Method and system for dynamically analyzing and checking reliability of important services of power communication network

Abstract

The invention discloses a method and a system for dynamically analyzing and checking the reliability of important services of a power communication network, which relate to the technical field of reliability analysis, and comprise the following steps: establishing an interface with a power communication network management system, automatically collecting topological structures, network element equipment, optical cable resources, service modes and alarm information, and combining operation parameters and environmental data to obtain a dynamic analysis result; constructing a basic data warehouse of multi-source fusion; according to a hierarchical structure of equipment, optical cables, channels, businesses and lines in the basic data warehouse, constructing a multi-level reliability index; and based on the multi-level reliability index, generating a plurality of candidate routes meeting constraint conditions by using a graph neural network and a deep reinforcement learning algorithm, and executing prior reliability evaluation on a generation result. The method supports time-space related reliability evaluation of the electric power communication operation mode, realizes automatic check analysis when the mode is opened and routes are alternative, and reduces non-objectivity and uncertainty caused by manual participation in a traditional method.

Description

Technical Field

[0001] This invention relates to the field of reliability analysis technology, specifically to a method and system for dynamic analysis and verification of the reliability of important services in power communication networks. Background Technology

[0002] With the construction of new power systems, under the large-scale power grid situation, the stable operation of the power grid highly depends on the reliable operation of secondary systems such as protection and safety control. The reliable operation of these secondary systems, in turn, highly depends on the robust support of the communication network. There is a strong mutual influence and correlation between these two systems. In recent years, with the continuous expansion of the power communication network, the increasing number of important services it carries, and the deepening of resource sharing among networks at all levels, the complexity and diversification of communication circuits have been continuously increasing. The power transmission backbone network carries important services such as relay protection and safety and stability control systems, and is a crucial support for ensuring the safe and stable operation of the power grid. The extensive application of safety and stability, relay protection, and other services has placed even higher reliability requirements on the communication network.

[0003] Currently, there is a lack of effective intelligent support methods for reliability assessment and risk response strategies in power communication network services. There is a lack of comprehensive and unified reliability analysis and evaluation models and indicator systems for power communication network services; reliability and risk lack unified quantitative standards. Furthermore, there is a lack of dynamic reliability analysis and security verification methods for important power communication network services, making online real-time risk analysis and strategy response impossible. Moreover, there is a lack of intelligent automatic orchestration and scheme generation technology for important power communication service modes to achieve automatic orchestration and generation of power communication service modes. For these reasons, the reliability analysis and verification capabilities of power communication are severely inadequate in the current analysis of new power systems and large power grid integration. There is an urgent need to research key technologies for dynamic reliability analysis and security verification of important power communication network services, and to apply these technologies to system functional modules to comprehensively improve the ability to assess and respond to power communication risks. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by this invention is that existing power communication network service reliability assessment and risk response strategies lack effective intelligent support methods, lack a comprehensive and unified power communication network service reliability analysis and evaluation model and indicator system, and lack unified quantitative standards for reliability and risk; there is a lack of dynamic reliability analysis and security verification methods for important power communication network services, making it impossible to achieve online real-time risk analysis and strategy response; and there is no intelligent automatic orchestration and scheme generation technology for important power communication service modes to achieve automatic orchestration and generation of power communication service modes.

[0006] To address the aforementioned technical problems, this invention provides the following technical solution: a method for dynamic analysis and verification of the reliability of important services in a power communication network, comprising: establishing an interface with the power communication network management system to automatically collect topology, network element equipment, optical cable resources, service modes, and alarm information; combining operating parameters and environmental data to construct a multi-source fusion basic data warehouse; constructing multi-level reliability indicators based on the hierarchical structure of equipment, optical cables, channels, services, and lines in the basic data warehouse; and generating multiple candidate routes that meet the constraints using graph neural networks and deep reinforcement learning algorithms based on the multi-level reliability indicators, and performing a pre-reliability assessment on the generated results.

[0007] As a preferred embodiment of the dynamic analysis and verification method for the reliability of important services in power communication networks described in this invention, the multi-level reliability indicators include: overall average service reliability indicator, cross-sectional average service reliability indicator, line service reliability, service reliability configuration indicator, channel reliability indicator, node reliability indicator, equipment reliability indicator, and optical cable reliability indicator.

[0008] As a preferred embodiment of the dynamic analysis and verification method for the reliability of important services in power communication networks described in this invention, the overall average reliability index and the cross-sectional average reliability index include: Verification of the overall average reliability index, which reflects the average stable operation capability of the relevant services by calculating the arithmetic mean of the reliability of each service, is expressed as follows: , in, This indicates the number of services for which average reliability needs to be calculated. Indicates the first The reliability of this service.

[0009] The cross-section service average reliability index verification is performed by calculating the arithmetic mean of the service reliability of each line in the cross-section, reflecting the overall service stability capability of the cross-section. The reliability is expressed by the reliability output of each line connected in parallel as follows: , in, This indicates the number of all service lines participating in the evaluation within the cross-section. Indicates the first section The reliability of each business line.

[0010] As a preferred embodiment of the dynamic analysis and verification method for the reliability of important services in power communication networks described in this invention, the line service reliability and service reliability configuration indicators include: line service reliability verification, which reflects the overall stability capability of the line based on the services carried on the line, through the probability of at least one service operating normally, expressed as follows: , in, This indicates the total number of services carried on the line. Indicates the first The reliability of this service.

[0011] Service reliability configuration index verification, based on the reliability of components the service depends on, reflects the overall stability of the service by the probability that at least one component is operating normally. When the service depends on independent channels, the service will not be interrupted as long as at least one channel is working normally. The stability of the service is measured by excluding the simultaneous failure of all channels, as follows: , in, This indicates the total number of components that the business depends on. Indicates the first The reliability of each component.

[0012] As a preferred embodiment of the dynamic reliability analysis and verification method for important services in power communication networks described in this invention, the channel reliability index and node reliability index include: the channel reliability index verification is the joint probability of all equipment nodes being normal and all optical cable segments being normal, expressed as: , in, This indicates the total number of device nodes contained in the channel. This represents the reliability of the c-th device node. The total number of optical cable segments contained in the channel. Indicates the first The reliability of each optical cable segment.

[0013] Node reliability verification involves equipment and optical cables, which represent the reliability of different physical carriers in the communication channel. Together, the equipment and optical cables determine the overall stable operation capability of the channel.

