formed at the cutting end, metal residues and dust are prevented from being diffused to the focus lens and the lens cone, a physical isolation barrier is formed through the protection sleeve, impurities are prevented from being attached to equipment parts or blocking a pipeline, long-term stable operation of equipment is guaranteed, and diffusion of the equipment to the working environment is reduced.

The invention relates to the technical field of torque converters, in particular to a hydrodynamic transmission power chain optimization method and system.The method comprises the steps that a hydrodynamic torque converter parameterized geometric model is built, and a pump impeller blade outflow angle, a guide wheel runner input / output angle, turbine blade geometric parameters and the relative position of a pump impeller and a turbine are set as design variables; based on CFD three-dimensional flow field simulation, a k-epsilon model is adopted for rapid analysis, an SST model is adopted for transient simulation, and simulation data under different variable combinations are obtained; training a BP neural network by using the simulation data, inputting each design variable, and constructing a multi-target optimization model with maximization of efficiency and minimization of noise as targets; a design variable combination is selected in the Pareto optimal solution set, a model is reconstructed, and an optimized hydraulic torque converter is obtained; according to the method, the problems that the design optimization efficiency of the hydraulic torque converter is low, the parameter adjusting period is long, and good compromise between the transmission efficiency and noise suppression is difficult to obtain can be solved.

The invention discloses a pyrolysis recovery system for cooperative treatment of waste wind power blades by a power station boiler, and belongs to the technical field of solid waste recovery. The system comprises a power station boiler, a pyrolyzing furnace, a mixed flue, a nitrogen air flue and a controller. Oxygen is accurately controlled by mixing flue gas at different temperature levels and mixing nitrogen, and a safe and stable heat source is provided for the pyrolyzing furnace; pyrolysis gas returns to a boiler hearth through an outlet flue to be burnt out, and recyclable fibers and residues are conveyed out through a chain grate stoker; and the controller is linked with each sensor to execute oxygen control, temperature regulation, fiber quality protection and safety interlocking operation. The problems that in pyrolysis of the waste wind power blade, heat source adaptability is poor, oxygen concentration is out of control, fiber quality is poor, the risk is high, and pyrolysis gas is difficult to dispose are solved, and gradient utilization of energy, intrinsically safe operation, high-quality and high-purity recovery of fibers and collaborative treatment of pollutants are achieved.

The invention relates to a multi-dimensional high-resolution turbine blade heat-flow coupling field synchronous measurement method and system, and the method comprises the steps: obtaining a target spot image of known space distribution in a measurement space, and building a three-dimensional space mapping function; carrying out particle matching on the velocity field measurement original image based on a three-dimensional space mapping function, and reconstructing a three-dimensional particle trajectory by adopting a self-adaptive grid algorithm combined with machine learning to obtain a high-resolution three-dimensional velocity vector field; acquiring a temperature field measurement original image, performing three-dimensional space registration according to a three-dimensional space mapping function, further calculating voxel-level temperature distribution, and inverting a three-dimensional temperature field; and carrying out coupling analysis on the three-dimensional velocity vector field and the three-dimensional temperature field, and outputting a three-dimensional heat-flow coupling cloud picture. According to the invention, multi-dimensional and high-precision synchronous measurement of the temperature field and the velocity field in the complex flow field of the turbine blade is realized, the spatial resolution and dynamic response capabilities are remarkably improved, and a reliable experimental basis is provided for analysis and optimization of the cooling performance of the blade.

The invention belongs to the technical field of wind power generation equipment state monitoring and intelligent fault diagnosis, and discloses a wind turbine generator blade acoustic fault detection method based on transfer learning, and the method comprises the steps: building a standardized sample through acoustic signal simulation and multi-dimensional data enhancement, and extracting weak fault features through an STFT-Mel frequency spectrum; a dual-scale time-frequency attention module is introduced into the lightweight MobileNetV3, so that the focusing and recognition capability on early crack features is improved; by combining transfer learning with MMD domain difference and entropy minimization regularization, efficient alignment of a simulation domain and actually-measured wind field data is achieved, and the generalization performance of the model under the small sample condition is enhanced; a transverse difference spectrogram and longitudinal historical baseline self-evolution double-flow feature fusion mechanism is adopted, common-mode noise is suppressed, and single-blade positioning, progressive degradation early warning and synchronous aging recognition are achieved. The method is small in parameter quantity, low in calculation overhead and suitable for high-precision and low-cost intelligent detection of early damage of the wind turbine generator blades.

