60 results about "Recursive analysis" patented technology

The invention discloses a method for detecting viscosity of a regulating valve in a control loop based on phase-space reconstruction, and relates to the field of valve fault diagnosis. The method provided by the invention is an unsupervised nonlinear signal analysis method, combines various technologies such as phase-space reconstruction, recursive analysis and power spectrum analysis, and proposes a viscosity statistical characteristic index and a viscosity distribution characteristic index, so as to characterize nonlinear and periodic laws caused by viscosity. And unsupervised adjusting valve viscosity fault detection is realized only through loop parameters. According to the method, the viscosity characteristics in the recursion plot are effectively extracted, calculation is simple and convenient, meanwhile, the method has high interpretability and accuracy, the huge potential of recursion analysis in valve viscosity detection is shown, and a method basis is provided for online monitoring and performance evaluation of an industrial loop.

The invention discloses a virtual network security-oriented communication dynamic analysis method, which relates to the technical field of network security, and comprises the following steps of: acquiring a communication time sequence; performing multi-scale decomposition on the communication sequential sequence to obtain a reference communication sequential sequence; calculating a slope and a propagation rate, and determining abnormal communication data based on the slope and the propagation rate; determining continuous abnormal communication data according to the periodic characteristics of the abnormal communication data and the propagation sequence of the abnormal communication data in network nodes, and determining an initial node and a propagation path of the continuous abnormal communication data by adopting reverse time sequence recursive analysis; inputting the starting node of the continuous abnormal communication data and the abnormal data characteristics of the propagation path into the LSTM neural network model, and predicting subsequent abnormal nodes; according to the method, high-precision identification of communication abnormity is facilitated, and the security detection capability and the response efficiency in a virtualized network environment are remarkably improved.

The invention discloses a combustion oscillation on-line monitoring method and device based on recursive quantitative analysis. The method comprises the steps that dynamic signals near a combustion chamber are obtained; performing recursive analysis on the dynamic signals in a period of time window, reconstructing a phase space, calculating time delay and embedding dimensions, and constructing a recursive matrix to obtain a recursive plot; extracting features from the recursion plot to obtain recursion quantization features; taking the recursive quantization features as input variables of the neural network, and inputting the recursive quantization features into the trained neural network; and the neural network gives a judgment result of the combustion oscillation state, and triggers an early warning mechanism when an abnormality is detected. According to the method, recursive quantitative analysis and deep learning are combined, online real-time monitoring of the combustion oscillation state is achieved, the precision and real-time performance of combustion oscillation monitoring are improved, efficient recognition and early warning of combustion oscillation are achieved, operation of a combustion system is optimized, combustion stability and safety are improved, the operation and maintenance cost of equipment is reduced, and the working efficiency is improved. And the method has wide engineering application value.

The invention relates to the technical field of fault testing, in particular to a dry-type air-core reactor turn-to-turn short circuit monitoring method based on a magnetic field difference method. According to the method, regularization constraint is introduced in an initial baseline stage to construct a reference electromagnetic coupling matrix, a heat accumulation index is recursively analyzed based on three-phase current energy, a thermally-induced magnetic field drift model is fitted in combination with magnetic field residual errors, and combined with combined constraint of the reference electromagnetic coupling matrix and the thermal drift model, a three-phase electromagnetic coupling model is established. The normal thermally induced magnetic field drift component is dynamically stripped in real-time monitoring; and under the constraint of a reference electromagnetic coupling matrix, fitting and optimizing a current vector through weighted least square state estimation, and integrating magnetic field and current two-dimensional deviation to obtain a structure consistency deviation index for fault monitoring. According to the invention, monitoring is carried out in consideration of a linear electromagnetic transfer rule and nonlinear thermal drift compensation, a complex magnetic field environment and a variable load operation condition of the dry-type air-core reactor are adapted, and continuous and reliable monitoring guarantee is provided for long-term stable operation of equipment.

Provided are systems and methods to transform a specified source dataset into a fully defined data format that details every attribute value in all levels for each document or record in the source dataset. According to various embodiments, the systems and methods are configured to execute recursive analysis on a specified data source, build out a fully specified data format and associated meta-data, enable user adjustments to a fully schema, and trigger automatic generation of code to transform the source to the new destination format even in the presence of polymorphic data. The process to scan source data involves recursively evaluating every attribute value in all levels for each document or record in the source dataset to account for any polymorphic data. The scan determines each attribute's data type usage, datetime formats and can interrogate string data to identify objects within string data.

