165 results about "Life assessment" patented technology

The present invention relates to the technical field of mechanical property testing and characterization. Disclosed are a method and apparatus for calculating a crack propagation life of an engine structure in vibration fatigue, which method and apparatus aim to obtain reliable fracture mechanics parameters and a crack propagation rate curve and provide an accurately quantified crack propagation life, so as to provide methodological guidance for the life assessment of reusable engines. The calculation method comprises: acquiring a time-domain random stress spectrum of stress responses in an assessment section in a finite element model of an engine structure; on the basis of the time-domain random stress spectrum, performing finite element analysis processing on a crack model of the engine structure, so as to determine fracture mechanics parameters of a cracked structure; performing a vibration fatigue performance test on a crack propagation rate model, which is set up according to a preset crack propagation mode, and determining, by using parameter identification, a target parameter value corresponding to the crack propagation rate model; and in combination with the parameter value corresponding to the crack propagation rate model and a preset critical crack length value, performing crack propagation life calculation, so as to obtain a target crack propagation life.

The invention relates to the technical field of semiconductor photoelectronics, and discloses a multi-physics field coupling silicon-based optical interconnection chip degradation model construction method and application, and the method comprises the steps: firstly constructing a multi-physics field coupling analysis model, and quantitatively representing the coupling relation of thermodynamics, optics, electricity and material aging through an inter-field coupling equation and a material aging dynamic model; simulating field distribution of a chip key area under multi-environment stress through finite element analysis, and extracting data; then historical degradation data is collected by combining an accelerated aging test and long-term operation monitoring, and a degradation parameter prediction model is established after data processing based on machine learning; and finally, inputting a finite element result and a prediction result into a material aging dynamic model, and finally forming a multi-physics field coupling degradation model. The problems that the prior art depends on a single physical field, degradation mechanism analysis is incomplete, and service life evaluation is inaccurate are solved, and support can be provided for reliability evaluation, structure optimization and service life prediction of the silicon-based optical interconnection chip.

The invention discloses an intelligent battery cell life prediction system and method based on multi-physics field data fusion, and the method comprises the following steps: carrying out the initial configuration of the system hardware composition corresponding to a battery cell life prediction electronic measurement system, achieving the distribution point optimization and visual mapping, and obtaining the distribution point visual configuration data; performing millisecond-level hardware synchronization and CRC verification based on the distribution point visual configuration data, and performing multi-physics field association fusion and cell coupling feature construction at the same time to generate a cell multi-physics field coupling feature matrix; carrying out life event self-injection processing and battery cell life intelligent prediction on the battery cell multi-physics field coupling characteristic matrix to obtain a battery cell life evaluation report; and performing visualization and archiving processing based on the battery cell life evaluation report to generate a battery cell life prediction electronic measurement file. According to the invention, high-precision, multi-point and synchronous closed-loop acquisition of the multi-physical field data of the battery cell can be realized, and the battery cell life prediction efficiency is improved.

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

The invention relates to the technical field of life evaluation, in particular to a circuit breaker life evaluation method and system for switching an alternating current filter in an extra-high voltage converter station, and the method comprises the steps: collecting multi-dimensional operation data in the operation process of a circuit breaker in real time; extracting a high-frequency-band energy ratio as a contact system abrasion loss characteristic parameter; establishing an arcing energy accumulation model according to the arc light intensity time sequence signal, and calculating an effective arcing energy value of a single operation; constructing a life weight distribution model, inputting the wear loss characteristic parameters, the arcing energy accumulation value and the environment temperature and humidity data into the model, and outputting a mechanical wear index, an electric corrosion index and an environment degradation index; establishing a three-axis linkage correction function; generating a comprehensive life evaluation index based on the corrected mechanical wear index, electric corrosion index and environmental degradation index, and triggering an early warning signal when the index exceeds a preset threshold value; according to the invention, by establishing the life evaluation model based on multi-dimensional data fusion, the precision and reliability of life prediction of the circuit breaker of the extra-high voltage converter station are significantly improved.

