96 results about "Interval model" patented technology

The invention relates to an automatic generating method of an electric network station wiring diagram, which comprises the following steps of: a. establishing an interval model database, wherein the interval model database comprises all types of interval models in a station, each interval model is the most complete interval, each element equipment in the interval models is related to a check box, and the check box is used for numbering the related element equipment and supplying an operation interface for deleting the related element equipment; b. when the diagram is generated, selecting the interval model corresponding to the voltage grade of the station from the interval model database; and if the interval model needs to be modified, deleting the related and undesired element equipment by setting the check box, connecting the residual element equipment according to an interval wiring rule, and generating the corresponding electric network station wiring diagram. The invention realizes the function of automatically generating the diagram; the station wiring diagram can be automatically generated by a user through only simple selection and character input, the method saves time and labor, and the work efficiency is greatly improved.

The invention discloses a method for determining the credibility of photovoltaic power capacities. The method comprises the following steps of: (1) creating a time-interval model of a hybrid power generation system containing a photovoltaic power station; (2) calculating a daytime reliability index Rd and a night reliability index of an original power generation system not containing a photovoltaic power station, and superimposing the indexes to obtain a synthetic reliability index Rx of the original power generation system; (3) connecting a photovoltaic power station to the original power generation system, and adjusting the load level of the hybrid power generation system with Ry and Rd as targets, thus obtaining a new load level of the hybrid power generation system; and (4) replacing the photovoltaic power station with a virtual conventional unit, performing iterative computation respectively at the new load level to obtain a daytime generating capacity Cy and a whole day generating capacity credibility Cd of the photovoltaic power station. By virtue of the method, the improvement on the daytime reliability of the system after the photovoltaic power station is added can be clearly investigated, and the credibility of the daytime and full-day photovoltaic power capacities can be calculated.

The invention discloses a combined navigation method and device for an unmanned aerial vehicle based on expanded auto-adaptive interval Kalman. The method comprises the following steps: measuring an inertial navigation parameter of the unmanned aerial vehicle by using a micro electro mechanical system inertial measurement unit and measuring a visual navigation parameter of the unmanned aerial vehicle by a visual navigation system; and by taking a digital signal processing module as a navigation computer, obtaining the optimum estimation of the navigation parameter of the system by taking an expanded auto-adaptive interval Kalman filter technology as a combined method fused with inertial and visual navigation parameters. The device disclosed by the invention is easy to realize, low in cost, relatively small in mass, relatively small in power consumption and suitable for being popularized in the civil field. A linear system model can be obtained by means of the expanded auto-adaptive interval Kalman filter technology. A time-varying parameter of the system is modeled as an auto-adaptive interval model, so that the capability of the navigation system operating the navigation positioning task during temperature variation, frequent gesture variation of a transporter and unsatisfactory lighting condition or in complex and severe conditions that a visual sensor is hard to fix the focus is improved.

The invention relates to a method for intelligently generating a monitoring information point list of a dispatching automation system.The method comprises the steps of 1, intelligent input of interval information, wherein an interval model is generated by inquiring an 'equipment category' list in an SCADA database of the dispatching automation system and inquiring an 'under-installation equipment parameter information list' exported out of a PMS of the State Grid Corporation of China; 2, intelligently-aided modification of the interval information, wherein multiple interval batch modification dispatching numbers are provided by analyzing mouse action and the keyboard input state of a user, and equipment contained in an interval is added or modified or deleted in batches; 3, outputting of the standard monitoring information point list, wherein corresponding protection information in a substation standard monitoring information point list template is searched for according to the 'interval type' in the interval model, interval standard information is formed, the template format is imported according to the dispatching automation system, and the monitoring information point list is output.By means of the method, generation efficiency of the monitoring information point list is greatly improved, labor intensity is lowered, and correctness and standardization of the generated monitoring information point list can be guaranteed.

The present invention provide a modeling method for intelligent substation secondary equipment interval information model. The method particularly comprises the following steps of: establishing an association relationship between a primary equipment model and a secondary equipment model, dividing a secondary equipment interval model, and automatically collecting secondary equipment elements to the secondary equipment interval model. According to the method, the association relationship between the primary equipment model and the secondary equipment model is established, and advanced applications of intelligent analysis of mutual interference of reorganization and expansion, intelligent alarming, five-prevention interlocking, data identification and the like are powerfully supported, thereby reducing labor and time consumption, improving the security and stability of a substation and a power grid, and enhancing the support of the substation to a primary station; According to the method provided by the present invention, the association relationship between the primary equipment model and the secondary equipment model in an SCD (substation configuration description) model of the intelligent substation can be accurately analyzed, so that isolated states of information models can be avoided and correct functional analysis application of intelligent alarming, five-prevention interlocking, data identification and source-end maintenance in the intelligent substation can be facilitated.

