578 results about "Material fatigue" patented technology

The invention provides a surface flaw analysis method combined with metal material fatigue life prediction, which comprises the following steps: carrying out grid optimization and refinement processing on an initial three-dimensional model, and carrying out refinement reconstruction on a local area to obtain a three-dimensional geometric model of the surface of a metal material, the three-dimensional geometric model comprising micro-scale surface flaw information; carrying out region division on the three-dimensional geometric model, identifying and extracting a surface defect region, carrying out edge detection on the surface defect region, and determining an accurate geometric contour and spatial position information of a defect; using finite element analysis software to import the three-dimensional geometric model and the flaw mathematical description model of the metal material, setting material attributes, boundary conditions and load conditions, and establishing a finite element analysis model containing microscopic flaws; and carrying out stress-strain analysis on the finite element analysis model of the microscopic flaws, calculating stress distribution and stress concentration coefficients around the flaws, and evaluating the influence of the flaws on fatigue crack initiation and expansion by adopting a fracture mechanics theory.

The invention relates to the technical field of material fatigue performance testing, in particular to a fatigue acceleration detection method and system for a high-fatigue-resistance cast wheel, and the method comprises the steps: generating a dynamic load spectrum containing a multi-axis combined load according to the actual operation condition of a target cast wheel; applying a dynamic load spectrum to the target casting wheel to perform an acceleration test, and monitoring dynamic strain responses on the surface and inside of the target casting wheel in real time based on the distributed sensing array; establishing a damage accumulation calculation model by taking a loading parameter of the dynamic load spectrum as an additional correlation condition, and calculating an equivalent fatigue damage accumulation value based on the dynamic strain response; when the equivalent fatigue damage accumulated value reaches a preset damage threshold value, it is judged that the target cast wheel reaches the fatigue life end point, and the damage evolution rule in the acceleration test is kept consistent with the damage mechanism of the actual operation working condition. According to the invention, the problems of multi-axis load simulation distortion, incomplete damage monitoring, low service life prediction precision and the like in traditional fatigue detection are effectively solved.

The invention relates to the technical field of welding material performance testing, and discloses an acoustic-optical-electric synergistic welding material fatigue performance testing method and system, and the method comprises the steps: synchronously collecting a first multi-mode signal data set of a welding material in a fatigue testing process; carrying out fusion processing to obtain a fusion feature vector; performing time sequence feature extraction to obtain time sequence comprehensive representation; constructing and training an initial fatigue performance multi-task learning model comprising a shared feature extractor and a task-specific sub-network based on time sequence comprehensive representation; implementing domain adaptation and transfer learning on the fatigue performance multi-task learning model to obtain a target fatigue performance multi-task learning model; acquiring a second multi-mode signal data set in real time and inputting the second multi-mode signal data set into the target fatigue performance multi-task learning model to obtain a welding material fatigue performance test result, so that acoustic, optical and electric multi-mode signals can be effectively integrated, and high-precision, multi-task and migratable welding material performance test is realized.

The invention provides a natural gas pipeline leakage probability calculation method and system based on a genetic algorithm, and relates to the technical field of probability calculation, and the method comprises the steps: collecting pipeline operation parameters, building a pipeline structure dynamic stress model, a material fatigue model and a corrosion damage model, carrying out the coupling analysis of the three models, and obtaining a risk assessment parameter matrix; a leakage risk assessment initial model is constructed as a fitness function, and a leakage probability calculation model is obtained through genetic algorithm optimization. According to the method, the pipeline leakage risk can be accurately predicted, accurate evaluation and early warning of pipeline safety are realized, and the pipeline operation safety is improved.

The invention discloses a casting detection method and system based on machine vision, and relates to the technical field of intersection of machine vision and material science, and the method comprises the steps: extracting the boundary coordinates of a region with a risk value exceeding a risk threshold according to a defect risk weight map, and forming a dynamic region of interest scanning frame; adjusting the incident angle of a polarized light source according to the track of the dynamic attention area scanning frame, collecting a local image, and obtaining a high-contrast image sequence for eliminating the interference of a surface oxide layer; extracting a defect edge feature map from the high-contrast image sequence through a deformable convolution kernel, and obtaining a defect candidate region mask; the defect candidate region mask is mapped to a von Mises stress field, and a crack germination probability is predicted in combination with a material fatigue limit parameter. According to the method, the accuracy and reliability of detection are improved, and the applicability under complex working conditions is remarkably improved, so that the casting quality control level is effectively improved, and the repair and quality control cost is reduced.