[0014] As a preferred embodiment of the dynamic reliability analysis and verification method for important services in power communication networks described in this invention, the equipment reliability indicators include: Equipment reliability verification is expressed as follows: , , , , in, Indicates the fault flag bit. This refers to the number of times a device or board model appears on the negative list. Indicates the fan coefficient of the equipment. Indicates the temperature coefficient of the equipment. The optical power coefficient, This is the bit error rate coefficient. This indicates the total number of components in the equipment system that participate in the reliability assessment. Refers to the first The weights of each component Indicates the first The reliability of each component Indicates the temperature value. Indicates the optical power value. This indicates the bit error rate.

[0015] Multi-data factors affecting equipment reliability include power supply dualization. Computer room temperature Commissioning time Number of failures in the past three years Is there any maintenance or repair arrangements for the equipment? ; Dual power supply If yes, it is 1; otherwise, it is 0.5.

[0016] Computer room temperature Represented as: ), in, Indicates temperature.

[0017] Commissioning time Represented as: , in, This refers to the number of years the equipment has been in operation.

[0018] Number of failures in the past three years Represented as: , in, This represents the number of malfunctions that have occurred in the past three years.

[0019] Is there any maintenance or repair schedule for the equipment? If yes, it is 0.95; otherwise, it is 1.

[0020] As a preferred embodiment of the dynamic reliability analysis and verification method for important services in power communication networks described in this invention, the optical cable reliability index includes optical cable reliability verification, which involves weighted summation of the reliability of each component of the optical cable and then converting the summation into a percentage, reflecting the overall capability of the optical cable to perform communication functions under specified conditions. , , , If configured as a 1+1 MSP primary / backup optical path, with fiber cores carried on the same optical cable, considering the probability that neither the primary nor backup fiber cores will fail simultaneously in the event of cable failure, the output reliability is expressed as: , If configured as a 1+1 MSP (Master and Backup) optical path, with fiber cores carried on different optical cables, the parallel reliability of the two optical cables is expressed as follows: , otherwise .

[0021] in, For fault identification bits, Therefore, the number of times the fiber optic cable manufacturer's model, junction box model, and joint installation manufacturer appear on the negative list is as follows. For 1+1 MSP, ensure the main and backup optical paths are in place. Number of fiber cores in the optical cable This is the optical cable loss coefficient. This is the icing coefficient. This represents the total number of components in an optical cable. Indicates the serial number of the component. Refers to the first The weights of each component Indicates the first The reliability of each component Indicates the loss value. Indicates the icing coefficient. This indicates the overall reliability index of the optical cable. This indicates the reliability index of optical fiber communication cables.

[0022] Multi-data factors affecting the reliability of optical cables include the optical cable voltage level. Fiber optic cable type Is it located in an area with abnormal climate? Fiber optic cable length Commissioning time Number of failures in the past three years .

[0023] Optical cable voltage level =1 for 1000kV, 0.95 for 500kV, and 0.9 for 220kV; Fiber optic cable type =OPGW is 1, the rest are 0.9; Is it located in an abnormal climate zone? If yes, the value is 0.8; otherwise, it is 1. Fiber optic cable length =1 for distances below 50km, 0.95 for distances between 50-200km, and 0.9 for distances above 200km; Commissioning time Represented as: , in, This refers to the number of years the fiber optic cable has been in operation. Number of failures in the past three years Represented as: , in, This represents the total number of components in an optical cable.

[0024] Another objective of this invention is to provide a dynamic reliability analysis and verification system for important services in power communication networks. This system can construct a quantitative evaluation model and configuration indicators for the reliability analysis of important services in power communication networks. It comprehensively analyzes factors such as dual power supply for equipment, equipment room temperature, commissioning time, number of failures in the past three years, maintenance or mode arrangements, optical cable voltage level, optical cable type and length, icing, typhoons, and other abnormal weather conditions. This enables multi-level, multi-dimensional, and comprehensive reliability analysis and evaluation, including multi-layered nesting of optical cables, equipment, channels, services, lines / sections, and the overall network. It supports automatic dynamic verification and analysis of the reliability of services related to the spatiotemporal nature of power communication operation modes, and enables automatic reliability verification analysis of alternative routes generated when a mode is activated. This reduces the objectivity and uncertainty caused by manual intervention in traditional methods, and improves the reliability analysis and optimization capabilities of communication networks.

[0025] As a preferred embodiment of the dynamic analysis and verification system for the reliability of important services in power communication networks according to the present invention, it includes: a data acquisition unit, a basic database construction unit, and a dynamic verification unit; the data acquisition unit is used to acquire verification data for important communication services; the basic database construction unit is used to establish a reliability verification basic database based on the verification data for important communication services; the dynamic verification unit is used to perform overall average reliability verification, cross-sectional service average reliability verification, line service reliability verification, service reliability configuration index verification, channel reliability verification, node reliability verification, equipment reliability verification, and optical cable reliability verification on the reliability verification basic database, forming automatic analysis results for dynamic verification of service reliability, and realizing reliability verification analysis including mode routing generation.

[0026] Another objective of this invention is to provide a dynamic analysis and verification device for the reliability of important services in a power communication network, comprising a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement a method for dynamic analysis and verification of the reliability of important services in a power communication network.

[0027] Another object of the present invention is to provide a storage medium for dynamic analysis and verification of the reliability of important services in a power communication network, wherein a computer program is stored thereon, and when the computer program is executed by a processor, the steps of the dynamic analysis and verification method for the reliability of important services in a power communication network are implemented.

[0028] The beneficial effects of this invention are:

[0029] The dynamic reliability analysis and verification method for important services in power communication networks provided by this invention constructs a quantitative evaluation model and configuration indicators for the reliability analysis of important services in power communication networks. It comprehensively analyzes factors such as dual power supply for equipment, equipment room temperature, commissioning time, number of failures in the past three years, maintenance or mode arrangement, optical cable voltage level, optical cable type and length, icing, typhoons and other abnormal weather conditions. It achieves multi-level, multi-dimensional, and comprehensive reliability analysis and evaluation, including optical cables, equipment, channels, services, lines / sections and overall multi-layer nesting of power communication networks. It supports spatiotemporal reliability assessment of power communication operation modes and realizes automatic verification analysis when routes are selected during mode activation. It reduces the objectivity and uncertainty caused by manual intervention in traditional methods and improves the reliability analysis and optimization capabilities of communication networks. Attached Figure Description

[0030] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 The above is an overall flowchart of a dynamic analysis and verification method for the reliability of important services in a power communication network, provided in Embodiment 1 of the present invention.

