126 results about "Life assessment" patented technology

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 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 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 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 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 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 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 invention relates to a method for calculating the dynamic wear of a plunger pair in a marine common rail jet pump. First, a dynamic model is established to solve for the forces and micro-motions (eccentricity and tilt angle) of the plunger. Then, based on e and , the oil film thickness and pressure are calculated, and the oil film bearing capacity and lateral load are balanced through iteration. Next, surface roughness is introduced to determine the lubrication state, and the Reynolds equation is modified to characterize mixed lubrication. Force balance iteration is performed again to obtain a more accurate oil film pressure and thickness distribution. Finally, based on the results of the modified model, the wear amount is calculated using the micro-protrusion contact theory and the Arcard wear formula. This method, by coupling plunger micro-motion, oil film state, surface morphology, and operating parameters, realizes the calculation of dynamic wear, improves the operating condition adaptability of wear assessment, and provides a certain basis for the condition monitoring and life assessment of the plunger pair.

The application discloses a hydrogen-induced cracking molecular dynamics-cohesion cross-scale simulation method, comprising the following steps: constructing a geometric model reflecting the actual microstructure of a material based on the multi-scale structure characteristics such as grain size and grain boundary angle obtained through metallographic observation and electron backscatter diffraction experiments; simulating the fracture process of a micro-interface under different hydrogen concentrations through a molecular dynamics method, obtaining traction-separation data, and calibrating the core parameters of a cohesion model; embedding the above parameters into a polycrystalline finite element model constructed based on a tessellation polygon, realizing parameter transmission and coupled calculation from a micro-scale to a meso-scale; and accurately describing hydrogen-induced grain boundary damage and crack propagation behavior through a cohesion element. The method significantly improves the reliability and prediction accuracy of the model through multi-scale correlation modeling and direct parameter calibration, and provides a theoretical basis and an engineering applicable tool for hydrogen-induced cracking resistance design and life assessment of equipment materials.

The application discloses a mud pump accessory fault intelligent prediction method and system, belonging to the technical field of fault diagnosis and prediction. The method comprises the following steps: constructing a multi-dimensional heterogeneous perception array unit to synchronously collect multi-dimensional physical state parameters; performing adaptive time-frequency feature enhancement processing, enhancing weak fault features through variational mode decomposition, envelope spectrum entropy and correlation coefficient double screening, and Hilbert transform; establishing a multi-physical field coupling mechanism mapping, constructing a hydraulics mechanism based on the Bingham model, calculating the pressure residual and flow residual of the measured value and the theoretical value, and fusing the enhanced time-frequency features to construct a physical consistency feature vector; using a long short-term memory network with an integrated attention mechanism to identify the evolution trend; implementing variable working condition migration adaptation and dynamic compensation; and outputting fault diagnosis and life assessment results. Through deep fusion of physical mechanism and data driving, the application effectively suppresses strong background noise interference, and improves the prediction accuracy and generalization ability under variable working conditions.

This invention discloses a rapid prediction method for rail rolling contact fatigue damage in the field of rail damage prediction technology. The method includes establishing a three-dimensional elastoplastic wheel-rail cyclic rolling contact finite element model, improving the cyclic plastic constitutive model, and simulating the stress-strain evolution of the rail. A rail stress-strain sample library is generated through parametric sampling and batch calculation. A Physically Constrained Generative Adversarial Network (PC-GAN) is constructed, embedding physical constraints such as contact force conservation and energy consistency into the loss function to achieve rapid and high-precision mapping from operating parameters to the stress-strain field. Based on the PC-AN prediction results, cumulative damage and fatigue life are calculated using an incremental multiaxial fatigue damage model, and a damage distribution map of the entire rail line is drawn, identifying high-risk sections. This invention deeply integrates physical modeling with intelligent algorithms, achieving an order-of-magnitude improvement in rail fatigue damage assessment efficiency while ensuring prediction accuracy, providing efficient and reliable technical support for rail life assessment and maintenance decisions across the entire rail line.