The invention provides an aerodynamic geometry co-evolution fan blade intelligent generation system, and relates to the field of fan blade design, and the system comprises an aerodynamic geometry co-evolution module which constructs a blade geometric model in a unified high-dimensional space, generates a coupling performance field in real time, responds to disturbance, updates the performance field, and feeds back index changes; establishing a performance target balance path by adjusting disturbance; a manufacturing constraint processing module identifies a non-adjustable area to construct a tension avoidance ring, limits the approach to a path and redirects the path; the precipitation feedback module monitors and recognizes lag signal storage, remaps the lag signal to a structural area in a static and stable state and applies a correction coefficient to intervene in subsequent evolution; the mutual exclusion coordination center module establishes a conflict detection mechanism, judges conflicts based on a label atlas and executes a dislocation locking scheduling feedback chain; the potential state coordination module constructs a graph based on historical data to pre-judge a future conflict path, pre-locks a conflict mechanism and guides construction of an alternative path to form a non-concurrent dislocation execution model.

The invention discloses a fan blade inspection system and method based on an unmanned aerial vehicle, and relates to the technical field of fan blade inspection, and the method comprises the following steps: a priority analysis module constructs a health scoring model through collecting the historical inspection data and working data of each fan blade of a wind power plant, generates a health priority queue, and sends the health priority queue to an unmanned aerial vehicle; the inspection target determination module selects inspection fans to form a target set according to the initial endurance distance and the health priority queue of the unmanned aerial vehicle, the inspection route planning module plans an inspection route based on the target set in combination with fan space distribution, and the blade defect detection module controls the unmanned aerial vehicle to inspect according to the planned route, collects image data and identifies defects. And the real-time target adjustment module analyzes the fans with defects, determines an associated detection field, adds the fans which are not inspected to a target set, and regenerates an inspection path, so that all inspection tasks are completed, and the flexibility of the inspection tasks and the resource utilization efficiency are improved.

The invention discloses a single crystal turbine blade crystal orientation defect detection system based on adaptive optics, particularly relates to the field of nondestructive testing, and is used for solving the problem that thermal damage and signal consistency are difficult to consider in acoustic imaging of complex structural parts. Through partition energy threshold setting, dynamic pulse planning, photoacoustic processing and unified coordinate cross-subarea data synthesis, local thermal damage caused by excessive concentration of energy is effectively avoided in the material detection process, and the requirement for collecting high-bandwidth signals can be met in a large range. The signal-to-noise ratio and the detection efficiency are improved by regulating and controlling pulse energy and a scanning path, the amplitude comparability and the image coherence among regions are ensured through signal normalization correction and subregion image set splicing, high-resolution and comprehensive-coverage acoustic mapping is output, the crystal orientation defects of the single crystal turbine blade are positioned and evaluated, the detection precision is improved, the measurement period is shortened, and the method is suitable for large-scale popularization and application. And the method has an applicable value for aero-engine parts requiring rapid and high-precision nondestructive detection.

The invention relates to the technical field of wind power blade material testing, and discloses a testing device and method for a salt spray corrosion test of a wind power blade composite material layer. According to the method, wind power blade composite material coating preparation parameters are obtained, and coating basic information is provided for subsequent performance evaluation; based on preset salt spray test environment control parameters, dynamic salt spray environment simulation conditions are generated so as to better fit the actual outdoor environment; then, a multi-sensor coupling monitoring network is constructed, real-time data acquisition is conducted on the corrosion process of the composite material coating, and comprehensive tracking of the corrosion process is achieved; processing real-time data by utilizing a corrosion characteristic analysis algorithm, generating a multi-dimensional corrosion characteristic index, and quantitatively representing the corrosion condition of the coating; and finally, evaluating the anti-corrosion stability of the new material coating in combination with the coating characteristic parameters and the multi-dimensional corrosion characteristic indexes. According to the method, the corrosion resistance of the coating in the actual environment can be more accurately reflected, and support is provided for research, development and application of the composite coating of the wind power blade.