[0032] Figure 2 This is a framework diagram of an index model for a dynamic analysis and verification method for the reliability of important services in a power communication network, provided in Embodiment 1 of the present invention.

[0033] Figure 3 This is a schematic diagram of a dynamic analysis and security verification method for the reliability of important services in a power communication network, as provided in Embodiment 1 of the present invention.

[0034] Figure 4 The flowchart of dynamic analysis of service reliability is provided for a method for dynamic analysis and verification of the reliability of important services in power communication networks according to Embodiment 1 of the present invention.

[0035] Figure 5The flowchart of the dynamic verification analysis of the reliability of important services in a power communication network provided in Embodiment 1 of the present invention is shown.

[0036] Figure 6 This is a service mode orchestration technical architecture diagram of a dynamic analysis and verification system for the reliability of important services in a power communication network, provided in Embodiment 1 of the present invention. Detailed Implementation

[0037] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0038] Example 1, referring to Figures 1-6 As an embodiment of the present invention, a method for dynamic analysis and verification of the reliability of important services in a power communication network is provided, comprising: S1: By establishing an interface with the power communication network management system, it automatically collects topology, network element equipment, optical cable resources, service methods and alarm information, and combines operating parameters and environmental data to build a multi-source integrated basic data warehouse.

[0039] Furthermore, by constructing a quantitative evaluation model and configuration indicators for the reliability analysis of important services in the power communication network, this method comprehensively analyzes factors such as dual power supply for equipment, equipment room temperature, commissioning time, number of failures in the past three years, maintenance or mode arrangements, optical cable voltage level, optical cable type and length, icing, typhoons, and other abnormal weather conditions. This enables multi-level, multi-dimensional, and comprehensive reliability analysis and evaluation, including optical cables, equipment, channels, services, lines / sections, and overall multi-layer nesting in the power communication network. It supports automatic analysis and evaluation of the dynamic verification of service reliability related to the time and space of power communication operation modes, and enables automatic verification and analysis of the reliability of alternative routes generated when a mode is activated. This reduces the objectivity and uncertainty caused by manual intervention in traditional methods and improves the reliability analysis and optimization capabilities of the communication network.

[0042] S2: Based on the hierarchical structure of equipment, optical cables, channels, services, and lines in the basic data warehouse, construct multi-level reliability indicators.

[0043] Furthermore, a framework for a dynamic analysis and verification method for the reliability of important services in power communication networks is established. Its main features include: overall average service reliability index, cross-sectional average service reliability index, line service reliability, service reliability configuration index, channel reliability index, node reliability index, equipment reliability index, and optical cable reliability index. For example... Figure 2 As shown:

[0044] Overall business average reliability ( This metric measures the average reliability of multiple services at an overall level, including protection and security control services. It calculates the arithmetic mean of the reliability of each service to comprehensively reflect the average stable operation capability of a series of related services. It is expressed as: , First, sum the reliability of all services, then divide by the total number of services to get the average value, and finally multiply by 100% to convert it into a percentage.

[0045] in, This indicates the number of services for which average reliability needs to be calculated. Indicates the first The reliability of a service is usually expressed as a probability (with a value between 0 and 1). For example, if the reliability of a service is 0.98, it means that the probability of the service being able to operate normally under the specified conditions and within the specified time is 98%.

[0046] Suppose a company has 3 core businesses, whose reliability includes business 1: =0.95; Business 2: =0.92; Business 3: =0.98; therefore, the overall average reliability of the business is: .

[0047] That is, the overall average reliability of these three services is 95%.

[0048] First, the overall average reliability of the business ( It is intuitive. The calculation results directly reflect the average reliability probability of multiple services; the closer the value is to 100%, the higher the overall average reliability of the services. Furthermore, it emphasizes the concept of "average," ensuring fairness. This indicator treats all services equally, without considering differences in the importance of individual services, reflecting the overall level simply through averaging. Therefore, it is more suitable for evaluating service portfolios with similar importance that require a comprehensive understanding of average reliability performance, and for quickly assessing overall reliability levels when it is not necessary to differentiate service importance.

[0049] It should be noted that the reliability of cross-sectional services ( The reliability average (RAA) is an indicator used to evaluate the average reliability of multiple service lines within a specific "section," including inter-provincial sections for protection and security control services. It reflects the overall stable operation capability of the section by calculating the arithmetic mean of the service reliability of each line within that section. Its reliability is calculated from the reliability of each line operating in parallel. It is expressed as: , First, sum the service reliability of all lines within the cross-section, then divide by the total number of lines. The average value is obtained, and then multiplied by 100% to convert it into a percentage.

[0050] in, This indicates the number of all service lines participating in the evaluation within the cross-section. Indicates the first section The reliability of a service line is usually expressed as a probability (with a value between 0 and 1). For example, if the reliability of a line is 0.96, it means that the probability that the line can transmit services normally under specified conditions and within a specified time is 96%.

[0051] Suppose a communication interface contains 4 service transmission lines. The reliability of each line includes: Route 1: =0.93; Route 2: =0.95; Route 3: =0.91; Route 4: =0.97; Then the reliability of the service at this section is: .

[0052] That is, the average reliability of the four services within this section is 94%.

[0053] A cross-section typically refers to a region or set of paths with specific boundaries or functions (such as a transmission cross-section in a communication network or a hub cross-section in a transportation system). The service lines within a cross-section collectively undertake the services of that region and transmit or process tasks. By averaging the reliability of each line, the overall service reliability level of the cross-section is intuitively reflected. The closer the value is to 100%, the higher the average reliability of the lines within the cross-section, and the stronger the overall service stability of the cross-section. Compared to the overall average service reliability, cross-section service reliability focuses more on the specific scope of the "cross-section," providing an average assessment of the service reliability of multiple lines within a local area. This indicator uses an arithmetic mean, assuming that each line within the cross-section has an equal weight in its impact on the overall system. It is suitable for evaluating cross-sections with similar line importance and is commonly used in network planning and regional fault analysis.

[0054] It should also be noted that the reliability of line services ( This refers to the reliability of multiple services operating in parallel on a line. It is an indicator that measures the overall reliability of a single line, i.e., the reliability under the combined effect of multiple services. A higher line service reliability value indicates a stronger ability to withstand overall failure under the support of multiple services, making it suitable for scenarios emphasizing "continuous line availability." It reflects the line's comprehensive stability capability based on the probability that "at least one service operates normally" among the multiple services carried on the line. It is expressed as: , Subtract the probability of all services failing simultaneously from 1 to get the probability of "at least one service operating normally", which is the line service reliability. Finally, multiply by 100% to convert it into a percentage.