The invention relates to the crossing field of rail transit intelligent operation and maintenance and digital twinning technologies, and discloses a subway train full-life-cycle intelligent maintenance decision-making system and a subway train full-life-cycle intelligent maintenance decision-making method. The system comprises a digital twin modeling module used for constructing a train full-dimension virtual model and realizing real-time data synchronization with a physical entity; the full-life-cycle data acquisition and fusion module is used for integrating multi-source heterogeneous data of all stages of design, manufacturing, operation, maintenance and decommissioning to form a unified data asset library; the intelligent analysis and decision-making module is used for performing state monitoring, fault prediction and residual life evaluation based on the virtual model and the data asset library, and generating a maintenance decision-making scheme through multi-objective optimization; and the maintenance execution and feedback module is used for issuing a decision and executing data feedback to realize closed-loop optimization of the system. The method is realized based on the system. The method can support the subway train maintenance mode-to-state guide conversion.

The invention belongs to the technical field of transformer insulation loss and life evaluation, and discloses a power transformer thermal life loss calculation method, system, device and medium, and the method comprises the steps: calculating the bidirectional load rate when a transformer is connected with distributed new energy, and judging the current power flow operation state of the transformer; obtaining a rated loss parameter of the transformer under a rated condition, and calculating the load loss of the transformer in combination with a harmonic loss factor corresponding to the transformer under the bidirectional power flow; voltage per unit values of the high-voltage side and the low-voltage side of the transformer are obtained, and the no-load loss of the transformer is calculated in combination with the iron core loss factor of the transformer; calculating the hot spot temperature of the transformer under the power flow switching condition; and calculating the relative aging rate of the transformer. The method is suitable for calculating the hot-spot temperature and the insulation life loss of the transformer in the scene of transformer power flow switching caused by high-proportion new energy penetration, the hot-spot temperature and the relative thermal life loss of the transformer under the condition of power flow reversal can be predicted, and operation and maintenance management is facilitated.

The invention discloses a crane full life cycle evaluation method based on digital twinning, and relates to the technical field of cranes, the method comprises the following steps: determining a primary loss structural component set and a secondary loss structural component set; constructing an initial digital twin structure model; performing time sequence updating on the initial digital twinning structure model to obtain a digital twinning structure monitoring model sequence; performing multi-receptive-field space-time state interaction enhancement on the digital twin structure monitoring model sequence, and determining digital twin space-time state features of the target crane; and carrying out life evaluation based on the digital twin space-time state characteristics of the target crane, and determining a full life cycle stage and a life evaluation result of the target crane. The technical problems that in the prior art, crane operation data analysis depth is not enough, so that full life cycle evaluation is not comprehensive, and hysteresis exists are solved. The technical effects of carrying out multi-level component interaction analysis on the crane and improving the accuracy of full-life-cycle evaluation are achieved.

The invention provides a ship and ocean engineering structure corrosion fatigue crack propagation rate prediction method based on machine learning. The method comprises the following steps: S1, obtaining all characteristic variables; s2, screening core influence factors from all feature variables through a feature selection algorithm to obtain feature data; s3, establishing a machine learning prediction model which adopts one of a plurality of machine learning algorithms, and inputting the feature data into the machine learning prediction model to learn a nonlinear mapping relationship between corrosion fatigue crack growth rate data and the selected variables, optimizing the machine learning prediction model by using a hyper-parameter optimization method to obtain a trained model; and S4, inputting feature data of a to-be-predicted target into the trained model for prediction to obtain the corrosion fatigue crack growth rate of the to-be-predicted target. The method is suitable for service safety analysis and life evaluation of key facilities such as ships, ocean platforms and submarine pipelines.

The invention discloses a method for evaluating a fatigue weak area of a welded joint based on crystal plasticity, which aims at the problem of fatigue failure of the welded joint caused by complex microstructures such as grain orientation difference and uneven grain size distribution, establishes a quantitative correlation model of grain orientation and size evolution through CPFEM, and combines a macro-micro cross-scale analysis method to evaluate the fatigue weak area of the welded joint. And precise prediction of local stress concentration and crack initiation behaviors of the welding joint under a real fatigue load working condition is realized, so that scientific evaluation of a fatigue weak region is completed. According to the method, an innovative framework of fatigue weak area evaluation is constructed through load working condition reduction and grain characteristic multi-scale coupling, so that excessive simplification of a traditional method on real load conditions is made up, the limitation that a traditional model is difficult to couple a microstructure and a real load is overcome, and the fatigue weakening quantization precision is remarkably improved; and a high-precision analysis technology is provided for anti-fatigue design, process optimization and service life evaluation of the engineering welding structure.

