42results about How to "Address dynamics" patented technology

The invention discloses a data sharing exchange model and a method based on cloud computation. The model comprises a data sharing service module, a data exchange service module, a management service module, an enterprise service bus, a front-end exchange database and a front-end interchanger, wherein the data sharing service module is used for realizing distributed heterogeneous data resource sharing; the data exchange service module is used for realizing a heterogeneous data exchange function; the management service module is used for realizing sharing exchange and system management; the enterprise service bus is used for realizing service registration and management; the front-end exchange database is used for realizing an intermediate storage logic information database which is established for information exchange; and the front-end interchanger is used for realizing the function of unified exchange output and input ports of exchange nodes. The method comprises the steps of constructing a data sharing exchange service system based on SaaS (Software as a Service) to share data which is stored in a business database in a distributed way and providing exchange request submission and approval service; using the enterprise service bus to conduct unified management on service and establishing a model of an exchange service business process by virtue of management service to realize dynamic combination of inter-business service; and using the front-end exchange database to conduct exchange, storage and forwarding, and pushing the data to target nodes through the front-end interchanger.

The invention discloses a reconfigurable multi-source data importing method in an ERP system. The reconfigurable multi-source data importing method includes the following steps that importing templates are configured according to data needing to be imported; the data which are represented in an EXCEL format, or a CSV format, or an XML format or other formats and provided by a user are converted into intermediate processing files through a standard interface; the corresponding importing templates are matched according to the types of the imported data; information after the matching is carried out is updated according to matching information; updating of associated information is finished according to associated information configuration and importing mode configuration; according to configured checking specifications, the imported data are checked item by item; after passing the check, the data enter the intermediate processing process of data to form an intermediate transition table of the imported data; the data in the transition table are imported into a target table according to the configured data importing mode. The multiple data importing modes are provided in a reconfigurable form, the flexibility and the dynamism needed by data importing are achieved, and a checking rule base provides data integrity and validity rules in different modes.

The invention discloses a self-adaptive hunting device using multiple robot pursuers to hunt a single moving target and a method. The method comprises multiple-stage dividing of a hunting process, a pursuing policy based on a bionic neural network, angular relationship surrounding and multiple virtual potential points. According to the step of multiple-stage dividing of the hunting process, multiple-stage modeling is carried out for the hunting process; a hunting task is divided into four stages of searching, pursuing, surrounding and arresting; and policies corresponding to four stages are used for controlling. According to the pursuing policy based on the bionic neural network, a bionic neural network method used in a multiple-robot system is migrated to a hunting environment, and hunting guide is carried out on multiple robot pursuers. According to angular relationship surrounding, an angular relationship is used to adjust the movement direction of the pursuers. According to multiple virtual potential points, multiple virtual potential points are arranged to form an arresting formation, and the final hunting task is completed. According to the invention, the hunting process is divided into different stages; in the pursuing stage, the bionic neural network method is used to solve uncertainty, dynamics and instantaneity of an environment; and efficient obstacle avoidance and hunting are completed.

The invention discloses a TPM-based multi-instance dynamic remote attestation method which belongs to the field of information security technology. The method comprises the steps as follows: a) an RAI instance is started: the TPM measures the RAI instance and issues an initial attestation certificate for the RAI instance; the remote relying party of the RAI instance obtains and authenticates the initial attestation certificate, if the authentication is passed, the link between the RAI instance and the remote relying party of the RAI instance is established; b) if the component of the RAI instance is updated, the TPM re-measures the RAI instance and issues an updating attestation certificate; the remote relying party of the RAI instance obtains and authenticates the updating attestation certificate; if the authentication is passed, the link is maintained; and c) the step b) is repeated until the RAI instance is closed and the link is disconnected; meanwhile, all the attestation steps of a plurality of RAI instances intersperse with each other for forming a TPM attestation chain. Compared with the remote attestation methods of other trusted computing platforms, the method is characterized by the dynamic attestation of platform status, the concurrent attestations of multiple network programs, and anti-replay attack, etc.

