Electric power communication resource management and hidden danger identification analysis system and method

Abstract

The invention relates to an electric power communication resource management and hidden danger identification and analysis system and method, and the system comprises a data collection module, a data processing module, a hidden danger identification and analysis module and an alarm module which are sequentially connected, the data collection module is used for collecting data, and the data processing module is used for processing the data. The data processing module is used for processing data acquired by the data acquisition module, the hidden danger identification and analysis module is used for carrying out hidden danger identification and analysis according to a processing result of the data processing module, and the alarm module is used for deciding whether to give an alarm or not according to a hidden danger identification and analysis result of the hidden danger identification and analysis module. Through data acquisition and analysis of the electric power communication resources, potential safety hazards of the electric power communication resources can be recognized in time, safety accidents are avoided, and meanwhile the utilization efficiency of the electric power communication resources is improved. The system has high reliability and practicability, and is suitable for power communication resource management of various scales.

Description

Technical Field

[0001] The present invention belongs to the field of power grid hidden danger identification, and in particular to a power communication resource management and hidden danger identification and analysis system and method. Background Art

[0002] In the power industry, the management of communication resources is crucial to ensure the safe and stable operation of the power system. However, traditional communication resource management methods have many problems, including incomplete resource data and difficulty in timely analysis and identification of potential hidden dangers.

[0003] The electric power communication network is a physical network, an operating platform that carries all kinds of electric power information services, the basis for the safe and stable operation of the primary system of the power grid, and an important guarantee for the safe production of power grid companies. With the rapid development of the electric power communication network, the network scale is becoming larger and larger, the network structure is becoming more and more complex, and the communication services carried are becoming more and more abundant, which puts forward higher requirements on the robustness of the electric power communication network and the reliability of communication services. Reasonable planning of the network structure of the electric power communication network to ensure the self-healing ability of the network and reasonable planning of the routing of the service channels to ensure the reliability of the services carried have become one of the important tasks of communication operation and maintenance organizations at all levels.

[0004] By studying the analysis methods of potential risks in power communication network services and channels, and analyzing the channel routing planning of network-borne services, we can find risk points in network structure and service channel planning, and provide data support for network optimization and transformation such as technical transformation and overhaul, as well as optimization of communication operation mode, and promote the self-healing ability and service guarantee ability of power communication network. However, the existing analysis methods only analyze network risks at the physical link level, and are not combined with power communication services, so they cannot analyze network potential risks at the service logic level. Summary of the invention

[0005] The purpose of the present invention is to overcome the shortcomings of the prior art and propose a power communication resource management and hidden danger identification and analysis system and method. Through data collection and analysis of power communication resources, the safety hazards of power communication resources can be identified in time to avoid the occurrence of safety accidents and improve the utilization efficiency of power communication resources. The system has high reliability and practicality and is suitable for power communication resource management of various scales.

[0006] The present invention solves the technical problem by adopting the following technical solutions:

[0007] A power communication resource management and hidden danger identification and analysis system comprises a data acquisition module, a data processing module, a hidden danger identification and analysis module and an alarm module, wherein the data acquisition module, the data processing module, the hidden danger identification and analysis module and the alarm module are connected in sequence, the data acquisition module is used to collect data, the data processing module is used to process the data collected by the data acquisition module, the hidden danger identification and analysis module is used to perform hidden danger identification and analysis according to the processing results of the data processing module, and the alarm module is used to decide whether to issue an alarm according to the hidden danger identification and analysis results of the hidden danger identification and analysis module.

[0008] Moreover, the data acquisition module is precisely configured to achieve seamless connection with various acquisition devices in the power communication network, and can automatically and efficiently extract valuable communication resource data from these devices; the data includes the real-time operating status of the communication equipment: whether the equipment is online, operating temperature and signal strength; network topology information: detailed description of the connection relationship between each node, providing a basis for network optimization and troubleshooting; and bandwidth utilization: including the real-time bandwidth occupancy rate and historical peak value of each link.

