40results about How to "Enables dynamic evaluation" patented technology

The invention discloses a karst tunnel water outburst and mud outburst overall process gradual dynamic risk assessment method. The method includes the steps that 1, in the tunnel investigation stage, the tunnel address and the hydrogeological information of the surrounding rock near the tunnel are obtained, that is, the hidden danger environment for water outburst of the tunnel is obtained, and the risk states of the geological conditions of all segments of the tunnel are known; 2, the risk rating value is worked out according to an expert evaluation vector and a factor weight vector, and consistency check is conducted; 3, danger factors are introduced to influence factors of risk evaluation, the hidden danger environment and the danger factors are considered comprehensively, water outburst risk evaluation is conducted, and the segment distribution feature with the tunnel water outburst risk is divided; 4. The values of all indexes are corrected in real time in combination with actual field construction so as to achieve dynamic evaluation of the water outburst and mud outburst risks. The purposes of optimizing construction organization design and avoiding medium and large water outburst geological disasters are achieved through dynamic construction risk evaluation and control, and important data are provided for later-period tunnel operation risks, and the method has very wide application prospects.

The invention discloses an urban gas pipeline system danger forecast and evaluation method. The method comprises the following steps: 1) establishing a system danger evaluation index system; 2) carrying out index weight assignment through a rough set theory; 3) carrying out system danger grading; and 4) carrying out system dynamic prediction and analysis. The method can solve the problem that, for the previous gas pipeline system danger evaluation methods, evaluation index weight assignment depends on subjective grading, and since the subjective grading has too many subjective views of an evaluator, the assignment result is not objective; the method can also solve the problem of the static evaluation method, and thus dynamic evaluation of the system is realized, and dynamic prediction of the system can be carried out; and the method is of great significance to safety management of gas pipelines, and meanwhile, provides important theoretical reference basis for the public safety management of a city.

The invention discloses an aero-engine turbine blade reliability digital twinning modeling method, relates to the technical field of aero-engines, and aims to realize high fidelity simulation and tracking of aero-engine turbine blade damage and life loss and quickly and efficiently evaluate the reliability and residual life of the aero-engine turbine blade. According to the invention, the turbineblade is taken as an object, aiming at the characteristics of multi-source and multi-time-scale use reliability related information, few fault samples and the like of the turbine blade, a physical model driving and data driving fusion method is adopted, that is, the specialty of a physical model in the aspect of explaining specific data is fully utilized, and a turbine blade digital entity model based on a high-precision physical model and multi-source data is constructed by means of the advantages of a machine learning method in the aspects of dimension reduction and multi-modal data fitting.The model can reflect the physical characteristics of the turbine blade and the variable characteristics dealing with different environments and damages, and can realize the product operation reliability dynamic evaluation and residual life prediction of multimode information fusion.

The invention discloses a Markov chain Monte Carlo method-based photovoltaic power station reliability evaluation method. The method is used for a concentrated photovoltaic power station composed of n power generating units; each power generating unit includes a photovoltaic array, a direct current combiner box, a photovoltaic inverter and a transformer; and the power generating units are finally connected into an alternating current power grid. The method includes the following steps of: establishment of the Markov chain models of each component; state sampling; operation process simulation; and judgment algorithm convergence. The method of the invention has high stability, and has high correctness and superiority in reliability evaluation of large-scale photovoltaic power stations.

Embodiments of the invention provide a method and device for dynamically assessing full-life cycle real-time reliability of shale gas fracturing equipment. The method comprises the following steps of:fitting a failure rate of an appointed component under a natural degradation state on the basis of Weibull distribution, and establishing a dynamic Bayesian network-based reliability prediction model; establishing a dynamic Bayesian network-based network fault cause reasoning model by taking monitoring parameters of the appointed component as fault symptom nodes; obtaining monitoring parameter values of the appointed component in real time, and inputting the monitoring parameter values into the fault cause reasoning model so as to predict the current state of the appointed component; and whenthe current state of the appointed component is abnormal, updating the reliability prediction model according to the current abnormal state of the appointed component, and predicting reliability of the appointed component according to the updated reliability model. The method and device are capable of improving the correctness of result for assessing full-life cycle real-time reliability of shalegas fracturing equipment.