The invention relates to a digital twinning method, device, medium and equipment for evaluating the service performance of a structural material, and the method comprises the following steps: building a digital geometric model of the structural material, and configuring boundary conditions and loads according to the real service environment of the digital geometric model; collecting multi-source service state data of the structural material in the multi-factor coupling service environment; calibrating and updating the digital geometric model by adopting the state data, and constructing a physical-data fusion digital twinborn model of the structural material; and performing analysis and life prediction on the service state of the structural material based on a machine learning algorithm, and outputting a performance degradation trend and a residual life evaluation result of the structural material. According to the method, digital twinning is applied to service performance evaluation of the structural material, performance prediction and health state evaluation of the material in a complex environment are achieved, the full-life-cycle safety guarantee capacity of the structural material is improved, and the method has important engineering value and strategic significance.

The invention relates to the technical field of circuit breaker service life evaluation, and particularly discloses a circuit breaker service life evaluation system based on loss analysis. Comprising a circuit breaker operation time division module, a circuit breaker operation data acquisition module, a circuit breaker loss analysis module, a circuit breaker loss monitoring module, a circuit breaker performance analysis module, a circuit breaker service life evaluation module, a circuit breaker service life evaluation correction module and a circuit breaker service life early warning module. According to the method, the running loss and performance data of each monitoring sub-region are collected, the loss change coefficient and the performance evaluation coefficient are obtained through analysis, the service life evaluation index is further obtained comprehensively, and correction is performed by using the correction factor; the loss monitoring module can compare loss change coefficients in real time, screen abnormal data and control the abnormal data; according to the invention, accurate evaluation, real-time regulation and early warning of the service life of the circuit breaker are realized, the operation and maintenance cost is reduced, the operation reliability and economical efficiency of a power system are improved, and powerful support is provided for intelligent management of the power system.

The invention discloses a lithium ion battery outlier early warning method and system, a product, a medium and equipment, and relates to the technical field of battery fault prediction. The method comprises the steps that electrical performance testing is carried out on the lithium ion battery, a life evaluation model comprising three branches is constructed, the life evaluation model is trained, and the three branches comprise a first branch used for local outlier detection, a second branch used for residual analysis and a third branch used for deep learning; the three branches in the life evaluation model process the direct current internal resistance, the constant voltage stage capacity ratio and the constant current stage capacity ratio in parallel, fusion decision is carried out on results obtained by the three branches respectively, and an outlier detection result is obtained. According to the method, the service life attenuation rule of the battery is calculated based on the capacity ratio in the constant-voltage stage, the advantages of actual experiments and model learning can be brought into full play, and accurate recognition and early warning of the lithium ion battery outlier phenomenon are achieved through comprehensive analysis of multi-modal data.

The invention discloses a mold life management system based on vehicle lamp production mold monitoring, which comprises a data acquisition module, a mold health assessment module and an early warning and decision module, and relates to the technical field of mold life management. According to the mold life management system based on vehicle lamp production mold monitoring, data are preprocessed, various characteristics of the temperature change rate, the pressure value, the strain amplitude and the vibration frequency are extracted for analysis and processing, and the extracted characteristic parameters are integrated to establish and form a mold life evaluation model; then real-time data is extracted and introduced into the mold life evaluation model to evaluate the health index of the mold, and the actual wear condition and performance change of the mold can be more accurately mastered by monitoring various physical quantity data of the mold in real time and utilizing an advanced algorithm and model to evaluate the life; and subjectivity and uncertainty of artificial experience judgment are avoided.

The invention discloses an aero-engine structure surface defect intelligent characterization and life evaluation method, and relates to the technical field of aero-engine structure health management. According to the method, defect data are fused and collected through a multi-source sensing technology, and a knowledge graph is constructed; utilizing a multi-branch deep learning model to realize automatic identification of defect types and intelligent extraction of key geometric features; determining a standard defect size based on the statistical distribution model of the group defect data; a defect stress concentration coefficient is rapidly calculated through the trained AI agent model, and mechanical equivalence of irregular defects is achieved; and finally, implanting the equivalent defect into the digital twinborn model of the component, and dynamically simulating and predicting the evolution path and the residual life of the equivalent defect. According to the method, the technical problems that characterization depends on experience, analysis links are isolated, and evaluation is static and conservative are solved, intelligent processing from accurate digital characterization to individualized life prediction of the surface defects of the engine is achieved, and support is provided for condition-based maintenance and predictive health management of the engine.

