Intelligent dynamic monitoring and early warning system based on multi-source data fusion

Abstract

The invention relates to the technical field of intelligent monitoring systems, in particular to an intelligent dynamic monitoring and early warning system based on multi-source data fusion, which adopts a distributed architecture and is divided into an acquisition layer, a processing layer, an analysis layer and a display layer. The acquisition layer is responsible for real-time acquisition of multi-source monitoring data; the processing layer is responsible for data cleaning, standardization and fusion processing; the analysis layer is responsible for performing real-time analysis on the fused data by applying an intelligent analysis algorithm; the display layer is responsible for displaying an analysis result to a user in a visual mode, and the monitoring coverage rate and accuracy are improved: through multi-source data fusion, the system can comprehensively collect and integrate monitoring data from different devices and systems, the problem of data islands is avoided, and the monitoring coverage rate and accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent monitoring systems, and in particular to an intelligent dynamic monitoring and early warning system based on multi-source data fusion. Background Art

[0002] With the deepening of digital grid construction and digital transformation, grid companies are increasingly demanding information system and network security. However, current monitoring and early warning systems face many challenges:

[0003] 1. Data silo problem: The monitoring data of different devices and systems are independent of each other, making it difficult to fully reflect the overall operating status.

[0004] 2. Warning lag: Traditional monitoring systems respond slowly to abnormal events and cannot meet real-time warning requirements.

[0005] 3. Low operation and maintenance efficiency: Lack of automated operation and maintenance support, fault handling and resource allocation rely on manual operations, which is inefficient.

[0006] 4. Complex security threats: Cyber ​​attack methods are constantly upgrading, and traditional security monitoring systems are unable to cope with new threats.

[0007] While existing technologies, such as the Intelligent Monitoring and Early Warning System (CN117935447A) and the Distributed System Monitoring Method (CN117762725A), have achieved breakthroughs in specific areas, they have failed to fully address key issues such as multi-source data integration, intelligent dynamic early warning, and automated operations and maintenance. Therefore, a new monitoring and early warning system is urgently needed to meet the digital transformation and network security needs of power grid companies. Summary of the Invention

[0008] The purpose of the present invention is to provide an intelligent dynamic monitoring and early warning system based on multi-source data fusion, which aims to achieve real-time monitoring, dynamic early warning and efficient operation and maintenance of complex information systems and network security status by integrating multi-source monitoring data, applying intelligent analysis algorithms and distributed architecture, so as to solve the problems raised in the background technology and facilitate promotion.

[0009] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is:

[0010] An intelligent dynamic monitoring and early warning system based on multi-source data fusion, including the following features:

[0011] a. Multi-source data acquisition module: used to collect multi-source monitoring data from IT equipment, network equipment, security equipment and computer room dynamic environment in real time;

[0012] b. Data fusion processing module: used to clean, standardize and fuse the collected multi-source monitoring data and build a unified data representation and storage model;

[0013] c. Intelligent analysis and early warning module: This module uses big data processing technology and intelligent analysis algorithms to conduct real-time analysis of integrated monitoring data, dynamically identify potential risks, and generate early warning information;

[0014] d. Visual display module: used to display system operation status, warning information and operation and maintenance data to users in an intuitive manner;

[0015] E. Automated Operation and Maintenance Module: Supports the configuration and execution of automated operation and maintenance scenarios, including automated inspections, fault handling, and resource allocation.

[0016] Furthermore, the multi-source data acquisition module supports multiple data acquisition protocols, including SNMP, WMI, SSH and HTTP, and can adapt to devices of different manufacturers and types.

[0017] Furthermore, the data fusion processing module adopts a distributed architecture to support large-scale data processing and real-time response, thereby improving the scalability and reliability of the system.

[0018] Furthermore, the intelligent analysis and early warning module uses machine learning algorithms, including cluster analysis, anomaly detection and prediction models, to analyze monitoring data in real time and dynamically identify potential risks.

[0019] Furthermore, the visual display module provides a variety of display methods, including dashboards, topology maps, alarm lists and trend charts, and users can customize the display content according to their needs.

[0020] Furthermore, the automated operation and maintenance module supports the configuration and execution of operation and maintenance processes, including automated inspection processes, fault handling processes, and resource allocation processes, thereby improving operation and maintenance efficiency.