The invention relates to the technical field of rubber material data processing, in particular to a rubber material fatigue life prediction method based on data analysis. The method comprises the following steps: performing crack three-dimensional morphology reconstruction on a target rubber material to generate crack three-dimensional morphology data; performing material geometric model modeling on the target rubber material according to the crack three-dimensional shape data to generate an optimized rubber material geometric model; acquiring fatigue load condition data; carrying out cyclic load simulation by optimizing the rubber material geometric model based on the fatigue load condition data, and carrying out cyclic rubber fatigue characteristic analysis to obtain rubber crack fatigue characteristic data; and predicting the fatigue life of the rubber sample according to the rubber crack fatigue characteristic data to generate predicted fatigue life data. The fatigue life of the rubber material under the cyclic load is accurately predicted by analyzing the fatigue crack propagation of the rubber material.

The invention belongs to the field of material performance testing of mechanical structure strength, and particularly relates to an ultrasonic fatigue experiment monitoring method based on digital twinning. According to the method, on the basis of an ultrasonic fatigue testing machine platform, an ultrasonic fatigue digital twin model of a tested object is established by collecting frequency, temperature, load and other test data, and real-time online monitoring of ultrasonic fatigue and life prediction are carried out in combination with a fatigue life prediction model. Compared with a traditional test method, the method has the advantages that ultrasonic detection data and a digital twinborn model technology are combined, the fatigue life of the material is predicted and evaluated, the test efficiency is improved, the long-life test cost is reduced, and the accuracy and reliability of test data are improved.

The invention provides an air tightness optimization method for a soft pressurization cabin, and the method comprises the steps: presetting a dynamic sensor array at a specific position where a structure is liable to fail according to a failure risk assessment table, collecting stress concentration data caused by non-uniform pressure distribution in real time, and generating a stress distribution dynamic graph containing a time sequence; the dynamic adjusting device is driven to operate through the homogenized pressure distribution adjusting scheme, pressure field data in the cabin body is updated in real time, whether material fatigue is within the fracture risk range or not is judged, and a fatigue state monitoring report is generated; obtaining a fracture risk index in the fatigue state monitoring report, carrying out iterative adjustment on the fiber weaving density and the elastic modulus of the key area by adopting a material design optimization algorithm, and determining a final structure layout parameter for improving the performance; and extracting a limiting condition of dynamic adjustment difficulty from the final structure layout parameters, simulating a cabin operation state in an extreme environment through a digital twin technology, calculating a boundary value of performance limitation, and obtaining a verification result of performance improvement.

The invention discloses a high-rise shear wall structure anti-seismic effect evaluation method and system, and particularly relates to the technical field of high-rise shear walls. The method comprises the following steps: accurately collecting low-cycle fatigue parameters, constructing a concrete and steel bar degradation model considering a fatigue effect, applying the model to anti-seismic analysis of a shear wall structure, simulating the influence of main shock and multiple aftershock loading on structural performance, drawing a bearing capacity degradation curve according to multiple loading results, and analyzing a degradation speed abnormal state. The risk that the structural rigidity and the bearing capacity are abnormal is judged by combining the change of the residual rigidity and the bearing capacity, the risk is divided into high, medium and low levels, and proper reinforcement or prevention measures are provided for different risk levels, so that the defect that the material fatigue effect is not fully considered in the existing anti-seismic evaluation is effectively overcome, and the anti-seismic evaluation accuracy is improved. According to the method, the damage accumulation condition of the high-rise shear wall structure in frequent aftershocks can be predicted more accurately, so that the risk of premature failure of the structure is reduced, and the durability and safety of a building in an earthquake are improved.