The invention relates to an error lock-resistant logic rule generation and check system characterized by comprising an input-output module, a graphic editing module, a typical interval model library, a graphic analysis module, an abstract logic formula library, an abstract logic formula rule library and a logic formula generation module. With built-in transformer stations, various typical wiring models and a general five-prevention logic formula, after concrete transformer station main wiring information is read, the main wiring information can be matched with a system built-in typical device wiring model; then the general five-prevention logic formula corresponding to a matching result can be changed into practical device information and then output, and a concrete five-prevention logic formula can be acquired; further, the automatically-generated logic formula and the well-edit logic formula are checked; and problems of low transform station five-prevention logic formula writing and checking efficiency, poor reliability and incapability of self-reliability prove can be solved.

The present invention discloses a machine learning method, a machine learning device, a system, a storage medium and an apparatus. The machine learning method, the machine learning device, the system,the storage medium and the apparatus are used for identifying malicious network bots. The method includes an obtaining step and a learning step. According to the obtaining step, user access log datain a target website are obtained, wherein the user access log data contain the network addresses of user requests and time intervals between the requests. According to the learning step, machine learning is performed on the user access log data to obtain a time interval model of the requests. According to the method provided by the technical schemes of the invention, an invasion technology is notneeded; network abnormal bots can be effectively identified; and the accuracy of the detection of the abnormal bots can be remarkably improved.

The invention provides a vertex analysis method for in-car vibration noise prediction based on an agent model. The method comprises the steps that at first, a finite element model of the in-car vibration noise prediction is established according to actual demands of an engineering field, and a target response is determined according to a given target space position and a target frequency scope; secondly, an interval model is used to quantify uncertain parameters, a Gaussian integration point is used to sample interval parameters, and the finite element model of the in-car vibration noise prediction is used to compute real responses at interval parameter sample points; and finally, the agent model of the target response is established by the real response values of a discretization scheme based on high-dimensional model representation theories, values of the agent model at all the vertexes of a hypercube are computed based on a vertex analysis theory, and finally a frequency response distribution of in-car vibration noise interval boundaries can be obtained. The method provided by the invention overcomes dependence of the in-car vibration noise prediction on large sample size experiment data of parameters and applicability limiting of small-interval parameters; and the method provides a basis for formulation of noise reduction measures such as in-car noise optimization and control.

The invention discloses an entity material and truss-like microstructure material integrated non-probability reliability topology optimization method. The method comprises the steps of indirectly realizing establishment of an entity material and truss-like microstructure material double-material interpolation model through utilization of elastic constants of materials; obtaining the elastic constant of a micro-level truss-like microstructure equivalent to macro-level rigidity performance of the materials through utilization of a strain energy equivalent method; describing uncertainty of optimization model parameters through utilization of an interval model, and establishing reliability displacement as a non-probability reliability index; solving the sensitivity of the reliability displacement to design variables through utilization of an adjoint vector method; and updating the design variables through application of an MMA algorithm, and carrying out iterative optimization until the optimum design scheme is obtained. According to the method, in a continuum structure topology optimization process, the entity material and truss-like microstructure material integrated design is effectively realized, influence of uncertain parameters described by the interval model on the structure performance is reasonably represented, and the light weight, safety performance and economy of the structure are effectively improved.

The invention provides a virtual power plant operation modeling method, which comprises the following steps: 1) a robust mixed integer linear programming model with profit maximum of a virtual power plant in participation in power market operation as a target function is built, and a robust interval optimization method is adopted in the mathematical model to handle uncertainty of the electricity price; 2) with an upper limit and a lower limit of the electricity price as a boundary, the robust interval model is built; 3) an iteration number, an iteration step size and a robust coefficient are set; and 4) IBM CPLEX software is used for acquiring the optimal bidding result of the virtual power plant in participation in market operation. Compared with the prior art, the virtual power plant operation modeling method has the advantages of good economic benefits, high calculation efficiency and the like.

The invention provides a speech endpoint detection method, device and equipment and a storage medium. The speech endpoint detection method comprises the steps of extracting audio features used for determining the dynamic detection interval from audio data to be detected to serve as dynamic detection interval features; determining attributes of the audio data to be detected through a pre-established audio attribute determination model according to the dynamic detection interval features, and determining the dynamic detection interval of the audio data to be detected through a pre-established dynamic detection interval model according to the dynamic detection interval features; and determining the speech endpoint of the audio data to be detected based on the attributes and the dynamic detection interval of the audio data to be detected. The speech endpoint detection method provided by the invention realizes speech endpoint detection based on the dynamic detection interval, has a good detection effect and is excellent in user experience.