The invention provides a structural damage evolution digital twinning prediction method applicable to multiple working conditions, and belongs to the field of structural life evaluation. Comprising the following steps: 1) acquiring sensor layout information, recording mechanical response and damage parameters at a t1 moment, and calculating working conditions and increment of the damage parameters; (2) establishing a parameterized finite element model, obtaining a simulation result, extracting mechanical response data of a sensor measuring point at multiple moments and corresponding working conditions and damage parameters, and calculating increments of the working conditions and the damage parameters from the moments t1 to t2; 3) training to obtain a deep neural network, and obtaining a digital twinborn prediction model to predict a damage evolution state; and 4) obtaining a target load history, detecting real-time working conditions and damage parameters, collecting mechanical response of a sensor measuring point, realizing damage parameter increment prediction of a new working condition, and finally realizing damage evolution digital twinning prediction of the new working condition. According to the method, a large number of accurate predictions of the structural damage evolution state under new working conditions are provided, and the structural life evaluation cost can be greatly reduced.

According to the relay service life prediction method based on the multi-dimensional data, by introducing multi-dimensional operation data collection and fusion analysis, the defect that relay micro-sparks and complex coupling disturbance are difficult to accurately capture through a traditional single signal monitoring means is effectively overcome. High-frequency signal components are extracted through variational mode decomposition, high-sensitivity detection of micro-sparks is achieved in combination with micro-arc energy entropy, and the early-stage anomaly recognition capacity is remarkably improved. Through coupling characteristic analysis of a magnetic field distortion sequence, a micro transient coupling index is constructed, dynamic quantification of a multi-source disturbance coupling effect is realized, and a potential failure risk of a relay can be accurately evaluated. And a service life prediction model is constructed by integrating working condition labels and structural parameter empowerment, so that the accuracy and applicability of service life evaluation are enhanced. The overall method improves the comprehensiveness and reliability of relay operation state monitoring, provides a scientific basis for equipment maintenance decision, effectively prolongs the service life of the relay, reduces the maintenance cost, and improves the operation safety of the system.

The invention relates to the technical field of clutches, and discloses a clutch service life evaluation method and device, a vehicle and a medium, and the clutch service life evaluation method comprises the following steps: establishing a relation curve of a clutch friction material at different working temperatures and the working duration of reaching a set abrasion loss, and performing segmented regression analysis on the relation curve in combination with a set reference temperature; the accuracy of the segmented regression equation near the reference temperature is guaranteed, and then a clutch service life evaluation model with the working time and the working temperature of the clutch as variables is constructed through the segmented regression equation, so that clutch service life evaluation is conducted through the real relation between the working temperature of the friction material and the working duration. According to the method, the accuracy of the evaluation result of the service life of the clutch is guaranteed, unified real-time quantifiable fine evaluation on the service life of the clutch is realized, the wear trend and the health decline state of the clutch friction plate in long-term use can be reflected more accurately, and accurate maintenance suggestions and vehicle use suggestions are conveniently provided for users.

The invention discloses a boiler heating surface three-dimensional digital twin construction method and system based on multi-source data fusion, and relates to the field of boiler monitoring. Comprising the following steps: carrying out multi-source data space-time alignment and structured processing, and unifying CAD design coordinates, installation welding seam GPS positioning, DCS operation measuring points and ultrasonic detection point positions to a boiler absolute coordinate system by adopting a space-time reference conversion technology; analyzing the unstructured data through a data cleaning engine, generating a welded junction level equipment ledger, and forming a time-space aligned standardized database; carrying out multi-scale point cloud fusion and three-dimensional model reconstruction, fusing laser scanning point cloud, BIM parametric modeling and welding seam ray imaging data, and constructing a multi-scale model by adopting an octree spatial index; cT scanning point cloud is introduced into the key area to enhance the precision. Compared with traditional BIM modeling, the geometric accuracy is improved, the creep damage simulation error of the high-temperature pipeline is reduced, and a real geometric base is provided for life evaluation.

