606 results about "Fatigue cracking" patented technology

The invention relates to the technical field of machine vision structure health monitoring, and discloses a steel structure weld fatigue cracking real-time monitoring system based on machine vision. The system comprises a space-time registration and fusion module, a multi-scale feature analysis module, a health monitoring module, a crack deduction calculation module and a regulation and control strategy generation module. Performing space-time registration and pixel-level fusion through the visual data of the plurality of image sensors to generate a synchronous multi-source image stream; a multi-level welding seam characteristic spectrum is constructed through multi-scale characteristic analysis, and a welding seam structure knowledge base is dynamically updated; the knowledge base and the real-time characteristic spectrum are used for monitoring the welding seam health state, and abnormity is recognized; deducing a crack initiation position and an evolution path in combination with historical damage data; and real-time load information is fused to pre-estimate the remaining service life, and a structural integrity regulation and control strategy is generated online. According to the invention, high-precision fusion of the multi-source visual data and active prediction of the crack trend are realized, and the monitoring accuracy and the early warning capability are improved.

The invention discloses a method and device for predicting the fatigue life of a high-temperature alloy vacuum electron beam welding structure, and belongs to the technical field of aero-engines. The method comprises the following steps: acquiring fatigue experiment data of a target high-temperature alloy standard sample; extracting the maximum area of an initial defect, a defect shape factor and crack source position information; obtaining a stress intensity factor range considering defect morphological characteristics and a fatigue crack propagation threshold value of a material structure containing initial defects, and correcting a damage tolerance theoretical formula to obtain simulation data; fatigue test data and simulation data are fused to form an initial data set, a fatigue limit is calculated and expanded to the data set, the expanded data set serves as input, training is conducted through a support vector regression method, hyper-parameters are determined through Bayesian optimization, and a fatigue life prediction result of the high-temperature alloy vacuum electron beam welding structure is output. The method provided by the invention can well consider the influence of different morphology defects on the fatigue performance of the welded joint.

The invention discloses an elevator steel wire rope wear real-time monitoring system and equipment thereof, and relates to the technical field of safety monitoring, the elevator steel wire rope wear real-time monitoring system comprises an acquisition and extraction module which acquires real-time surface image data and vibration signal data of a steel wire rope through a sensor array, extracts surface damage features and vibration spectrum features by adopting an image processing algorithm, and sends the surface damage features and the vibration spectrum features to a server; fusing kernel function selection and hyperplane separation to process the preliminary wear feature set; the crack identification module is used for fusing tensile strength and corrosion resistance data in the material characteristic database according to the initial wear characteristic set, classifying potential fatigue crack types through support vector identification and crack morphological characteristics by adopting a support vector machine algorithm, and determining a fatigue crack distribution diagram; according to the elevator steel wire rope abrasion real-time monitoring system and equipment thereof, accurate abrasion evaluation and dynamic maintenance optimization are achieved, the safety of the steel wire rope is improved, and the service life of the steel wire rope is prolonged.

The invention discloses an active learning and physical loss-based fatigue crack growth rate prediction method, which comprises the following steps of: splicing and fusing a preprocessed stress intensity factor, a stress ratio, pre-strain and stress amplitude, and taking the fused characteristics as the input of a model; embedding the Jones model into a loss function of the neural network, constructing a physical information time sequence model based on the Jones model, setting a parameter set, selecting a most valuable training sample from a training set by using active learning, retraining the model by using the selected most valuable training sample, selecting an optimal model, and evaluating the optimal model by using a test set; fusing the actually measured stress intensity factor, stress ratio, pre-strain and stress amplitude of the to-be-predicted material, and inputting into the obtained prediction model to obtain a predicted value of the fatigue crack growth rate. By adopting the technical scheme of the invention, the fatigue crack growth rate of the material in the whole life period can be efficiently and accurately predicted at low cost.