The invention relates to the technical field of flywheel energy storage, in particular to a flywheel energy storage management system for renewable energy integration, which comprises a state monitoring module, an energy access module, a material fatigue prediction and optimization module and an energy scheduling module, the state monitoring module collects the operation state of the flywheel energy storage unit in real time. The energy access module receives input power from renewable energy sources; the material fatigue prediction and optimization module generates an operation optimization strategy when a fatigue risk is predicted; and the energy scheduling module performs dynamic energy distribution among the flywheel energy storage unit, the power grid and the standby energy storage unit, and formulates an optimal energy flow strategy in combination with historical load data and real-time input power. According to the invention, the service life of the flywheel energy storage unit is greatly prolonged, and the overall safety and reliability of the system are improved.

The invention relates to the field of mechanical fatigue simulation, and discloses a method for simulating and deducing the number of torsion cycles. Comprising the steps that a component three-dimensional parameterized model is constructed, and material fatigue characteristics are defined; applying a periodic torsion load spectrum containing a harmonic component; adopting a stress influence coefficient matrix method to execute quasi-static finite element analysis, and extracting a multi-axis stress state; calculating the maximum alternating shear stress and the average shear stress based on a critical plane recognition technology; converting into a single-axis equivalent stress amplitude through a gradient enhanced multi-axis correction rule; calculating node fatigue damage by combining an S-N curve and a damage accumulation theory; and when the damage reaches a threshold value, outputting a failure cycle number and a position. The innovation points are as follows: the prediction error is controlled within 10% by a critical plane and multi-axis correction technology; a stress matrix method realizes ten thousand times of cycle-level efficient simulation, and the efficiency is improved by 10 times; the risk early warning accuracy rate is improved to 96% by integrating a process correlation defect model; and the research and development period is shortened by 40% through a life cloud picture and an automatic optimization closed loop. The method is suitable for transmission shaft system reliability design.

The invention discloses a self-adaptive constant-force vibration reduction mechanism base and a robot, and belongs to the technical field of specialized robots. Two sets of buffer units and vibration reduction units are arranged at the front end and the rear end of the base correspondingly; driving wheels are arranged on the buffer unit and the vibration reduction unit; the buffer unit comprises a horizontal buffer structure, a vertical buffer structure and a support; the horizontal buffer structure is slidably connected with the support in the vertical direction; the top of the vertical buffer structure is hinged to the support, and the bottom is fixedly connected with the driving wheel; the support is fixedly connected with the base; the vibration reduction unit comprises a rotating support and a constant force component. According to the self-adaptive constant-force vibration reduction mechanism base and the robot, the problems that in the prior art, a vibration reduction mechanism cannot completely avoid vibration generated by a wheel type moving device in the vertical direction when the wheel type moving device moves on an uneven road surface, and consequently bolt looseness, wire harness interface looseness, material fatigue strain and the like occur can be effectively solved; and therefore, the wheel type moving device has a fault in the operation process and cannot stably operate, and the like.

The invention relates to the technical field of material fatigue prediction, in particular to a material fatigue prediction method and system based on a physical guidance neural network, and the method comprises the steps: obtaining mechanical response data and material microstructure feature data in a material cyclic loading process; based on the mechanical response data and the material microstructure feature data, constructing a physical guidance neural network model; the method comprises the following steps: a) acquiring fatigue damage parameters through a physical constraint unit by utilizing a physical guidance neural network model; b) incorporating microstructure characteristics of the material into a fatigue damage evolution equation through an attention layer; c) quantizing the uncertainty of the fatigue damage evolution equation through an uncertainty quantization unit; d) obtaining a prediction result through a feature mapping unit; the prediction result is subjected to uncertainty quantification through the prediction unit, a final material fatigue prediction result is obtained, material mechanics knowledge is introduced into the neural network through the physical constraint unit, and it is ensured that the prediction result conforms to the basic physical law.

The invention discloses a metal material fatigue life prediction method and device considering non-uniform grain size distribution, equipment, a medium and a product, and relates to the field of material fatigue life finite element numerical calculation. The method comprises the following steps: acquiring material parameters of a metal material; determining a crystal plastic constitutive model; determining a parameter group based on the crystal plasticity constitutive model; constructing a microstructure model to be tested; based on the microstructure model to be tested, according to the crystal plasticity constitutive model and the parameter group, applying a set loading condition and a set boundary condition, and determining material fatigue data; determining the fatigue crack initiation life according to the fatigue indication factor and the material fatigue data; according to the fatigue crack propagation curve, determining the fatigue crack propagation life by adopting a fitting mode; and determining the fatigue full life according to the fatigue crack initiation life and the fatigue crack propagation life. The method can improve the accuracy of determining the fatigue life of the metal material.

