CN117118853A - Communication state monitoring and management method and system for power communication - Google Patents
Communication state monitoring and management method and system for power communication Download PDFInfo
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Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/14—Network analysis or design
- H04L41/142—Network analysis or design using statistical or mathematical methods
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0805—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability
- H04L43/0811—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability by checking connectivity
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/16—Threshold monitoring
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
Abstract
The application discloses a communication state monitoring and managing method and a system for electric power communication, wherein the method comprises the following steps: collecting transmission information of the communication node, generating a node data transmission state index, monitoring the data state transmitted by the communication node, and generating a risk data transmission node grade; step two: and acquiring self information of the communication node, generating a node self state index, monitoring the communication node self state index, and generating a risk node grade. According to the application, the communication nodes of power communication are overhauled regularly to obtain the risk data transmission node grade and the risk node grade, so that the comprehensive risk grade of the nodes is judged, and the nodes with the high risk data transmission node grade and the high risk node grade are overhauled simultaneously, so that the nodes can meet the low risk data transmission node grade and the low risk node grade simultaneously, and the interruption of the communication between the high risk data transmission node grade and the high risk node grade is effectively prevented.
Description
Technical Field
The application relates to the technical field of communication supervision, in particular to a communication state monitoring and managing method and system for power communication.
Background
Currently, integrated automation systems for power stations are typically composed of subsystems of individual stations and communicate with a dispatch center. The subsystem of each station collects the information of each device at the station end and then uploads the information to the dispatching center, the dispatching center stores and analyzes the obtained data, and the station is remotely controlled and monitored through the subsystem of each station.
The prior art has the following defects:
most of the electric power communication systems in the prior art do not monitor and manage the electric power communication state in advance, when communication interruption occurs, the communication situation can be known, serious hysteresis exists, when the communication is interrupted suddenly, data loss transmitted between subsystems of all stations and a dispatching center and real-time monitoring failure of the dispatching center to the stations can be caused, serious trouble is caused to electric power dispatching, and therefore the practicability is poor;
secondly, when communication is interrupted or seriously abnormal, the communication nodes are generally checked one by one, the working efficiency is low, the time spent is long, and the communication efficiency is seriously delayed.
The above information disclosed in the background section is only for enhancement of understanding of the background of the disclosure and therefore it may include information that does not form the prior art that is already known to a person of ordinary skill in the art.
Disclosure of Invention
The application aims to provide a communication state monitoring and managing method and system for power communication, which are used for solving the problems in the background technology.
In order to achieve the above object, the present application provides the following technical solutions: a communication state monitoring and managing method for power communication comprises the following steps:
step one: collecting transmission information of the communication node, generating a node data transmission state index, monitoring the data state transmitted by the communication node, and generating a risk data transmission node grade;
step two: collecting self information of the communication node, generating a node self state index, monitoring the communication node self state index, and generating a risk node grade;
step three: acquiring risk data transmission node grades and risk node grades of n nodes, comprehensively analyzing the risk data transmission node grades and the risk node grades, and determining the comprehensive risk grade of the nodes;
step four: and re-analyzing the nodes, generating a risk index, and judging the risk of the nodes in the comprehensive risk level.
Preferably, in the first step, the information collected by the data collection module includes efficiency of node data transmission and quality of node transmission, the quality of node transmission includes frequency of node data transmission errors and frequency of node data transmission packet loss, and after the information collection, the data collection module marks the collected efficiency of node data transmission asThe quality of the collected node transmission is marked as +.>The frequency of the data transmission errors of the collected nodes is marked as +.>Marking the frequency of packet loss of node data transmission as +.>。
Preferably, will、/>、/>、/>Carrying out normalization formula processing after dimensionless processing to obtain a node data transmission state index, which is marked as +.>The specific formula of the treatment is as follows:
；
in the method, in the process of the application,is an efficiency parameter of node data transmission, wherein +.>Data quantity transmitted for data node, +.>Time required for transmitting the data quantity, +.>And e1 and e2 are preset proportionality coefficients of the efficiency parameter of node data transmission and the quality parameter of node transmission, and e1 and e2 are both larger than 0.