The invention discloses a fault-tolerant control method based on a hidden Markov model. On-line fault recognition is carried out by utilizing the strong dynamic process time sequence modeling capability and the time sequence mode classification capability of the hidden Markov model, and the diversity factor between PDFs (Probability Density Function) in a predictable state is improved through introduction of Hellinger Distance, so that the accuracy and reliability of fault recognition are improved. According to the method, higher reliability is achieved for ensuring normal operation of an industrial process under a condition that a fault occurs in a strong dynamic industrial process.

The invention relates to an active-disturbance-rejection controller for a high-voltage circuit breaker linear motor operation mechanism. The active-disturbance-rejection controller is characterized in that the controller comprises an active-disturbance-rejection position module and an active-disturbance-rejection speed module. The active-disturbance-rejection position control module is connected in series with the active-disturbance-rejection speed control module; the output of the active-disturbance-rejection position control module serves as the input of a given speed of the active-disturbance-rejection speed control module; and the active-disturbance-rejection position control module and the active-disturbance-rejection speed control module are respectively formed by a tracking differentiator, a nonlinear extended state observer and a nonlinear error feedback control law. The nonlinear active-disturbance-rejection technology is applied to the control of the high-voltage circuit breaker operation mechanism, thereby improving response speed, reducing impact force and prolonging electrical life of contacts; the system is designed into a three-closed-loop system, wherein the position loop and the speed loop adopt the active-disturbance-rejection control technology, so that thrust ripple disturbance and friction disturbance can be suppressed in real time, the influence of end effect on motor output is reduced, and the conflict between the operation mechanism dynamic property and overshoot performance is solved.

The invention provides an intermittent process fault detection method based on a double-weight multi-neighborhood preserving embedding algorithm, and the method comprises the following steps: (1) collecting intermittent process data of a plurality of batches under normal working conditions, and forming three-dimensional training data X; (2) expanding the acquired three-dimensional training data Xinto two-dimensional data and performing standardization processing; (3) establishing a double-weight multi-neighborhood preserving embedding model, solving a mapping transformation matrix A, and obtaining a dimension reduction data matrix Y according to Y = ATX; (4) establishing statistics of a Hutlin statistical model T2 and a square prediction error statistical model SPE under normal data, andsolving control limits of the statistics; (5) collecting online intermittent process data to form test data Xtest, and carrying out expansion and standardization processing on the test data Xtest; (6)projecting the test data through the mapping transformation matrix A to obtain a dimension reduction data matrix Ytest; and (7) solving the statistical magnitude T2 of the Hutlin statistical model and the statistical magnitude SPE of the square prediction error statistical model of the test data, and judging whether a fault occurs.

The present invention provides a simplified boost type electric vehicle composite power supply structure and a control method thereof. The simplified boost type electric vehicle composite power supply structure comprises a lithium battery, a super capacitor, MOSFETs, a current-limiting diode, an inductor and a capacitor. When the demand power of an electric vehicle is positive, according to the SOC and the output voltages of the lithium battery and the super capacitor, a composite power supply forms a Boost circuit structure, and the duty ratio of the MOSFET SW1 or SW2 is adjusted; and when the demand power of the electric vehicle is negative, the composite power supply forms a Buck circuit structure, and the duty ratio of the MOSFET SW3 is adjusted, thereby realizing the braking energy recovery of the lithium battery and the super capacitor. According to the present invention, the multimode work of the electric vehicle on a general working condition can be satisfied, and the composite power supply simplifies the structure of a cascaded DC-DC converter, so that the energy consumption of the composite power supply is reduced, the energy conversion efficiency is improved, and a control strategy is simpler.

The invention relates to a low noise GPS (Global Positioning System) carrier wave tracking method based on an RLS (Recursive least square filter). The low noise GPS carrier wave tracking method comprises the following steps of: measuring an instantaneous phase difference of a local carrier wave and a tracking satellite by a carrier wave tracking loop by utilizing a table look-up type second quadrant arc tangent phase discriminator; introducing the RLS to filter measurement noises; meanwhile estimating a frequency difference according to phase difference variation; utilizing the frequency difference and the phase difference as frequency discrimination input and phase discrimination input of a loop filter with a second order lock frequency loop assistant in a three-order phase locking loop; filtering by the loop filter to output a carrier wave control adjustment variable with high precision and low noise, and correspondingly adjusting carrier wave NCO (Numerical Control Oscillation) to control the local carrier wave so that a receiver keeps phases and frequencies of the local carrier and a tracking satellite carrier wave consistent. In the invention, the low noise GPS carrier wave tracking method based on the RSL ensures that the GPS carrier wave tracking loop can work stably under the condition of low signal to noise ratio and certain dynamic state, keeps the phase not to overturn or skip cycles and ensures the carrier wave tracking precision.