The invention belongs to the technical field of aircraft strength experiments, and particularly relates to a hybrid-driven metal multi-fatigue crack propagation fusion prediction method. The method comprises the following steps: establishing a stress intensity factor expression under multiple fatigue cracks; initial distribution of material parameters in the Paris physical model is obtained, and posterior distribution of the material parameters is adjusted; based on the stress intensity factor expression under the multi-fatigue crack and the posterior distribution of the material parameters, obtaining an improved Paris physical model for describing the multi-fatigue crack propagation process; a depth encoder network model is established, and a network bottleneck layer is utilized to extract guided wave deep features with strong correlation with the fatigue crack length; establishing a guided wave data driven multi-fatigue crack length online monitoring model; and building a particle filter fusion framework, and correcting and improving a distribution interval of uncertain material parameters in the Paris physical model according to guided wave monitoring data to realize dynamic tracking and prediction of metal multi-fatigue crack propagation.

The invention relates to the technical field of railway track engineering, in particular to a heavy haul railway steel rail optimization method, device, equipment, medium and product, and the method comprises the following steps: determining a stress concentration area of a heavy haul railway based on a fatigue crack distribution position and dynamic observation data on the surface of a steel rail of the heavy haul railway; curve fitting processing is conducted on the steel rail profile of the stress concentration area, and fitting profile control parameters of the fitted steel rail profile are obtained; inputting the fitting molded surface control parameters and the wheel parameters of the truck into a pre-constructed vehicle-track multi-body dynamic model to obtain multiple pieces of special molded surface data, and obtaining fatigue crack initiation life corresponding to the special molded surface data based on the special molded surface data; and on the basis of the fatigue crack initiation life, screening molded surface data meeting a preset requirement from the special molded surface data to obtain target molded surface data, and determining the steel rail molded surface corresponding to the target molded surface data as a target steel rail molded surface. The determined target steel rail profile can prolong the service life of the steel rail.

The invention discloses a method and device for testing the fatigue crack growth rate of a metal material based on temperature gradient change, and relates to the technical field of metal material detection. Mounting a constant low-temperature component and a constant high-temperature component close to two ends of the sample respectively; pasting a plurality of thermocouples on the middle surface of the sample; a magnetic powder dynamic moving assembly is installed on the surface of the sample, and a constant-temperature state is given to magnetic powder; loading a bidirectional tension-compression fatigue testing machine along the through hole of the sample; a thermal imager is arranged far away from the parallel sample, and a thermal imaging image is shot; according to the data, the fatigue crack growth rate of the sample at the corresponding temperature is obtained; according to the method, the fatigue crack growth rate of the metal material can be rapidly tested, meanwhile, the temperature gradient is formed in the sample, the influence of the temperature on the crack growth rate can be obtained in different temperature areas, the device required by the whole test is simple in structure, low in cost and convenient to load and disassemble, and the whole efficiency of the test is effectively improved.

The invention relates to precipitation-hardening stainless steel and a preparation method and application thereof. The stainless steel comprises the following chemical components: 0.05%-0.25% of C, 0-0.15% of Si, 0.2%-0.5% of Mn, 9%-18% of Cr, 0.2%-5% of Ni, 0.5%-5% of Mo, 0-0.5% of V, 5%-13% of Co and the balance of Fe and inevitable impurities. During preparation, alloy raw materials are forged or rolled after being smelted and cast, or prepared into spherical alloy powder through an atomization method / rotating electrode method and then subjected to 3D printing, a formed component is prepared, and then the product is obtained through aftertreatment. By controlling the proportion of alloy elements and cooperating with an optimized post-treatment process, the dispersion degree and strengthening effect of second-phase precipitation are improved, impact toughness is improved, 3D printing cracking is avoided, excellent comprehensive mechanical properties, especially high-temperature strength, are obtained, the fatigue cracking risk is reduced, the service life is prolonged, and the production cost is reduced. And the corrosion resistance of polishing, machining and complex environments is improved, and the mold can be used in the field of molds.

The invention discloses a fatigue crack automatic segmentation and quantification method and device in a structural strength test, and the method comprises the steps: obtaining a material fatigue crack image, and constructing a material fatigue crack image data set; a fatigue crack segmentation and quantification network CrackDAM-Net is constructed; comprising the following steps: constructing a local feature encoder, a global information encoder, a multi-scale feature fusion module, a decoder module and a crack length automatic quantization module, and training a fatigue crack automatic segmentation and quantization network; and inputting a crack image to be detected into the fatigue crack segmentation and quantization network CrackDAM-Net, and carrying out crack segmentation and length quantization to obtain the fatigue crack length. According to the method, the calculation complexity of the model is reduced by constructing the fatigue crack segmentation and quantification network-CrackDAM-Net; the effective fusion of fine-grained details and coarse-grained information is realized, and the extraction effect of crack global information, the accuracy of crack segmentation and the precision of crack length measurement are improved.