The invention discloses a high-performance cast cold roll evaluation method based on stress of a working layer and a bonding layer, and belongs to the technical field of metallurgical mechanical equipment design and life evaluation, and the method comprises the following steps: calculating the maximum contact pressure between a working roll and a supporting roll and the flattening width of a contact surface; further determining the maximum shear stress in the working roll and the depth position corresponding to the shear stress; according to radius changes of the working roller in different wear stages, the maximum contact pressure and the contact surface flattening width in different wear stages are calculated for multiple times, and then normal stress at the position of a bonding layer in each stage and shear stress derived from the normal stress are calculated; performing simulation verification on calculation data based on a stress field of finite element simulation; comparing the shear stress of the bonding layer obtained after calculation with the total stress level after the residual stress is considered, and the allowable shear stress of the same material; and the risk is judged. The service life of the roller can be prolonged, and the equipment loss cost of cold-rolled strip steel production is reduced.

The invention relates to the technical field of power system automation, in particular to a new energy box-type substation state estimation, regulation and control method, which comprises the following steps of: injecting a multi-frequency electrical excitation signal into a box-type substation, acquiring a voltage signal and a current signal, establishing a digital twin model based on primary wiring topology and grounding grid topology, performing combined state estimation and parameter estimation to obtain a comprehensive feature vector representing a degradation state, and inputting the comprehensive feature vector into a fault diagnosis and life evaluation model to obtain a risk index; and constructing a risk weighting objective function taking active output, reactive output and current as independent variables, and solving to obtain a control quantity vector for adjusting power output, reactive compensation and an electric protection device action constant value, thereby reducing the operation risk and prolonging the service life of equipment while ensuring the grid-connected requirement.

The application discloses a kind of crack propagation prediction method and system of water turbine runner under transient hydraulic excitation, belong to the technical field of water conservancy and hydropower engineering, to solve the technical problem that existing prediction method cannot simulate crack propagation under transient hydraulic excitation.The application is by constructing finite element grid and level set field, encryption grid, identify enhanced node and solve runner time sequence displacement field, then calculate the stress intensity factor and energy release rate of crack front node, and calculate crack propagation direction and rate based on this, thereby update and correct level set field, to obtain the crack after expansion, to realize the accurate simulation of crack propagation under transient hydraulic excitation, provide reliable basis for runner crack monitoring, expansion trend prediction and fracture life assessment.Further, the application can track the crack propagation process from the current small condition to the penetration by multiple iterations, and accurately predict the fracture life of the runner according to the propagation law.

This invention provides a method for predicting the service life of concrete under alkali-aggregate reaction failure. Based on the kinetics of alkali-aggregate reaction expansion and the theory of temperature acceleration, the method first determines the activation energy Ea of the alkali-silica reaction expansion of reactive aggregates through accelerated tests at different temperatures. Then, concrete specimens are prepared using actual engineering mix proportions, and accelerated temperature tests are conducted in a simulated pore solution at 70℃ to obtain the time t1 required for the expansion rate to reach the failure threshold of 0.040%. Finally, based on the Arrhenius equation, a mathematical model is established comparing the failure time of the concrete specimens under accelerated temperature conditions with the failure time of the concrete in the engineering structure, and the service life t2 of the concrete under engineering conditions is calculated. This invention solves the problems of existing technologies lacking a unified physical basis and being difficult to quantitatively extrapolate, improving the engineering applicability and universality of service life assessment, and providing a scientific basis for the long-term safety evaluation of major infrastructure such as hydraulic engineering and transportation.

The invention discloses a shell temperature control method for a high-power-consumption spacecraft in a life evaluation test. The method comprises the following steps: determining heating power required by a heating resistor according to characteristics of the high-power-consumption spacecraft and an expected shell temperature during the life evaluation test; selecting the type and parameters of a heating resistor according to the required heating power, and determining the resistance value; determining power supply voltage required by the heating resistor according to the heating power and the resistance value; the heating resistor is fixedly installed on a shell of the large-power-consumption spacecraft part; and when the service life evaluation test is carried out on the large-power-consumption spacecraft part, the heating resistor is powered by the required power supply voltage. According to the method, the shell temperature of the large-power-consumption spacecraft in the life evaluation test process can be effectively controlled, so that the influence rule of thermal stress on key characteristic parameters of the device is explored in the life evaluation test, the service life of the large-power-consumption spacecraft in the space irradiation environment is predicted, and the design or process weak points of the large-power-consumption spacecraft are identified; and support is provided for improvement of large-power-consumption spacecraft parts.