The invention discloses a method for identifying a fault of a variable-pitch bearing of a wind turbine generator set. The method comprises the steps of: 1, offline modeling, and training sample set acquisition, which are implemented by acquiring data containing normal operation working condition data and variable-pitch bearing faulty working condition data of the wind turbine generator set, performing variable coefficient analysis on the training set data, selecting variables sensitive to the fault of the variable-pitch bearing as input variables of a hidden Markov model (HMM), and training the hidden Markov model; 2, online data identification, which is implemented by carrying out online identification, namely, still adopting the variables selected by the training set as observation variables of the hidden Markov model, and performing variable-pitch bearing fault identification on the online data by means of the hidden Markov model. The method has higher precision in identifying the fault of the variable-pitch bearing of the wind turbine generator set.

The invention discloses a product configuration method and system supporting a multilevel platform. According to the method, an enterprise-level product platform main structure is established according to division of a product platform in an enterprise; all sub-platform main structures and a bottommost product family main structure are sequentially established on the basis of the enterprise-level product platform main structure; according to a product configuration demand, a variable condition is defined for a module selected by the product family main structure; according to the product configuration demand, whether a sub-module meeting the variable condition exists in the product family mains structure is judged, and whether the sub-module is associated with the variable condition is judged; the product platform main structure is traversed according to a product configuration demand table, assignment is performed on node variables, and a constraint relation and the module not meeting the demand are removed till all the variables are subjected to assignment; and finally a product variable general bill of materials (BOM) containing the variable condition is screened out, instance components are used to replace corresponding nodes in the product variable BOM, an engineering general BOM is formed, and a design result is output.

The invention discloses a warehouse construction method and system based on a PBFT block chain technology, and the method comprises the steps that an intelligent contract is formulated in a block chain network, and a node is elected; other nodes vote the candidate nodes; a user signs a part needing consensus, sends the signed part to a network, broadcasts a consensus request, judges after receiving the consensus request by a certain node, rebroadcasts a transaction if the consensus request is met, and puts the transaction into a consensus cache sequence; after the system initializes consensus,the nodes enter a consensus process, a main node of the PBFT encapsulates and signs consensus information, the main node broadcasts the information in the whole network, and an auxiliary node judgesthe information; if the information is valid, a 'preparation' stage is entered, the information is packaged and signed, and the information is broadcasted to the whole network; and after the main nodedoes not respond within the specified time or has reached the consensus, view switching is performed to enter the next round of consensus to generate a new block. In the embodiment of the invention,the problems of opaque information, low safety performance and low throughput in the supply chain are effectively solved.

The invention discloses a traffic congestion prediction method and system, relates to the technical field of traffic, and solves the problems of slow training speed, low prediction accuracy, and diversity and dynamics of the global road network in the traffic congestion prediction in the prior art. A traffic congestion prediction method comprises the following steps of dividing the traffic data ofthe whole road network into a plurality of clustering cluster sub-models according to the feature of the road segment attribute; inputting the feature data of each clustering cluster sub-model into different transfinite learning machine predictors respectively to obtain a predicted congestion value at a certain time point corresponding to each clustering cluster sub-model; and integrating the predicted congestion values of each clustering cluster sub-model at each time point into an integral predicted congestion value of the whole road network.

The invention discloses an asset information control method in a distributed infrastructure system. The method comprises the following steps of establishing an RDF model and collecting original data of a system asset; instantiating the original data of the asset in the system and carrying out data association on asset instances in acquired data sets; through calculating a similarity of asset instances among the data sets, acquiring all the asset instances corresponding to the same asset, and carrying out data association; and according to a data association relation, merging the data sets and generating an RDF graph. In the invention, a lot of data from a plurality of data sources is fused, a unified formal is reached and the RDF graph is used to describe the distributed infrastructure system so that problems that a traditional registration mode is not suitable for a large scale system and information is limited are solved; and abundant and various information is provided for asset management and data bases are provided for subsequent safety management and other applications. The asset information control method in the distributed infrastructure system can be widely applied to the infrastructure management control field.