The invention relates to the field of test methods, in particular to a method for estimating the fatigue crack growth rate of a corrosion-resistant metal composite material, which comprises the following specific steps: S1, preparing a sample, and measuring and recording the thickness B, the width W and the machining notch length am of the sample; s2, prefabricating fatigue cracks; s3, selecting test parameters; s4, carrying out a fatigue crack growth rate test; s5, calculating the opening displacement variation (delta delta) of the crack tip; s6, forming a data group, analyzing a distribution rule and establishing a mathematical model; and S7, carrying out damage tolerance design and fatigue life check. According to the method, the crack tip opening displacement variation delta delta is used as a driving parameter to describe the fatigue crack propagation rule of the corrosion-resistant low-strength high-plasticity metal material and the composite material of the high-strength low-plasticity metal material; the method can solve the crack propagation problem that K is only suitable for elastic or small-range yield and r cannot be fully covered under the condition of plastic yield.

The invention relates to the technical field of intelligent scheduling, in particular to a steel structure weld fatigue cracking real-time monitoring system based on machine vision, which is characterized in that an image acquisition module acquires a high-stability image sequence in a strong vibration environment; the displacement field reconstruction module adopts a frequency domain-space domain combined decomposition technology to isolate environmental noise and material non-uniformity interference in a breakthrough manner, and an anti-noise deformation field and a stress distribution diagram are synchronously output through dual-channel parallel processing; a damage response module accurately locks sub-pixel-level crack initiation coordinates based on strain energy accumulation rate mutation, and dynamically predicts a yield risk area in combination with a displacement gradient diffusion model; the early warning module intelligently triggers graded response according to the crack position and the space coupling state of the risk area, performs positioning maintenance in a low risk area and automatic strengthening in a high risk area, and outputs heat treatment scheme coordinates when no crack exists; the system solves the problems of false detection caused by vibration noise and lagging response of single-parameter monitoring, and active protection from damage initiation to failure blocking is realized.

The invention discloses a spherical tank structure damage identification method based on optical fiber sensing network information. In the service process of a spherical tank, damage such as local cracks, corrosion and fatigue cracking may occur, and a traditional detection method has the problems of low efficiency, limited range, low sensitivity to tiny damage and the like. According to the method, the load and damage characteristics of the spherical tank structure are analyzed, quasi-distributed optical fiber sensing devices and layout are designed, an effective multi-scale optical fiber sensing information network is established, and the damage of the spherical tank structure is identified by sensing strain and temperature information, a structure theory and a data analysis method. A spherical tank structure damage source mode recognition method is developed based on continuously monitored mass data information and a BP neural network algorithm, damage types, positions and degrees are determined, and corresponding damage sensitivity indexes and early warning thresholds are established. According to the invention, the problem of difficulty in positioning and identifying the damage of the spherical tank structure is solved, the accuracy and efficiency of online monitoring are improved, and reliable technical guarantee is provided for safe operation of the spherical tank.

The invention discloses a new energy automobile motor shaft damage detection method, and relates to the technical field of mechanical part tests.The new energy automobile motor shaft damage detection system comprises an eddy current detection module, an ultrasonic detection module and a track setting module, and the eddy current detection module sweeps a motor shaft through an eddy current detection method; the estimation module is used for estimating approximate distribution of distortion cracks and fatigue cracks, the ultrasonic detection module is used for scanning axial areas of the distortion cracks and the fatigue cracks by adopting a spiral scanning method and a circumferential stepping scanning method, and the track setting module is used for setting a scanning track according to the axial distribution of the fatigue cracks and the distortion cracks. The eddy current detection module comprises an eddy current sensor, a signal processing unit and a data acquisition module, the signal processing unit is electrically connected with the eddy current sensor, and the data acquisition module is electrically connected with the signal processing unit.