[0055] in, This indicates the total number of services carried on the line (i.e., the number of services that need to be considered simultaneously on the line). Indicates the first The reliability of a service (value between 0 and 1), i.e., the probability that the service will operate normally under specified conditions. Indicates the first The unreliability of a service, i.e., the probability of service failure. This indicates the probability that all services will fail simultaneously.

[0056] Furthermore, suppose there are 3 services on a certain line, and the reliability includes service 1: =0.9 (failure probability 0.1); Business 2: =0.8 (failure probability 0.2); Service 3: =0.7 (failure probability 0.3); therefore, the reliability of this line service is calculated as follows: the probability of all services failing simultaneously is: Line service reliability .

[0057] That is, the probability that "at least one service on the line is operating normally" is 99.4%.

[0058] The essence of line service reliability is "the probability of a line not completely failing." Its core logic is: as long as one service on the line can operate normally, the line is considered to have a certain degree of effective service capability. The higher the line service reliability value, the stronger the line's ability to withstand overall failure when supported by multiple services. It is suitable for evaluating lines that require the joint support of multiple services—as long as one service on the line can work normally, the line has not completely lost its function. It is used in scenarios emphasizing "continuous line availability," such as: in communication transmission lines, which may simultaneously carry multiple services such as voice, data, and video, the line still has value as long as one service can be transmitted. In power distribution lines, if multiple users or devices are connected, the line has not completely failed as long as one user or device can supply power normally.

[0059] It should be noted that the service reliability configuration index ( The reliability index (RDI) is an indicator that measures the overall reliability of a service. It is calculated using the parallel reliability method for all channels of the service, and the RDI should not be lower than 0.995. It reflects the overall stability of the service based on the probability that "at least one component is operating normally," based on the reliability of multiple components (or units) upon which the service depends. That is, when the service relies on... When multiple components (such as transmission links, device ports, routing paths, etc.) are not functioning, as long as at least one channel is working properly, the service will not be interrupted. Therefore, The calculation does not rely on the probability of "all channels being normal," but rather measures business stability by "excluding the extreme case of all channels failing simultaneously." As long as at least one of the critical components of the business is functioning correctly, the business will not completely fail. This is expressed as: , Subtract the probability of all components failing simultaneously from 1 to get the probability of "at least one component working properly", which is the overall reliability of the business. Finally, multiply by 100% to convert it into a percentage.

[0060] in, This indicates the total number of components that the business depends on. Indicates the first The reliability of a component (value between 0 and 1), that is, the probability that the component will function normally under specified conditions. : No. The unreliability of a component, that is, the probability of component failure. This represents the probability that all components fail simultaneously.

[0061] Suppose a data transmission service relies on 3 channel components, and the reliability of each component includes component 1 (the main channel): Component 2 (Backup Channel 1): Component 3 (Backup Channel 2): The service reliability configuration index is calculated as follows: failure probability of each component: The probability of all components failing simultaneously. Business reliability .

[0062] This means that the reliability of the service is 99.856%, which implies that under specified conditions, the probability of the service being completely interrupted due to the simultaneous failure of all components is extremely low, and the overall stability is very strong.

[0063] The essence of service reliability configuration metrics is "the probability of a service not completely failing." It is suitable for evaluating services supported by multiple components "in parallel"—as long as one component is functioning properly, the service can maintain basic functionality. For example, in communication services, multiple transmission nodes, servers, or channels (such as a primary channel + a backup channel) may be relied upon. As long as one channel is functioning normally, the service can transmit.

[0064] In short, Transforming the "limited reliability of a single channel" into "high reliability of services" through parallel logic is a core quantitative tool for redundant design and quality control in communication networks. Reliability configuration not only reflects the overall reliability assessment but also the specific aspects and locations of potential vulnerabilities. By drilling down into reliability data, specific defects can be located, allowing for targeted network optimization. This primarily manifests at the channel and node levels.

[0065] It should also be noted that channel reliability ( The reliability of a communication channel (such as a transmission link) is calculated by cascading reliability of all nodes along the channel. These nodes are the optical cables, equipment, and other components that the channel passes through, and the reliability of these nodes is cascaded together. The core logic is "cascaded reliability"—the channel is composed of multiple nodes (including optical cable segments and equipment units) connected sequentially; only when all nodes are functioning normally simultaneously can the channel maintain effective transmission capability. The two core types of nodes corresponding to the channel are the reliability of "equipment" and "optical cable." Channel reliability is the joint probability of "all equipment nodes functioning normally" and "all optical cable segments functioning normally" (both must be satisfied simultaneously), expressed as: , The product of the reliability of the two types of nodes is used to express the value, and finally multiplied by 100% to convert it into a percentage.

[0066] in, This indicates the total number of device nodes in the channel (e.g., if a link passes through 3 switches, then...). =3), This represents the reliability of the c-th device node (with a value between 0 and 1), which is the probability that the device (such as a router, switch, server, etc.) will work normally under specified conditions (refer to the definition of "device reliability" above). The total number of optical fiber segments contained in the channel (e.g., if a link is connected by 2 optical fiber segments, then...) =2), Indicates the first The reliability of an optical cable segment (with a value between 0 and 1), that is, the probability that the optical cable segment (such as intercity optical cable, jumper fiber in equipment room, etc.) will transmit without failure under specified conditions. This represents the probability that all device nodes are working normally at the same time (since the devices are independent, the reliability needs to be multiplied together). This represents the probability that all optical cable segments are working normally at the same time (similarly, the optical cable segments are independent, and the reliability is multiplied).

[0067] Suppose a communication channel is configured as follows: the device nodes include two routers, with respective reliability values... =0.99、 =0.98. The optical cable segment includes one trunk optical cable segment with a reliability of... =0.995.

[0068] The channel reliability is then calculated as: Total reliability of device nodes: Overall reliability of the optical cable segment: =0.995.

[0069] Channel reliability (Keep one decimal place).

[0070] That is, the probability of the channel working normally is 96.5%, and its reliability is determined by all equipment and optical cable segments, and is lower than that of the node with the highest reliability (99.5%).