The invention discloses a bridge laying high-voltage cable mechanical fatigue evaluation method and system, and relates to the field of cable fatigue evaluation. Existing methods for evaluating cable fatigue caused by factors such as bridge expansion and vibration are lacked. The method comprises the following steps: arranging a test cable on a mobile test platform, and collecting sensor data to obtain bending, stretching and compression stress of the cable; data are repeatedly acquired by moving the movable box body, and the stress condition of the cable is simulated; carrying out a slice test on the cable, and measuring the elongation at break of a cable sheath and insulation; in combination with sensor data and cable material fatigue characteristics, shape parameters and scale parameters of Weibull joint distribution are fitted, and the fatigue life, the fault probability and the mechanical failure risk of the cable are predicted based on a fitting result, so that whether the fatigue failure of the cable occurs or not is judged. According to the technical scheme, through combination of the test platform and the Weibull distribution model, the mechanical fatigue of the bridge laying high-voltage cable is accurately evaluated, and the accuracy of cable life prediction is improved.

The invention relates to a method for simulating fatigue small crack propagation of a polycrystalline metal material. The method comprises the following steps: determining a crystal plastic constitutive model and accurate values of all undetermined parameters of the crystal plastic constitutive model; establishing a crack propagation finite element model of the polycrystalline metal material, and embedding the crystal plasticity constitutive model of which each undetermined parameter has a respective accurate value and a pre-obtained crack propagation criterion into the crack propagation finite element model; applying load and boundary conditions to the crack propagation finite element model, and performing crack propagation finite element analysis to obtain a finite element analysis result, including stress-strain data calculated based on the crystal plasticity constitutive model and crack propagation data calculated based on a crack propagation criterion and the stress-strain data. According to the method for simulating the fatigue small crack growth of the polycrystalline metal material, the Hall epicy size effect is introduced into the crystal plasticity constitutive model to consider the influence of the grain size on the sliding resistance, so that the simulation accuracy is improved.

The invention relates to the technical field of intelligent diagnosis, in particular to a pressure vessel health monitoring method based on an intelligent algorithm, which comprises the following steps: acquiring pressure, stress and temperature data in real time by using a sensor array, calculating a track evolution parameter set, identifying a damaged area, detecting a fault event, and predicting a health state and residual service life. And establishing a damage grade classification framework, and obtaining a damage grade classification result. According to the method, through multi-source data real-time acquisition and spatial gradient refining processing, by using a pressure and stress distribution coupling relation, accurate damage positioning is realized, the anomaly detection sensitivity is improved, damage boundary coordinates are marked, the expansion rate of adjacent damage areas is quantified, and phase delay is judged in combination with a multi-period pressure track; fault recognition stability is enhanced, abnormal event classification precision is optimized, a material fatigue accumulation and pressure uniformity correlation means is adopted, health score attenuation observation is enhanced, health state quantification depth is improved, and life prediction reliability is expanded.

The invention discloses a metal fatigue crack initiation simulation method for coupling holes and microstructures, which comprises the following steps of: firstly, establishing a microscopic scale model by collecting microstructure characteristic data and hole distribution data in a metal material, obtaining basic parameters by combining a mechanical property test result, and deducing and calculating microscopic orthotropic parameters; the method comprises the following steps of: scanning internal defects of an alloy, establishing a hole defect model with the same characteristic information according to the scanned internal defects of the alloy, extracting key holes through finite element simulation to establish a geometric model, introducing a stress concentration coefficient, and replacing a shear stress amplitude calculation mode in a Tanaka-Mura dislocation theoretical formula with a stress amplitude calculation mode. And micro-scale numerical simulation of fatigue crack initiation of the metal material with the hole defect is completed. According to the method, factors such as the microstructure and the internal holes of the material are considered, and the finite element simulation technology is combined, so that accurate prediction of the microscale metal fatigue crack initiation life can be realized.