The invention discloses a method for estimating the fatigue crack propagation rate of a laminated structure, and belongs to the technical field of laminated structure fatigue crack prediction. The invention aims to solve the problem that the prediction of the existing fatigue crack growth rate cannot be separated from experimental data support. Comprising the following steps: dividing a laminated structure into an upper sub-beam and a lower sub-beam, calculating tangential displacement and normal displacement of a crack interface, and calculating tangential traction force and normal traction force of the layered crack interface by combining the interface fracture toughness of the laminated structure; calculating the total strain energy of the laminated structure by combining the internal stress resultant force, the bending moment and the shear stress resultant force of the upper sub-beam and the lower sub-beam; establishing a laminated structure balance equation and obtaining a control equation set; and solving the control equation set to obtain the theoretically calculated crack length, cycle index, upper sub-beam applied load theoretical value and upper sub-beam displacement theoretical value of the laminated structure under the fatigue load of the laminated structure, calculating to obtain the cycle energy release rate, and further calculating to obtain the crack growth rate. The method is used for estimating the fatigue crack growth rate.

The invention relates to the technical field of highway engineering monitoring, in particular to an acoustic emission diagnosis method and system for fatigue cracks of a heavy-duty highway, and the method comprises the steps: collecting acoustic emission signals by a multi-depth piezoelectric ceramic sensor array pre-buried in a pavement structure; carrying out time-frequency domain topological feature extraction on the collected signals, wherein the time-frequency domain topological feature extraction comprises wavelet packet entropy value mapping and phase-space reconstruction, and extracting topological invariants such as correlation dimensions and Lyapunov indexes; inputting the time-frequency feature vector into a transfer learning model to realize multi-scale feature fusion, and innovatively adopting a gradual change domain to realize smooth transition from a source domain to a target domain; a fractal stress field model is constructed based on the fusion features, and stress diffusion depth estimation and crack evolution prediction are achieved; a crack propagation area is automatically marked through correlation coefficient analysis, a crack temperature diagram is generated, and a maintenance decision suggestion is output, so that early-stage microcrack detection of the heavy-load highway is realized, the detection sensitivity is improved by about 35%, and the depth positioning precision reaches + / -1.5 cm.

The utility model discloses a shockproof bearing, which belongs to the technical field of bearings and comprises a bearing body and a damping pad, the damping pad is arranged on the outer diameter of the bearing body, lock sleeves are arranged at two ends of the bearing body, exhaust holes are arranged on the outer diameters of the bearing body and the damping pad, and the exhaust holes are communicated with the lock sleeves. The outer diameter of the bearing body and the outer diameter of the damping pad are each provided with an oil injection hole, meanwhile, the outer diameter of the bearing body and the outer diameter of the damping pad are each provided with an oil outlet hole, four first fixing columns are fixedly installed on the outer diameter of the damping pad, and meanwhile the other ends of the first fixing columns are connected with second fixing columns in a sliding mode. In the actual use process, the stress borne by the bearing in the operation process can be dispersed, and when vibration or impact occurs, the stress can be absorbed and dispersed to a larger area by the buffering part instead of being concentrated on a certain part, so that the fatigue damage risk of the bearing part is reduced, and the service life of the bearing part is prolonged. And the bearing is not easy to generate fatigue cracks and other failure forms in the long-time use process.

The invention provides a method and system for evaluating fatigue crack life of a welding structure under a random load, and relates to the technical field of rail transit, and the method comprises the steps: recognizing a load peak value and a load valley value through a point-by-point extreme value extraction method, and generating an equivalent variable-amplitude load data set; initial crack propagation rate parameters C and m and stress intensity factor distribution are calculated, and then a deterministic crack propagation increment result is output; a hierarchical Bayesian framework is combined with an MCMC sampling method, and global parameter distribution considering material heterogeneity and observation noise is generated through a posterior distribution formula; predicting crack depth evolution curves under different confidence coefficients, and outputting fatigue life probability distribution and confidence intervals; and finally generating a fatigue life reliability evaluation report of the welding structure under the random load. The method has the beneficial effects that the problem of fatigue crack propagation of the railway vehicle welding structure under the action of the complex random load can be better solved, and more accurate and reasonable technical support is provided for reliability evaluation of the welding structure.