[0009] Moreover, the data processing module first performs strict cleaning of the original data to eliminate erroneous, duplicate or invalid information to ensure the accuracy and reliability of subsequent analysis; the cleaned data will then be properly stored in a high-performance database for instant query, which also provides rich materials for long-term trend analysis; on this basis, the data processing module also uses advanced algorithms to perform multi-dimensional analysis of the data, including time series analysis and association rule mining, and presents the analysis results to users in the form of intuitive and easy-to-understand charts, reports, etc.

[0010] Moreover, the hidden danger identification and analysis module uses deep learning and data mining technology to conduct in-depth analysis of massive data and capture hidden danger signals that may threaten network security from subtle details; by building complex predictive models, the module identifies potential risks such as equipment aging, overload operation or abnormal traffic patterns, and automatically assigns priority and urgency to the hidden dangers based on their severity, scope of impact and possible consequences.

[0011] Moreover, the hidden danger identification and analysis module generates an alarm message, and the alarm module will be activated immediately to send the alarm message containing hidden danger details, recommended treatment measures and urgency to the designated operation and maintenance personnel or management team through multiple channels such as SMS, email, and instant messaging software.

[0012] An identification and analysis method for a power communication resource management and hidden danger identification and analysis system comprises the following steps:

[0013] Step 1, the data acquisition module collects data related to communication equipment, optical paths and optical cables;

[0014] Step 2: The data processing module preprocesses the collected data, including data cleaning and data conversion. Cleaning the data removes missing values ​​and outliers, and data conversion applies normalization or standardization to ensure that the data is on the same scale.

[0015] Step 3, the data processing module calculates the outlier detection Z-Score value of each data point for the preprocessed data;

[0016] Step 4: The data processing module determines the threshold of the outlier according to specific requirements, where the threshold is defined by setting the boundary of the Z-Score;

[0017] Step 5, the hidden danger identification and analysis module identifies data points with Z-Score values ​​exceeding the set threshold, which are considered outliers, indicating potential hidden dangers or abnormal situations;

[0018] Step 6: The hidden danger identification and analysis module further analyzes and processes the identified outliers;

[0019] Step 7: The hidden danger identification and analysis module identifies and analyzes the hidden dangers of specific power communication resources based on the outlier detection Z-Score results;

[0020] Step 8: The alarm module obtains a fault assessment basis value based on the calculation result Re in step 7, and performs different feedback processing according to the following range values.

[0021] Moreover, the relevant data in step 1 includes equipment status data, performance indicator data and transmission quality data.

[0022] Moreover, the specific implementation method of step 3 is:

[0023] The Z-Score is a statistic used to measure how different a data point is from the mean;

[0024] Apply the Z-Score formula to each data point:

[0025] Z=(X-μ) / σ

[0026] Where X is the value of the data point, μ is the mean of the data set, and σ is the standard deviation of the data set.

[0027] Moreover, the specific implementation method of step 7 is:

[0028] Re=(E*Q*EQ_v+T*T_v+O*O_v+EN*EN_v) / (EQ_v+T_v+O_v+EN_v)

[0029] Among them, E and Q are the number and frequency of outliers: identify whether the outliers are individual abnormalities or there are systemic problems; EQ_v is the weight of the number and frequency of outliers in the analysis; T is the duration of the outliers: observe the duration of the outliers to determine whether it is a temporary problem or a long-term hidden danger; T_v is the weight of the duration of the outliers in the analysis; O is the correlation with other indicators: O_v is the weight of the correlation with other indicators; EN is the relevant environmental factors; EN_v is the weight of the relevant environmental factors.

[0030] Moreover, the specific implementation method of step 8 is:

[0031] [0,0.5] is provided and recorded normally;

[0032] (0,0.7] is to warn and record that there may be abnormalities in communication resources;

[0033] (0.7, 0.9] is a serious warning and records that the communication resources are abnormal and need manual processing;

[0034] (0.9,1.0) is a fault notification.