The invention discloses an aircraft shell surface quality detection method. According to the method, a passenger cabin pressure difference curve and a shell outer surface temperature curve are calculated to obtain a pressure difference change node and a temperature difference change node respectively, and then partitioning is carried out to obtain phase thermoelastic coupling partitions; when a temperature difference change node reaches a phase change threshold value, performing beta-phase to alpha-phase transformation on the polyvinylidene fluoride microcapsule premixed in the finish paint, and forming a polarized memory cavity at a defect cementing position; when a voltage difference change node reaches a peak value, triggering a polarized memory hole to release charges, exciting a high-order thin film elastic wave, and performing integer ratio phase locking on the high-order thin film elastic wave and a natural vibration wave of a machine body to obtain a defect harmonic signal; carrying out acoustic-mechanical coupling calculation according to the amplitude of the defect harmonic signal to obtain a virtual work increment, and recording the virtual work increment to a damage matrix; and performing multi-leg accumulation calculation on the virtual work increment, and outputting a defect early warning signal when an accumulation value exceeds a material fatigue critical value. According to the invention, the hidden fatigue defect of the surface of the aircraft shell under the dynamic load can be detected.

The invention relates to an anchoring system life intelligent evaluation method, system and device and a medium, and the method comprises the steps: constructing a topological network through the space coordinates of anchoring points and the rigidity of components, and quantifying the mechanical correlation between nodes; the load is monitored in real time and compared with a design value, and the dynamic sensitivity of the node is calculated by fusing material strength characteristics; identifying a set of overload source nodes based on a sensitivity threshold; a Monte Carlo path simulation technology is adopted, a material fatigue accumulation effect is combined to model a failure conduction probability, and a risk conduction path and a strength index are generated; integrating historical degradation data to predict single anchor life, and coupling the maximum path risk and the minimum single anchor life to calculate a system attenuation coefficient; and outputting an evaluation report containing the remaining service life and the position of the high-risk unit. The method breaks through the limitation of traditional single-anchor isolated evaluation, realizes dynamic quantification of the failure conduction effect of the multiple anchoring units, and solves the problem of maintenance decision blindness caused by conduction effect deficiency.

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 the technical field of glass detection, in particular to a building glass flatness testing device and a testing method thereof.The building glass flatness testing device comprises a supporting frame, a lifting platform is arranged on the inner bottom face of the supporting frame and used for supporting glass to be tested on a testing station, and the building glass flatness testing device further comprises two oval plates, a supporting plate and a driving device, the supporting rods are symmetrically and fixedly connected to two ends of the supporting frame; the two dual-function limiting mechanisms are arranged on the opposite sides of the two elliptical plates respectively and are jointly used for clamping the two sides of the glass to be detected and supporting the bottom of the glass to be detected; through the design of an elliptical track, simultaneous detection of two surfaces of glass is realized, turn-over operation is avoided, efficiency is greatly improved, in addition, proper bottom support of the glass in the whole detection process is ensured through dynamic adjustment of the dual-function limiting mechanism, and the detection precision is improved. The problem that the clamping force is reduced due to material fatigue caused by long-time suspended clamping of the glass is solved, and the operation safety is remarkably improved.

A deep sea ball valve with an improved valve seat sealing system comprises a valve body, a valve rod, a valve element, a valve seat box and a valve seat matched with the valve element, the valve seat comprises a supporting ring, the supporting ring comprises a sealing face used for being matched with the valve element in a sealing mode, and the sealing face comprises an upper sealing angle and a lower sealing angle. The upper sealing angle is used for supporting the valve element and forms sealing with the valve element, the lower sealing angle is in clearance fit with the valve element when the valve is opened and is in interference fit with the valve element when the valve is closed, compared with one sealing, the upper sealing angle and the lower sealing angle are safer, spherical dirt is wiped away in the opening and closing process of the upper sealing angle, and the sealing effect is better. The lower sealing angle is protected, sealing is more durable, the sealing angle does not make contact with the valve element when the valve is in a normally-open state, the problem of material fatigue is avoided, and the problem of root leakage of an original sealing ring is solved through the integral design that the supporting ring and the sealing face are combined into one.

