44 results about "Fatigue Intensity" patented technology

The invention provides an additive repair blade high-cycle fatigue limit prediction method based on random defect probability distribution, and relates to the field of aero-engine fan and compressor blade maintenance, and the method comprises the steps: obtaining the defect distribution of a real blade; establishing a prediction model based on a critical distance theory; according to the prediction model, critical distances of the multiple real blades are determined, and a first critical distance is generated; performing defect reconstruction based on the defect distribution of the real blade to generate a virtual blade; obtaining the first high-cycle fatigue strength of the virtual blade according to the defect distribution of the virtual blade, the first critical distance and the prediction model; respectively determining a plurality of defect parameters and a Pearson coefficient of the first high-cycle fatigue strength, and screening a first parameter significantly related to the first high-cycle fatigue strength; constructing a fatigue strength evaluation model; and inputting the first parameter into the trained fatigue strength evaluation model, and outputting the predicted high-cycle fatigue strength. According to the scheme, the high-cycle fatigue limit of the blade can be quickly predicted, and the prediction accuracy is improved.

The present application relates to the technical field of high-temperature structural component fatigue strength design and life assessment, and particularly relates to a low-cycle multi-axial fatigue life prediction method based on powder high-temperature alloy damage mechanism. The method comprises: for the dangerous point of the component under non-isothermal multi-axial cyclic loading, calculating pure fatigue damage, pure creep damage and fatigue-creep interaction damage caused by a single load cycle; accumulating the pure fatigue damage, the pure creep damage and the fatigue-creep interaction damage to obtain the total damage of the single load cycle; taking the inverse of the total damage to predict the total failure life of the component under non-isothermal multi-axial cyclic loading. The method of the present application realizes effective prediction of the low-cycle multi-axial fatigue life of the powder high-temperature alloy component by accurately decomposing the damage of the dangerous point under non-isothermal multi-axial cyclic loading, can more truly reflect the comprehensive prediction model of the failure physics of the powder high-temperature alloy under multi-axial thermal mechanical loading, and improves the accuracy and reliability of the life assessment.

The utility model relates to the technical field of spine surgery nursing, in particular to a rehabilitation exercise device which comprises a nursing bed, a shell, two round rods, a sliding plate, a rolling shaft, a plurality of rubber wheels, a stepping motor, a rotating frame, a connecting rod, a fixing column, two sets of buffering units, an auxiliary unit and a protection unit. A controller is clicked to start a stepping motor, so that the stepping motor drives a rotating frame to rotate, a connecting rod is used for pulling a fixing column to move leftwards, at the moment, a buffering unit pulls a rolling shaft to move, a rubber wheel rolls on the back of a patient, the rotating frame rotates in a shaft mode, a sliding plate is pulled to move back and forth on a round rod, and rehabilitation treatment is conducted on the patient through repeated operation. The auxiliary unit is used for supporting the patient to get on and off the nursing bed, so that the fatigue strength of workers is reduced, and the rehabilitation quality and efficiency can be effectively improved.

This invention provides a novel vibration fatigue testing method for gas turbine blades. Addressing the problems of large specimen wear, long testing time, and limited results associated with traditional step-and-step stress loading methods for obtaining blade fatigue limits, this invention excites blade resonance on an electromagnetic vibration table using novel step-and-step stress loading techniques on identical blade specimens. While retaining the step-and-step matching standard, when limited test data cannot meet the matching requirements, a stress "concession" method is rationally applied based on the turbine blade structure and fatigue strength level to eliminate test data with significant stress deviations, thereby obtaining the median fatigue strength of blades from the same batch. This invention makes stress matching faster and more flexible, requiring only 2-3 stress levels to achieve a test fitting result with a confidence level of over 95%, demonstrating high accuracy. This method is applicable to fatigue limit tests of all gas turbine blades.

The application discloses a testing device integrating the testing of the elasticity of a hair piece and the fatigue strength of a shuttlecock, and relates to the technical field of the fatigue strength testing of the shuttlecock. The testing device comprises a machine table, a guide rail horizontally arranged on the top surface of the machine table, a mounting seat fixed on the top surface of a sliding block, a pressure sensor fixed on the right end surface of the mounting seat, a mounting plate fixed on the right end surface of the pressure sensor, a force transmission rod fixed on the right end surface of the mounting plate, and a hitting block fixed on the right end of the force transmission rod. A tooling mechanism for fixing the hair piece and the shuttlecock is further arranged on the machine table. The application has the advantages that the elasticity of the hair piece can be tested, and the fatigue strength testing efficiency of the shuttlecock is improved.