[0035] The advantages and positive effects of the present invention are:

[0036] The present invention includes a data acquisition module, a data processing module, a hidden danger identification and analysis module and an alarm module, wherein the data acquisition module, the data processing module, the hidden danger identification and analysis module and the alarm module are connected in sequence, the data acquisition module is used to collect data, the data processing module is used to process the data collected by the data acquisition module, the hidden danger identification and analysis module is used to perform hidden danger identification and analysis according to the processing result of the data processing module, and the alarm module is used to decide whether to alarm according to the hidden danger identification and analysis result of the hidden danger identification and analysis module. The present invention can timely identify the safety hidden dangers of power communication resources through data collection and analysis of power communication resources, avoid the occurrence of safety accidents, and improve the utilization efficiency of power communication resources at the same time. The system has high reliability and practicality, and is suitable for power communication resource management of various scales. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a system structure diagram of the present invention;

[0038] Figure 2 This is a diagram of the data acquisition and processing architecture in the system of the present invention;

[0039] Figure 3 This is a diagram of the data processing architecture in the system of the present invention. DETAILED DESCRIPTION

[0040] The present invention is further described in detail below with reference to the accompanying drawings.

[0041] A power communication resource management and hidden danger identification and analysis system, such as Figure 1 As shown in the figure, it includes data acquisition module, data processing module, hidden danger identification and analysis module and alarm module, among which, data acquisition module, data processing module, hidden danger identification and analysis module and alarm module are connected in sequence. Data acquisition module constitutes the data cornerstone of the system and can be regarded as the preparation stage of the basic data model. Next, the data processing module, as the subsequent link of data acquisition, generates high-quality data required for business display by cleaning, converting and managing these basic data. Subsequently, the hidden danger identification and analysis module is built on the data processing module, and uses deep learning and data mining technology to conduct in-depth analysis of these processed data, aiming to accurately identify potential safety hazards. Finally, as the top layer of the system, the alarm module is responsible for notifying relevant personnel of the identified hidden dangers immediately and initiating the supervision process to ensure that the hidden dangers are handled in a timely manner.

[0042] like Figure 2 As shown in the figure, the data acquisition module is one of the core components in the communication resource management and hidden danger identification and analysis system, and it plays a key role in information collection and preliminary organization. Through precise configuration, this module can seamlessly connect with various acquisition devices in the power communication network, and can automatically and efficiently extract valuable communication resource data from these devices. These data cover the real-time operating status of communication equipment, such as whether the equipment is online, operating temperature, signal strength and other key indicators; network topology information, which details the connection relationship between each node, providing a basis for network optimization and troubleshooting; and bandwidth utilization, including real-time bandwidth occupancy of each link, historical peak value and other data, which is crucial for evaluating network performance and planning future expansion.

[0043] like Figure 3 As shown in the figure, the data processing module performs more in-depth processing and analysis. The data processing module first performs strict cleaning of the original data to eliminate erroneous, duplicated or invalid information to ensure the accuracy and reliability of subsequent analysis. Subsequently, the cleaned data will be properly stored in a high-performance database, which is convenient for instant query and provides rich materials for long-term trend analysis. On this basis, the data processing module also uses advanced algorithms to perform multi-dimensional analysis of the data, such as time series analysis and association rule mining, and presents the analysis results to users in the form of intuitive and easy-to-understand charts and reports. These visualization tools not only help users quickly grasp the overall health of the network, but also provide in-depth insights into abnormal situations in specific time periods or specific areas, providing a strong basis for decision support.

[0044] The hidden danger identification and analysis module is the intelligent brain of the entire system. It uses deep learning and data mining technology to conduct in-depth analysis of massive data, aiming to capture hidden danger signals that may threaten network security from subtle details. By building a complex prediction model, the module can identify potential risks such as equipment aging, overload operation, and abnormal traffic patterns, and automatically assign priorities and urgency to the hidden dangers according to their severity, scope of impact, and possible consequences. This capability greatly improves the speed and accuracy of hidden danger discovery, and buys valuable time for taking preventive measures in a timely manner.