The invention provides a special-shaped air film hole thermal mechanical fatigue simulation part design method, which comprises the following steps of: 1, analyzing the strength and the service life of a turbine blade, and identifying a key part of the service life of a special-shaped air film hole; 2, determining that the thermal mechanical fatigue simulation piece is of a hollow structure; 3, parameters of a clamping part of the hollow simulation piece are stipulated; 4, determining the mechanical stress of the key part through three-dimensional finite element simulation of the turbine blade; 5, verifying the included angle between the principal stress direction and the growth direction of the key part of the simulation part; step 6, measuring stress by using a strain gauge under a normal-temperature initial mechanical load, and verifying whether the load is compliant or not; 7, performing three-dimensional finite element simulation analysis on the temperature field of the test piece and calculating thermal stress; 8, controlling the thermal stress distribution of the section of the simulation piece by controlling the temperature distribution; step 9, when cooling gas is introduced into the inner cavity of the special-shaped gas film hole simulation piece, carrying out a thermal mechanical fatigue test by adopting an in-phase mechanical-temperature load; and step 10, optimizing the structure of the special-shaped gas film hole and analyzing the strength.

The invention discloses a wind turbine blade semi-coupling aeroelastic modeling method considering nonlinear deformation, and belongs to the technical field of fan simulation calculation. In combination with calculation parameters used by three-party software, establishing a blade structured load model and a blade correction aerodynamic model, calculating an aerodynamic load and a structural load, and superposing: superposing the aerodynamic load, the gravity load and the centrifugal force load of the blade as an external load of a nonlinear structure control equation of the blade, and taking the external load as a calculation parameter; according to the method, the blade nonlinear structure model and the semi-coupling simulation process of the three-party wind turbine simulation software are constructed, and under the same simulation environment and load conditions, the blade nonlinear structure model and the three-party wind turbine simulation software can be subjected to semi-coupling simulation, so that the blade nonlinear structure model and the three-party wind turbine simulation software can be subjected to semi-coupling simulation calculation. The higher-precision non-linear motion response characteristics of the super-long flexible wind turbine blade are calculated, and a good effect can be achieved in the aspects of initial structure design and response evaluation of the large wind turbine blade.

The invention relates to the technical field of gas turbines, and discloses a geometric parameter optimization method, system and equipment for turbine blades and a medium. The method comprises the following steps: modeling the turbine blade according to geometric parameters, working condition parameters and material parameters of the turbine blade to obtain a plurality of first input samples with first fidelity and a plurality of second input samples with second fidelity; obtaining performance parameters of the turbine blade corresponding to each first input sample and each second input sample as a first response sample and a second response sample; and training the gas turbine performance prediction network, and predicting the performance parameters of the target turbine blade through the trained gas turbine performance prediction network according to the geometric parameters, the working condition parameters and the material parameters of the target turbine blade. And optimizing the geometric parameters of the target turbine blade by taking the maximum reliability and robustness of the target turbine blade indicated by the predicted performance parameters as a target.

The invention discloses an intelligent temperature control wind turbine generator blade electric heating deicing system and method, and belongs to the technical field of wind power generation. The system comprises an electric heating film arranged on a blade, a thermal infrared imager and a plurality of sensors, the electric heating film, the thermal infrared imager and the plurality of sensors are all connected with an intelligent control unit; the intelligent control unit is connected with an unmanned aerial vehicle carrying a laser radar and is used for regularly scanning ice layer distribution on the surface of the blade; and the electric heating film adopts zone control. The method comprises the following steps: acquiring environmental parameters and blade state monitoring data, and starting a deicing system; the method comprises the following steps: collecting deicing data from a deicing system in real time and preprocessing the deicing data to obtain preprocessed deicing data; establishing an intelligent temperature control model based on the environmental parameters and the blade state monitoring data; and inputting the pre-processed deicing data into an intelligent temperature control model, calculating to obtain dynamic adjustment data of the heating power, and transmitting the dynamic adjustment data to a deicing system for deicing.

