77 results about "Component modeling" patented technology

Connection objects or other such data structures facilitate establishing and configuring connections between objects that model components in a process control system. A first set of data structures (e.g. the object connection type structures) identify valid types for component-to-component pairings and the respective roles of each component in the pairing (e.g., parent or child, source or sink). A second set of data structures (e.g., the parameter connection type structures) supply similar information for parameter-to-parameter connections. Together, these data structures can be used, for example, to validate component-to-component connections suggested by the user and to automatically configure parameter-to-parameter connections. Actual connections, both at the component or parameter level, are reflected using parameter overrides within the parameterized object model—with which the connection objects are constructed.

Graphical representations of operational process control data associated with monitored processes is displayed within the context of the geographical locations at which the processes operate, and in a manner as to model individual components of the processes.

A system generates optimal global set points for an environmental management system. The system comprises a system model for modeling components of a thermal plant, an objective function for modeling a parameter of the thermal plant, and an optimization engine for optimizing the parameter modeled by the objective function. The system model is coupled to an input data collector for receiving building data and weather data corresponding to a particular site. The system model includes models for thermal plant system components that may be implemented using classical models or artificial intelligence models. Classical models are those models that are implemented using linear programming, unconstrained non-linear programming, or constrained non-linear programming methodologies. The artificial intelligence models are those models that may be implemented using a fuzzy expert control system with crisp and fuzzy rules, genetic algorithms for optimization, or neural networks.

A method for reducing vibration of a drilling tool assembly is disclosed. The method includes modeling the drilling tool assembly based on input parameters, simulating a vibration of a drill string coupled with a vibration of a drill bit, determining an initial total vibration from output parameters generated by the simulation, determining a location for at least one vibrational control device based on the initial total vibration to reduce the initial total vibration, and disposing the at least one vibrational control device on the drill string at the determined location.

A method for modeling components of a stream processing application, includes: defining an input message pattern of a processing element, wherein the input message pattern includes variables representing data objects that must be included in a message input to the processing element, and a graph pattern that semantically describes the data objects that must be included in the message input to the processing element; and defining an output message pattern of the processing element, wherein the output message pattern includes variables and new data objects, the variables and new data objects representing data objects that must be included in a message output from the processing element, and a graph pattern that semantically describes the data objects in the message output from the processing element.

Graphical representations of operational process control data associated with monitored processes is displayed within the context of the geographical locations at which the processes operate, and in a manner as to model individual components of the processes.

The invention provides a power system three-dimensional device scene modeling method which comprises the following steps: establishing all sorts of three-dimensional device assembly models in the three-dimensional scene by adopting the virtual technology; uploading the three-dimensional device assembly models into a three-dimensional assembly library through a client side; accessing to a server side through the client side, and acquiring the three-dimensional device assembly models needed by the three-dimensional scene modeling from the three-dimensional assembly library; building a three-dimensional device scene model by adopting the three-dimensional device assembly models; guiding the built three-dimensional device scene model into a power system simulating system, and carrying out simulating training and visual display or virtual test. Because the modeling process comprises the assembly modeling stage and the scene assembling stage, the scene modeling difficulty is reduced, the scene modeling efficiency is improved, the models have high reusability, particularly the team can carry out modeling cooperatively, the position of the device assembly is accurate in the virtual scene, the later maintenance workload is low, and the later maintenance process is simple and not difficult.

A method for modeling a component of an information processing application, includes: defining an applicability condition of a component, wherein the applicability conditions includes variables representing objects that must be included in a pre-inclusion state and a graph pattern that semantically describes the objects that must be included in the pre-inclusion state, wherein the pre-inclusion state is a state against which the applicability of the component for inclusion in a processing graph is evaluated; and defining an inclusion effect of the component, wherein the inclusion effect includes variables representing objects that must be included in a post-inclusion state and a graph pattern that semantically describes the objects that must be in the post-inclusion state, wherein the post-inclusion state is a state resulting from inclusion of the component in the processing graph.

The invention discloses a temporal difference radar interference method applicable to large-gradient ground surface settlement monitoring. According to the whole technical scheme, the method comprises the steps of short-time base line difference interference pattern screening, discrete point phase unwrapping, shape changing component modeling and calculation based on short-time base line difference interference patterns, shape changing component reliability testing, difference interference pattern phase gradient correction, iteration of the processes so as to ensure correctness of shape changing component calculation, and shape changing time sequence modeling and calculation based on corrected difference interference patterns. The problem that shape changing phase ambiguity calculation is difficult or fails due to the fact that shape changes and phase gradients are large in an original temporal difference radar interference technology is solved, finally the purpose of correctly extracting the large-gradient ground surface shape changing speed and the shape changing time sequence is achieved, the effect of decreasing the number of synthetic aperture radar images needed by large-gradient shape changing modeling and calculation is achieved, and the temporal difference radar interference application economic cost is reduced.