[0071] Core Indicators of Channel Design It directly reflects the fault tolerance of a communication channel and is the basis for evaluating link stability in network planning (e.g., backbone network channels need to achieve higher stability). (to reduce frequent interruptions).

[0072] The foundational channel for business reliability is the carrier of the business. The higher the level, the more reliable the business operations ( The lower the difficulty of achieving the target (e.g., a single high-reliability channel can reduce the number of parallel channels required for the business).

[0073] The basis for optimizing weak links is through decomposition. The composition (contributions of equipment and optical cables) can locate low-reliability nodes in the channel (such as a section of old optical cable) and make targeted improvements to enhance the overall channel quality.

[0074] In conclusion, By integrating the reliability of all nodes in the channel through "serial logic," it is a key indicator for measuring the effectiveness of a single communication link and an important quantitative tool for communication network architecture design and operation and maintenance optimization.

[0075] Furthermore, node reliability metrics: In channel reliability ( In the calculation, "equipment" and "optical cable" serve as two core nodes, representing the reliability of different physical carriers in the communication channel. Together, they determine the overall stable operation capability of a channel. The following is a detailed analysis of the reliability of these two types of nodes.

[0076] It should be noted that the equipment reliability ( The reliability index (RDI) is a core indicator used to comprehensively evaluate the overall reliability of a device system. Its calculation is based on a weighted average method, taking into account the differences in importance among the components of the equipment. The RDI for communication transmission equipment should be no less than 0.93. This index quantifies "the ability of equipment to perform its specified functions under specified conditions and within a specified time," providing a crucial basis for equipment design, maintenance, and upgrades. It is expressed as: , , , , Equipment reliability is determined by weighting the various influencing factors. With the corresponding reliability coefficient ( From 1 to Multiply the results and sum them, then multiply by 100% to convert them into percentage form.

[0077] in, This indicates a fault flag, indicating a situation where the device is severely affected by power failure, damage to the channel via the board port, or other serious issues. =0, in all other usable cases =1; The number of times a device or board model appears on the negative list. The negative list can be automatically generated by the system based on the fault summary, or manually set based on publicly available family defect models, requirements such as domestic production rather than domestic production, etc. This indicates the device fan factor, which defaults to 1. This represents the equipment temperature coefficient, which defaults to 1. This is the optical power coefficient, which defaults to 1. This is the bit error rate coefficient, which defaults to 1. This indicates the total number of components (such as subsystems, key components, etc.) involved in the reliability assessment of the equipment system. Refers to the first The weight of each component is usually determined based on factors such as the importance of the component in the equipment system and its impact on the overall function. The sum of the weights of all components is generally 1. Indicates the first The reliability of a component is usually expressed as a probability (with a value between 0 and 1). For example, if the reliability of a component is 0.95, it means that the component has a 95% probability of working properly under specified conditions and within a specified time.

[0078] This represents the device fan coefficient, which defaults to 1. If the device fan status can be obtained, and there is an anomaly, such as a fan alarm, the coefficient is 0.5.

[0079] This represents the equipment temperature coefficient, which defaults to 1. If the temperature of the equipment is available, set the temperature value to tmp (°C). If it is not greater than 60°C, it is considered acceptable. When it is greater than this value, the equipment temperature coefficient decreases as the temperature rises.

[0080] The optical power coefficient is 1 by default. If the power of the light emitted by the board or the light amplifier / receiver can be obtained, the optical power value is set to lp (dBm). If it is not less than 20dBm, it is considered acceptable. If it is less than this value, the optical power decreases and the attenuation coefficient decreases.

[0081] This is the bit error rate coefficient, which defaults to 1. If a 2M bit error rate for the channel is available, the bit error rate is set to err (dB). If it is less than or equal to 10⁻⁹ dB, it is considered normal. When it exceeds this value, the bit error rate increases, and the bit error rate coefficient decreases.

[0082] It should also be noted that this weighted calculation method can more scientifically reflect the reliability of the equipment system because it takes into account the differences in the impact of different components on the whole, which is more in line with the actual situation than simply taking the average value.

[0083] The main factors affecting equipment reliability indicators are: 1. Dual power supply The value is 1 if yes, and 0.5 otherwise. Dual power supply refers to a load being powered by two independent circuits. These two circuits are considered independent and unaffected by each other in terms of power supply safety. This design aims to ensure that if either power source fails, the other can seamlessly take over, guaranteeing a continuous power supply.

[0084] 2. Computer room temperature : ), in, Indicates temperature.

[0085] The environmental temperature requirements for communication power rooms are even stricter, needing to be maintained within the range of 10℃-30℃. High temperatures significantly reduce equipment reliability when they exceed 30℃, potentially leading to malfunctions, data loss, or even fire risks. For example, when the temperature in the computer room reaches above 35℃, network equipment performance decreases by 25%, and battery life is shortened, requiring immediate cooling measures.

[0086] 3. Commissioning time (years) : , in, This refers to the number of years the equipment has been in operation; the industry standard specifies a design life of 10 years for transmission equipment.

[0087] Servers are typically designed for a lifespan of 5 to 10 years, which can be extended to more than 10 years with proper maintenance.

[0088] Communication lines (including fiber optic cables, utility poles, etc.) are covered by a 20-year warranty.

[0089] Transmission equipment (such as switches and wireless subsystems) has a lifespan of 10 years.

[0090] 4. Number of failures in the past three years : , in, The number of failures over the past three years shows a negative correlation between the number of communication equipment failures and reliability.

[0091] The number of failures in communication equipment is negatively correlated with its reliability: the more failures, the lower the reliability.

[0092] 5. Is there any maintenance or repair schedule for the equipment? If yes, the value is 0.95; otherwise, it is 1.

[0093] Equipment with work orders has a certain risk of failure.

[0094] Furthermore, the overall reliability index of optical cables ( Essentially, the reliability index (RDI) is calculated by "weighted summation" of the reliability of each component of the optical cable, then converted into a percentage. This RDI ultimately reflects the overall capability of the optical cable to perform its communication function under specified conditions (such as environment, time, and load). The RDI of a communication optical cable should not be lower than 0.95, usually expressed as a percentage (%). A higher value indicates better overall reliability. This is expressed as: , , , By using a weighted summation method, the result is multiplied by 100% to convert it into a percentage. This integrates the reliability of each component of the optical cable into an overall reliability index, facilitating the assessment and comparison of the cable's reliability level.