The invention discloses a double-wall blade internal particle deposition characteristic rapid prediction method based on a reduced-order model. The method comprises the steps of model establishment, grid division, numerical simulation, data set establishment and establishment of a rapid prediction model combining POD and MLP. A deep learning method is combined with an internal channel of a cooling structure, high-dimensional data are converted into low-dimensional modal coefficients representing particle deposition characteristics based on POD decomposition for three parameters of film hole diameter, air blowing ratio and temperature ratio, an MLP deep neural network method is used for fitting the modal coefficients and related parameters, a rapid prediction model is established, and a rapid prediction result is obtained. And rapid analysis and evaluation of the particle deposition rule in the blade are realized. According to the method, the particle deposition condition in the double-wall turbine blade can be effectively predicted, and certain data support and guidance are provided for design and timely cleaning of a cooling channel in the blade.

The invention discloses a two-degree-of-freedom clamp capable of adjusting the bending moment and direction of a turbine blade and a test method. The two-degree-of-freedom clamp comprises a blade clamping component, an upper adjustable U-shaped head, a lower adjustable U-shaped head, an upper clamping rod and a lower clamping rod. The blade clamping component is in threaded connection with the upper adjustable U-shaped head and the lower adjustable U-shaped head, the other end of the upper adjustable U-shaped head and the other end of the lower adjustable U-shaped head are connected with the upper clamping rod and the lower clamping rod respectively, and the other end of the upper clamping rod and the other end of the lower clamping rod are connected with an upper clamping head and a lower clamping head of the fatigue testing machine respectively. The upper clamping rod and the upper adjustable U-shaped head are adjustably connected in pairs in the transverse direction intersecting with the vertical axis so as to adjust the eccentricity of the turbine blade load. The eccentric angle of the blade load can be adjusted by adjusting the rotation cycle of the blade clamping component. According to the clamp disclosed by the invention, by adjusting the eccentricity and the eccentricity angle during a turbine blade test, different bending moment directions and relative sizes of different sections during the turbine blade test can be realized, so that the aim of simulating a real load is fulfilled.

The invention belongs to the technical field of aero-engine high-temperature part test, and particularly relates to a thermal mechanical composite fatigue test device in a turbine blade rotation environment, which comprises a high-temperature gas system, a stator system, a rotor system, a support system, a test system, an auxiliary system and a turbine rotor blade test piece, the high-temperature fuel gas system is used for providing a fuel gas environment for a turbine rotor blade test piece and controlling the high-low temperature circulation state of fuel gas, a combustion chamber is arranged at the front end of the high-temperature fuel gas system and provided with a double-oil-way nozzle, a fuel gas flowing system is arranged at the rear end of the high-temperature fuel gas system, and a blade grid structure is designed for the fuel gas flowing system according to the geometrical shape of a turbine rotor blade. And a spray cooling section is arranged at the rear part of the test section. The device is composed of six core systems including a high-temperature fuel gas system, a stator system, a rotor system, a supporting system, a testing system and an auxiliary system, all the systems work cooperatively, and integrated simulation of the high-temperature fuel gas environment, rotating centrifugal loads and heat-force synchronous circulation is achieved.

The invention provides a wind turbine generator blade pneumatic unbalance monitoring method and system based on deep learning, and belongs to the field of deep learning. Airflow motion state data generated by a distributed sensing array in the operation process of a wind turbine generator blade are collected; performing aerodynamic feature extraction and unbalance degree quantization processing on the airflow motion state data to obtain a blade aerodynamic feature vector set; correlation learning is carried out on the blade aerodynamic feature vector set and a preset blade historical aerodynamic performance evolution trajectory, and an aerodynamic imbalance development prediction vector is generated; based on the pneumatic unbalance development prediction vector, performing unbalance trend dynamic analysis to obtain a key influence factor and an influence degree sequence of pneumatic unbalance of the blade; and outputting an evaluation result of the pneumatic imbalance of the blade and a corresponding predictive maintenance strategy according to the key influence factor and the influence degree sequence. The adaptability of the maintenance strategy and the pneumatic unbalance state of the blade can be improved, and monitoring and predictive maintenance of the pneumatic unbalance of the blade of the wind turbine generator system are supported.

A mold arrangement for producing a preform element of a wind turbine blade includes a mold carrier and a plate- or tray-like mold element arranged at the mold carrier with a form defining mold surface adapted to receive preform building material, a first heating device arranged below the mold element for heating the preform building material from below the mold element, and a second heating device for heating the preform building material from above.