The invention relates to an intelligent protocol configuration method for a Cat1 module. The method comprises the following steps: performing signal analysis on communication signal data to obtain an initial state sequence; performing multi-dimensional analysis on the signal change characteristics to obtain adaptive communication parameters; performing recursive analysis on the adaptive communication parameters to obtain a protocol configuration set; a configuration priority is obtained through calculation of the communication efficiency index; traversing the protocol parameter linked list to obtain a parameter sequence; analyzing and evaluating the parameter sequence to obtain effective configuration; performing mapping conversion through a protocol parameter mapping table to obtain a protocol instruction sequence; obtaining a protocol identifier according to the response feature; and executing the module configuration instruction and recording a configuration result. According to the invention, continuous acquisition and analysis of signal features are realized, the technical problem that a traditional single fixed window cannot give consideration to long-term trend and short-term fluctuation at the same time is solved, and standardized management and flexible adjustment of parameter configuration are realized.

The invention discloses a collaborative optimization allocation method and system for air route resources, particularly relates to the field of collaborative optimization of the air route resources, is used for solving the problems of dynamic allocation and real-time adaptation of complex resources, and is realized by constructing a basic resource node mapping graph in which dominant resources and recessive resources are combined. A resource dependency relationship path diagram is generated through time sequence disturbance analysis, collaborative response behaviors of resource nodes in a path are subjected to recursive analysis, path dynamic stability is classified in combination with offset parameters, and therefore the optimal allocation proportion of resources is accurately determined through a multi-target optimization model. And the allocation strategy is dynamically adjusted through real-time monitoring and a rolling optimization mechanism in actual execution, so that the allocation strategy of the air route resources is optimized, the risk of flight delay and airspace conflict is reduced, the response speed and decision accuracy of air route management are improved, and the safety and economic benefits of overall aviation operation are enhanced.

The invention provides a source analysis method embedded in atmospheric monitoring equipment. The method comprises the following steps: (1) data acquisition; (2) data preprocessing and feature extraction; (3) constructing a lightweight source component spectrum database; (4) performing online recursion analysis calculation; and (5) non-negative constraint and result output. According to the method, the problem of how to systematically and fundamentally solve multiple bottleneck problems caused by time lag, space limitation, huge equipment, lengthy flow and data distortion under the background that a traditional atmospheric particulate matter and gaseous pollutant source analysis system is bound by an off-line sampling-laboratory analysis mode for a long time is solved.

The embodiment of the invention provides a domain name resolution path determination method and device, equipment, a storage medium and a product. The method comprises the following steps: acquiring an internet protocol address IP of a target server; generating a prefix part of the second-level domain name according to the IP address of the target server; splicing the prefix part with the secondary domain name to determine a detection domain name of the target server; controlling the client to send an analysis request for the detection domain name to a target server, so that the target server sends a request data packet to an authoritative server; receiving all request data packets sent by the authoritative server, and screening all request data packets according to the detection domain name to obtain a first target data packet; judging whether a source address in the first target data packet is consistent with a target server IP; and if the source address is consistent with the IP of the target server, determining that the analysis path is composed of the client, the target server and the authoritative server. The method is used for achieving the effect of comprehensively restoring the recursive analysis path.

The invention provides a computing power identifier recursive analysis and resource allocation method and device based on a domain name system, which support analysis and addressing of wide area network computing power identifiers based on the domain name system based on a domain name service infrastructure, and have higher reliability, safety and stability than a new identification system. On the basis of domain name service nodes, analysis of computing power resources and allocation scheduling of computing power demands can be synchronously carried out in the identification analysis process, utilization of the computing power resources is efficiently achieved, and computing network integration is achieved; the analysis and resource allocation method from the top to the bottom of the root node is beneficial to macro-regulation and allocation of computing power resources between and within calculations in the wide area network range, and can realize service equalization of the computing power resources on the network level so as to improve the comprehensive service performance of the computing power network.