[0095] If configured as a 1+1 MSP primary / backup optical path, with fiber cores carried on the same optical cable, considering the probability that neither the primary nor backup fiber cores will fail simultaneously in the event of cable failure, the output reliability is expressed as: , If configured as a 1+1 MSP (Master and Backup) optical path, with fiber cores carried on different optical cables, the parallel reliability of the two optical cables is expressed as follows: , otherwise ; in, This is a fault flag bit; Therefore, the number of times the optical cable manufacturer's model, junction box model, and joint installation manufacturer appear on the negative list; For 1+1 MSP, ensure the main and backup optical paths are in place. Number of fiber cores in the optical cable The optical cable loss coefficient; This is the icing coefficient; This represents the total number of components in an optical cable. Indicates the serial number of the component. Refers to the first The weight of each component reflects its contribution or importance to the overall reliability of the optical cable. The weights may be determined based on failure mode analysis, historical failure data, expert evaluation, etc. Indicates the first The reliability of a component is usually expressed as a decimal or percentage, representing the probability that the component will perform its intended function under specified conditions and within a specified time.

[0096] This is a fault indicator bit; it is used when there are serious issues such as fiber optic cable breakage. =0, in all other usable cases The value is 1.

[0097] Therefore, the number of times the optical cable manufacturer's model, junction box model, and joint installation manufacturer appear on the negative list can be automatically generated by the system based on fault summaries, or manually set based on publicly available family defect models, requirements such as requiring domestic products instead of domestic ones, etc.

[0098] The number of failures in optical fiber communication cables is negatively correlated with their reliability; that is, the more failures, the lower the reliability.

[0099] If the fiber optic cable manufacturer, junction box model, or connector installation manufacturer is on the negative list, it means that the fiber optic cable manufacturer, junction box model, or connector installation manufacturer has experienced failures in the past. The probability of failure occurring again will increase, and the reliability will decrease.

[0100] This is the optical cable loss coefficient, which is 1 by default. If the loss value is available, it is set to los (dB / km). If it is ≤0.18dB / km, it is considered acceptable. If it is greater than this value, the attenuation coefficient decreases as the loss increases.

[0101] This represents the icing coefficient, which defaults to 1. If the icing coefficient is available, it is set as a percentage of the line design value d, denoted as ice (%). A value ≤ 50% is considered acceptable; when it exceeds this value, increasing the icing coefficient decreases. The relationship between ice thickness and temperature is mainly reflected in the duration of the temperature remaining below 0°C and the heat dissipation efficiency of the ice layer. The duration of the temperature affects the ice thickness, which increases as the temperature remains below 0°C. For example, when the temperature is stable at -10°C, the ice thickness increases exponentially over time, and a significant ice layer can form in approximately 80 days.

[0102] It should be noted that this weighted calculation allows for a comprehensive consideration of the impact of each component, preventing the reliability of a single part from masking the overall problem. It can be used for reliability assessments during the optical cable design phase, comparisons of different optical cable solutions, and reliability analysis during operation and maintenance. Furthermore, factors influencing reliability include: for each component... Influencing factors include material properties (such as the tensile strength of the optical fiber and the aging resistance of the sheath), manufacturing processes (such as the splicing quality of the joints), operating environment (temperature, humidity, corrosion, mechanical stress), and maintenance level. (Weight) The determination of the weight needs to be combined with the actual situation. For example, in a strong mechanical stress environment, the weight of the reinforcement may be higher; in a humid environment, the weight of the sheath may be higher.

[0103] The main factors affecting the reliability of optical cables are: 1. Optical cable voltage level : =1000kV:1;500kV:0.95;220kV:0.9, The base value for 1000kV substation equipment is 1, the base value for 500kV is 0.95, and the base value for 220kV is 0.9.

[0104] 2. Optical cable type : =OPGW:1; Others:0.9

[0105] OPGW is 1, and the others are 0.9.

[0106] 3. Is it located in an area prone to abnormal weather conditions such as icing or typhoons? : =Yes: 0.8; No: 1

[0107] The relationship between ice thickness and temperature is mainly reflected in the duration of sustained temperatures below 0°C and the heat dissipation efficiency of the ice layer. The duration of sustained temperatures affects ice thickness, which increases as the temperature remains below 0°C. For example, when the temperature is stable at -10°C, the ice thickness increases exponentially over time, and a significant ice layer can form in about 80 days.

[0108] 4. Fiber optic cable length : =Below 50kM: 1; 50-200kM: 0.95; Above 200kM: 0.9

[0109] That is, the fiber optic cable length is 1 for less than 50kM, 0.95 for 50-200kM, and 0.9 for more than 200kM.

[0110] 5. Commissioning time (years) : , in, This refers to the number of years the optical cable has been in operation. The industry standard for the design life of communication lines is 20 years.

[0111] Servers are typically designed to last 5 to 10 years, but with proper maintenance, this can be extended to more than 10 years.

[0112] Communication lines (including fiber optic cables, utility poles, etc.) are covered by a 20-year warranty.

[0113] Transmission equipment (such as switches and wireless subsystems) has a lifespan of 10 years.

[0114] 6. Number of failures in the past three years : , in, The total number of components in an optical cable is represented by the number of failures, and the reliability of an optical cable is negatively correlated with its number of failures.

[0115] The number of failures in communication optical cables is negatively correlated with their reliability; the more failures, the lower the reliability.

[0116] S3: Based on multi-level reliability indicators, use graph neural networks and deep reinforcement learning algorithms to generate multiple candidate routes that meet the constraints, and perform a pre-reliability assessment on the generated results.

[0117] Furthermore, based on the verification and early warning results of existing communication methods, and using routing selection technologies such as graph neural networks and deep reinforcement learning algorithms, we will study intelligent method orchestration methods such as automatic routing detours and method optimization to achieve incremental intelligent orchestration and adjustment of communication methods, automatically generate communication method adjustment schemes, and realize intelligent application technology support such as intelligent method arrangement including the "three routes" for protection services.

[0118] This paper proposes a reliability analysis method for backbone communication systems of large power grids, driven by graph technology, by constructing reliability models, mining hidden danger data, and assessing the spatiotemporal correlation of operation and maintenance. It studies dynamic reliability analysis algorithms and risk response strategies for important services in the power communication network. The paper also conducts model design for the entire process of communication network dispatching and operation, researches real-time intelligent analysis algorithms based on a reliability analysis and evaluation index system, and studies intelligent auxiliary decision-making and risk response strategies for communication dispatching and operation under complex operating conditions, supporting functions such as route recommendation during planning and auxiliary analysis during operation. Reliability dynamic analysis and safety verification methods are as follows: Figure 3 As shown.