The invention relates to the technical field of fan blades, in particular to an automatic fan blade coating spraying method and system based on an unmanned aerial vehicle. Comprising the steps that a plurality of blade subareas are set according to the surface structure of the fan blade; according to a preset wear simulation model, an expected wear value of each blade sub-region is generated, and whether a primary spraying strategy is generated or not is judged according to the expected wear values; acquiring a spraying monitoring packet according to a preset feedback time node, and judging whether to correct the primary spraying strategy according to the spraying monitoring packet; the wear degree of each area of the fan blade is remotely predicted according to the wear simulation model in combination with environmental monitoring parameters, each wear point of the protective coating is accurately positioned in combination with image data acquired by the unmanned aerial vehicle, and accurate control of the flight position of the unmanned aerial vehicle is realized by acquiring feature points of each blade sub-area. And meanwhile, the flight speed and the coating flow of the unmanned aerial vehicle are dynamically corrected in time by periodically collecting the thickness of a spraying layer in the spraying process, and the spraying execution efficiency is improved.

The invention relates to an intelligent wind power blade defect identification method based on phased array detection, which aims at the anisotropic characteristic of a wind power blade glass fiber reinforced composite material, and can flexibly adjust the sound beam angle, effectively penetrate through the material and inhibit the scattering of an ultrasonic signal through a low-frequency linear array probe with characteristic parameters and an electronic focusing technology. Defects in different directions such as impurities perpendicular to layers, cracks in the fiber direction, wrinkles and the like can be accurately detected, meanwhile, by combining wavelet packet transformation noise reduction and a feature extraction algorithm, the distinguishing capacity of defect echoes and noise in complex materials is remarkably improved, the method is adaptive to complex structures and material characteristics of wind power blades, the application range of the detection technology is expanded, and the detection efficiency is improved. An ultrasonic phased array detection technology and an intelligent algorithm (a K-means clustering algorithm and a YOLOv8 target detection model) are deeply fused, the limitation that traditional detection depends on manual analysis is broken through, and a full-process automatic detection system of data acquisition, feature extraction and intelligent recognition is constructed.

The invention discloses a wind turbine blade fault diagnosis method based on aerodynamic noise and image recognition, and relates to the technical field of wind turbine blade fault diagnosis, and the method comprises the steps: building a plurality of typical fault models of a wind turbine blade based on a numerical simulation platform, and extracting simulation acoustic image data; the position of the aerodynamic noise source is positioned through an acoustic camera, and corresponding blade image information is collected by an unmanned aerial vehicle; and carrying out feature training on the image sample and the acoustic image data by using a deep neural network and executing fault matching judgment. According to the method, a fault acoustic image database under multiple working conditions is constructed through numerical simulation, outfield data acquisition is performed in combination with an acoustic camera and an unmanned aerial vehicle, and joint feature training and fault matching of acoustic frequency spectrums and images are realized by using a deep neural network. The method can break through the limitations of the prior art in the aspects of real-time performance, accuracy and intelligence, and achieves the efficient and reliable diagnosis of the fault of the wind turbine blade.

The invention relates to the technical field of wind power operation and maintenance, and discloses a wind power blade crack diagnosis method and system based on knowledge graph large model enhancement, and the method comprises the steps: S1, edge end image collection and crack semantic recognition: an edge end carries out the crack detection and semantic feature extraction of a collected wind power blade image sequence through an ECL-Net lightweight network, generating structured semantic information and transmitting the structured semantic information to a cloud; s2, cloud knowledge graph retrieval and semantic reasoning: the cloud performs semantic retrieval and causal reasoning on the structured semantic information through a KFR-Net knowledge graph reasoning network based on a pre-constructed wind power blade operation and maintenance knowledge graph, and outputs a knowledge retrieval result; and S3, multi-modal information is fused through an MMR-Cogntive multi-modal memory retrieval-cognitive generation network, and a structured maintenance report including crack detection summarization, cause analysis, maintenance measures and risk assessment is generated. The method has the advantage that intelligent closed-loop management of wind power blade cracks from detection to maintenance suggestions is realized.