The invention discloses a boiler flue gas denitrification control method based on a self-adaptive fuzzy PID algorithm. The implementation processes comprises the following steps of collecting an actual measured value of the nitrogen oxide at a flue gas outlet, and calculating a deviation value and a change rate of the nitrogen oxide at the flue gas outlet; determining membership functions of nitrogen oxide deviation, a deviation change rate, a proportion change value, an integral change value and a differential change value; outputting a new fuzzy set membership function according to a fuzzy control rule, calculating the proportional change value, the integral change value and the differential change value according to the fuzzy set membership function, and adjusting corresponding parameters in the PID in real time to obtain new PID parameters; and controlling the ammonia spraying amount according to the new PID parameters. According to the denitrification control method disclosed by the invention, the PID control parameters can be adjusted by adopting a fuzzy control algorithm, on one hand, the condition that the content of nitrogen oxide at the outlet exceeds the standard irregularly can be avoided; on the other hand, the usage amount of ammonia gas can be more reasonably and efficiently controlled.

The invention provides a password authentication system which comprises a system server (1) used for storing the system information and carrying out identification password authentication and an authentication password generator (2) used for generating an identification password. The system server (1) comprises a system interface (11) and a system database (13), an authentication module (12) used for reading the user identification password and the additional code submitted by the system interface (11) and customizing different generating modes by the written parameters in the authentication password generator (2). The authentication password generator (2) comprises an identification password register (24), a clock (23), a password generating module (22), a key input module (25) and a display module (21); the authentication password generator (2) adopts the X arithmetic which is the same as the system server (1) to generate the identification password; the X arithmetic can be different in each authentication password generator (2); the identification password is a numeric string.

The invention relates to an intelligent networked automobile system cooperative control method based on TPZN, which belongs to the field of unmanned driving, prediction and control strategies, and realizes functions by fusing Z language formal description and a TPN model into a new TPZN model, and can effectively solve the problems of state explosion caused by numerous node devices of a time Petrinetwork and insufficient dynamic capability and real-time performance of a Z frame. The established TPZN formal model for intelligent networked automobile system cooperative control can realize cooperative control of intelligent networked automobile system information security transmission in a multi-source heterogeneous complex environment. And the driving safety and reliability of the intelligent networked automobile are improved.

The invention discloses a decoupling multi-access method based on an evolutionary game theory in an ultra-dense network. According to the invention, all users are regarded as a group, and the problemof decoupling multi-access in an ultra-dense network is solved by adopting an evolutionary game theory, i.e., the users can access a plurality of different base stations in uplink and downlink. In thegame process, the strategy of the player (namely the user) is the access selection which can be taken by the user in the uplink and downlink in the network. On the premise of ensuring the average benefit of the group, each user dynamically selects an access strategy with the aim of maximizing the access benefit of the user. In order to obtain the stable state of the group, an evolutionary game-based algorithm is provided, and the complexity of the decoupling multi-access process is effectively solved.

The invention discloses an efficient and fair dynamic spectrum allocation method which is applicable to interactive cognitive radio networks and comprises the following steps: on the basis of cooperative differential game theory, dividing the interactive cognitive radio network into different alliances and establishing an alliance-competition type architecture; setting that the interactive cognitive radio network has a plurality of cognitive users as well as the objective function and the payoff function of each cognitive user; and solving the objective function and the payoff function. The invention can effectively relieve the shortage of spectrum, improve the utilization ratio of spectrum, and take account of the fairness and the efficiency of spectrum use.