[0021] Furthermore, the system also includes an interactive interface with the configuration management database (CMDB) system, which obtains device configuration information and association relationships through a standard interface to improve the accuracy and completeness of monitoring data.

[0022] Furthermore, the system supports security monitoring and compliance management functions, including threat intelligence collection, security incident monitoring, compliance baseline management, vulnerability scanning, etc., to ensure that the system complies with the requirements of relevant laws, regulations and security standards.

[0023] Furthermore, the system supports multi-tenant management functions, and can provide independent monitoring views and operation and maintenance permissions for different users, meeting the needs of enterprise-level multi-tenant environments.

[0024] As an improvement, the beneficial effects of the present invention are:

[0025] 1. Improve monitoring coverage and accuracy: Through multi-source data fusion, the system can comprehensively collect and integrate monitoring data from different devices and systems, avoid data silos, and improve monitoring coverage and accuracy.

[0026] 2. Realize intelligent dynamic early warning: Using big data processing technology and intelligent analysis algorithms, the system can analyze monitoring data in real time, dynamically identify potential risks, achieve accurate early warning, and improve the system's response speed and early warning effect.

[0027] 3. Improve operation and maintenance efficiency: Support automated operation and maintenance scenarios, such as automated inspection, fault handling, resource allocation, etc., to reduce manual intervention and improve operation and maintenance efficiency.

[0028] 4. Enhance security monitoring and compliance management capabilities: Establish a comprehensive security monitoring system to monitor and respond to security incidents in real time to ensure that the system complies with relevant laws, regulations and safety standards.

[0029] 5. Improve system scalability and reliability: Adopt a distributed architecture to support large-scale data processing and real-time response, improve system scalability and reliability, and meet the needs of digital transformation and network security of power grid enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a flow chart of an intelligent dynamic monitoring and early warning system based on multi-source data fusion according to the present invention; DETAILED DESCRIPTION

[0031] In order to make the contents of the present invention more clearly understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0032] 1. System Architecture

[0033] The system adopts a distributed architecture and is divided into the collection layer, processing layer, analysis layer, and presentation layer. The collection layer is responsible for the real-time collection of multi-source monitoring data; the processing layer is responsible for data cleaning, standardization, and fusion processing; the analysis layer is responsible for real-time analysis of the fused data using intelligent analysis algorithms; and the presentation layer is responsible for presenting the analysis results to users in an intuitive manner.

[0034] 2. Multi-source data collection

[0035] The system supports multiple data collection protocols, adapting to devices from different manufacturers and types. For IT equipment, the system collects CPU, memory, disk, and other performance metrics using the SNMP protocol; for network equipment, the system collects traffic data using the NetFlow protocol; for security equipment, the system collects security logs using the Syslog protocol; and for computer room dynamic and environmental equipment, the system collects environmental data such as temperature, humidity, and power using the Modbus protocol.

[0036] 3. Data fusion processing

[0037] The system uses distributed data processing frameworks, such as Apache Spark, to clean, standardize, and fuse collected multi-source monitoring data. The cleaning process includes removing noise and filling missing values; standardization converts data into a unified format and units; and fusion involves correlating and integrating data from different devices to create a unified data representation and storage model.

[0038] 4. Intelligent analysis and early warning

[0039] The system uses machine learning algorithms, such as cluster analysis, anomaly detection, and predictive modeling, to analyze integrated monitoring data in real time. Cluster analysis is used to identify unusual patterns in the data; anomaly detection identifies potential risk events; and predictive modeling predicts future system load and performance trends. When the system detects an unusual event or potential risk, it automatically generates an alert and notifies users through various channels.

[0040] 5. Visual display

[0041] The system provides multiple display methods, including dashboards, topology maps, alarm lists, and trend charts. The dashboard displays key performance indicators and system status; the topology map shows the relationships and operational status of devices; the alarm list displays current alarm information and processing status; and the trend chart shows the changing trends of historical data. Users can customize the display content based on their needs, such as selecting specific devices, indicators, and time ranges.

[0042] 6. Automated Operations and Maintenance

[0043] The system supports the configuration and execution of automated O&M scenarios. Users can use the system's O&M process design tools to define automated inspection processes, troubleshooting processes, resource allocation processes, and more. The system automatically executes corresponding operations based on pre-defined processes, such as inspecting device status, handling fault alerts, and allocating computing resources. Automated O&M can significantly improve O&M efficiency and reduce manual intervention.