[0045] As the terminal response link of the entire process, the alarm module is responsible for quickly conveying hidden danger information to relevant responsible persons. Once the hidden danger identification and analysis module generates an alarm message, the alarm module will be activated immediately and send the alarm message containing hidden danger details, recommended treatment measures and urgency to the designated operation and maintenance personnel or management team through multiple channels such as SMS, email, and instant messaging software. This instant messaging mechanism ensures that hidden dangers can be responded to quickly and effectively, thereby minimizing potential losses and ensuring the stable operation of the power communication network and power supply safety.

[0046] The system of the present invention has a series of processes from data collection to processing, analysis, and then to hidden danger identification and alarm, which constitutes an efficient closed loop of communication resource management and hidden danger identification and analysis system, which not only improves the intelligent level of network management, but also lays a solid foundation for the sustainable development of the power industry.

[0047] The functions and features of the system of the present invention are as follows:

[0048] Resource management: The system can manage and monitor the equipment, links, transmission lines and other resources in the power communication network. It can track and record the status, configuration information, location and usage of each resource, and provide real-time resource monitoring and management functions.

[0049] Hidden danger identification and analysis: The system can identify potential hidden dangers and failure risks by analyzing and monitoring the power communication network. It can detect abnormal behavior, signal interference, transmission delay and other problems in the network based on preset rules and algorithms, and provide corresponding warnings and reports.

[0050] Fault management and maintenance: The system can monitor, diagnose and handle faults in the power communication network. It can automatically or manually locate and identify faults, and provide troubleshooting and maintenance guidance to speed up fault recovery and network repair.

[0051] Security monitoring and protection: The system can monitor the security of the power communication network and provide an alarm and response mechanism for security incidents. It can detect and prevent potential security risks such as network attacks, data leakage and unauthorized access, and provide security assessments and improvement suggestions.

[0052] Data analysis and reporting: The system can collect, store and analyze data from the power communication network. It can generate real-time data reports, trend analysis and performance indicators to help users understand the network operation status and optimize the configuration of network resources.

[0053] Remote monitoring and control: The system can monitor and control the devices and connections of the power communication network in real time through remote access. It can remotely configure and manage network devices, monitor and control device status, and improve the response speed and manageability of the network.

[0054] An identification and analysis method for a power communication resource management and hidden danger identification and analysis system comprises the following steps:

[0055] Step 1: The data acquisition module collects data related to communication equipment, optical paths, and optical cables. The relevant data includes equipment status data, performance indicator data, transmission quality data, etc. Ensure that the data is accurate, complete, and covers observations over a period of time.

[0056] Step 2: The data processing module preprocesses the collected data, including data cleaning and data conversion; data cleaning can remove missing values, outliers, etc. Data conversion can apply necessary normalization or standardization to ensure that the data is on the same scale.

[0057] Step 3: The data processing module calculates the outlier detection Z-Score value of each data point for the preprocessed data.

[0058] The Z-Score is a statistic used to measure how different a data point is from the mean;

[0059] Apply the Z-Score formula to each data point:

[0060] Z=(X-μ) / σ

[0061] Where X is the value of the data point, μ is the mean of the data set, and σ is the standard deviation of the data set.

[0062] Step 4: The data processing module determines the threshold of outliers according to specific requirements. Usually, the threshold can be defined by setting the boundary of the Z-Score. For example, data points exceeding 2 or 3 standard deviations are considered outliers.

[0063] Step 5, the hidden danger identification and analysis module identifies data points with Z-Score values ​​exceeding the set threshold. These data points are considered outliers and may indicate potential hidden dangers or abnormal situations.

[0064] Step 6: The hidden danger identification and analysis module further analyzes and processes the identified outliers. The knowledge of domain experts can be used to evaluate the causes and potential impacts of outliers and take appropriate measures to resolve or mitigate the hidden dangers.

[0065] Step 7: The hidden danger identification and analysis module identifies and analyzes specific power communication resource hidden dangers based on the outlier detection Z-Score results.