The invention discloses an uncertain wind power output-based coordinated optimization method for wind power grid connection. The method comprises the following steps: collecting related parameters of a system; establishing a wind power prediction error calculation model and a wind power prediction error growth model, and obtaining uncertain wind power output according to the wind power prediction error growth model; on the basis of establishing a weight interval model that load can participate into scheduling and introducing a schedulable load and energy storage system, establishing a wind power cost model and establishing a coordinated optimization scheduling model for wind power grid connection of considering the schedulable load and energy storage system, and obtaining power output of various units within the scheduling period according to the optimization model; and calculating the wind curtailment rate of the system according to the power output of various units, and analyzing various costs and the standby condition of the system. According to the internet coordinated optimization model for wind power grid connection based on the uncertain wind power output and the schedulable load weight interval established by the method, the optimization scheduling scheme with obvious social and economic benefits is provided for scheduling personnel when solving the wind power integration problem.

The invention relates to a transformer-substation micro-computer five-prevention main wiring diagram analysis system. The system comprises an input and output module, a typical interval model library, a model editing module, a graphic analysis module and a graphic editing module, wherein the input and output module is used for reading a primary main wiring diagram message of a micro-computer five-prevention system and passing back an analysis result to the micro-computer five-prevention system; the typical interval model library is used for storing different types of typical interval wiring models; the model editing module is used for establishing a typical wiring model; the graphic analysis module disassembles the primary main wiring diagram message read by the input and output module into several intervals, the several intervals match with the typical interval model library respectively and acquiring a wiring diagram analysis result; and the graphic editing module converts the typical wiring models in the typical interval model library into an editable wiring diagram and displays the wiring diagram in a window. In the invention, automatic identification of the primary main wiring diagram of the micro-computer five-prevention system is realized and necessary five-prevention attribute parameters needed by the micro-computer five-prevention system are acquired, and simultaneously system maintenance and usage are simple, which is good for increasing practicability of the system.

The invention discloses an optimization method, device, electronic equipment and computer-readable medium for a sample value interval model, relates to the technical field of computer technology, can establish a sample value interval model, saves configuration and maintenance costs, and provides users with more reasonable samples Value interval configuration to improve user experience. A specific implementation of the method includes: obtaining a sample set of data; for each positive integer k in a given range, applying a clustering algorithm to cluster the sample set to generate k non-overlapping sub-sets of the sample set set, so as to obtain the corresponding sample value interval model, and when the sample value interval model satisfies the preset optimization objective, the sample value interval model is output.

The invention discloses a comprehensive energy system scheduling method for a dynamic time interval, and the method comprises the following steps: establishing a comprehensive energy system schedulingframework based on the prediction control of a dynamic time interval model; establishing a comprehensive energy system day-ahead scheduling model; establishing an intra-day scheduling 'track deviation-control energy-control cost ' performance index based on model prediction control; establishing a dynamic time interval decision index; and establishing an energy conversion unit, a heat supply network model, a gas network model and a power grid model. The comprehensive energy system scheduling method has the beneficial effects that the dynamic time interval comprehensive energy system scheduling method taking trajectory deviation-control energy-control cost as a performance index is considered, so that the performance index has enough adjustable margin, and different scene requirements aremet; the dynamic time interval decision index is considered, the real state that the system is about to generate or even has a large error can be reflected, and the decision index is provided for judging whether the system needs to issue a scheduling instruction.

The invention discloses an interval model time varying reliability based on active service structure optimized maintenance design method taking into account dynamic uncertainty. According to the invention, influence on mechanical behaviors of an on active service structure by time varying uncertainty is taken into account comprehensively. First, through defining the uncertainty characteristics ofquantified basic variables of a non-probability interval model and through uncertainty propagation analysis, a limit state function of the structure taking into account a static-dynamic hybrid uncertainty condition is deduced; reliability indexes of the on active service structure based on the non-probability interval model are established based on a first-time passage theory; establishment of a maintenance cost model under a non-probability frame is tried by taking a maintenance cost formula proposed by Frangopol as the basis and an optimized maintenance design method for the on active service structure is constructed; the optimal scheme for maintenance in the service cycle of the on active structure is finally determined through repeated iteration of particle swarm optimization by takingthe structure maintenance total cost as the optimization target, taking the maintenance frequency, the type and the corresponding time points as design variables and taking the structure reliabilityas optimization constraints.