Preferably, the node data transmission state indexComparing with preset node data transmission state indexes YZ1 and YZ2, wherein YZ1<YZ2, when node data transmission status index +.>When the data transmission state index is larger than YZ2, the data acquisition module generates low-risk data transmission node grade, and when the node data transmission state index +.>Greater than or equal toYZ1, when less than or equal to YZ2, indicate that the node data transmission state index is bad, the data acquisition module generates a risk data transmission node grade, when the node data transmission state index +.>And when the data transmission state index is smaller than YZ1, indicating that the node data transmission state index is worst, and generating a high-risk data transmission node grade by the data acquisition module.
Preferably, in the second step, the collected information includes a change amplitude of node throughput and node load, and after the information is collected, the data collection module respectively marks the change amplitude of the collected node throughput and the node load as、/>Will be、/>Carrying out normalization formula processing after dimensionless processing to obtain a node self state index, and marking the node self state index as +.>The specific formula of the treatment is as follows:
；
wherein b1 and b2 are weight coefficients of node throughput and node load respectively, and b1 and b2 are both greater than 0.
Preferably, the node itself state indexComparing with preset node data transmission state indexes YZ3 and YZ4, wherein YZ3<YZ4, when node self State index +.>When the node self state index is larger than YZ4, the node self state index is shown to be optimal, the data acquisition module generates low risk node grades, and when the node self state index is +.>When YZ3 and YZ4 are larger than or equal to each other, the node self state index is not good, the data acquisition module generates a risk node grade, and when the node self state index is +.>And when the node state index is smaller than YZ3, indicating that the node state index is worst, and generating a high risk node grade by the data acquisition module.
Preferably, in the third step, if any node has both the high risk data transmission node level and the high risk node level, the first analysis module identifies the node as a comprehensive high risk level; if any node has a high risk data transmission node level and a medium risk node level, a medium risk data transmission node level and a high risk node level, and a medium risk data transmission node level and a medium risk node level, the first analysis module identifies the node as a comprehensive medium risk level; the remaining cases the first analysis module identifies the node as an integrated low risk level.
Preferably, in the fourth step, the risk index is generated for the nodes in the integrated risk level as follows, and the analysis formula is:
；
in the method, in the process of the application,is an efficiency parameter of node data transmission, wherein +.>Data quantity transmitted for data node, +.>Required for transmitting the data volumeTime (F)>Quality parameters transmitted for nodes, < >>、/>The change amplitude of the node throughput and the node load are respectively +.>For node data transmission status parameter->And f1 and f2 are preset proportionality coefficients of the node data transmission state parameter and the node self state parameter, and f1 and f2 are both larger than 0.
Preferably, the analysis results inComparing with a set threshold YZ, if yes>The risk index of the node is high, which indicates that the risk index of the node is close to the comprehensive high risk level, and the second analysis module marks the node through a marking module in the node and sorts and records the marked node according to the risk index from small to large through a sorting module in the node, if yes>Above threshold YZ, a node risk index indicating a risk level in the aggregate is low, at which point the second analysis module does not flag the node.
The communication state monitoring management system for power communication comprises a first data acquisition module, a second data acquisition module, a first analysis module and a second analysis module;
the first data acquisition module acquires transmission information of the communication node, generates a node data transmission state index, monitors the data state transmitted by the communication node and generates a risk data transmission node grade;
the second data acquisition module acquires self information of the communication node, generates a node self state index, monitors the communication node self state index and generates a risk node grade;
the first analysis module comprehensively analyzes the acquired risk data transmission node grades and risk node grades of the n nodes, and determines the comprehensive risk grade of the node;
and the second analysis module re-analyzes the nodes, generates a risk index and judges the risk of the nodes in the comprehensive risk level.
In the technical scheme, the application has the technical effects and advantages that:
1. the comprehensive risk level of the node is judged by periodically overhauling the communication node of the power communication to acquire the risk data transmission node level and the risk node level, and the node with the high risk data transmission node level and the high risk node level is overhauled, so that the node simultaneously meets the low risk data transmission node level and the low risk node level, and the interruption of the communication between the high risk data transmission node level and the high risk node level is effectively prevented;
2. the risk indexes obtained through analysis are compared with the set threshold value, the nodes of the comprehensive risk level are re-analyzed, the node with the higher risk index in the node of the comprehensive risk level is marked and selected, when the subsequent communication is interrupted, the nodes are firstly checked according to the checking sequence from small to large for the risk indexes of the marked nodes, so that the damaged nodes can be quickly checked out, the working efficiency is higher, the time spent is shorter, and the high-efficiency communication efficiency is ensured.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments described in the present application, and other drawings may be obtained according to these drawings for a person having ordinary skill in the art.