The invention discloses a method for calculating and evaluating the leakage rate of safety shell of a nuclear power plant, comprising the following steps of: obtaining uncertainty of a class A assessment for calculating the leakage rate of safety shell; obtaining uncertainty of a class B assessment for calculating the leakage rate of safety shell according to the real time measured data of the sensors in the safety shell; and synthesizing the uncertainty of the class A assessment and the uncertainty of the class B assessment into a uncertainty of the leakage rate of safety shell to evaluate calculation of the leakage rate of safety shell according to the uncertainty of the leakage rate of safety shell. The invention also discloses a system for calculating and evaluating leakage rate of safety shell of nuclear power plant. According to the method and system for calculating and evaluating the leakage rate of safety shell of a nuclear power plant, the reliability and accuracy of the evaluation can be improved.

The invention discloses a system efficiency evaluation method based on a data station field and belongs to the technical field of simulation. The method comprises the steps of: 1, analyzing various performance indices of a system to be evaluated, obtaining simulation data of the performance indices from subsystems for different system design schemes, 2, constructing an information matrix for each subsystem under each system design scheme, placing the simulation data belonging to the same subsystem and the same system design scheme into the corresponding information matrix where subsystem attributes and scheme attributes are also stored, establishing search directories of the information matrices, 3, establishing an evaluation method set, searching the simulation data of the performance indices from the matrices according to the search directories, evaluating respectively by evaluation methods in the evaluation method set, setting weights of the evaluation methods in the evaluation method set, conducting weighted combination on evaluation results corresponding to the evaluation methods, and obtaining a final system evaluation result. The system efficiency evaluation method is applicable to dynamic evaluation of system efficiency.

A method for visualized dynamic assessment of rolling bearing reliability based on classified statistics comprises the steps that vibration signals of a rolling bearing are acquired at first; a root-mean-square index and a kurtosis index of the signals are computed, and the two performance index sequences are taken as an analysis object to obtain a certain quantity of statistic samples at normal running moments; an initial classified probability model based on a kernel density method is established; an initial classified probability image model is obtained through visualized processing; then, classification boundary lines are determined; a fault rate is extracted from the classified probability image mode; a reliability index is computed; when new performance data exists, class judgment will be conducted according to the classification boundary lines, a new classified probability image model will be established, classification boundary lines of each class are determined, and a reliability index is extracted; and different classes of samples are obtained along with continuous accumulation of the analysis samples, so that the classified probability image and the reliability index can be updated continuous, and the dynamic assessment of the rolling bearing reliability can be achieved. The method provided by the invention is dynamic, accurate and visualized.

The invention relates to an evaluating system, an information interactive system comprising the evaluating system, and an evaluating method. The evaluating system which is used for evaluating a terminal comprises a database, an evaluating server and a security level confirming server, wherein the database is used for storing evaluation relevant data of the terminal, the evaluating server is used for evaluating the terminal and businesses of the terminal through utilization of the evaluation relevant data in the database, and the security level confirming server is used for confirming security levels of the terminal. The evaluating system is characterized in that the evaluating server comprises an initial score processor and a cumulative score processor, wherein the initial score processor is used for carrying out initial evaluation on the terminal and a current business of the terminal based on the evaluation relevant data of the terminal and evaluation relevant data of the current business of the terminal, and calculating a score of a current time point, and the cumulative score processor is used for carrying out cumulative score process on the terminal and calculating a composite score based on the score, calculated by the initial score processor, of the current time point, a history score and a recommend score value. Based on the composite score of the cumulative score value, the security level confirming server confirms the security levels of the terminal.

The invention discloses a human health risk assessment method for heavy metal contaminated soil. The method comprises the following steps: firstly, respectively constructing functional relationships C1 (pH) and C2 (pH) between the leaching concentration and acid dissolution state concentration of heavy metals in a soil sample and the pH value of an extracting agent; then, calculating the human health risk concentration Crisk in the soil sample, enabling the Crisk to meet a formula: Crisk = 0.5*C1 (pH)+0.5*C2 (pH); then, calculating the total carcinogenic risk and/or hazard index of heavy metalin the soil sample by referring to related parameters provided in "Technical Guidelines for Soil Pollution Risk Assessment of Construction Land (HJ 25.3-2019)" and a calculation model; and finally, evaluating whether the heavy metal contaminated soil has human health risks or not by referring to (HJ 25.3-2019) evaluation standards. The method is stricter, and dynamic evaluation of the human health risk of reutilization of the heavy metal contaminated soil after remediation under different pH environmental conditions is achieved.