According to the invention, considering that unknown faults which are not considered in the operation process of a wind turbine generator are also likely to occur in addition to known faults, a wind generating set variable pitch bearing fault identification method based on an improved hidden Markov model is disclosed, comprises offline modeling and online identification, in the offline modeling step, a threshold statistic is defined based on the hidden Markov model, and the threshold statistic is used for identifying unknown faults. According to the method, a new threshold statistic is introduced, so that the probability that other unknown faults are mistakenly recognized as the variable-pitch bearing faults can be greatly reduced when online recognition is carried out on the variable-pitch bearing faults of the wind generating set. Therefore, compared with other existing methods, due to the fact that the time sequence of the data and the occurrence of unknown faults are fully considered, the method has higher accuracy for identifying the variable pitch bearing faults of the wind generating set.

The invention provides a dynamic password authentication system which comprises a system server (1) used for storing system information and identifying an identity password, and an authentication password generator (2) used for generating the identity password. The system server (1) comprises a system interface (11); a system database (13); an authentication module (12) used for reading the user identity password and an additional code submitted by the system interface (11) and customizing different generation modes based on different parameters written by users in the authentication password generator (2). The authentication password generator (2) comprises an identity password register (24), a clock (23), a password generating module (22), a key input module (25) and a display module (21); the authentication password generator (2) adopts the X arithmetic which is the same as the system server (1) to generate the identity password; the X arithmetic can be different in each authentication password generator (2); the identity password is a numeric string.

The invention provides a steel catenary riser risk assessment method and device based on information fusion and a medium, and the method comprises the steps: building an identification frame in advance according to a fault mode of a steel catenary riser, and installing data sensors at fault collection points respectively to collect fault signals; then, multi-sensor data is preprocessed, and a corresponding basic probability distribution function is generated; a dynamic reliability index of multiple sensors is obtained through construction of an intuitionistic fuzzy multi-attribute decision model, on this basis, in a multi-evidence body information fusion algorithm of an improved mixed similar reasoning theory model (mixed DSm model), the conflict of evidences is reduced through solved focal element credibility, and the reliability of the multi-evidence body information fusion algorithm is improved. And the risk assessment of the steel catenary riser is realized according to the information fusion result. According to the method, on the basis of the sensor data condition of the existing riser monitoring system, high-efficiency, high-recognition-rate and high-adaptability risk assessment of the steel catenary riser is realized.

The invention relates to a low noise GPS (Global Positioning System) carrier wave tracking method based on an RLS (Recursive least square filter). The low noise GPS carrier wave tracking method comprises the following steps of: measuring an instantaneous phase difference of a local carrier wave and a tracking satellite by a carrier wave tracking loop by utilizing a table look-up type second quadrant arc tangent phase discriminator; introducing the RLS to filter measurement noises; meanwhile estimating a frequency difference according to phase difference variation; utilizing the frequency difference and the phase difference as frequency discrimination input and phase discrimination input of a loop filter with a second order lock frequency loop assistant in a three-order phase locking loop; filtering by the loop filter to output a carrier wave control adjustment variable with high precision and low noise, and correspondingly adjusting carrier wave NCO (Numerical Control Oscillation) to control the local carrier wave so that a receiver keeps phases and frequencies of the local carrier and a tracking satellite carrier wave consistent. In the invention, the low noise GPS carrier wave tracking method based on the RSL ensures that the GPS carrier wave tracking loop can work stably under the condition of low signal to noise ratio and certain dynamic state, keeps the phase not to overturn or skip cycles and ensures the carrier wave tracking precision.

The invention discloses an efficient and fair dynamic spectrum allocation method which is applicable to interactive cognitive radio networks and comprises the following steps: on the basis of cooperative differential game theory, dividing the interactive cognitive radio network into different alliances and establishing an alliance-competition type architecture; setting that the interactive cognitive radio network has a plurality of cognitive users as well as the objective function and the payoff function of each cognitive user; and solving the objective function and the payoff function. The invention can effectively relieve the shortage of spectrum, improve the utilization ratio of spectrum, and take account of the fairness and the efficiency of spectrum use.

The invention discloses a power system machine room temperature control coordination control method based on an optimal working point, which comprises the following steps: step 1, storing fan frequency, chilled water valve opening and load parameters under the optimal working point corresponding to each enthalpy value of a system into a database; 2, calculating an air enthalpy value at the front end of a heat exchanger after system pretreatment is finished; step 3, calculating a tail end load; step 4, querying the database according to calculation results of the step 2 and the step 3, and extracting optimal system operation parameters; and step 5, updating the optimal operation parameters. The technical problems that it is difficult to enable an air conditioner air system and a water system to have good dynamic performance and steady-state performance in the prior art and the like are solved.

