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 relates to an urban flood disaster dynamic assessment method based on multi-source data. The method comprises the following steps: collecting real-time data; carrying out spatialization processing; establishing a flood disaster affected body data set; simulating a submerging process; simulating population disaster; calculating the passing speed during rainstorm and flood; analyzing differences; and generating a dynamic evaluation result. According to the method, the superiority of a big data technology is fully utilized, urban population and traffic conditions are obtained based on a web crawler technology, and dynamic assessment of flood disaster loss is realized through the constructed disaster affected body data set and an urban rainfall flood model simulation result; the defects that traditional data are difficult to obtain and the temporal-spatial resolution is relatively poor are overcome, the cross research of the big data technology and the urban hydrological field is realized, the loss difference of disaster affected bodies at different flood occurrence time points can be captured, and the influence of flood disasters on the society can be truly reflected. The method can be combined with any urban rainfall flood model to guide disaster prevention and reduction work, and the toughness of a city is enhanced.

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 provides a switchgear reliability evaluation method which comprises the following steps: (S1) pretreating and initializing the basic data and operation data generated by a switchgear respectively, and establishing corresponding vector comparison tables; (S2) establishing a tree structure of the basic data, and modeling by use of a recurrent neural network; (S3) establishing a time sequence structure of the operation data, and modeling by use of a circular neural network; (S4) establishing a loss function according to the models established in the step (S2) and step (S3), and performing model training; and (S5) in combination with the vector comparison tables, performing model-based reasoning to obtain final risk assessment. According to the invention, by combining the recurrent neural network and the circular neural network and introducing an attribute vector and an event vector, the problem of low-dimensional coding of nonnumeric data is solved; and in combination with the basic data and the operation data, the fusion of multi-source information can be realized so as to provide accurate quantitative evaluation and dynamic evaluation of the switchgear reliability.

The invention relates to the field of soil pollution risk management and control and ecological risk evaluation, and discloses a heavy metal contaminated soil ecological risk assessment method which comprises the following steps: firstly, constructing a function relationship C1 (pH) between the leaching concentration of heavy metals in a soil sample and the pH value of an extracting agent; then, constructing a function relationship C2 (pH) between the acid dissolution state concentration of the heavy metals in the soil sample and the pH value of the extracting agent; then, calculating the heavy metal risk concentration Crisk in the soil sample, Crisk being equal to 0.5 * C1 (pH) + 0.5 * C2 (pH); then, determining the total concentration C3 of the heavy metals in the soil sample; and finally, calculating the ecological risk R of the heavy metal contaminated soil: R = Crisk / C3 * 100%, and dividing risk levels according to the ecological risk R of the heavy metal contaminated soil. The evaluation method provided by the invention is stricter, more scientific and reasonable, and more beneficial to ecological environment protection.

The invention relates to an evaluating system, an information interaction system with the same and an evaluating method. The evaluating system for evaluating a terminal comprises a database for storing evaluation related data for a terminal, an evaluating server for evaluating the terminal and businesses of the terminal by using the evaluation related data in the database, and a safety level determining server for determining the safety level of the terminal. The evaluating system is characterized in that the evaluating server comprises an initial evaluation processor and a accumulative evaluation processor, wherein the initial evaluation processor is used for initially evaluating the terminal and the current business thereof based on the evaluation related data of the terminal and the evaluation related data of the current business of the terminal, and calculating the score of the current time point; the accumulative evaluation processor is used for processing an accumulative score based on the score of the current time point, calculated by the initial evaluation processor, a history score and a recommended evaluation value, and calculating the comprehensive score; and the safety level determining server is used for determining the safety level of the terminal based on the comprehensive score of the accumulative evaluation processor.

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 embodiment of the invention discloses a method and equipment for acquiring a risk prevention and control grade of a power transmission line, and relates to the technical field of computers. The risk prevention and control grade of the power transmission line can be accurately acquired; therefore, risk prevention and control measures are correctly determined, and risks are prevented from being converted into accidents. The method for acquiring the risk prevention and control grade of the power transmission line comprises the following steps of: searching a line evaluation standard list according to each line evaluation element of the power transmission line, and acquiring a score corresponding to each line evaluation element; weighting the score corresponding to each line evaluation element to obtain an equipment comprehensive score and an environmental comprehensive score; and determining the risk prevention and control grade of the power transmission line according to the equipment comprehensive score and an environmental comprehensive score. The method and the equipment are applied to operation of power grids.