The invention discloses a system reliability analysis method based on an interval model, which comprises the following steps of: establishing a system failure fault tree model; calculating a top eventoccurrence probability expression of the failure fault tree through the failure fault tree; acquiring a probability interval of occurrence of a bottom event of the failure fault tree; Calculating theoccurrence probability interval of the top event according to the occurrence probability expression of the top event and the occurrence probability interval of the bottom event; According to the occurrence probability interval of the top event and the preset reliability standard, whether the system is reliable or not is judged. It solves the problem that when analyzing the reliability of the system through the occurrence probability of the basic event, the occurrence probability of the basic event needs to be obtained through a large number of experimental statistics, which leads to the difficulty of obtaining the experimental data for the complex system and consumes a lot of manpower and material resources, and reduces the cost of the reliability analysis of the system.

The invention provides a three-dimensional barrier-bypassing well drilling design method and device, and a storage medium, and relates to the technical field of coalbed gas well drilling. The three-dimensional barrier-bypassing well drilling design method comprises the steps that the part of a barrier well section of an adjacent well to a to-be-drilled well is determined according to an actual drilling trajectory of the adjacent well, the self-size parameter, the repetition measurement error and the single shot instrument error of the barrier well section and the measurement error and the actual drilling well trajectory control error of the to-be-drilled well are superposed, and thus a barrier interval model of the barrier well section is established; and the minimum anti-collision distance is obtained through the barrier interval model, and a barrier-bypassing track is designed based on the minimum anti-collision distance, so that the to-be-drilled well safely bypasses a barrier interval corresponding to the barrier interval model. According to the three-dimensional barrier-bypassing well drilling design method, the barrier interval model is established through error superposition, thus the minimum anti-collision distance is more accurate, accordingly the barrier-bypassing well section is effectively shortened, and the safety factor of barrier-bypassing well drilling is increased.

The invention discloses a substation equipment infrared thermal image shooting navigation method and device. The method is characterized is that, to begin with, a shooting task package is input into a thermal imager, wherein the shooting task package at least comprises interval names, interval models and interval coordinate information of a substation to be shot; a region where a shooting person locates is judged according to the position coordinates of the thermal imager; when the shooting person enters a danger zone, the thermal imager gives a warning signal for reminding of entering the danger zone and reminds the shooting person to leave the danger zone; when the shooting person enters a work zone, the thermal imager gives a reminding signal for reminding of entering the work zone, and reminds the shooting person that infrared thermal image shooting can be carried out; and after the shooting person enters the work zone, the thermal imager judges the position of the shooting person in an interval, reminds the shooting person to carry out shooting, and automatically associates and records the names of shot devices in shot infrared thermal images. The navigation method and device is specially developed for substation equipment infrared thermal image shooting, thereby reducing burden of task package producers and shooting persons, improving shooting safety and efficiency, saving cost and facilitating big data archiving and cloud computing of the infrared thermal images.

The invention discloses a nonlinear system characteristic variable significance mining method based on data stream processing, wherein the method comprises the following steps: collecting the historical data and preprocessing the historical data; DBSCAN parameters are optimized by closed-loop structure, and the data set is divided by DBSCAN clustering. A nonlinear model based on LGBMRegressor is established for each type of data, and the number of times each feature variable is used in the iterative training process of the model is recorded to characterize its significance, and the sequence ofsignificant feature variables is established. Determine the main distribution intervals of each variable value, form the eigenvalue distribution interval model of a single class, integrate the eigenvalue distribution interval models of all classes to establish the grid model, and map the salient eigenvariable series to the corresponding class in the grid model to form the composite grid model; Build the real-time computing framework based on Storm, design the Topology (topology) based on stream processing, and load the composite mesh model at the same time.

The invention discloses a double-crane system dynamic modeling algorithm and a nonsingular interval parameter design method. The dynamic modeling algorithm comprises the main steps that 1, a constraint equation of a system is established; 2, a variable-argument response equation and a kinematic Jacobian matrix are established according to the constraint equation; 3, a deviation angular velocity matrix and a deviation velocity matrix of crane jibs are obtained according to the kinematic Jacobian matrix and velocity vectors of all points; 4, inertia force and inertia moments of the crane jibs and loads are obtained according to acceleration vectors of hinged points; and 5, a dynamic model of the system is established according to the virtual work principle in combination with the equation. The nonsingular interval parameter design method comprises the steps that 1, the uncertainty of structural parameters is described according to an interval model; and 2, a nonsingular interval parameter model is established based on the dynamic model of the system and the interval model. Through the double-crane system dynamic modeling algorithm and the nonsingular interval parameter design method,analysis of a double-crane system dynamic response can be realized, and a foundation is laid for prediction of a response domain under interval parameters.