The invention relates to the technical field of mechanical structure fatigue testing, and discloses a copper valve clack fatigue strength testing method based on an intelligent sensor. Pressure sensors are arranged at an inlet and an outlet of the valve, pressure in the whole opening and closing process is continuously collected to form an original time sequence, and pulsating pressure is obtained by subtracting the average pressure in the whole time period; an overlapping analysis window is constructed based on pulsating pressure, frequency energy of each window is solved by using a preset frequency mapping function and weighted to obtain a frequency spectrum gravity center and statistical characteristics of the frequency spectrum gravity center changing along with the window, and accordingly, a single-side fatigue damage index of each sensor is constructed and a most unfavorable measuring point is selected as an overall damage index. And combining the pulsating pressure root-mean-square value to obtain a fatigue strength evaluation value. Through the process, pressure fluctuation of the valve under all working conditions is reflected, static bias and noise influences are restrained, fatigue related frequency energy is highlighted, and online quantitative evaluation and early warning of the fatigue evolution degree of the valve clack are achieved.

This invention discloses a system fatigue reliability prediction method for large aerospace planetary mechanisms. The steps are as follows: The fatigue load history of gear teeth under the coupled action of the system's global elastic behavior is calculated using the hierarchical finite element method to obtain load information; the probabilistic fatigue strength curve of the gear teeth is fitted based on gear low-cycle fatigue testing and the minimum order statistic conversion method; the load information and the probabilistic fatigue strength of the gear teeth are input into a reliability prediction model to obtain a system fatigue reliability prediction model that can consider the influence of system structural elements, establishing a mapping path from key structural elements of large aerospace planetary mechanisms to system reliability indicators. This invention leverages the stiffness potential of core structural elements to balance the contradiction between reliability and lightweight requirements in large aerospace planetary equipment; detailed tooth root stress calculations are not required in the system-level model; and a gear tooth probabilistic fatigue strength conversion method is proposed, thereby saving significant simulation and testing costs.

The invention provides a gas turbine compressor blade service life evaluation method based on high-cycle fatigue characteristics, and aims to solve the problem that fatigue tests under pure simulation and laboratory conditions cannot be effectively combined to meet the requirement of gas turbine blade type core component service life evaluation. According to the method, the strength condition and the vibration condition of the blade are determined through finite element analysis, then the stable attenuation law of the fatigue strength of the blade is obtained by actually measuring the vibration stress and the fatigue limit values of the blade in different use time periods, and the service life of the gas turbine compressor blade is comprehensively evaluated by taking the high-cycle vibration fatigue reserve as the standard. The method is not limited to a ship gas turbine compressor, is also suitable for effective evaluation of the service life of the moving blades of an industrial gas turbine and an aero-engine compressor, and can provide a fatigue reliability design direction for a new model.

The utility model discloses a device for detecting fatigue strength of torsion bar springs of chassis of various vehicles. The device structurally comprises an electrified positioning block, a parallel base, a protection plate, an electric control plate, a first detection body, a second detection body and a sliding rail, according to the utility model, the transverse slide rail is arranged on the parallel base as a basis, and the slide block at the lower end of the solid block of the second detection body slides in the slide rail, so that the distance between the detection rotating shaft in the convex block at the upper end of the solid block and the detection rotating shaft of the first detection body can be changed, and therefore, the torsion bar spring detection device can be matched with various torsion bar springs with different lengths; the torsion bar spring detection device can effectively adapt to torsion bar springs with different lengths for detection, a large number of driving parts can be saved for use through manual pushing of the control push block on the solid block, and the effects of saving cost and improving the practicability of the whole detection device can be achieved.

The invention provides a fatigue strength simulation method and device and a readable storage medium. An electronic device establishes a finite element model for a planet carrier with the fatigue strength to be simulated, and the finite element model is used for outputting a finite element simulation file set of the planet carrier under the unit working condition. Then, the electronic equipment generates an input file set of simulation software according to the time sequence load file of the planet carrier and the finite element simulation file set; finally, the input file set is processed through simulation software to obtain a simulation result of the fatigue strength of the planet carrier, the automation degree is high, the accuracy is high, the fatigue strength simulation efficiency is improved to a great extent, and the labor cost is saved.

The application relates to the technical field of machine learning and intelligent manufacturing, in particular to a material fatigue strength prediction method, equipment and a storage medium. The method comprises the following steps: acquiring the load level of each sample of a measured material; determining a global smoothing parameter with a Gaussian kernel function as a reference based on the load level of each sample, and determining the smoothing parameter of each kernel function based on the global smoothing parameter; estimating the probability density function of the fatigue strength of the measured material based on each kernel function and the smoothing parameter of each kernel function; and calculating an expected value and a standard deviation based on the estimated probability density function, and taking the expected value and the standard deviation as the estimated value and the estimated standard deviation of the fatigue strength of the measured material respectively. The method of the application effectively improves the accuracy and reliability of the estimated average value and the estimated standard deviation of the fatigue strength.