The invention discloses a fan operation state evaluation method, device and equipment and a storage medium. The method comprises the steps that operation parameters of a fan during operation and environment parameters of the environment where the fan is located are obtained in real time; determining an evaluation model corresponding to the environmental parameter according to a corresponding relationship between the environmental parameter and the evaluation model; based on the evaluation model, evaluation parameters corresponding to the operation parameters are determined according to the operation parameters and judgment thresholds corresponding to the operation parameters, and the judgment thresholds are determined according to historical data of the operation parameters; and outputtinga state evaluation result corresponding to the evaluation parameter according to a corresponding relationship between the evaluation parameter and the state evaluation result, thereby solving the technical problem of inaccurate evaluation when the operation state of the fan is evaluated in the prior art.

The invention provides a mobile user credit line evaluation method and an evaluation system. The mobile user credit line evaluation method comprises the steps of judging the category of a user to be evaluated, predicting the call charge of the user to be evaluated in a time period to be evaluated, and calculating the credit line of the user to be evaluated in the time period to be evaluated according to the category of the user to be evaluated and the call charge predicting result. According to the mobile user credit line evaluation method, the consumption change of a user can be dynamically predicted by dynamically perceiving and analyzing the historical consumption information of the user in a training sample, the credit line of the user is determined dynamically according to the consumption change of the user, dynamic evaluation of user credit line is realized, and therefore, the degree of satisfaction of users is improved effectively.

The invention discloses a mined-out area deformation and stability assessment method based on gravity anomaly, comprising the following steps: 1, arrangement of an absolute gravimeter observation point and erection of an absolute gravimeter; 2, acquisition of an absolute gravity observation value; 3, establishment of a space rectangular coordinate system; 4, center-of-mass coordinate calculation of a mined-out area rock surrounding sphere; and 5, drawing of a center-of-mass change curve of the mined-out area rock surrounding sphere and acquisition of stable deformation. The method is simple, reasonable in design, low in cost and convenient to operate; the deformation of the mined-out area can be accurately monitored by using gravity anomaly, so that the monitoring result is accurate; and the stability of the mined-out area is assessed according to the deformation of the mined area, and the stable deformation of the mined-out area is obtained, so the practicability is strong.

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 personal credit assessment method based on a fusion neural network, and the method comprises the steps: carrying out the data preprocessing: obtaining behavior data for reflecting the personal credit condition, and carrying out the extraction, cleaning and normalization processing; decomposing the different behavior data to obtain multi-layer local feature information; inputting the decomposed behavior data into a first neural network to obtain a prediction data value of the behavior data, and predicting the change trend of the real-time behavior data for assisting inevaluating the personal credit rating; based on the prediction data value obtained by the first neural network, inputting the prediction data value into the second neural network for fitting to obtain the personal credit judgment result. Feature extraction of the behavior data by adopting the LSTM neural network is realized, fitting of multiple behavior data weights is performed through the BP neural network, and the accuracy of personal credit evaluation is improved.

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.

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.

An embodiment of the present invention provides a method for evaluating the amount of rainfall regulation and storage by ridges and ditches, including: obtaining the net rainfall of each time period of the ditch in the rainstorm according to a predetermined time interval, and obtaining the net rainfall of each accumulation period; according to the The characteristic parameters of the size of the furrow and the net rainfall in each accumulation period are evaluated by using the rainfall regulation and storage capacity evaluation model to evaluate the regulation and storage capacity of the ridge for each session, and the regulation and storage capacity of the furrow for each session is obtained in each time period. The method for evaluating the amount of rain regulation and storage by furrows for each field provided by the embodiment of the present invention can realize the dynamic evaluation of the amount of rainfall adjustment and storage by furrows.

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.