The utility model provides an adhesion agent emulsification reaction kettle which comprises a kettle body, an inclined motor, an inclined stirring component, a stirring driving motor, a stirring shaft, a plurality of stirring blades and turbine blades, the kettle body is provided with a closed inner cavity, a feeding port is formed in the top of the kettle body, a discharging port is formed in the bottom of the kettle body, and the inclined motor is arranged at the bottom of the kettle body. The inclined stirring component is fixedly connected with the power output end of the inclined motor and located at the bottom of the closed inner cavity, the stirring driving motor is arranged at the top of the kettle body, the power output end of the stirring driving motor is fixedly connected with a stirring shaft, and the stirring shaft is located in the closed inner cavity; the multiple stirring blades are fixed to the surface of the stirring shaft at intervals in the axis direction of the stirring shaft, the turbine blades are fixed to the bottom end of the stirring shaft, and a gap is formed between the turbine blades and the cavity bottom of the closed inner cavity. According to the utility model, materials at the bottom of the kettle generate stronger radial flow to form local strong turbulent flow, so that the mixing and circulation of the materials in the kettle are enhanced.

The invention discloses a micro-scale turbine blade boundary layer heat-flow double-field synchronous test method and system. The test method comprises the steps that temperature field initial data and velocity field initial data are acquired; based on the initial data of the temperature field and the initial data of the velocity field, the distribution state of the microparticles in the boundary layer is diagnosed, and according to the diagnosis result, the optimal distribution of the microparticles in the boundary layer is obtained by feeding back and controlling the operation parameters of the reverse cyclone separation system; based on the optimal distribution, an improved PIV algorithm is adopted to calculate a boundary layer velocity field, and the improved PIV algorithm is obtained by introducing multistage grid adaptive encryption, physical constraint conditions and a transition area recognition mechanism into the PIV algorithm; a boundary layer temperature field reconstruction model is established, depth phase coupling is carried out on a temperature field reconstruction result and a boundary layer velocity field, synchronous analysis of heat-flow coupling behaviors in a turbine blade boundary layer is achieved, and finally a boundary layer coupling cloud picture reflecting heat-flow interaction characteristics is obtained.

The invention discloses a heavy-duty gas turbine blade creep fatigue life design method considering an anisotropic effect, and relates to the technical field of gas turbine key component creep fatigue life evaluation.The method comprises the steps that orientation factor parameters on characteristic orientation are determined based on tensile data on [001] crystal orientation; constructing a modified stress relaxation formula; constructing an anisotropic failure strain energy density equation based on the pure creep performance data and the orientation factor parameters, and determining an upper platform of failure inelastic strain energy density on [001] crystal orientation; further determining an upper platform of the failure inelastic strain energy density on the feature orientation; constructing a creep damage prediction model based on a modified stress relaxation formula and an anisotropic failure strain energy density equation; and adopting the creep damage prediction model to obtain the creep fatigue life of the anisotropic turbine blade material sample. The method meets the actual requirements of service life evaluation of the high-temperature part of the heavy-duty gas turbine.

The invention provides a turbine blade with a cooling structure for a gas turbine, and relates to the technical field of gas turbine blade cooling, the turbine blade comprises an inner layer wall and an outer layer wall, the inner layer wall is a hollow pipe body extending out from the normal direction of a turbine rotating shaft, and the hollow part is used as a cold air flow channel and receives cooling air flow. The outer layer wall is arranged on the outer side of the inner layer wall in a sleeving mode at intervals, an annular runner is defined by the outer layer wall and the inner layer wall, a plurality of impact holes are formed in the inner layer wall, a plurality of air film holes are formed in the outer layer wall, and cooling air flow in the cold air flow channel enters the annular runner through the impact holes to impact and cool the outer layer wall and is attached to the outer layer wall after being jetted through the air film holes. And a protective layer is formed between the outer layer wall and high-temperature fuel gas to realize gas film cooling. The opposite surfaces of the inner layer wall and the outer layer wall are flow guide curved surfaces, the projection of the flow guide curved surfaces in the normal direction of the rotating shaft is a first curve, the projection of the flow guide curved surfaces in the tangential direction of the annular flow channel is a second curve, and the flow guide curved surfaces are modeled to restrain secondary contra-rotating vortexes generated when cooling airflow flows in the annular flow channel.