54 results about "Model expansion" patented technology

The present invention represents a procedure for compensating the heave movement of offshore cranes. The dynamic model of the compensation actuator (hydraulically operated winch) and the load hanging on a rope are derived. Based on this model, a path-tracking control unit is developed. To compensate the movement of the ship/watercraft caused by waves, the heave movement is defined as a time-varying disturbance and is analyzed with respect to uncoupling conditions. With a model expansion, these conditions are satisfied, and an inversion-based uncoupling control law is formulated. To stabilize the system, an observer is used for reconstructing the unknown state by means of a force measurement. Furthermore, the compensation efficiency can be improved by predicting the heave movement. There is proposed a prediction method in which no ship/watercraft models or properties are required. The simulation and measurement results validate the heave compensation method.

A general mathematical framework is formulated to characterize the contribution of gradient non-uniformities to diffusion tensor imaging in MRI. Based on a model expansion, the actual gradient field is approximated and employed, after elimination of geometric distortions, for predicting and correcting the errors in diffusion encoding. Prior to corrections, experiments clearly reveal marked deviations of the calculated diffusivity for fields of view generally used in diffusion experiments. These deviations are most significant with greater distance from the magnet's isocenter. For a FOV of 25 cm the resultant errors in absolute diffusivity can range from approximately −10 to +20 percent. Within the same field of view, the diffusion-encoding direction and the orientation of the calculated eigenvectors can be significantly altered if the perturbations by the gradient non-uniformities are not considered. With the proposed correction scheme most of the errors introduced by gradient non-uniformities can be removed.

The invention provides a method for diagnosing faults of a multi-model flight control system based on expected model expansion, comprising the following steps: making a statistic of various faults of the flight control system, and building a basic model collection; forecasting the probability of the multiple fault models at the current time, and building an expected model collection; combining the basic model collection with the expected model collection to build a fault model collection at the current time; filtering each fault model in the model collection at the current time, and updating the probability; if the probability of certain fault model in the model collection at the current time is more than or equal to the preset probability threshold value, judging that the flight control system has the fault corresponding to the fault model. The invention further provides a device for diagnosing the faults of the multi-model flight control system based on expected model expansion, comprising a basic model collection building module, an expected model collection building module, a model collection at the current time building module, a filtering and probability updating module and a fault judging module. The invention further provides a flight control system.

The invention provides a model transformation method of an IEC61850 to an IEC61970 and an apparatus thereof. The model transformation method comprises steps that: a memory data model is built on the basis of an IEC61850 SCL model; on the basis of the memory data model, a hierarchical structure of an SCL primary model is converted to an IEC61970CIM topology model; and a secondary model transformation is carried out on the basis of the memory data model and a secondary rule conversion description language. According to the model transformation method of the IEC61850 to the IEC61970 and the apparatus thereof provided by the invention, a model extension is carried out on the IEC61850 standard, and the problem that when the IEC61850 standard is adopted to develop electric power automation products, the SCL specification cannot fully meet model specifications required by master station automation product development is solved. Therefore, time and effort needed to add new plants and stations to an EMS are greatly reduced, and the model transformation method and the apparatus of the invention have good application prospect.

The invention provides an extended target tracking method based on GP-VSMM-JPDA. The method is characterized by firstly, using an expected model expansion method to construct an adaptive model set, and initializing an extended target state based on a model; secondly, establishing an extended target combined tracking gate based on a Gaussian process to select effective measurement; then, combiningthe Gaussian process with a combined data correlation filter to form a new filter so as to update the states and the covariances of each extended target under different models; and finally, based on avariable structure interactive multi-model method, fusing the state and covariance of each extended target to obtain final state estimation. Compared with an interactive multi-model (IMM-RM) maneuvering extended target tracking method based on a random matrix, a GP-VSMM-JPDA method can be used to track multiple maneuvering non-elliptic models simultaneously in a clutter environment and can be used to accurately estimate a target shape so as to provide more target information.

The invention discloses an information conversion method, a device and a system, and relates to the field of communication. In the information conversion method, after the SNMP service information sent by SNMP network equipment is received by an SNMP processing module, the MIB information associated with the SNMP service information is sent to a data model conversion module. The data model conversion module converts the received MIB information into the service information based on the YANG model extension, and transmits the obtained service information to a NETCONF message processing module through an XML message processing module. The NETCONF message processing module converts the received service information into a transmission announcement, and the transmission announcement is sent toan NETCONF server. According to the invention, the NETCONF/ SNMP conversion is achieved on the basis of the YANG model expansion, and the automatic management of traditional equipment is realized. A feasible technical scheme is provided for achieving the compatibility of traditional equipment in an SDN scene.