This invention relates to the field of fault testing technology, specifically to a method for monitoring inter-turn short circuits in dry-type air-core reactors based on the magnetic field difference method. This method constructs a reference electromagnetic coupling matrix by introducing regularization constraints in the initial baseline stage. Based on the recursive analysis of the three-phase current energy thermal accumulation index, it combines the magnetic field residual to fit a thermally induced magnetic field drift model. By combining the joint constraints of the reference electromagnetic coupling matrix and the thermal drift model, the normal thermally induced magnetic field drift component is dynamically removed during real-time monitoring. Under the constraints of the reference electromagnetic coupling matrix, the current vector is optimized through weighted least squares state estimation. The structural consistency deviation index is obtained by comprehensively considering the dual-dimensional deviations of the magnetic field and current for fault monitoring. This invention balances linear electromagnetic transfer laws with nonlinear thermal drift compensation for monitoring, adapting to the complex magnetic field environment and variable load operating conditions of dry-type air-core reactors, providing continuous and reliable monitoring assurance for the long-term stable operation of the equipment.

The application provides a kind of intelligent delivery and replenishment management method and system based on multi-dimensional inventory early warning, belong to goods management technical field, this method includes: obtaining the global demand data and full-link supply data of inventory object, and determining demand fluctuation intensity sequence and supply interruption frequency sequence;The demand fluctuation intensity sequence and supply interruption frequency sequence are cross recursive analysis, determine the mismatch risk evolution path between the goods demand and goods supply;According to the mismatch risk evolution path, the adaptive adjustment coefficient when safety stock is determined, and the safety stock threshold curve that evolves smoothly with time is obtained;When the inventory level of inventory object is lower than safety stock threshold curve, generate out-of-stock risk early warning, when inventory level is higher than safety stock threshold curve, generate backlog risk early warning.The technical scheme provided by the application can realize the adaptive management of delivery and replenishment under the nonlinear coupling effect of demand fluctuation and supply interruption.

The invention discloses a ZFS deleted data recovery method and system, and the method comprises the steps: comprehensively scanning a local storage medium, and obtaining a vdev tag and uberblock information; the method comprises the following steps of: establishing a set U according to gidsum and txg, establishing a topvdev set T, eliminating repeated and old data according to gidsum and txg to establish a set U, and verifying that giid of sub-equipment of topvdev equipment in the set T is paired with gidsum of uberblock; analyzing an uberblock corresponding to the topvdev to extract a block pointer of a metadata object set, reading and analyzing a DSL object directory set, obtaining a set D of each mounting point, and reconstructing a directory tree structure only containing the mounting points by utilizing a DSL object directory set membership; and analyzing each mounting point to read the ZAP object in the directory to obtain the sub-file and sub-folder information of the current directory, continuously performing recursive analysis until the directories and files of all the mounting points are completely analyzed, and completing data recovery.

The invention discloses an anesthetic dosage prediction method based on big data analysis, and relates to the field of anesthetic dosage prediction, and the method comprises the steps: obtaining patient information of anesthetic injection, screening useful information, including influence factors and prediction factors, according to the patient information by using a multi-round regression model, dividing the useful information into a training group and a control group according to a proportion, and establishing a linear regression model according to the predictive factor and the anesthesia site and area, visualizing the linear regression model in a column diagram form, and adjusting and evaluating the linear regression model to obtain a predictive model. Complex data of a patient is collected through big data, prediction to be performed is more accurate based on multiple regression model recursive analysis data, the interpretability of a prediction model is improved, the prediction data is visualized, the interactivity of the prediction data is increased, and the prediction efficiency is improved. Based on the linear regression model, the anesthetic injection dosage required by a patient individual can be quickly analyzed and predicted, so that the workload of an anesthetist is reduced.

The invention relates to the technical field of data analysis, in particular to a customized multi-thread analysis method for an equipment model based on an XML (Extensible Markup Language) file. Comprising the following steps: S1, configuring an equipment XML file and an XML analysis configuration file; s2, constructing an index table and a mapping table; s3, determining a target equipment model needing to be analyzed; s4, performing task allocation and recursive analysis; s5, combining and outputting analysis results; according to the equipment model customization analysis method based on the XML file, when the equipment type or the component type needing to be analyzed is newly added, only the newly added equipment type in the XML analysis configuration file and the component type and the attribute tag corresponding to the newly added equipment type need to be modified, and codes do not need to be reconstructed; and the equipment XML file can be specifically analyzed according to the equipment type, the component type list and the attribute tag list in the file through the XML analysis configuration file, so that the problems of resource waste and overlong time consumption caused by full analysis can be avoided.