The invention discloses a Bayesian probability fatigue strength evaluation method for a structural member with defects, and relates to the technical field of fatigue strength prediction of aerospace metal structural members. The method comprises the following steps: firstly, drawing a fatigue limit curve based on test data of a defective material sample, embedding a physical rule of an El Hadad curve through a synthetic data set, and establishing physical priori knowledge of a defect size and a fatigue strength behavior; training model parameters by using test data of the structural member, constructing a Bernoulli likelihood function, and matching an actual failure tag of the structural member; and finally, fusing the prior distribution and the likelihood function through the Bayesian theorem to obtain probability distribution after parameter updating, and outputting a predicted failure probability expected value and uncertainty. According to the method, material sample data containing defects are fused as physical prior based on the Bayesian theory, and the probability fatigue strength is evaluated through experimental data of a small amount of structural parts.

The invention discloses a fatigue strength analysis method based on an opposite-pulling angle box R area. Calculating the working stress sigma g of the dangerous section of the R area of the angle box under each working condition; calculating a detail fatigue rated value DFR of a key structure of the dangerous section of the R area; the maximum allowable working stress [sigma max] is converted from the value; and calculating the fatigue margin MS of the dangerous section position of the R area of the opposite-pulling angle box. According to the method, the structural detail fatigue margin estimation precision of the R region of the corner box is improved, and the reliability and credibility of structural safety life design are improved.

The invention belongs to the field of fatigue strength evaluation of metal materials, and particularly relates to a method for predicting the fatigue strength of maraging stainless steel based on short plate structure hardness, which comprises the following steps: 1) determining a material fatigue cracking mechanism; (2) fatigue strength testing is carried out on the materials in various different heat treatment states, and the fatigue strength of the materials is obtained; (3) carrying out microhardness testing on the materials in various different heat treatment states to obtain hardness values of the materials; 4) fitting parameters of the fatigue strength prediction model according to the fatigue strength and the hardness value of the material, and establishing the fatigue strength prediction model; and 5) for the target heat treatment state material, performing fatigue strength prediction through the established fatigue strength prediction model. According to the method, the fatigue performance of the materials with the same component in different heat treatment states can be rapidly compared, only a small number of fatigue tests are needed for determining the fatigue cracking mechanism of the materials and testing the microhardness, and the progress of material selection, research and development and the like is effectively accelerated.

The invention discloses a fatigue strength analysis method based on opposite-pulling angle box studs. Calculating the working stress of the dangerous section of the stud of the opposite-pulling angle box under each working condition; calculating a detail fatigue rated value DFR of a key structure of the dangerous section of the stud; the maximum allowable working stress is converted through the DFR; and calculating the fatigue margin MS of the dangerous section of the stud of the opposite-pulling angle box, and when the fatigue margin MS is greater than 0, determining that the dangerous section of the stud meets the fatigue strength design requirement. According to the method, the DFR estimation precision of the corner box stud is improved, and the reliability and credibility of structural safe life design are improved.

The invention relates to the technical field of alloy materials, and discloses a method for establishing a proxy model of fatigue strength of steel, which comprises the following steps: S1, carrying out uniaxial tensile test on an alloy material sample, and calculating to obtain Young modulus of the material; performing a fatigue test on the alloy material sample to obtain the fatigue strength of the material; combining the Young modulus, the fatigue strength and the chemical components and machining process parameters of the alloy material to form a data set; s2, performing cleaning and standardized data preprocessing operation on the data set; and S3, a random forest model is constructed, and the chemical components and the machining process parameters of the alloy material serve as characteristics. A random forest model and an artificial neural network model are constructed, a staged prediction method is adopted, the Young modulus is predicted through chemical components and processing technology parameters, then the Young modulus and the parameters are jointly used as features to predict fatigue strength, feature enhancement is achieved, more associated information is mined, and the fatigue strength is improved. Therefore, the prediction precision of the fatigue strength of the alloy material is improved.