The generalized functional model refers to a functional model which is formed in a generalized mode after functional maintenance requirements are added on the basis of the traditional functional model. When the traditional functional model is built, a reliability factor is not considered comprehensively, and the reliability requirements corresponding to each function are not clearly expressed in the model. In order to solve the above problems, a generalized functional model building method considering reliability design requirements is designed. The method comprises steps: 1, a functional model containing the functional maintenance requirements is expanded, functional implementation requirements are firstly determined according to requirements of a customer, the reliability design requirement corresponding to each functional implementation requirement is determined through recognizing a functional failure mode on the basis, the functional maintenance requirements are formed finally through merging, and functional model expansion is completed; and 2, a functional principle model characterization method is designed, and the generalized functional model is built. That is, a set of metamodel for the functional model is designed, a product working principle is combined and the metamodel is used to build the generalized functional model for the product.

The invention belongs o the technical field of power grid automatic dispatch, and particularly relates to a power grid equipment monitoring big data analysis oriented uniform information model and modeling method. The uniform information model includes a resource model and a measurement model; the resource model includes an equipment container, a primary equipment model and an associated secondary equipment model. The modeling method includes the following steps: (S1) using a CIM model in IEC 61970 to describe and establish the equipment container, the primary device model and a correlation thereof, and importing the equipment container and the primary device model and the correlation thereof to the uniform information model; (S2) using an SCL model in IEC61850 to establish the secondary equipment model, and importing the secondary equipment model to the uniform information model; (S3) establishing the correlation between the primary equipment model and the secondary equipment model; and (S4) expanding measurement class information to a measurement package, and establishing a generalized measurement model. The uniform information model can achieve the correlation between primary equipment and secondary equipment, can perform model expansion on measurement classes in the CIM model, can intensively access all the measurement class information, and can achieve uniform modeling.

The invention provides an active scheduled power flow adjusting method and device based on grid model expansion. The method comprises the following steps: calculating sensitivity of line nodes of a power grid in the current scheduling area according to data and system frequency response characteristics of a power grid topology model; performing equivalent calculation on tie lines between the current scheduling area and a high-level scheduling area according to the sensitivity, local scheduling planning data of the current scheduling area as well as power grid topology model data and unit planning data of the high-level scheduling area, and setting boundary parameters of the power grid topology model in the current scheduling area; adjusting active scheduled power flow of the current scheduling area according to the local scheduling planning data, the power grid topology model data and the unit planning data of the high-level scheduling area, the sensitivity and the power grid topology model subjected to boundary parameter setting in the current scheduling area. The accuracy of scheduled power flow calculation is improved with the method.

The present disclosure relates to a model expansion method and device, an electronic device and a storage medium. The method includes: determining importance parameters of a plurality of nodes according to activation values and gradients of activation values of a plurality of nodes in a plurality of network layers of a first model; determining a node to be expanded among the plurality of nodes according to an importance parameter of the plurality of nodes and a preset growth ratio of the plurality of network layers; expanding the first model according to the nodes to be expanded of the plurality of network layers, and obtaining a second model. The disclosed embodiment can determine the nodes to be expanded among a plurality of nodes through the importance parameter, and expand the first model to obtain a second model, and the nodes in the first model can be used to obtain the second model, so that excessive computational resources and training time need not be consumed, and the fittingeffect is good.

The invention discloses a topology analysis-based regional power grid fault loss consequence calculation method. A "load" of a regional power grid intelligent dispatching main station system is subjected to model expansion, and attributes including "a power failure affected user number", "a power failure affected important user number", "important users" and "important user levels" are added; the regional power grid intelligent dispatching main station system stores data sections and divides power grid fault devices into loads and other devices, and the system can accurately calculate fault loss loads based on topology analysis and load models regardless of faults, judge power failure devices, analyze a power failure range and perform statistics on the power failure affected users; and by adopting the method, a fault loss load calculation result is more accurate, and relatively rich power failure affected user information and a power failure range analysis function are provided, so that the technical requirements of an intelligent power grid are better met, and the method has very high engineering practicality and very wide application prospects.

A method for storing model parameters is disclosed. The method includes: storing the underlying parameters of a model object in the first parameter table, and storing the extended parameters of the model object in a vertically extended form to a second parameter table, such that attributes of model objects that would otherwise require column expansion in the first parameter table to be added can be stored in the second parameter table in the form of row expansion. Therefore, the structure of the first parameter table and the second parameter table need not be modified, and the newly added attributes can be stored without creating a new table, thereby simplifying the program of the model expansion, facilitating the model expansion, more adapting to the increasing demand of the model data, and lightening the work pressure of the model data management and maintenance. The invention also discloses an apparatus and a device for storing model parameters, which have the beneficial effects.