[0066] Re=(E*Q*EQ_v+T*T_v+O*O_v+EN*EN_v) / (EQ_v+T_v+O_v+EN_v)

[0067] Among them, E and Q are the number and frequency of outliers: identify whether the outliers are individual abnormalities or there are systemic problems; EQ_v is the weight of the number and frequency of outliers in the analysis; T is the duration of the outliers: observe the duration of the outliers to determine whether it is a temporary problem or a long-term hidden danger; T_v is the weight of the duration of the outliers in the analysis; O is the correlation with other indicators: O_v is the weight of the correlation with other indicators; EN is the relevant environmental factors; EN_v is the weight of the relevant environmental factors.

[0068] Step 8: The alarm module obtains a fault assessment basis value based on the calculation result Re in step 7, and performs different feedback processing according to the following range values.

[0069] [0,0.5] is provided and recorded normally;

[0070] (0,0.7] is to warn and record that there may be abnormalities in communication resources;

[0071] (0.7, 0.9] is a serious warning and records that the communication resources are abnormal and need manual processing;

[0072] (0.9,1.0) is a fault notification.

[0073] The present invention can improve the fault diagnosis and hidden danger identification capabilities: by monitoring and analyzing the power communication network data, the system can accurately diagnose faults and identify potential hidden dangers. This helps to detect problems early and take appropriate measures to repair and prevent them, so as to improve the reliability and stability of the communication network.

[0074] The present invention can enhance resource management and optimization: the system can manage and monitor the equipment, links, optical cables and other resources in the power communication network. Through real-time monitoring of resource status and usage, resource allocation can be effectively planned and optimized, and resource utilization and performance can be improved.

[0075] The present invention can improve communication quality and service level: by analyzing and monitoring communication network data, the system can identify and handle problems that lead to reduced communication quality, such as high latency, packet loss rate, etc. This helps to provide more stable and reliable communication services and improve user experience.

[0076] The present invention can enhance security and protection capabilities: the system can monitor security events and potential threats in the network, such as network attacks, data leaks, etc. Through real-time security monitoring and alarm mechanisms, defensive measures can be taken in time to protect the security of the communication network.

[0077] The present invention can improve operation and maintenance efficiency and cost control: through automated fault diagnosis and resource management functions, the system can reduce the need for human intervention and manual operation, improve operation and maintenance efficiency, and reduce operation and maintenance costs.

[0078] The present invention can perform data analysis and decision support: the system collects, stores and analyzes a large amount of communication network data, and can generate real-time data reports, trend analysis and performance indicators. This provides valuable data support for decision makers, helping them understand the network operation status and make reasonable decisions and plans.

[0079] It should be emphasized that the embodiments described in the present invention are illustrative rather than restrictive. Therefore, the present invention includes but is not limited to the embodiments described in the specific implementation manner. Any other implementation manners derived by those skilled in the art based on the technical solution of the present invention also fall within the scope of protection of the present invention.

Claims

1. A power communication resource management and hidden danger identification and analysis system, characterized in that: It includes a data acquisition module, a data processing module, a hidden danger identification and analysis module and an alarm module, wherein the data acquisition module, the data processing module, the hidden danger identification and analysis module and the alarm module are connected in sequence, the data acquisition module is used to collect data, the data processing module is used to process the data collected by the data acquisition module, the hidden danger identification and analysis module is used to perform hidden danger identification and analysis according to the processing results of the data processing module, and the alarm module is used to decide whether to issue an alarm according to the hidden danger identification and analysis results of the hidden danger identification and analysis module.

2. The power communication resource management and hidden danger identification and analysis system according to claim 1, characterized in that: The data acquisition module is precisely configured to achieve seamless connection with various acquisition devices in the power communication network, and can automatically and efficiently extract valuable communication resource data from these devices; the data includes the real-time operating status of the communication equipment: whether the equipment is online, operating temperature and signal strength; network topology information: detailed description of the connection relationship between each node, providing a basis for network optimization and troubleshooting; and bandwidth utilization: including the real-time bandwidth occupancy rate and historical peak value of each link.