Provided is a detecting apparatus for detecting one or more anomalies of an operating body. The detecting apparatus includes a processor communicatively coupled to a dividing unit, a model learning unit, a difference calculating unit, and an anomaly detecting unit. The dividing unit divides a data sequence corresponding to an operation of the operating body into a plurality of divided data sequences in a time direction. The model learning unit learns each of the plurality of divided data sequences according to a regression model in the time direction, and calculates a model component modeling each of the divided data sequences. The difference calculating unit calculates a difference component indicating a difference between each of the plurality of divided data sequences and their corresponding model component. The anomaly detecting unit detects one or more anomalies of the operating body based on the calculated difference components.

A method and apparatus for producing predictive performance and capacity information employing a type of factory to reduce the ongoing cost of providing simulation models to answer questions raised by the various business entities is provided. To achieve this, a continual process for providing on-going performance information is provided. The core concept is the development and long-term reuse of component models to create other, more broadly scoped performance models. This requires the implementation of standard simulation model constructs to facilitate reuse, processes for the development of models and their use by clients, and a stable yet flexible repository for component models. The invention comprises processes, standards, templates, and software tools that implement a performance service that consists of the long term maintenance of predictive performance models for repeated use by lines of business to provide capacity planning information.

A method for modeling a component of an information processing application, includes: defining an applicability condition of a component, wherein the applicability conditions includes variables representing objects that must be included in a pre-inclusion state and a graph pattern that semantically describes the objects that must be included in the pre-inclusion state, wherein the pre-inclusion state is a state against which the applicability of the component for inclusion in a processing graph is evaluated; and defining an inclusion effect of the component, wherein the inclusion effect includes variables representing objects that must be included in a post-inclusion state and a graph pattern that semantically describes the objects that must be in the post-inclusion state, wherein the post-inclusion state is a state resulting from inclusion of the component in the processing graph.

Automatic deployment of an information technology (TT) system instance having hardware and software components. An application model of the software components is generated based on use cases and is associated with functional and non-functional requirements. An infrastructure model of the hardware components is generated based on the application model. The same software component modeling language represents both the application and infrastructure models. A markup language computer file is generated to include a design of the IT system instance and instructions for accessing library-stored assets that specify the hardware and software components. The computer file is exported to a deployment tool for automatic deployment of the IT system instance based on carrying out the instructions. In one embodiment, the impact of a proposed change is identified and managed in real time prior to a deployment of the proposed change.

A broadband loaded antenna and matching network with related methods for design optimization are disclosed. The loaded antenna structures may preferably be either monopole or dipole antennas, but the particular methods and techniques presented herein may be applied to additional antenna configurations. The load circuits positioned along an antenna may comprise parallel inductor-resistor configurations or other combinations of passive circuit elements. A matching network for connecting an antenna to a transmission line or other medium preferably includes at least a transmission line transformer and a parallel inductor. Various optimization techniques are presented to optimize the design of such broadband monopole antennas. These techniques include implementation of simple genetic algorithms (GAs) or micro-GAs. Component modeling for selected components may be effected through either lumped element representation or curved wire representation. Measured results are presented to ensure that certain design criteria are met, including low voltage standing wave ratio (VSWR) and high gain over a desired frequency band.

The invention provides a road and building simulation modeling method based on real road surface data, the method comprising the following steps: S10, establishing a road network simulation model by using aerial photograph images; S20, generating building simulation models along the road by aerial survey data, and matching the building simulation models with the road network simulation models; S30, importing the digital elevation model data, so that the simulation model of the road network and the building conforms to the digital elevation model, and simulating the undulation condition of thereal pavement; S40, optimizing the overall appearance ratio of the model with reference to the real image to obtain the final model. According to the idea that the model attribute information groupware is modeled and matched with the space, by means of multi-source data fusion, the road model and the building model along the road are combined and matched with reference to the actual pavement, so that the model can show more details of the pavement, can restore the shape of the real street scene, undulation and other details, and can be better used in driving perspective simulation and other application scenes.

An inertial navigation system includes a navigation component, such as an inertial measurement unit, a processor in communication with the navigation component, and a filter embedded in computer code implemented within the processor. The filter includes a model of the navigation component, and one or more parameters of the model are configured after startup of the inertial navigation system based upon performance characteristics of the individual navigation component included in the inertial navigation system.

A simulation platform design method based on a Power PC SoC framework comprises the following steps: instruction set simulation, using QEMU virtual machine dynamic binary system translation technology as an instruction set simulation device of the Power PC SoC framework simulation platform to carry out instruction set simulation; modeling key assemblies in the simulation platform, accurately modeling main equipment modules and slave equipment modules according to a System C transaction level modeling method, and designing the Power PC SoC framework simulation platform with complete functions; interruption design, realizing an interruption system of the simulation platform. The novel method can realize software and hardware cooperation simulation, can reduce design risks and error correction cost, can accelerate product design process, reduces product market period, and instruction set expansion and IP module functions can provide certain guide meanings for hardware development.

The invention provides a describing and modeling method of general simulation assemblies. The describing and modeling method is applied to the system simulation field. According to the describing and modeling method of the general simulation assemblies, simulation application builders can develop and accumulate reusable simulation assemblies, assemble the simulation assemblies under the condition that coding is not performed according to different application requirements and accordingly establish a simulation application system which meets the requirements rapidly. Compared with a system which is built in a mode that the reusable assemblies are not utilized, the simulation system can improve the quality and the development efficiency due to the reusable assemblies.