The invention discloses a mechanical modeling method for a nonholonomic constraint system. The mechanical modeling method comprises the steps of introducing an intermediate variable to describe a nonholonomic constraint relation according to the complexity of nonholonomic constraints when constraint analysis is carried out; revealing independent generalized velocity information included in kinetic energy through the constraint analysis, extracting a coefficient of a product item of independent generalized velocity and defining the coefficient as the intermediate variable, and changing the kinetic energy into a new form of expression; in a modeling process, calculating partial derivatives of some function variables to generalized coordinates or total derivatives of the function variables to time massively, establishing a function-variable implication relation table and introducing composite derivation to solve by analyzing a variable subordinate structure; and defining several structural arrays to store calculation results since the calculation of the influence of the nonholonomic constraints on the system is more complex. In order to avoid a model expansion problem caused by back substitution of the intermediate variable, the calculation expression of the model needs to be outputted in a reverse order.

The invention discloses a dynamic response reconstruction method and system based on EMD and model polycondensation and a computer readable storage medium. According to the method, substructure division is carried out on a finite element model, then degree-of-freedom division is carried out on each substructure, modal coordinate transformation is carried out, each substructure is coupled into a super-unit model, a modal shape matrix of the unit model is solved, and modal response is extracted from measurement data through an EMD decomposition method, and finally a substructure interface response is reconstructed based on the extracted response data and the modal shape matrix. According to the method, the super-element model of the structure is generated based on the finite element model, the current time domain reconstruction method based on EMD decomposition is expanded, the modal synthesis method is used in the response reconstruction method for the first time, response information of key points is predicted through a modal superposition method, the dimensionality of a finite element model related parameter mathematical matrix is effectively reduced, the calculation efficiency ofresponse reconstruction is improved, and the method has the advantages of high accuracy, high analysis speed and the like.

The invention provides a signal processing method for measuring mercury concentration of smoke of a heat-engine plant on the basis of a CVAFS method. The method comprises the following steps: acquiring an output voltage signal of a mercury analyzer; preprocessing data of the voltage signal; carrying out segmented polynomial fitting on a voltage curve; establishing a corresponding state-space equation for a fitted polynomial; and carrying out multi-model extension Kalman filtering processing on a noised signal. The signal processing method is used for the situation that a system accurate mechanism model in the field of online monitoring of mercury concentration of the smoke of the heat-engine plant on the basis of the CVAFS method is difficult to determine; filtering processing on output signals of a photomultiplier can be realized; the method is simple and is easy to implement; and the filtering effect is good.

The invention relates to a rack assembly for a compressor; the rack assembly comprises a cylinder and a rack; a cylinder insertion hole is formed in the rack; a first end part of the cylinder insertion hole is provided with a U-shaped slot; the cylinder is mounted in the cylinder insertion hole. The invention also relates to an assembling method. Unfavorable influences such as cylinder deformation caused by the fact that a U-shaped slot is formed in the cylinder are avoided, the machining deformation of the cylinder is reduced, and the cylinder precision is improved; the sealing distance on the cylinder is increased, the sealing effect is improved, the universality is strong, and model expansion is convenient; besides, the split cylinder is smaller in mass and shape, so large-batch machining is facilitated, the machining efficiency is improved, and the machining cost is reduced; a piston mounted in the cylinder can be very easily assembled onto a crankshaft by a connection rod, so the production efficiency is improved.

The invention discloses a genome selection method for complex character genetic improvement. The genome selection method comprises the following steps: (1) establishing a statistical genetic model; (2) positioning a major gene; (3) estimating genetic parameters; (4) performing selection based on an individual whole genome breeding value. Compared with the prior art, the method provided by the invention has the beneficial effects that a) compared with a GBLUP model hypothesis, the model hypothesis provided by the invention is more in line with a biological genetic law and has higher predictive power, namely higher genome selection precision; and b) the method is based on a mixed linear model, has great flexibility and is convenient for model expansion.

The invention relates to a power grid harmonic power flow phasor matrix calculation method supporting rapid development and model expansion. The method comprises the steps of S1, setting harmonic times, statistical model initial values of various harmonic sources and an iterative error limit; S2, generating a fundamental wave and harmonic wave admittance matrix according to the input network parameters; S3, calculatng fundamental wave power flow; S4, detecting a node with a harmonic source, generating an index matrix, predicting harmonic data by using a harmonic source statistical model according to a fundamental wave power flow result, and performing harmonic power flow calculation; S5, updating the fundamental wave load power by utilizing the harmonic network loss power; and S6, judging whether the front and back node injection power errors are smaller than an iterative error limit, if so, calculating convergence, outputting a harmonic power flow calculation result, and otherwise, returning to the step S3. According to the power grid harmonic power flow phasor matrix calculation method based on support of rapid development and model expansion and program architecture based on thinking of the phasor matrix, rapid development and efficient calculation of large-scale power grid harmonic power flow simulation are realized.