3. The power communication resource management and hidden danger identification and analysis system according to claim 1, characterized in that: The data processing module first performs strict cleaning of the original data to eliminate erroneous, duplicate or invalid information to ensure the accuracy and reliability of subsequent analysis; the cleaned data will then be properly stored in a high-performance database for instant query and to provide rich material for long-term trend analysis; on this basis, the data processing module also uses advanced algorithms to perform multi-dimensional analysis of the data, including time series analysis and association rule mining, and presents the analysis results to users in the form of intuitive and easy-to-understand charts, reports, etc.

4. The power communication resource management and hidden danger identification and analysis system according to claim 1, characterized in that: The hidden danger identification and analysis module uses deep learning and data mining technology to conduct in-depth analysis of massive data and capture hidden danger signals that may threaten network security from subtle details. By building complex predictive models, the module identifies potential risks such as equipment aging, overload operation, or abnormal traffic patterns, and automatically assigns priority and urgency to the hidden dangers based on their severity, scope of impact, and possible consequences.

5. The power communication resource management and hidden danger identification and analysis system according to claim 1, characterized in that: The hidden danger identification and analysis module generates an alarm message, and the alarm module will be activated immediately to send the alarm message containing hidden danger details, recommended treatment measures and urgency to the designated operation and maintenance personnel or management team through multiple channels such as SMS, email, and instant messaging software.

6. An identification and analysis method of the power communication resource management and hidden danger identification and analysis system according to any one of claims 1 to 5, characterized in that: The following steps are involved: Step 1, the data acquisition module collects data related to communication equipment, optical paths and optical cables; Step 2: The data processing module preprocesses the collected data, including data cleaning and data conversion. Cleaning the data removes missing values ​​and outliers, and data conversion applies normalization or standardization to ensure that the data is on the same scale. Step 3, the data processing module calculates the outlier detection Z-Score value of each data point for the preprocessed data; Step 4: The data processing module determines the threshold of the outlier according to specific requirements, where the threshold is defined by setting the boundary of the Z-Score; Step 5, the hidden danger identification and analysis module identifies data points with Z-Score values ​​exceeding the set threshold, which are considered outliers, indicating potential hidden dangers or abnormal situations; Step 6: The hidden danger identification and analysis module further analyzes and processes the identified outliers; Step 7: The hidden danger identification and analysis module identifies and analyzes the hidden dangers of specific power communication resources based on the outlier detection Z-Score results; Step 8: The alarm module obtains a fault assessment basis value based on the calculation result Re in step 7, and performs different feedback processing according to the following range values.

7. The identification and analysis method of the power communication resource management and hidden danger identification and analysis system according to claim 6, characterized in that: The relevant data in step 1 includes equipment status data, performance indicator data and transmission quality data.

8. The identification and analysis method of the power communication resource management and hidden danger identification and analysis system according to claim 6, characterized in that: The specific implementation method of step 3 is: The Z-Score is a statistic used to measure how different a data point is from the mean; Apply the Z-Score formula to each data point: Z=(X-μ) / σ Where X is the value of the data point, μ is the mean of the data set, and σ is the standard deviation of the data set.

9. The identification and analysis method of the power communication resource management and hidden danger identification and analysis system according to claim 6, characterized in that: The specific implementation method of step 7 is: Re=(E*Q*EQ_v+T*T_v+O*O_v+EN*EN_v) / (EQ_v+T_v+O_v+EN_v) Among them, E and Q are the number and frequency of outliers: identify whether the outliers are individual abnormalities or there are systemic problems; EQ_v is the weight of the number and frequency of outliers in the analysis; T is the duration of the outliers: observe the duration of the outliers to determine whether it is a temporary problem or a long-term hidden danger; T_v is the weight of the duration of the outliers in the analysis; O is the correlation with other indicators: O_v is the weight of the correlation with other indicators; EN is the relevant environmental factors; EN_v is the weight of the relevant environmental factors.

10. The identification and analysis method of the power communication resource management and hidden danger identification and analysis system according to claim 6, characterized in that: The specific implementation method of step 8 is: [0,0.5] is provided and recorded normally; (0,0.7] is to warn and record that there may be abnormalities in communication resources; (0.7, 0.9] is a serious warning and records that the communication resources are abnormal and need manual processing; (0.9,1.0) is a fault notification.

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