The invention relates to the technical field of nondestructive testing of engine blades, and discloses an in-service in-situ electromagnetic acoustic detection system and method for aero-engine blades, which adopt an integrated design of an array eddy current sensor and an array surface wave sensor, ensure that dangerous cracks exposed out of a blade tenon can be reliably detected by an eddy current method, and meanwhile, improve the detection accuracy of the blade tenon. The internal fatigue damage can also be detected by an ultrasonic method, so that the engineering application problem that the embedded fatigue crack of the blade tenon of the aero-engine cannot be effectively detected in situ is solved.

The invention relates to a phosphorus-dilute anisotropic fatigue life regulation and control method. The method comprises the following steps: (1) establishing a molecular dynamics fatigue model consisting of a phosphorene sheet with a semicircular prefabricated defect; (2) executing a simulation process and processing data: (1) when fatigue crack initiation in the Armchair direction of phosphorene is explored, rotating the model by 90 degrees and then cutting; (2) when the movement direction is the Zigzag direction, the excitation frequency is 0.027 THz-0. 05 THz; when the motion direction is an Armchair direction, the excitation frequency is 0.0315 THz to 0.05 THz; under the condition that the excitation amplitudes are respectively 2, 3 and 4, calculating the fatigue life of the phosphorene in different motion states so as to analyze the influence of the change of the excitation frequency and the excitation amplitude in different directions on the fatigue life of the phosphorene. The internal mechanism of the fatigue failure mechanism and the fatigue life difference is disclosed from the angles of stress distribution, energy dissipation rate and phonon characteristics.

The utility model provides a T-shaped component structure used for repairing cracks at a welding seam of a steel bridge deck cover plate and a U-shaped rib, which comprises a steel bridge deck, the steel bridge deck comprises the cover plate, the U-shaped rib is welded below the cover plate, a part of the cover plate at a fatigue crack position on the steel bridge deck and a part of U-shaped rib side web plate connected with the part of the cover plate are cut off to form a mounting hole, and the U-shaped rib is welded below the mounting hole. A T-shaped component is mounted on the mounting hole, the T-shaped component comprises a flange plate welded with the edge of the cover plate on the mounting hole, and an inclined web plate welded with the edge of the U-shaped rib side web plate on the mounting hole is arranged on the plate surface of one side of the flange plate. The structure is reasonable, construction is convenient and fast, the problem of crack fatigue at the position of the orthotropic steel bridge deck slab cover plate and the U rib is effectively solved, the service life of the steel box bridge deck slab is prolonged, and the fatigue problem of the steel box bridge deck slab is reduced.

The utility model relates to the technical field of traction motor bearing manufacturing, in particular to a deep groove ball bearing which comprises an outer ring, an inner ring, a plurality of rolling bodies and a retainer, the outer surface of the inner ring and the inner surface of the outer ring are respectively provided with a roller path for the rolling body to roll; the rolling body is located between the outer ring and the inner ring, and the retainer is located between the outer ring and the inner ring; the guide mode of the deep groove ball bearing is rolling body guide; the groove curvature coefficient of the outer ring is 0.520 Dw, and the groove curvature coefficient of the inner ring is 0.510 Dw. The curvature coefficient of the inner and outer ring channels is reduced by 0.005 Dw compared with a conventional bearing, and the contact area of the raceway and a rolling body is increased under the condition, so that the load borne by the unit area is reduced, the stress concentration and fatigue crack possibility is reduced, the operation temperature rise and vibration of the bearing under the high-speed working condition are reduced, and the fatigue life of the bearing is prolonged.

The application discloses a brake interface wear and fatigue crack prediction method based on complete thermal-mechanical coupling, comprising the following steps: S1, establishing a finite element model, and discretizing total analysis time into multiple time periods; S2, starting finite element analysis, and calculating interface node contact pressure and node slip rate; S3, performing transient thermal-mechanical coupling analysis; S4, calculating node wear depth and wear direction, and updating grid information by using ALE technology; S5, judging whether the interface contact state is stable convergence; S6, ending analysis, unloading brake load, and obtaining brake disc residual stress; and S7, presetting a crack at the maximum residual stress, simulating crack propagation behavior, calculating stress intensity factor and brake disc fatigue life. The application can simulate tribological behaviors such as contact stress, temperature and wear, and realizes brake disc fatigue life prediction by taking residual stress after the thermal-mechanical coupling process as load input.