The invention discloses a pipeline connection flange with a pressure-resistant structure, which is characterized in that a driving mechanism in a fixed cylinder is matched with a lacing wire structure on the peripheral side through a plurality of reinforcing pieces to form a firm supporting system, so that stress can be effectively dispersed when a flange plate bears external pressure, and the pressure resistance of the flange plate is improved. And the damage risk caused by local stress concentration is prevented. Under the action of pressure, the reinforcing piece can uniformly distribute external force to the periphery of the fixing cylinder, so that excessive concentration at a certain point is avoided, and the possibility of material fatigue and yield is reduced. And meanwhile, the overall supporting capacity is further enhanced through the tie bar structure, a force transmission network is constructed, connection between the assemblies is more stable, and the overall strength is improved. According to the structural optimization, the flange plate can still keep good performance under the high-load working condition through a reinforced support and stress dispersion mechanism.

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 field of mechanical transmission control, and discloses a self-adaptive torsion optimization method and system based on a stress model. The method mainly comprises the following steps: acquiring strain, temperature and vibration data of a transmission system in real time through a distributed sensor network; constructing a three-dimensional dynamic stress field model, and marking a high-risk area; dynamically adjusting a safety threshold based on material fatigue characteristics, and generating a torque control curve by adopting an optimization algorithm; and eliminating response delay through a pre-compensation mechanism. The system comprises an edge calculation unit, a millisecond-level actuator and a grading protection module. According to the method, the tooth root stress concentration is successfully inhibited by 35% in the wind power gear box, the impact load is reduced by 52% in the industrial robot joint, the equipment reliability is remarkably improved, and the service life is remarkably prolonged. The device is suitable for transmission systems of wind power, electric automobiles, industrial robots and the like.

The invention belongs to the technical field of computer simulation, and particularly discloses a method, a system and equipment for predicting the fatigue life of a composite material patching and repairing structure. The prediction method comprises the following steps: establishing a composite laminated plate fatigue damage analysis method in combination with an improved Hashin criterion, finite element analysis, a strength degradation model, a rigidity degradation model and a Camanho material parameter degradation model; fatigue life prediction analysis is carried out on the non-porous laminated plate and the porous laminated plate by using the method; and comparing a prediction result with a test result, and verifying the effectiveness of the established composite material laminated plate fatigue damage analysis method. On the basis, a composite material fatigue damage analysis method and a cohesion unit are combined, and a repair structure fatigue life prediction model is established. The fatigue life prediction method for the repair structure is provided by taking the composite material patching and repairing structure as a research object, and has certain engineering practical significance and better practical value.

The invention provides a water-cooled wall safety monitoring method and a combustion adjustment control method based on distributed optical fiber sensing, and the method specifically comprises the following steps: arranging a Bragg grating on a water-cooled wall, and obtaining the Bragg wavelength offset; predicting a temperature value and a strain value at the current moment according to historical temperature and strain data by using a state equation of stress and temperature; the Bragg wavelength prediction offset is obtained by combining the temperature value and the strain value at the current moment with the sensor error; obtaining a wavelength change residual error according to the Bragg wavelength offset and the Bragg wavelength prediction offset, and correcting the temperature value and the strain value at the current moment by using the wavelength change residual error to obtain a real temperature value and a real strain value at the current moment; a real strain value at the current moment is converted into a stress value, a water-cooled wall tearing factor is established by utilizing the stress value, the number of thermal cycles and the fatigue life of a water-cooled wall material, water-cooled wall safety monitoring and combustion adjustment control are realized by utilizing the water-cooled wall tearing factor, and the operation safety of the boiler is improved.

The invention discloses a 3D metal printing steel bar real-time detection system based on deep learning intelligent identification, and relates to the technical field of 3D metal printing steel bars. According to the method, appearance and internal structure data of 3D printing steel bars are collected in real time, a neural network model is utilized for anomaly detection, surface defects and internal invisible defects are classified and recognized, the system further analyzes the severity of the internal defects, and the stress concentration degree and the material fatigue life reduction condition are combined. The reinforcing steel bars with serious defects are reprinted, the reinforcing steel bars with middle defects are subjected to subsequent production optimization by adjusting printing parameters, and the reinforcing steel bars with slight defects are marked as qualified products, so that the precision, quality and safety of reinforcing steel bar production are effectively improved, and structural failure caused by hidden defects is prevented.