[0119] The analysis process is as follows: Figure 4 As shown: The dynamic verification analysis of business reliability includes three triggering methods: the first is the periodic work plan configured by the system, which is automatically initiated; the second is triggered when there is a maintenance, defect or mode work order; the third is triggered by severe weather conditions, such as icing, typhoon or high temperature in the area; and the fourth is triggered automatically when there are important root alarm analysis results, such as LOS alarm.

[0120] After starting the analysis, obtain the business list, perform reliability analysis for each important business, start the analysis according to the business reliability configuration index method in the index model, and obtain the reliability index.

[0121] If the reliability is greater than 90%, record the reliability configuration index data and analyze the next business.

[0122] If the reliability is low, below 80%, first determine if the data is incomplete, fragmented, or inaccurate. If issues arise due to unmaintained data attributes or relationships, mark this business as having a data quality problem, set the reliability to pending, initiate a data governance work order, and re-analyze the relevant data before re-analyzing this business. If the data is accurate but the reliability is low, record the reliability configuration index data and continue analyzing other business processes.

[0123] After analyzing all business operations, the reliability of major business categories is calculated according to the indicator model calculation method. The overall business reliability index is obtained by comprehensive averaging, which reflects the overall assessment of the reliability of important business operations of the system.

[0124] Record services with reliability issues in the unified resource alarm and operation verification database (based on TMS data). Archive reliability configuration data to reflect the specific aspects and locations of potential problems. Drill down into reliability data to pinpoint specific defects for targeted network optimization.

[0125] Based on the verification and early warning results of existing communication methods, and using routing selection technologies such as graph neural networks and deep reinforcement learning algorithms, we study intelligent mode orchestration methods such as automatic routing detours and mode optimization to achieve incremental intelligent orchestration and adjustment of communication methods, automatically generate communication mode adjustment schemes, and realize intelligent application technology support such as intelligent mode arrangement including the "three routes" for protection services.

[0126] Building upon previous reliability capability assessment models and network reliability analysis, this work further analyzes the bearer relationships and inter-network connectivity of power grid communication services, and studies automatic routing planning technology for cross-level communication services in long-distance power grids, achieving hierarchical and collaborative communication operation planning and intelligent orchestration. The verification process is as follows: Figure 5 .

[0127] There are two triggering methods for automatic business mode orchestration and solution generation: the first is automatic triggering when a defect occurs and a detour is required; the second is manual triggering when the mode is being executed.

[0128] Specify the business start and end points. When arranging the startup method, if it is automatically triggered, the system will automatically determine the business start and end points; if it is manually triggered, the method programmer will specify the business start and end points.

[0129] Determine whether to bypass certain nodes. Nodes can be manually bypassed as needed; alternatively, the system can automatically bypass them based on factors such as node overload, expired age, effective dual power supply, location in areas prone to extreme weather, historical fault records, autonomous controllability, and whether the system would cause any of the three scenarios. This ensures that new routes meet reliability requirements. If bypassing certain nodes is determined, a generated node unavailability status will be set.

[0130] Generate a route with different optical cables, different power supplies, and different sites for selection.

[0131] After selecting a route, check whether this routing method reduces service reliability. The method is to perform a method replay. Under the current selected method, use the "Dynamic Verification and Analysis of Service Reliability" method to verify and analyze whether the reliability of the system, business category, and business has decreased. If the reliability decreases by more than 0.1%, mark the route as unusable and the route needs to be re-standardized.

[0132] Output a list of routing methods, sorted by reliability degradation. Record the results of the "Dynamic Verification Analysis of Business Reliability" and archive any changes in routing methods.

[0133] Live network data is extracted from the SG-TMS system as input for service fault analysis and intelligent optimization. Network planning and independence checks are performed based on intelligent routing technologies that guarantee different service reliability, and the network planning and optimization results are stored in a planning and optimization result database. For example... Figure 6 As shown.

[0134] Through standard interconnect interfaces, the system automatically imports network topology, network element equipment, fiber optic routes, channel circuits, service modes, equipment alarms, and other relevant information from the existing network into the SG-TMS system, providing foundational data for system network planning and analysis. Then, through the standard interface, the mode arrangement data is returned to the TMS system. The interconnect interface is a data query interface based on the data transmission and reception method, provided by the data sender and invoked by the data receiver. The data transmitted and received through the standard interconnect interface follows existing public information models related to power communication.

[0135] Example 2, an embodiment of the present invention, provides a dynamic analysis and verification system for the reliability of important services in a power communication network, including a data acquisition unit, a basic database construction unit, and a dynamic verification unit.

[0136] The data acquisition unit is used to acquire important communication service verification data, the basic database construction unit is used to establish a reliability verification basic database based on the important communication service verification data, and the dynamic verification unit is used to perform overall average reliability verification, cross-section service average reliability verification, line service reliability verification, service reliability configuration index verification, channel reliability verification, node reliability verification, equipment reliability verification, and optical cable reliability verification on the reliability verification basic database, forming automatic analysis results of dynamic service reliability verification, and realizing reliability verification analysis including mode routing generation.

[0137] This embodiment also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the dynamic analysis and verification method for the reliability of important services in the power communication network proposed in the above embodiment.

[0138] This embodiment also provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the dynamic analysis and verification method for the reliability of important services in the power communication network as proposed in the above embodiments.

[0139] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0140] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0141] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0142] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0143] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for dynamic analysis and verification of the reliability of important services in power communication networks, characterized in that, include: By establishing an interface with the power communication network management system, the system automatically collects topology, network element equipment, optical cable resources, service methods and alarm information, and combines operating parameters and environmental data to build a multi-source integrated basic data warehouse. Based on the hierarchical structure of equipment, optical cables, channels, services, and lines in the basic data warehouse, multi-level reliability indicators are constructed. Based on multi-level reliability indicators, graph neural networks and deep reinforcement learning algorithms are used to generate multiple candidate routes that meet the constraints, and the generated results are subjected to a pre-reliability assessment.

2. The method for dynamic analysis and verification of the reliability of important services in power communication networks as described in claim 1, characterized in that: The multi-level reliability indicators include, Overall average reliability index of services, average reliability index of cross-section services, reliability of line services, service reliability configuration index, channel reliability index, node reliability index, equipment reliability index, and optical cable reliability index.