The invention relates to the technical field of glass product manufacturing, in particular to a production parameter optimization method and system for a lightweight glass bottle and a medium. The method comprises the following steps: acquiring a glass bottle structure drawing, and identifying a bottle body structure and a bottle bottom structure; constructing a lightweight glass bottle model according to the bottle body structure and the bottle bottom structure; performing impact load simulation according to the lightweight glass bottle model to obtain impact load data; identifying a structure weak point based on the impact load data; performing fatigue crack evolution according to the structure weak points to generate glass crack data; identifying a crack shape based on the glass crack data to obtain zigzag glass crack data and radial glass crack data; and performing grain interface detection based on the zigzag glass crack data to obtain grain interface data. Based on a glass product manufacturing technology, the strength retention rate and the parameter adjustment precision rate in the glass bottle lightweight production process are improved.

The invention belongs to the technical field of bolt life monitoring, and discloses a device and a method for monitoring a high-strength bolt in a space grid structure based on acoustic emission, and the device is characterized in that an acoustic emission probe is arranged on the surface of a nut of the high-strength bolt; the acoustic emission probe is connected with the charge adapter; the charge adapter is connected with the high-frequency signal acquisition instrument; the high-frequency signal acquisition instrument is connected with the computer; the high-strength bolts generate fatigue cracks under the action of circulating and reciprocating loads; the acoustic emission probe transmits the acoustic emission process before fatigue fracture of the high-strength bolt to the computer, the computer draws a fatigue curve of the high-strength bolt, and online prediction is conducted on the whole life of the bolt, accurate early warning can be conducted before fracture, structural safety accidents are avoided, and the method is suitable for bridges, large-span buildings and other scenes with the high requirement for bolt strength; and long-term safety of infrastructures is guaranteed.

The invention provides a simulation method for a microscopic fatigue cracking behavior of a semi-flexible pavement. The simulation method comprises the following steps: step 1, forming a large-gap matrix asphalt mixture test piece; 2, a cement grouting material is poured; step 3, acquiring an SFP mesoscopic image; step 4, obtaining a binary image of the SFP; 5, constructing a pavement structure model; 6, determining the thickness and the thickness proportion; step 7, constructing a mesoscopic finite element model; 8, constructing a pavement structure finite element model containing the SFP microstructure; step 9, determining CZM model parameters; step 10, inserting a CZM unit; step 11, setting CZM model parameters; 12, simulating a traffic load; and step 13, simulating the fatigue cracking behavior of the SFP in the pavement structure, and quantifying the damage and the change process thereof. According to the method, the normal and tangential CZM parameters and the difference thereof in the CZM model are considered at the same time, the CZM parameters of the two-phase cementing materials with different thicknesses and thickness ratios are determined through the self-designed pull-out test and direct shear test, and the fatigue cracking behavior of the SFP can be simulated and analyzed more accurately.

The invention relates to a steel structure fatigue crack detection system based on digital twinning, and the system comprises a sensing module which is used for collecting fatigue crack monitoring data of a steel structure in real time; the digital twinning back-end data fusion and management module is used for analyzing and standardizing the fatigue crack monitoring data and constructing a digital twinning model of the steel structure so as to map the entity state of the steel structure and the spatial distribution condition of the fatigue crack; the analysis module is used for detecting the fatigue crack of the steel structure according to the fatigue crack monitoring data, updating a detection result to the digital twinborn model for state synchronization, and performing crack risk early warning; and the visualization module is used for displaying the fatigue crack monitoring data and the detection and early warning result output by the analysis module. Compared with the prior art, real-time detection, trend prediction and multi-level early warning of the fatigue crack of the steel structure are realized through cooperative operation of sensing, fusion, analysis and visualization, and the safety and decision scientificity of the operation and maintenance stage are remarkably improved.