The invention provides a model expansion method and device, a storage medium and a computer program product, which are applied to various scenes such as games, cloud technologies, artificial intelligence, intelligent transportation and vehicle-mounted scenes. The model expansion method comprises the steps that a plane set of a three-dimensional grid model is recognized, at least one type of surface recognition result is obtained, the plane set comprises all planes used for forming the three-dimensional grid model, and the at least one type of surface recognition result at least comprises a side face recognition result; based on the at least one type of surface recognition result, combining at least one cylinder-like model, the cylinder-like model being a model at least comprising a side surface structure; performing model expansion on each cylinder-like body model to obtain at least one model expansion result corresponding to the at least one cylinder-like body model; and determining at least one model expansion result as an expansion result of the three-dimensional grid model. According to the invention, the model expansion efficiency can be improved.

The invention discloses an image alignment method based on illuminance constraint and grid deformation. The image alignment method is used for accurately aligning overlapped images. The method comprises the steps of initializing a color mapping model, jointly optimizing grid coordinates and the color mapping model, and optimizing and adjusting model parameters, estimating the model parameters in the grid deformation steadily; and finally, calculating a local homography transformation matrix in each grid according to the corresponding relationship between the coordinates of the grid points before and after deformation, and realizing accurate alignment between the images by utilizing an image deformation and texture mapping technology. According to the invention, on the basis of the traditional geometric constraint, the illumination constraint is further utilized, so that the alignment algorithm can process scenes with not rich textures. In addition, color mapping model expansion is carried out on a traditional image deformation framework, so that the grid deformation-based image alignment algorithm can realize accurate alignment between images with significant color differences.

The invention discloses a bridge abutment knocking-off structure, which comprises a bridge body and a bridge abutment body, and is characterized in that a knocking-off block is arranged on the top surface of the bridge abutment body, an anchoring steel bar is arranged between the knocking-off block and the bridge abutment body in a penetrating way for connection and position limitation, and a bridge end bracket is fixedly arranged on the end surface of the bridge body in a position positioned between the bridge body and the knocking-off block. The bridge abutment knocking-off structure has the advantages that (1) through the arrangement of the bridge end bracket, a large seam between the bridge end and a bridge abutment breast wall is reduced to an ordinary seam, an ordinary model expansion and contraction device is installed, the normal operation and small earthquake requirements are met, and the engineering manufacturing cost is reduced; (2) in strong earthquakes, the bridge end bracket pushes out the knocking-off block, the larger gap between the bridge end and the bridge abutment breast wall meets the relative displacement requirement of the bridge end and the bridge abutment breast wall in the strong earthquakes, the bridge abutment safety is ensured, the requirement of emergence vehicle passing after the earthquakes can be met, the normal use of a bridge can be recovered only through restoring the knocking-off block, the expansion and contraction device and the pavement behind the abutment, and the restoring cost is low.

The invention discloses a method for obtaining skin deformation based on subdivision model expansion. The method comprises the following steps: pasting mark points on key parts on the surface of a human body; obtaining human body lower limb point cloud data; human body point cloud data of all actions (including standing) are processed, complete human body models are obtained, contour line editing is carried out on all the models along mark points, then curved surface processing is carried out, the processed dynamic and static models are imported into three-dimensional modeling software UG NX at the same time to be flattened, and comparison is carried out. The human body model is curved and then expanded for comparison, the operation is simple, the method is rapid and accurate, the skin deformation rule of each part of the human body can be clearly and intuitively expressed, and the working efficiency is improved; the method is combined with a method for calculating the skin deformation by measuring the physical properties such as the size length and the area of the human body model, so that the acquisition of the skin deformation rule is more scientific and perfect, and a foundation is laid for the scientific setting of the dynamic looseness in the clothing plate making process.

The invention provides a model expansion method and device and a readable storage medium. The model expansion method comprises the following steps: collecting a model programming template; and compiling the model programming template by adopting an import file mechanism based on the application programming interface list according to a model expansion requirement to obtain an expanded model. According to the technical scheme, programming is carried out on the model programming template, and the usability of programming is improved. The application programming interface list is provided, a file importing mechanism is adopted, the processes of system development, test deployment, online and the like do not need to be carried out, and the cost is effectively reduced. The system security implicit is removed, the system security is ensured. The system risk is reduced while the use is convenient through an import file mechanism.