FIG. 1 is a schematic block diagram of the present application.
Fig. 2 is a flow chart of the method of the present application.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments may be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. The drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more example embodiments. In the following description, numerous specific details are provided to give a thorough understanding of example embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the aspects of the disclosure may be practiced without one or more of the specific details, or with other methods, components, steps, etc. In other instances, well-known structures, methods, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the disclosure.
The application provides a communication state monitoring and managing method for electric power communication as shown in fig. 1 and 2, which comprises the following steps:
the first data acquisition module acquires transmission information of the communication node, generates a node data transmission state index, monitors the data state transmitted by the communication node, and generates a risk data transmission node grade;
the information collected by the first data collection module comprises the efficiency of node data transmission and the quality of node transmission, and the nodeThe transmission quality comprises the frequency of node data transmission errors and the frequency of node data transmission packet loss, and after information acquisition, the data acquisition module marks the acquired node data transmission efficiency asThe quality of the collected node transmission is marked as +.>The frequency of the data transmission errors of the collected nodes is marked as +.>Marking the frequency of packet loss of node data transmission as +.>Will->、/>、/>、/>Carrying out normalization formula processing after dimensionless processing to obtain a node data transmission state index, which is marked as +.>The specific formula of the treatment is as follows:
；
in the method, in the process of the application,is an efficiency parameter of node data transmission, wherein +.>Is data ofData amount transmitted by node->Time required for transmitting the data quantity, +.>For the quality parameters transmitted by the nodes, e1 and e2 are the efficiency parameters of the data transmission of the nodes and the preset proportionality coefficients of the quality parameters transmitted by the nodes, and e1 and e2 are both larger than 0;
it should be noted that, the higher the efficiency of node data transmission, the higher the quality of node transmission, i.e. the higher the state index of node data transmission, which indicates that the better the state of node data transmission, the lower the efficiency of node data transmission, the lower the quality of node transmission, i.e. the lower the state index of node data transmission, which indicates that the worse the state of node data transmission.
The more the frequency of node data transmission errors is, the more the frequency of node data transmission packet losses is, which indicates that the quality of node transmission is worse, the less the frequency of node data transmission errors is, the less the frequency of node data transmission packet losses is, which indicates that the quality of node transmission is higher;
during maintenance, node data transmission information of n nodes is obtained, and after the node data transmission state indexes are calculated, the node data transmission state indexes are calculatedComparing with preset node data transmission state indexes YZ1 and YZ2, wherein YZ1<YZ2, when node data transmission status index +.>When the data transmission state index is larger than YZ2, the data acquisition module generates low-risk data transmission node grade, and when the node data transmission state index +.>When YZ1 and YZ2 are larger than or equal to each other, the node data transmission state index is indicated to be poor, the data acquisition module generates a risk data transmission node grade, and when node data is transmittedInput State index->When the data transmission state index is smaller than YZ1, the node data transmission state index is indicated to be worst, and the data acquisition module generates a high-risk data transmission node grade;
the second data acquisition module acquires self information of the communication node, generates a node self state index, monitors the communication node self state index and generates a risk node grade;
the information acquired by the second data acquisition module comprises the change amplitude value of the node throughput and the node load, and after the information is acquired, the data acquisition module respectively marks the change amplitude value of the acquired node throughput and the node load as、/>Will be、/>Carrying out normalization formula processing after dimensionless processing to obtain a node self state index, and marking the node self state index as +.>The specific formula of the treatment is as follows:
；
wherein b1 and b2 are weight coefficients of node throughput and node load respectively, and b1 and b2 are both greater than 0;
the throughput of the node refers to the number of messages which can be processed by the node in unit time, the throughput of the node can be changed along with the use of the node, and the larger the change amplitude of the throughput of the node is, the larger the number of messages which can be processed by the node in unit time is, the worse the state index of the node is, and the worse the state of the node is, and otherwise, the better the state index of the node is;
the node load refers to the current resource occupation condition of the node, and the higher the node load is, the worse the state index of the node is indicated, and the worse the state of the node is indicated, otherwise, the better the state index of the node is indicated;
during maintenance, the self state information of n nodes is acquired, and after the self state indexes of the nodes are calculated, the self state indexes of the nodes are calculatedComparing with preset node data transmission state indexes YZ3 and YZ4, wherein YZ3<YZ4, when node self State index +.>When the node self state index is larger than YZ4, the node self state index is shown to be optimal, the data acquisition module generates low risk node grades, and when the node self state index is +.>When YZ3 and YZ4 are larger than or equal to each other, the node self state index is not good, the data acquisition module generates a risk node grade, and when the node self state index is +.>When the node state index is smaller than YZ3, the node state index is the worst, and the data acquisition module generates a high risk node grade;
the first analysis module comprehensively analyzes the risk data transmission node level and the risk node level to determine the comprehensive risk level of the node;
after acquiring the risk data transmission node grades and the risk node grades of the n nodes, further analyzing the risk data transmission node grades and the risk node grades through a first analysis module, wherein the analysis process is as follows:
if any node has both a high risk data transmission node level and a high risk node level, the first analysis module identifies the node as a comprehensive high risk level; if any node has a high risk data transmission node level and a medium risk node level, a medium risk data transmission node level and a high risk node level, and a medium risk data transmission node level and a medium risk node level, the first analysis module identifies the node as a comprehensive medium risk level; the remaining cases the first analysis module identifies the node as an integrated low risk level.