The invention relates to a three-dimensional part color recovery method and device, equipment, a medium and a product. The method comprises the steps of obtaining an initial model file corresponding to a target part; recursive analysis processing is conducted on the initial model file, a topological shape set and a color set are obtained, and the color set comprises colors corresponding to all topological shapes in the topological shape set; obtaining a target assembly structure corresponding to the target part, and constructing a target shape combination based on the topological shape set and the target assembly structure; and performing color mapping processing on the target shape combination by using the color set and the target assembly structure to obtain a color model file corresponding to the target part. By adopting the method, the visualization accuracy can be improved.

Provided are systems and methods to transform a specified source dataset into a fully defined data format that details every attribute value in all levels for each document or record in the source dataset. According to various embodiments, the systems and methods are configured to execute recursive analysis on a specified data source, build out a fully specified data format and associated meta-data, enable user adjustments to a fully schema, and trigger automatic generation of code to transform the source to the new destination format even in the presence of polymorphic data. The process to scan source data involves recursively evaluating every attribute value in all levels for each document or record in the source dataset to account for any polymorphic data. The scan determines each attribute's data type usage, datetime formats and can interrogate string data to identify objects within string data.

The invention relates to an interface document automatic generation method and device, electronic equipment and a storage medium, and the method comprises the steps: analyzing a project source code to obtain a structure library and packaging functions, and constructing a function mapping table according to parameters and structure fields in each packaging function; based on the analyzed project source code, positioning a processing function and interface information corresponding to each interface path, and determining a response expression finally returned by the processing function; if the response expression is called by a packaging function, injecting a parameter type of a real parameter in the response expression into a structural body field of a corresponding packaging function according to a function mapping table, and performing recursive analysis on each field after the parameter type is injected in combination with a structural body library to obtain a field type tree; calling a large language model to perform semantic description on the field type tree and context information of each field to form an enhanced data structure; and integrating the interface information and the enhanced version data structure to generate an interface document. The accuracy of interface document generation is improved.

The present invention belongs to the field of Internet technology and communication, and particularly relates to a low-intrusive user operation behavior acquisition system and method under the QT framework. The system is deployed in a human-computer interaction function software developed based on QT. The system includes: a top-level event filter for capturing events generated by user operation behaviors of using the human-computer interaction function software and transmitting them to an operation behavior acquisition dynamic library; and an operation behavior acquisition dynamic library for recursively analyzing the attributes of events based on an object tree, determining user operation behaviors, and generating operation records. The low-intrusive acquisition architecture based on the event filter of the present invention greatly improves the generality and usability. Precise event capture can be achieved without the need to know the specific settings of the software control structure, enhancing the adaptability and flexibility. It has good generality and is applicable to all software developed based on QT. The use of a dynamic library for calling provides good flexibility.

The application discloses a kind of based on phase space reconstruction's control loop regulating valve stickiness detection method, it is related to valve fault diagnosis field.The method of the present application is the nonlinear signal analysis method of unsupervised, the method combines phase space reconstruction, recursive analysis and power spectrum analysis and other technologies, proposes stickiness statistical characteristic index and stickiness distribution characteristic index, to characterize the nonlinear and periodicity law brought by stickiness, only by loop parameter realizes the unsupervised regulating valve stickiness fault detection.The method proposed effectively extracts the stickiness characteristics in recurrence plot, not only simple and convenient to calculate, but also has high interpretability and accuracy, shows the great potential of recursive analysis in valve stickiness detection, provides a method basis for the online monitoring and performance evaluation of industrial loop.