The invention discloses an epidemic situation propagation risk quantitative evaluation method based on heterogeneous factors. The method comprises the following steps: S1, determining an epidemic situation risk level and an epidemic situation risk state of a risk area; s2, constructing and training an epidemic situation risk attribute model; s3, according to the trained epidemic situation risk attribute model, determining a state transition matrix of the risk area; and S4, according to the state transition matrix of the risky area, determining the stable state of the risky area, and determining the epidemic risk of the risky area by using the stable state. The progressive transmission method adopted by the invention has the effects of special epidemic situation risk influence factor weight distribution and evaluation result consistency check, can solve the conflict problem in the evaluation process, clarifies different influences of various factors on epidemic situation risks, and ensures the objectivity of the evaluation result.

The invention discloses a hepatic extracellular space information acquisition method, and belongs to the technical field of data information processing. The method comprises the following steps: (1),performing pretreatment; cleaning a sample, marking the sample, and standing for later use; (2), performing primary detection; to be specific, carrying out paraffin embedding and HE dyeing on the sample obtained by pretreatment in the step (1); and (3), performing final inspection; to be specific, carrying out image scanning on the sample obtained by initial inspection in the step (2), and evaluating the extracellular space of the hepatic cell. According to the method, invasive examination is avoided, fibrosis evaluation and treatment response observation can be repeatedly carried out, dynamicevaluation of pathological hepatic cells can be achieved, and the method has a positive effect on understanding of the dynamic process of liver fibrosis and fibrinolysis.

The invention discloses an automatic metering hopper. The automatic metering hopper comprises a main hopper (8), a material level sensor (9) is arranged on the inner side wall of the main hopper (8),a hopper pressure sensing device (5) is arranged at the bottom of the main hopper (5), a support (6) is arranged at the bottom of the hopper pressure sensing device (5), a feeding pressure sensing device (3) is arranged on the upper end surface of the main hopper (8), and a feeding hopper (10) is arranged on the feeding pressure sensing device (3); a support (16) is arranged on the feed hopper (10), the support (16) is connected with a motor (13), a turnover plate valve cover (4) and a rotary opening and closing latch(7), the feeding hopper (10) is connected with an automatic feeder (11), andan electric control box (2) and a hot air blowing device (1) are arranged on the outer side surface of the main hopper (8). According to the automatic metering hopper, the feeding and discharging condition of the main hopper (8) can be displayed in real time, and realizing of fine management is facilitated.

The invention discloses a real estate class loan business risk assessment method and device, which can be applied to but not limited to the field of big data, and the method comprises the steps: collecting the dynamic attribute information of a real estate mortgage by a real estate class loan business in different time periods; then according to the dynamic attribute information of the real estate mortgage by the real estate type loan business in different time periods and the loan information of the real estate type loan business, generating corresponding parameter values of each risk factor in different time periods; calculating default loss rates of the real estate loan business in different time periods according to the parameter values corresponding to the risk factors in different time periods; and according to the default loss rates of the real estate loan business in different time periods, generating a dynamic risk assessment result of the real estate loan business. According to the method, the dynamic assessment of the real estate loan business default risk of custom configuration risk factors can be supported.

The invention discloses a transformer substation flood prevention capability assessment method based on live data. The method comprises the steps that a multi-dimensional influence factor system is established; establishing a numerical value quantification model of the occupied area and the safe ponding depth based on a multi-dimensional influence factor system; constructing a risk level evaluation model; acquiring actual flood situation influence factor data; based on the risk level assessment model, obtaining a preliminary risk assessment level, and performing preliminary allocation of flood prevention materials; obtaining the real-time safe operation ponding depth of the power transformation equipment based on the numerical value quantification model of the occupied area and the safe ponding depth; calculating the real-time accumulated water depth of the transformer substation; and comparing the real-time accumulated water depth of the transformer substation with the safe operation accumulated water depth of the transformer equipment to evaluate the flood prevention capacity of the transformer substation. According to the invention, the flood prevention capability and risk real-time sensing capability of the transformer substation are improved, and the scientific configuration level of flood prevention materials, personnel and equipment is improved.