3. The method for dynamic analysis and verification of the reliability of important services in power communication networks as described in claim 2, characterized in that: The overall average reliability index and the cross-sectional average reliability index of the service include, The overall average reliability index of the business is verified by calculating the arithmetic mean of the reliability of each business item, reflecting the average stable operation capability of the relevant business, as expressed as: ， in, This indicates the number of services for which average reliability needs to be calculated. Indicates the first The reliability of the business; The cross-section service average reliability index verification is performed by calculating the arithmetic mean of the service reliability of each line in the cross-section, reflecting the overall service stability capability of the cross-section. The reliability is expressed by the reliability output of each line connected in parallel as follows: ， in, This indicates the number of all service lines participating in the evaluation within the cross-section. Indicates the first section The reliability of each business line.

4. The method for dynamic analysis and verification of the reliability of important services in power communication networks as described in claim 2 or 3, characterized in that: The line service reliability and service reliability configuration indicators include: Line service reliability verification, based on the services carried on the line, reflects the overall stability of the line by the probability that at least one service is operating normally, expressed as follows: ， in, This indicates the total number of services carried on the line. Indicates the first The reliability of the business; Service reliability configuration index verification, based on the reliability of components the service depends on, reflects the overall stability of the service by the probability that at least one component is operating normally. When the service depends on independent channels, the service will not be interrupted as long as at least one channel is working normally. The stability of the service is measured by excluding the simultaneous failure of all channels, as follows: ， in, This indicates the total number of components that the business depends on. Indicates the first The reliability of each component.

5. The method for dynamic analysis and verification of the reliability of important services in power communication networks as described in claim 4, characterized in that: The channel reliability indicators and node reliability indicators include, The channel reliability index verification is the joint probability of all device nodes being normal and all optical cable segments being normal, expressed as: ， in, This indicates the total number of device nodes contained in the channel. This represents the reliability of the c-th device node. The total number of optical cable segments contained in the channel. Indicates the first The reliability of each optical cable segment; Node reliability verification involves equipment and optical cables, which represent the reliability of different physical carriers in the communication channel. Together, the equipment and optical cables determine the overall stable operation capability of the channel.

6. The method for dynamic analysis and verification of the reliability of important services in power communication networks as described in claim 5, characterized in that: The equipment reliability indicators include, Equipment reliability verification is expressed as follows: ， ， ， ， in, Indicates the fault flag bit. This refers to the number of times a device or board model appears on the negative list. Indicates the fan coefficient of the equipment. Indicates the temperature coefficient of the equipment. The optical power coefficient, This is the bit error rate coefficient. This indicates the total number of components in the equipment system that participate in the reliability assessment. Refers to the first The weights of each component Indicates the first The reliability of each component Indicates the temperature value. Indicates the optical power value. Indicates the bit error rate; Multi-data factors affecting equipment reliability include power supply dualization. Computer room temperature Commissioning time Number of failures in the past three years Is there any maintenance or repair arrangements for the equipment? ; Dual power supply If yes, the value is 1; otherwise, it is 0.

5. Computer room temperature Represented as: )， in, Indicates temperature; Commissioning time Represented as: ， in, The number of years the equipment has been in operation; Number of failures in the past three years Represented as: ， in, This represents the number of malfunctions that have occurred in the past three years. Is there any maintenance or repair schedule for the equipment? If yes, it is 0.95; otherwise, it is 1.

7. The method for dynamic analysis and verification of the reliability of important services in power communication networks as described in any one of claims 2, 3, 5, and 6, characterized in that: The optical cable reliability indicators include, Optical cable reliability verification involves weighted summation of the reliability of each component of the optical cable, followed by a percentage calculation. This percentage reflects the overall capability of the optical cable to perform communication functions under specified conditions, expressed as follows: ， ， ， If configured as a 1+1 MSP primary / backup optical path, with fiber cores carried on the same optical cable, considering the probability that neither the primary nor backup fiber cores will fail simultaneously in the event of cable failure, the output reliability is expressed as: ， If configured as a 1+1 MSP (Master and Backup) optical path, with fiber cores carried on different optical cables, the parallel reliability of the two optical cables is expressed as follows: ， otherwise ; in, For fault identification bits, Therefore, the number of times the fiber optic cable manufacturer's model, junction box model, and joint installation manufacturer appear on the negative list is as follows. For 1+1 MSP, ensure the main and backup optical paths are in place. Number of fiber cores in the optical cable This is the optical cable loss coefficient. This is the icing coefficient. This represents the total number of components in an optical cable. Indicates the serial number of the component. Refers to the first The weights of each component Indicates the first The reliability of each component Indicates the loss value. Indicates the icing coefficient. This indicates the overall reliability index of the optical cable. Indicates the reliability index of communication optical cables; Multi-data factors affecting the reliability of optical cables include the optical cable voltage level. Fiber optic cable type Is it located in an area with abnormal climate? Fiber optic cable length Commissioning time Number of failures in the past three years ; Optical cable voltage level =1 for 1000kV, 0.95 for 500kV, and 0.9 for 220kV; Fiber optic cable type =OPGW is 1, the rest are 0.9; Is it located in an abnormal climate zone? If yes, the value is 0.8; otherwise, it is 1. Fiber optic cable length =1 for distances below 50km, 0.95 for distances between 50-200km, and 0.9 for distances above 200km; Commissioning time Represented as: ， in, The number of years the optical cable has been in operation; Number of failures in the past three years Represented as: ， in, This represents the total number of components in an optical cable.

8. A dynamic reliability analysis and verification system for important services in a power communication network, employing the dynamic reliability analysis and verification method for important services in a power communication network as described in any one of claims 1 to 7, characterized in that: It includes a data acquisition unit, a basic database construction unit, and a dynamic verification unit; The data acquisition unit is used to acquire important communication service verification data; The basic database construction unit is used to establish a reliability verification basic database based on the communication important service verification data. The dynamic verification unit is used to perform overall average reliability verification, cross-sectional service average reliability verification, line service reliability verification, service reliability configuration index verification, channel reliability verification, node reliability verification, equipment reliability verification, and optical cable reliability verification on the reliability verification basic database, forming automatic analysis results of dynamic service reliability verification, and realizing reliability verification analysis including mode routing generation.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the dynamic analysis and verification method for the reliability of important services in the power communication network as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the dynamic analysis and verification method for the reliability of important services in the power communication network as described in any one of claims 1 to 7.

Images