The invention is applicable to the technical field of database management systems, and relates to an SQL dialect adaptive conversion method and interceptor based on recursive parse, and the method comprises the following steps: S10, intercepting an SQL statement at a statement execution interception point of a persistent framework, judging the type of a target database, and skipping a conversion process if the target database is an ORACLE database; s20, performing standardized preprocessing on the SQL statement; s30, executing SQL statement conversion in stages according to the grammar dependency relationship; and S40, writing back the converted SQL to an internal object of the framework through a Java reflection mechanism. The method is simple in process and convenient to operate, realizes zero configuration and zero invasion of a single set of ORACLE SQL while ensuring the conversion accuracy, and can directly run across libraries to automatically convert SQL statements.

The embodiment of the present application discloses an abnormal impact analysis method, device, computer equipment and storage medium, wherein the abnormal impact analysis method includes: real-time acquisition of scheduling data in a scheduling platform, the scheduling data including task status data of at least one scheduling task; analyzing and processing the task status data of each scheduling task to determine an abnormal scheduling task in at least one scheduling task; acquiring a scheduling task chain; recursively analyzing the abnormal scheduling task based on the scheduling task chain to obtain an impact scheduling task corresponding to the abnormal scheduling task, the impact scheduling task is the mth layer node in the scheduling task chain, the abnormal scheduling task is the nth layer node in the scheduling task chain, and m is greater than n; outputting prompt information, the prompt information includes a task identifier of the impact scheduling task. The embodiment of the present application can quickly locate the impact scheduling task corresponding to the abnormal scheduling task, so that the user can grasp the impact range of the abnormal scheduling task in real time.

The application discloses a tax data blood relation analysis method and device, equipment and a storage medium, and relates to the technical field of data asset management, which comprises the following steps: performing lexical analysis and syntax analysis on a current data query statement input by a user to obtain a word list object; identifying CTE objects in each word list object, and constructing a CTE name set based on CTE names in all CTE objects; performing depth-first recursive analysis on CTE definition bodies in the CTE objects based on the CTE name set to extract internal association structures of the CTE definition bodies; constructing a dependency relationship between each CTE object and other CTE objects or physical tables referenced in the query statement based on the CTE name set and the internal association structures, obtaining a dependency relationship graph, and outputting the dependency relationship graph by using a topological sorting algorithm to obtain a blood relation analysis result. The application can improve the accuracy of data blood relation analysis and is helpful for the smooth completion of data auditing work.

The invention discloses a carbon asset data tracing method, device and equipment based on industrial internet identifier analysis, a medium and a product, and relates to the technical field of carbon asset management. The method comprises the following steps: initiating a recursive analysis request to an industrial internet identifier analysis system; the recursive analysis request is generated based on a unique identification code of to-be-traced carbon asset data; in response to the recursive analysis request, obtaining a target data storage address corresponding to the unique identification code, a digitally signed carbon asset data packet and a verification public key; the digital signature is generated by encrypting the carbon asset original data associated with the unique identification code by using a private key paired with the verification public key; verifying the digital signature based on the verification public key; and when the verification is passed, calling carbon asset full life cycle metadata associated with the carbon asset data packet from the target data storage address to complete traceability. According to the invention, data traceability can be realized, and the carbon asset management efficiency is improved.

The embodiment of the present application provides an abnormal link analysis method, device, equipment and storage medium, which receives a user's abnormal link analysis request, obtains the current operation information and historical operation information of the task to be processed according to the identifier of the task to be processed included in the abnormal link analysis request, first determines whether the task to be processed is abnormal according to the current operation information, historical operation information and a pre-configured service level agreement, and when it is determined that the task to be processed is abnormal, recursively analyzes whether the task of the previous level of the task to be processed is abnormal based on the task hierarchy information, until the task hierarchy of the task without abnormality is determined, and the abnormal link analysis result is obtained. In this technical solution, the analysis of abnormal links can be performed based on the needs of the user, and the cause of the abnormal link can be located, which improves the accuracy of task monitoring and provides implementation conditions for improving the data quality output by the big data platform.