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 embodiment of the invention provides a welding joint service life evaluation method and device, computing equipment and a storage medium, and the method comprises the steps: obtaining the service duration and the operation environment temperature of a target pipeline, and inputting the service duration and the operation environment temperature into a pre-constructed service life evaluation model; acquiring a creep damage accumulated value calculated and output by the life evaluation model based on the service duration and the operating environment temperature; and obtaining the remaining life of the welding structure of the output target pipeline calculated by the life evaluation model based on the creep damage accumulated value. A corresponding pipeline creep curve is determined by obtaining multi-layer damage characteristics and multi-dimensional fatigue test data of a target pipeline, and then a life evaluation model is constructed based on the creep curve and corresponding mechanical characteristics to predict and evaluate the remaining life of a welded joint of the target pipeline. According to the method, the data polyhedron of the model can be improved through multi-azimuth data acquisition, and the creep characteristic under the high-temperature condition is obtained, so that the prediction result of the model better fits the actual condition, and the operation safety of the power station boiler is improved.

The invention relates to the technical field of ultrahigh strength steel delayed cracking performance testing, in particular to an ultrahigh strength steel delayed cracking performance testing device and a testing method thereof.The testing method includes the following steps that firstly, a rectangular strip sample is cut from a to-be-tested ultrahigh strength steel plate, the width of the sample is 10-20 mm, the thickness of the sample is 0.5-6.0 mm, and the thickness of the sample is 10-20 mm; performing oil removal, grinding and ultrasonic cleaning, and recording a surface treatment mode; step II, bending the sample into a bending state according to a U shape, and enabling the surface of the outer layer to generate maximum surface strain, the method can be used for rapid screening and can also be used as a preposed step for threshold and life evaluation, the consistency and comparability of results between different laboratories and engineering units can be improved, and the method is suitable for large-scale popularization and application. And through hydrogen-free contrast, fracture microscopic analysis, diffusible hydrogen detection and finite element check, macroscopic crack behaviors are associated with microscopic fracture characteristics and hydrogen content, so that the capability of judging a fracturing mechanism is enhanced, and a reliable basis is provided for engineering material type selection and process verification.

This application provides a method for predicting the wear state of steel-based ceramic wear-resistant components, relating to the field of material life assessment technology. The method includes the following steps: emitting excitation eddy currents containing a first frequency and a second frequency into a steel substrate, and receiving the response signal modulated by the state of the steel substrate and the ceramic-steel interface; processing the response signals corresponding to the first and second frequencies respectively, extracting the first phase change of the first reference signal corresponding to the initial health state of the component relative to the first frequency, and the second phase change of the second reference signal corresponding to the second frequency; calculating the difference between the first and second phase changes to characterize the change in thermal conductivity state of the ceramic-steel interface; obtaining the real-time operating temperature of the wear-resistant component, and based on the real-time operating temperature and the difference, assessing the current state level of the ceramic-steel interface, and predicting the remaining safe service time of the ceramic wear-resistant layer by combining the trend of the difference over time.

The invention discloses a hydrogen-induced cracking molecular dynamics-cohesion cross-scale simulation method which comprises the following steps: constructing a geometric model reflecting an actual material microstructure on the basis of multi-scale structure characteristics such as grain size, grain boundary angle and the like obtained by metallographic observation and electron back scattering diffraction test; simulating a fracture process of a microscopic interface under different hydrogen concentrations through a molecular dynamics method, obtaining traction-separation data, and calibrating core parameters of the cohesion model; embedding the parameters into a polycrystalline finite element model constructed based on a Thiessen polygon to realize parameter transmission and coupling calculation from a micro scale to a micro scale; the cohesion unit accurately describes hydrogen-induced grain boundary damage and crack propagation behaviors. According to the method, through multi-scale correlation modeling and direct parameter calibration, the reliability and prediction precision of the model are remarkably improved, and a theoretical basis and an engineering applicable tool are provided for hydrogen embrittlement resistance design and service life evaluation of a hydrogen equipment material.

This application relates to a method, apparatus, device, and storage medium for assessing the service life of an electrical connector. The method includes: acquiring first information and second information about the electrical connector, the first information including attribute information of the connector, and the second information including the current operating voltage, temperature, and RMS power spectral density of operating vibration stress; determining the estimated service life of the electrical connector based on the first information and a predicted service life model; determining a correction coefficient based on the second information and a comprehensive physical model; and correcting the estimated service life based on the correction coefficient to obtain the service life of the electrical connector. This method can improve the accuracy of electrical connector service life assessment.