[0044] 7. Interact with CMDB system

[0045] The system interacts with the Configuration Management Database (CMDB) system through a standard interface. The CMDB system stores device configuration information and relationships, such as model, version, location, and dependencies. The system can retrieve device configuration information and relationships from the CMDB system to improve the accuracy and completeness of monitoring data. For example, if the system detects an anomaly on a device, it can quickly locate other affected devices and services by combining relationships in the CMDB system.

[0046] 8. Safety Monitoring and Compliance Management

[0047] The system supports security monitoring and compliance management. It collects threat intelligence, such as the latest vulnerability information and attack methods. The monitoring system monitors security events, such as intrusions and virus transmission, in real time. It manages compliance baselines to ensure that device configurations comply with relevant laws, regulations, and security standards. It also performs vulnerability scanning to identify security vulnerabilities in devices and promptly patch them.

[0048] 9. Multi-tenant management

[0049] The system supports multi-tenant management. It provides independent monitoring views and operational permissions for different users. For example, for different branches or departments of a power grid company, the system can provide independent monitoring views for each branch or department, displaying only the equipment and data relevant to that branch or department. Furthermore, the system can assign different operational permissions to different users, such as read-only permissions, operational permissions, and administrative permissions, ensuring system security and controllability.

[0050] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included in the scope of protection of the present invention.

Claims

1. An intelligent dynamic monitoring and early warning system based on multi-source data fusion, characterized in that: Features include: a. Multi-source data acquisition module: used to collect multi-source monitoring data from IT equipment, network equipment, security equipment and computer room dynamic environment in real time; b. Data fusion processing module: used to clean, standardize and fuse the collected multi-source monitoring data and build a unified data representation and storage model; c. Intelligent analysis and early warning module: This module uses big data processing technology and intelligent analysis algorithms to conduct real-time analysis of integrated monitoring data, dynamically identify potential risks, and generate early warning information; d. Visual display module: used to display system operation status, warning information and operation and maintenance data to users in an intuitive manner; E. Automated Operation and Maintenance Module: Supports the configuration and execution of automated operation and maintenance scenarios, including automated inspections, fault handling, and resource allocation.

2. The intelligent dynamic monitoring and early warning system based on multi-source data fusion according to claim 1 is characterized in that: The multi-source data acquisition module supports multiple data acquisition protocols, including SNMP, WMI, SSH and HTTP, and can adapt to devices of different manufacturers and types.

3. The intelligent dynamic monitoring and early warning system based on multi-source data fusion according to claim 1 is characterized in that: The data fusion processing module adopts a distributed architecture, supports large-scale data processing and real-time response, and improves the scalability and reliability of the system.

4. The intelligent dynamic monitoring and early warning system based on multi-source data fusion according to claim 1 is characterized in that: The intelligent analysis and early warning module uses machine learning algorithms, including cluster analysis, anomaly detection and prediction models, to analyze monitoring data in real time and dynamically identify potential risks.

5. The intelligent dynamic monitoring and early warning system based on multi-source data fusion according to claim 1 is characterized in that: The visualization module provides multiple display modes, including dashboards, topology maps, alarm lists and trend charts, and users can customize the display content according to their needs.

6. The intelligent dynamic monitoring and early warning system based on multi-source data fusion according to claim 1 is characterized in that: The automated operation and maintenance module supports the configuration and execution of operation and maintenance processes, including automated inspection processes, fault handling processes, and resource allocation processes, thereby improving operation and maintenance efficiency.

7. The intelligent dynamic monitoring and early warning system based on multi-source data fusion according to claim 1 is characterized in that: The system also includes an interactive interface with the Configuration Management Database (CMDB) system, which obtains device configuration information and association relationships through a standard interface to improve the accuracy and completeness of monitoring data.

8. The intelligent dynamic monitoring and early warning system based on multi-source data fusion according to claim 1 is characterized in that: The system supports security monitoring and compliance management functions, including threat intelligence collection, security incident monitoring, compliance baseline management, vulnerability scanning, etc., to ensure that the system complies with the requirements of relevant laws, regulations and security standards.

9. The intelligent dynamic monitoring and early warning system based on multi-source data fusion according to claim 1 is characterized in that: The system supports multi-tenant management functions and can provide independent monitoring views and operation and maintenance permissions for different users, meeting the needs of enterprise-level multi-tenant environments.

Images