The invention discloses a reconfigurable multi-source data importing method in an ERP system. The reconfigurable multi-source data importing method includes the following steps that importing templates are configured according to data needing to be imported; the data which are represented in an EXCEL format, or a CSV format, or an XML format or other formats and provided by a user are converted into intermediate processing files through a standard interface; the corresponding importing templates are matched according to the types of the imported data; information after the matching is carried out is updated according to matching information; updating of associated information is finished according to associated information configuration and importing mode configuration; according to configured checking specifications, the imported data are checked item by item; after passing the check, the data enter the intermediate processing process of data to form an intermediate transition table of the imported data; the data in the transition table are imported into a target table according to the configured data importing mode. The multiple data importing modes are provided in a reconfigurable form, the flexibility and the dynamism needed by data importing are achieved, and a checking rule base provides data integrity and validity rules in different modes.

The invention discloses a fuzzy control-based high-dynamic global positioning system (GPS) receiver carrier tracking loop, which belongs to the technical field of navigation. By using a fuzzy control theory, a fuzzy logic controller and an accuracy improvement unit are arranged in a Costas carrier tracking loop, wherein the fuzzy controller can self-adaptively regulate loop bandwidth according todynamic conditions of an input frequency error and a phase error so as to shorten loop response time; the accuracy improvement unit eliminates trembling phenomenon in the process of fuzzy control by a linear interpolation and discourse domain transformation method so as to improve steady-state tracking accuracy; and a fuzzy control amount of which the accuracy is improved drives a carrier digitalcontrol oscillator to generate local sine and cosine carrier signals so as to keep tracking and locking an input carrier signal. The fuzzy control-based high-dynamic GPS receiver carrier tracking loop has the advantages of high dynamic tracking performance, high noise suppression capacity, and capacity of quickly and steadily implementing the process of tracking a high-dynamic low-signal-to-noiseratio GPS carrier signal and keeping high frequency tracking accuracy.

The invention discloses a control method and system for deadbeat current prediction of a permanent magnet motor without a position sensor, belonging to the technical field of motor control. The invention solves the problems of large size and weight of the system, high maintenance cost and low current prediction accuracy when motor parameters change in the existing deadbeat current prediction method. The present invention uses the deadbeat current prediction equation including the feedback gain matrix as an adjustable model, constructs a new adaptive observer, and deduces the conditions that can ensure the stability of the system according to Popov's super-stability theory; not only the adjustable The model predicts the command voltage of the next sampling cycle to improve the dynamic performance of the system, and by increasing the feedback gain, the stable area of ​​the estimated speed and position angle information is improved, and the robustness of the system is improved. Combining dead-beat current prediction and position sensorless control into one observer form simplifies the motor control algorithm. The invention can be applied to the control of deadbeat current prediction.

The invention discloses an adaptive service combination method which is applied to a multi-robot Ad Hoc network and used for evaluating a selected service combination through fuzzy trust-level evaluating and optimizing the selected service combination. In the process of searching for a service combination plan, multiple solution ways can be possibly found; and at the moment, good and bad of the resolutions need to be judged according to an adaptation criterion to achieve service optimization; in the adaptive service combination mode, agent robots are used for organizing and managing various resources and services in a network environment and being in charge of selecting a service combination strategy related to a specific environment from a stored service combination strategy set to achieve adaption of the service combination; meanwhile, a rule is dynamically generated by adopting a machine learning method, rule inference is conducted by using a fuzzy inference technology, and then thedynamic level of the service combination is achieved; on the basis, a fuzzy synthesis mechanism for the trust level and a fuzzy evaluation algorithm for the trust level are provided, and a machine learning-based fuzzy trust-level evaluating system (FTEs) is achieved; and finally, the service combination is evaluated by applying a reinforcement learning method, feedback is used for judging the service combination mode adopted in the next planning process, and therefore the evaluation effect is more ideal.