The invention discloses a medium and long term path prediction method and device for a multivariable regional energy structure. The method comprises the following steps: setting a processing strategy, setting a target total energy consumption demand of a measurement and calculation region, and constructing a policy derived path according to the target total energy consumption demand; through a policy index strategy and a carbon pinch point calculation strategy, a 60-year target non-fossil primary energy demand proportion, a target non-fossil energy prediction usage amount and a fossil energy prediction usage amount of the measurement and calculation area are obtained through calculation; determining a policy derived path energy structure of 30-60 years through recursive analysis; step-by-step prediction is carried out through an autoregression prediction strategy of logarithm transformation to obtain slice annual classification fossil energy proportion data; step-by-step prediction is carried out through a Markov chain step-by-step prediction model, and slice annual classification non-fossil energy ratio data is obtained; and through iterative analysis, an algorithm external expansion path is obtained and structure prediction is carried out to obtain a final prediction path. The method can effectively predict the medium-and-long-term regional clean energy structure and consumption based on policy indexes and objective conditions.

The application discloses a gear box fault diagnosis method and system based on scatter recurrence analysis, and belongs to the technical field of wind turbine fault diagnosis, and comprises the following steps: collecting vibration signals of a wind turbine gear box under different health states; utilizing scatter recurrence analysis to represent sensitive fault features in the gear box vibration signals from multiple dimensions; proportionally dividing the multi-dimensional features into a training set and a test set; inputting the training set to train an intelligent fault diagnosis model based on a support vector machine; and finally inputting the test set data into the trained SVM to obtain a gear box fault diagnosis result. The application combines nonlinear dynamics and machine learning to provide a diagnosis method and system capable of accurately identifying various faults of a wind turbine gear box, provides a reference for realizing efficient operation and maintenance of the wind turbine, and guarantees reliable and stable operation of the wind turbine.

The application discloses a running-in state identification method based on a friction signal threshold-free recursive analysis result, extracts nonlinear components of a friction signal time sequence output in a friction and wear process by collecting the friction signal time sequence; constructs a threshold-free recursive matrix by combining a sliding window and an avoidance embedding phase space reconstruction method and realizes visualization of the threshold-free recursive matrix in a two-dimensional plane; divides a lower triangular matrix of the threshold-free recursive matrix into several regions by a group of equidistant line segments parallel to a main diagonal line of the recursive matrix, extracts mean values of recursive elements in the regions, analyzes a change rate of element values of the threshold-free recursive matrix when the threshold-free recursive matrix transitions along the main diagonal line to edges and corners as a recursive measure, analyzes variation rules of the recursive measure along with a running-in and wear process, and further realizes running-in state online identification driven by the friction signal threshold-free recursive analysis result. The application optimizes a recursive characteristic representation and a measure extraction method of the friction signal time sequence, and realizes running-in state online identification from a perspective of dynamics-friction coupling.

The present application belongs to the field of intelligent analysis of electrocardiosignal, and proposes a coronary heart disease detection system based on electrocardio dynamic and static fusion and joint recursive analysis. On the basis of variational mode decomposition of electrocardio vector signal and the change rule of the electrocardio vector signal, the joint recursive method is used to fuse the information of the static domain and the dynamic domain of the electrocardio signal, and the recursive fusion features that can complement each other are extracted. The limitation of insufficient features extracted from a single data domain is avoided, and the reliability of the diagnosis result is improved. The present application can capture the complementary information between the static domain and the dynamic domain of the electrocardio signal, fuse multi-level signals, reveal the internal rule of the electrocardio signal, better understand the pathogenesis, and provide a reliable basis for coronary heart disease detection.

The invention relates to an operation and maintenance task workflow arrangement system in a distributed graph database, and the system comprises a workflow arrangement layer which is used for carrying out the recursive analysis of a workflow specification inputted by a user, so as to generate an executable DAG operation and maintenance task graph; the task management layer is used for adopting a two-stage submission protocol to ensure the atomic consistency of each operation and maintenance task in the DAG operation and maintenance task graph in a volatile memory and a persistent storage, and performing fault recovery on the uncompleted operation and maintenance task from the persistent storage based on the atomic consistency under the condition of memory data loss; and the conditional task execution layer is used for creating a security isolation sandbox for execution of each operation and maintenance task in the DAG operation and maintenance task graph, and evaluating a task execution result based on a dynamically updated conditional function in the execution process of the current operation and maintenance task so as to determine an execution path of a subsequent operation and maintenance task. Through the method and the device, the problem of how to improve the workflow efficiency of the operation and maintenance task in the graph database is solved.