The invention discloses a logging curve prediction method based on modal decomposition reconstruction and a depth LSTM-RNN model. The logging curve prediction method comprises the steps: utilizing CEEMD to decompose logging curve data into limited intrinsic mode function IMF components and residual RES components which have local characteristics and are different in frequency; carrying out fluctuation degree detection on each component by a run-length detection method, and reconstructing CEEMD decomposition items with similar fluctuation frequencies into three new components with typical characteristics, namely a high-frequency item, a low-frequency item and a trend item; performing data normalization processing on the reconstructed new component and dividing training and test data; respectively establishing a depth LSTM-RNN model for each component and carrying out network training by utilizing the training data; and using the trained model to predict a missing or distorted logging curve, and finally reconstructing and reversely normalizing prediction results of the three components to obtain a logging curve prediction result. According to the logging curve prediction method, thenumber of prediction component modeling is reduced, and the prediction precision and speed are improved, and the simplicity and practicability are high, and the missing or distorted logging curve canbe predicted more accurately and effectively.

The present invention refers to an apparatus, a method and a computer program product for modelling causality in a flow system, and more specifically for modelling variable causality in the flow system. The apparatus 100 comprises a data storage means 110 configured to store model element data related to modelled components of the flow system, a causal rule storage means 120 configured to store a plurality of causal relations determining the causal relationships between model elements. The apparatus 100 comprises a state determination unit 130 arranged to receive a status signal from the flow system, identify the component related to the received status signal, identify a model element modelling the identified component and determine an operating state of the identified component. Further, the apparatus comprises a processing means 140 configured to activate or deactivate a causal relation related to the identified model element and dependent on the determined operating state.

An embedded assembly modeling and testing method based on an expansion interface automata model relates to the field of software testing and testing automation based on a model and is applicable to testing of an embedded assembly. The embedded assembly modeling and testing method is characterized in that the automata model with constraint conditions is used for description aiming at assembly interface operation, data and behaviors, and a testing case set is generated on the basis of the graph searching and constraint solving technology. The embedded assembly modeling and testing method includes: (1) constructing the expansion interface automata model of the embedded assembly and (2) defining a testing coverage rate goal on the basis of the automata model and generating a normal function testing case and a robustness testing case which achieve the testing coverage rate goal.

The invention relates to a high-rigidity and light-weight sensitivity analysis method for a passenger bus skeleton and belongs to the field of design of a passenger bus body. The method comprises the steps of parameterization assembly modeling of a passenger bus skeleton structure, static and dynamic rigidity defining and sensitivity analysis of the static and dynamic rigidity on the whole bus weight. The method is different from other rigidity and sensitivity analysis methods on the other bus body structures; the static and dynamic rigidity sensitivity of the method is the derivative of the whole bus weight, the bus body weight is reduced while the rigidity is increased and the light weight target is realized; in the traditional method, the static and dynamic rigidity is subjected to differentiation for the section size, and the bus body rigidity is improved while the bus body weight is not reduced. In addition, the invention adopts the adjoint variable sensitivity analysis method, and the calculated amount is greatly reduced, so a large-sized passenger bus body can be designed and the method has important guide action for the design technology of the passenger bus body.

A system and method are provided for modelling a hardware component of a data processing apparatus in order to generate an output identifying a value of an observable property of the hardware component. The system comprises a component model for modelling aspects of the hardware component, and feature extraction logic for extending the component model to cause the component model when executing to output one or more features identifying execution behaviour of the component model. A statistical model is then arranged to receive the one or more features output by the component model, and to generate the output dependent on said one or more features. In accordance with the invention, it is observed that although the component model may not explicitly model features that can be used to effectively predict values of the observable property, features that a statistical model depends on may still be captured in the underlying logic and implementation of the component model, and accordingly by extracting features identifying execution behaviour of the component model, this can provide a suitable input to the statistical model, thereby providing a simple and effective technique for producing values of the observable property of the hardware component.

The invention relates to a recognition method for components of Chinese character pictures and belongs to the field of image processing and pattern recognition. The method includes firstly pre-processing Chinese character component pictures with specific fonts, performing skeleton extracting, forming initial sections according to endpoints and intersections which are detected out, and merging some sections in an artificial interactive mode; next, performing statistical modeling on the marked sections and describing directional information of the sections by using a four-dimensional vector; then constructing section neighbor relations to complete the component modeling process according to the maximum spinning tree principle; for an input Chinese character, firstly decomposing the character into sections, then generating a group of section sets with the maximum similarity by contrasting each component in a library, finally obtaining recognition results of components of the input Chinese character through the optimum selection strategy, namely, obtaining the optimum solution through solution of the variety knapsack problem. Local features are introduced, the optimum combination strategy is adopted, the complete recognition method for the components of the Chinese character pictures is formed, and the recognition rate can be improved effectively.