The invention relates to a blade root fatigue load prediction and inversion system for an offshore wind turbine, and the system comprises a data collection assembly which obtains a circumferential strain gradient, and synchronously collects wave spectrum energy distribution, leading edge erosion degree and three-dimensional wind field data to establish a joint input spectrum; the hybrid calculation component is used for generating an adversarial network, reconstructing strain distribution of a bolt hole in a non-degraded state, and comparing a circumferential strain gradient to obtain an abnormal blade root dangerous point; and the control output assembly is used for superposing the damage accumulation cloud picture of the blade root dangerous point, displaying the fatigue life consumption rate and calling an equivalent load spectrum duration curve, and generating an independent variable pitch angle instruction according to the combination of asymmetric load distribution and the combined input spectrum. According to the method, quantitative identification and positioning of early-stage micro-damage can be realized, the hysteresis limitation of traditional threshold alarm is broken through, complex fatigue analysis is converted into engineering interpretable indexes, and a fault backtracking technical support is provided; load active compensation control is achieved through an independent variable pitch instruction, and fatigue crack initiation and expansion are effectively restrained.

The invention discloses a thermal mechanical fatigue crack growth rate testing method based on rigidity and a crack tip strain field. The method comprises the following steps: firstly, establishing a relation function between normalized crack length and normalized rigidity through finite element calculation; secondly, performing DIC speckle preparation for observing crack propagation and analyzing a strain field; then carrying out a thermal mechanical fatigue test, calculating the crack length based on a rigidity change result of the test, drawing an a-N relation curve in combination with a DIC synchronous observation result, and carrying out comparative analysis; and finally, calculating the crack growth rate through a three-point moving average secant method, and analyzing and determining the size of a crack tip plastic zone according to a DIC strain field, so as to accurately test the crack growth rate. The fatigue crack growth behavior under the thermal-mechanical coupling effect can be effectively tested, the thermal mechanical fatigue crack growth rate is accurately obtained by combining a crack tip strain field measurement method, and test data support is provided for damage tolerance design and structural integrity evaluation of high-temperature pressure-bearing equipment.

The invention discloses a method for improving the rotating bending fatigue strength of an AlCoCrFeNi 2.1 eutectic high-entropy alloy, and belongs to the technical field of alloys. According to the method, the AlCoCrFeNi 2.1 eutectic high-entropy alloy is treated by utilizing an ultrasonic surface rolling process (USRP), so that the density of surface defects and holes of the AlCoCrFeNi 2.1 eutectic high-entropy alloy is effectively reduced, and the rotating bending fatigue strength of the AlCoCrFeNi 2.1 eutectic high-entropy alloy is improved. And meanwhile, the surface roughness is reduced, the surface structure morphology is changed, the crack propagation path is prolonged, and finally the purpose of improving the fatigue performance of the AlCoCrFeNi 2.1 eutectic high-entropy alloy is achieved. According to the method, the surface structure of the AlCoCrFeNi 2.1 eutectic high-entropy alloy can generate residual compressive stress under the action of high-frequency vibration and static-load rolling of the USRP, so that the initiation time of fatigue cracks is effectively prolonged, and the fatigue performance of the AlCoCrFeNi 2.1 eutectic high-entropy alloy is enhanced.

The invention relates to the technical field of image segmentation, provides an image segmentation method and system for a cantilever system of a high-speed rail overhead line system supporting device, and solves the problems that defects in a metal part cannot be detected, and the defect recognition precision is low under high-frequency vibration noise interference. The method comprises the following steps: scanning a metal part of the cantilever system to generate a three-dimensional image, and collecting a stress wave signal of the surface of the metal part under the action of a dynamic load; based on the cyclic load parameter of the metal part, extracting the spectrum characteristic of the stress wave signal, and determining the energy distribution characteristic of the bolt joint by combining the geometric structure parameter of the bolt joint of the metal part; and fusing the three-dimensional image, the energy distribution characteristics, the temperature rise abnormal region and the electric field intensity distribution to generate a multi-source data set, and generating respective segmentation results of the fatigue crack and the insulation aging defect of the metal part in combination with the cyclic load parameters. According to the invention, high-precision collaborative segmentation of metal fatigue cracks and insulation aging defects of the cantilever system is realized.