8results about How to "Improve analysis" patented technology

This invention provides a method and system for compressing power messages, relating to the field of power system control technology. The method includes: acquiring power messages via a first FPGA; timestamping the acquired power messages; caching the timestamped messages in a first shared memory; extracting messages from the first shared memory; parsing the messages according to their type and classifying and storing them in a second shared memory; extracting messages from the second shared memory by control block using a second FPGA; compressing the compressed packages corresponding to the control blocks; storing the compressed packages in a third shared memory; packaging and secondary compression according to a set time period; generating a total compressed package for that time period; and storing it on an SSD for dual-disk storage. This invention effectively reduces the storage space requirements for historical messages, improves the storage time of historical messages, and solves the problem of frequent failures in storing historical messages for post-event analysis of power systems.

The invention provides a hot water force multi-field monitoring analysis method and system suitable for a TEHB test system, and the method comprises a model framework building step, a steady-state initial field solving step, a hot water force coupling solving step, and a multi-field response data collection and recording step. The invention further provides a hot water force multi-field monitoring and analyzing system suitable for the TEHB test system, a three-dimensional model containing the six-direction waveguide rod and the rock sample is established, a mechanical, seepage and temperature steady-state initial field before impact loading is obtained, hot water force coupling dynamic calculation is carried out under the action of triaxial six-direction synchronous impact, and the test result is obtained. And curves and statistical indexes of key results such as stress, fracture, pore pressure, temperature and the like are automatically output. According to the invention, the impact process simulation can be realized under the hot water-force coupling loading condition, and multi-field response data can be monitored and analyzed, so that the dynamic mechanical behavior of the rock under the hot water-force coupling effect can be revealed, and a basis is provided for the scientific design of deep engineering.

The invention belongs to the technical field of power transmission equipment maintenance, and particularly discloses a bird self-adaptive expelling method and a bird expelling rod mechanism for an electric power tower area, and the method comprises the steps: arranging terminal devices with image collection and expelling execution functions at a plurality of electric power towers, and recognizing the types and body types of birds through the image data collected by the terminals; the identification result is sent to the upper computer; the upper computer calls an expelling parameter combination according to the identification information, generates a control instruction and issues the control instruction to a corresponding terminal; the terminal adopts at least one preset expelling mode to execute expelling operation; after expelling is completed, recording parameters and expelling data and returning the parameters and the expelling data to the upper computer; and the upper computer disturbs at least one feature in the expelling parameters based on the recorded data to generate a new parameter combination, and the new parameter combination is applied when birds of the same type and body form appear again. According to the scheme, dynamic updating and continuous optimization of the repelling strategy can be realized, and the method is suitable for bird repelling management in a multi-tower scene.

The invention relates to the technical field of power fault diagnosis, and discloses a power fault diagnosis method and system based on cross-modal semantic alignment and agent coordination decision, and the method comprises the steps: obtaining multi-modal data needed in the operation and maintenance process of power equipment, and constructing a multi-modal power professional knowledge base; extracting multi-modal features contained in the multi-modal electric power professional knowledge base based on a feature representation technology, calculating dynamic weights of the multi-modal features, and generating an intelligent agent in combination with the electric power fault diagnosis instruction data set; an electric power fault diagnosis task is input, the modal weight of the electric power fault diagnosis task is calculated, and the intelligent agent outputs a fault diagnosis result of the electric power fault diagnosis task and a corresponding processing flow according to the modal weight; and generating a fault diagnosis report based on the fault diagnosis result of the power fault diagnosis task and the corresponding processing flow. According to the invention, intelligence and real-time performance of decision making are greatly improved, and dependence on artificial experience is reduced.

The invention relates to the technical field of network security, in particular to a network security monitoring system based on artificial intelligence, which comprises a data preprocessing module, an anomaly detection module, a fault mode learning module, a threshold dynamic adjustment module, an attack source positioning module, a behavior analysis and identification module, a decision support module and a recovery strategy optimization module. According to the method, the abnormal state can be efficiently identified through the isolation forest algorithm and the self-encoder model, the learning of the fault mode is deeper through the application of the long and short-term memory network, and the precise attack source positioning is realized through the combination of the self-regression differential moving average model and the graph database query technology; the accuracy of attack pattern recognition is improved by introducing the convolutional neural network and the graph neural network, the security decision is more scientific and reasonable by applying the analytic hierarchy process and the support vector machine algorithm, and the resource allocation and recovery strategy are optimized by using the genetic algorithm and the particle swarm optimization algorithm.

The invention discloses a knowledge-driven clustered settlement space updating method, and relates to the technical field of digital aided design of buildings and urban and rural planning, and the method comprises the steps: constructing a quantitative representation index system of a settlement space according to a settlement space cognition theory; based on the quantitative characterization index of the settlement space, constructing a knowledge graph of the settlement group; developing a settlement space analysis function module based on the quantitative characterization index of the settlement space and the knowledge graph of the settlement group; building a webpage front end of clustering settlement form analysis; a settlement space analysis function module is called through webpage front-end interactive operation, a settlement form problem is identified, a clustering protection range is delimited, case optimization is referred, and a settlement space updating strategy is provided. The invention further discloses a system of the clustered settlement space updating method based on knowledge driving. An efficient and interactive technical approach is provided for systematic management and clustered updating design of the settlement space.

The present application relates to the technical field of industrial process control and modeling, in particular to a soft instrument model optimization construction method based on a DCS system, the present application divides production conditions according to fluctuation of monitoring data; analyzes correlation characteristics between relevant monitoring parameters and irrelevant monitoring parameters under the same historical condition slice, and analyzes performance differences of irrelevant monitoring parameters in different historical condition slices on the influence on relevant monitoring parameters, and comprehensively evaluates reference weights of relevant monitoring parameters in the historical condition slice; according to consistency of changes of monitoring parameters in the current condition state window and the historical condition slice, the reference weights of the relevant monitoring parameters under the current condition state window are obtained, and then the soft instrument model of the current condition state window is constructed; the soft instrument model obtained by the method can adapt to different production conditions, effectively process auxiliary variables in the DCS system, and improve from local optimization of a single parameter to comprehensive optimization of all parameters.

The application provides an electric energy meter intelligent data processing method, system and terminal, relates to the technical field of electric energy meter intelligent data processing, and comprises the following steps: acquiring real-time data of an electric energy meter; cleaning and formatting the real-time data to determine basic data; analyzing the basic data to generate normal classification data and early warning information; analyzing the normal classification data and early warning information to generate a structured data packet; and uploading the structured data packet to a master station. The application has the effect of improving the real-time data analysis and early warning of an electric energy meter.