The application discloses a structure suitable for creep supervision of P91 pipeline containing a soft area, which comprises a plurality of creep supervision measuring points fixedly installed on the outer wall of the P91 pipeline containing the soft area, wherein the creep supervision measuring points comprise a creep supervision measuring point upper layer and a creep supervision measuring point lower layer which are stacked together, and at least one of the creep supervision measuring points is located on the soft area of the P91 pipeline. The structure suitable for the creep supervision of the P91 pipeline containing the soft area can carry out the creep supervision on the soft area with the worst creep performance, the supervision object is more targeted, the creep strain law of the soft area of the pipeline can be accurately reflected, lossy detection such as hardness detection and metallographic detection does not need to be frequently carried out, no damage is caused to the pipeline, and more data support can be provided for the supervision and evaluation and life assessment of the pipeline. The application also discloses an evaluation method suitable for the creep supervision of the P91 pipeline containing the soft area, which has the same advantages as the structure suitable for the creep supervision of the P91 pipeline containing the soft area.

This invention discloses a numerical simulation method for the corrosion rate of high-strength steel under marine stress environments, belonging to the field of corrosion and protection technology. The method includes the following steps: establishing a geometric model for simulation and meshing the model; setting material properties, including corrosion kinetic parameters and basic mechanical property parameters; applying boundary conditions to the geometric model to simulate the actual stress state of the high-strength steel plate; formulating a kinetic expression formula for the electrochemical reaction to describe the electrochemical behavior during corrosion; and performing a corrosion kinetic-mechanical coupling analysis to calculate the distribution of corrosion current, corrosion potential, and local corrosion rate. This invention, by constructing a multiphysics model, can accurately extrapolate and predict the dynamic corrosion rate of high-strength steel under different stresses and environmental parameters. It provides crucial theoretical basis and data support for the design, life assessment, and maintenance decisions of marine engineering structures.

The invention relates to the technical field of wind turbine generator management, in particular to a wind turbine generator assembly service life evaluation method and system based on multi-physics field coupling, and the method comprises the steps: dividing a plurality of evaluation units based on multi-physics field fine granularity according to a component function partitioning and physics field type matching principle for a wind turbine generator impeller gearbox system; obtaining multi-source sensing data of each evaluation unit; determining a multi-field coupling state threshold value of each evaluation unit based on geometrical characteristics and historical operation and maintenance fault data of the wind turbine impeller gearbox system; for each evaluation unit, determining a degradation candidate unit based on the multi-field coupling state threshold and the multi-source sensing data; historical data corresponding to the degradation candidate units are obtained, degradation trend analysis is carried out on the degradation candidate units according to the historical data, and the remaining service life of the wind turbine assembly corresponding to the degradation candidate units is obtained. The accuracy of life prediction can be improved.

The present disclosure relates to the field of sustainability and, in particular, to digital certificates, digital representations of a vehicle end-of-life assessment, and decentral identifiers to improve the environmental impact of production networks by increasing transparency among value chain participants. The disclosure relates to methods, apparatuses and systems for generating, monitoring, and / or transmitting digital certificates with circularity data.

The invention relates to the technical field of wind power generation, and discloses a wind power plant main bearing life evaluation method and device. The method comprises the following steps: firstly, constructing a main bearing life response surface model, and determining a mapping relation between a wind load parameter taking an average wind speed and turbulence intensity as a core and the main bearing life; then, joint probability distribution is constructed based on actually-measured wind parameters, discretization sampling is conducted on the joint probability distribution, and environment feature pairs containing the average wind speed and the turbulence intensity and corresponding probability weights of the environment feature pairs are determined; determining the fatigue life corresponding to each environment feature pair by using the response surface model, coupling the fatigue life with the probability weight, and calculating to obtain the comprehensive fatigue life of the main bearing; and finally, realizing individualized evaluation of the service life of the main bearing of each fan by traversing actually measured wind parameters of units of the same model in the wind power plant. According to the method, the efficiency of evaluating the service life of the main bearing of the wind power plant group can be remarkably improved on the premise of ensuring accuracy.

The application discloses a kind of digital operation management system and method, it is related to digital operation management technical field, including operation monitoring module, for through network interface and distributed industrial internet of things node communication, production environment parameter and process data are collected, equipment baseline parameter is formed;Knowledge graph engine module is based on equipment baseline parameter, equipment relationship network and process flow mapping are constructed;Predictive maintenance module is used for equipment life assessment and failure early warning according to the relationship data of the knowledge graph engine module;Decision support module is based on equipment life assessment and failure early warning, combines historical decision effect, generates resource scheduling scheme, and is transmitted to digital twin display module;Digital twin display module is used for presenting factory real-time running state using three-dimensional visualization technology.The application improves the data processing efficiency, resource utilization and flexibility in production process, realizes the global monitoring and intelligent optimization of production process.