The application discloses a kind of comprehensive test platform fatigue strength checking method and system, the method includes according to platform yield strength calculation checking result to determine the fatigue hot spot area to be analyzed;Through the Genie module of SESAM software, the fatigue hot spot area is refined to obtain refinement result;The statistical result of pre-set coastal wave dispersion diagram is selected to occur probability maximum three wave working conditions, and three kinds of calculation working conditions are designed according to the refinement result to obtain node stress calculation result;According to pre-set rule, node stress calculation result is processed, to predict the fatigue damage degree and fatigue life of fatigue hot spot area based on S-N curve fatigue analysis.The fatigue life evaluation of structure is provided.This process not only improves the accuracy of analysis, but also provides an important basis for subsequent design optimization and safety evaluation.

The invention discloses an airplane stringer and skin circumferential connection detail fatigue rated value determination method. The method comprises the following steps: S1, establishing a to-be-calculated common frame stringer and skin circumferential connection component finite element model; s2, applying a unit load, and analyzing the relationship between the extrusion stress of each component at the fastener and the gross area stress at the fastener in the model through a finite element; calculating a fatigue rated value of each detail part of each component according to a detail fatigue strength calculation method, and determining the most dangerous part of the connecting assembly; and S3, uniformly converting the fatigue rated values corresponding to all the components to a reference surface, and obtaining the fatigue rated values of all details of the common frame stringer and skin circumferential connecting assembly. According to the method, the situation that dangerous parts are missed to be checked due to subtle differences between structures or uniqueness of the structures is avoided, and the calculation result is more accurate.

The invention relates to a method for simulation-based emission of operating load signals to shorten fatigue strength tests, in particular for multi-channel loaded components, characterized by 1. Local stress calculation using the finite element method (FEM) and 2. Local fatigue damage calculation and identification of relevant reversal points, consisting of the following sub-steps: 2.1. Creation of a reference voltage-time curve, 2.2. Indexed Rainflow Counting and Classification, 2.3. Damage accumulation. 3. Reconstruction of the load-time profiles based on the relevant time points

The application discloses a kind of fatigue notch coefficient's consideration needle-punched composite material fatigue life prediction method, it is related to composite material fatigue strength theory field.The method of the application includes, the calculation of material stress concentration coefficient, the influence of establishing stress level to material, the relationship between stress concentration coefficient and fatigue notch coefficient is established, the influence of stress concentration coefficient and fatigue notch coefficient is introduced by establishing stress level, the fatigue life of notch is calculated by means of smooth test piece S-N curve (stress-life curve), equation simplification.The fatigue life prediction method of needle-punched composite material considering fatigue notch coefficient proposed in the application has been verified by corresponding test of needle-punched ceramic matrix composite material.The proposed method has clear physical meaning, and can be used for constant amplitude fatigue life prediction of needle-punched composite material containing notch.

The invention discloses a flexible screen folding test device and method. The device comprises a bottom plate; the first tensioning assembly is arranged on the bottom plate; the mounting assembly is arranged on the first tensioning assembly; the second tensioning assembly is arranged on the mounting assembly; the rotary driving module is arranged on the mounting assembly; and the plurality of strain sensors are divided into two groups, each group of strain sensors are arranged on the surface of the to-be-measured piece in an array along the Y direction, and the two groups of strain sensors are symmetrically distributed along the central axis of the to-be-measured piece in the X direction. Through the device, the accurate value of the fatigue strength can be detected in real time through the strain curve, the time does not need to be set, judgment can be performed through the strain curve when the to-be-tested piece is fractured, the test efficiency is improved, the positions of the corresponding strain sensors can be judged according to the strain curves of the plurality of strain sensors, and the fatigue strength of the to-be-tested piece is improved. And the corresponding strain sensors are connected to judge the fracture position of the to-be-tested piece.

The application discloses a method and system for predicting the fatigue strength of a welded joint, and relates to the technical field of fatigue fracture of a material welded joint. The method comprises the following steps: obtaining the fatigue strength of a smooth sample; establishing a target finite element model based on the weld appearance of the welded joint, and obtaining the nonlinear stress distribution of the target position of the welded joint; determining the structural hot spot stress and the peak stress of the target position based on the nonlinear stress distribution of the target position; performing integral processing on the peak stress of the target position based on the critical distance of the notch of the welded joint, to obtain the peak hot spot stress of the target position; obtaining the effective notch stress of the target position based on the structural hot spot stress and the peak hot spot stress of the target position; determining the fatigue notch coefficient of the welded joint based on the effective notch stress of the target position and the nominal stress of the target finite element model; and obtaining the fatigue strength prediction value of the welded joint based on the fatigue notch coefficient of the welded joint and the fatigue strength of the smooth sample.

The application provides a fatigue strength analysis method and device, electronic equipment and a storage medium, and relates to the technical field of simulation.The fatigue strength analysis method comprises the following steps: establishing a finite element analysis model according to simulation parameter data; performing statics analysis based on the finite element analysis model to determine a statics analysis result; and performing fatigue damage analysis according to the statics analysis result.The application sequentially performs finite element modeling, statics analysis and fatigue damage analysis, thereby constructing a complete fatigue strength analysis process for a friction stir welding structure, and quantitatively evaluating the fatigue performance of a weld area in a virtual prototype stage, so that the fatigue risk of the structure can be identified in advance, thereby reducing cracking failure problems in the test stage, shortening the product development cycle and reducing the development cost.

The invention relates to a method for manufacturing a component (1) made of a composite material, comprising one or more layers (2, 3) associated with one another. The method involves a series of steps (4) for the fatigue design of the component (1), comprising: (A) a first step of generating a discretized model (5), for example by means of a finite element model of the component (1), in which at least a first layer (2) and, as needed, at least a second layer (3) are divided into two or more first portions (6) and two or more second portions (7), respectively; (B) a second step of defining positions of one or more first injury initiation sites (8) and one or more second injury initiation sites (9) within each of the two or more first portions (6) and each of the two or more second portions (7), respectively; (C) a third step of assigning a fatigue strength parameter to each of the damage initiation sites; (D) a fourth step of establishing a load history to be simulated on the component on the basis of specific load conditions, the total number of cycles (NC) to be simulated being divided into discrete cycle blocks, each of which is assigned a load condition.

A shot-peening device capable of improving the fatigue strength of a workpiece by applying compressive residual stress to the inside of the workpiece has a hollow housing and a vibration device for vibrating the housing. The housing stores a workpiece and shot therein. The vibration device vibrates the housing with the workpiece and the shot stored therein. Accordingly, the fatigue strength of the workpiece is improved by applying compressive residual stress to the inside of the workpiece.

The invention discloses a cutting residual stress prediction method based on an energy indentation method and a related device, and relates to the technical field of machining quality control, and the method comprises the following steps: firstly, establishing a residual stress prediction model by using the energy indentation method, and representing residual stress as a function of a hardness-load ratio; then testing the high-temperature alloy bolt to be tested by adopting a micro Vickers hardness tester to obtain a corresponding target hardness value and a target load value when the indenter forms a preset indentation depth; and finally, substituting the parameters into the model to obtain a residual stress prediction value of the bolt. According to the scheme, the defects that a traditional residual stress detection mode is damaged in parts, expensive in equipment or complex in model and poor in practicability are overcome, near-nondestructive detection is achieved with the help of a conventional hardness tester, cost is low, operation is easy and convenient, rapid detection is adapted to a production site, the model is directly associated with physical quantities, calculation is easy, universality is high, the bolt stress state can be efficiently mastered, and the detection accuracy is high. The residual compressive stress is regulated and controlled in an assisted manner to improve the fatigue strength and prolong the service life, and the practical value is remarkable.

The utility model discloses a kind of strength testing devices of sports rehabilitation equipment parts, including operation platform, clamping assembly, push rod assembly, driving device and detection element;Clamping assembly is installed on the tabletop of operation platform, for clamping the part to be tested;Pushing assembly includes a U-shaped frame with opening upward and two ejector rods, and two ejector rods are fixedly arranged on the two inner side surfaces of U-shaped frame symmetrically;Pushing assembly is driven by driving device to move linearly on operation platform;When pushing assembly moves unidirectionally, it is used to apply load to the part to be tested clamped on clamping assembly unidirectionally, and detection element is used to test the maximum stress intensity of part;When pushing assembly reciprocates, it is used to apply load to the part to be tested clamped on clamping assembly bidirectionally, and detection element is used to test the fatigue strength of part.The present application can be adapted to different sizes and shapes of part testing, and can test parts in a larger size range.

The application discloses a laser welding high-strength steel fatigue prediction method fusing data enhancement and defect parameters. The method firstly obtains the cross-section defect geometric characteristics, loading conditions and fatigue life test results of a laser welding high-strength steel test piece to form a real sample data set; then, physical information feature engineering is used to extend the features such as defect relative depth, stress intensity factor and fatigue strength; a GMM-KNN algorithm is used to perform data enhancement on the extended data set to generate a virtual sample data set; the virtual sample is divided into a training set and a verification set, and the real sample is used as a test set; a deep neural network is constructed and an early stop mechanism is introduced, and the virtual sample is used to train the network; finally, the test set is input into the trained network, and a fatigue life prediction result is output and evaluated by using an R 2 index. The application overcomes the problems of high-cycle fatigue data scarcity and low traditional prediction accuracy, and realizes accurate prediction of high-cycle fatigue life of laser welding high-strength steel.