It should be noted that, the comprehensive high risk level is higher than the high risk data transmission node level and the high risk node level, that is, the probability of risk occurrence of the node corresponding to the comprehensive high risk level is maximum; the explanation of the comprehensive risk level is the same as above;
the comprehensive risk level of the node is judged by periodically overhauling the communication node of the power communication to acquire the risk data transmission node level and the risk node level, and the node with the high risk data transmission node level and the high risk node level is overhauled, so that the node simultaneously meets the low risk data transmission node level and the low risk node level, and the interruption of the communication between the high risk data transmission node level and the high risk node level is effectively prevented;
the first analysis module transmits the nodes of the comprehensive risk level to the second analysis module, re-analyzes the nodes through the second analysis module, generates a risk index, and judges the risk of the nodes of the comprehensive risk level;
the process of generating risk indexes for the nodes of the comprehensive risk level by the second analysis module is as follows, and the analysis formula is as follows:
；
in the method, in the process of the application,is an efficiency parameter of node data transmission, wherein +.>Data quantity transmitted for data node, +.>Time required for transmitting the data quantity, +.>Quality parameters transmitted for nodes, < >>、/>The change amplitude of the node throughput and the node load are respectively +.>For node data transmission status parameter->For the state parameters of the node, f1 and f2 are preset proportionality coefficients of the data transmission state parameters of the node and the state parameters of the node, and f1 and f2 are both larger than 0;
from analysisComparing with a set threshold YZ, if yes>The risk index of the node is high, which indicates that the risk index of the node is close to the comprehensive high risk level, and the second analysis module marks the node through a marking module in the node and sorts and records the marked node according to the risk index from small to large through a sorting module in the node, if yes>A node risk index greater than a threshold YZ, indicating a low risk level in the composite, at which time the second analysis module does not label the node;
according to the method, the nodes of the comprehensive risk level can be re-analyzed, the nodes with higher risk indexes in the nodes of the comprehensive risk level are marked and selected, when the subsequent communication is interrupted, the risk indexes of the marked nodes are firstly checked according to the checking sequence from small to large, so that the damaged nodes can be quickly checked out, the working efficiency is higher, the time spent is shorter, and the high-efficiency communication efficiency is ensured.
The communication state monitoring management system for power communication comprises a first data acquisition module, a second data acquisition module, a first analysis module and a second analysis module;
the first data acquisition module acquires transmission information of the communication node, generates a node data transmission state index, monitors the data state transmitted by the communication node and generates a risk data transmission node grade;
the second data acquisition module acquires self information of the communication node, generates a node self state index, monitors the communication node self state index and generates a risk node grade;
the first analysis module comprehensively analyzes the acquired risk data transmission node grades and risk node grades of the n nodes, and determines the comprehensive risk grade of the node;
the second analysis module re-analyzes the nodes, generates a risk index and judges the risk of the nodes in the comprehensive risk level;
the specific method and flow for implementing the corresponding functions based on each module included in the communication state monitoring management system for power communication are detailed in the embodiment of the communication state monitoring management method for power communication described above, and are not repeated herein.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.
While certain exemplary embodiments of the present application have been described above by way of illustration only, it will be apparent to those of ordinary skill in the art that modifications may be made to the described embodiments in various different ways without departing from the spirit and scope of the application. Accordingly, the drawings and description are to be regarded as illustrative in nature and not as restrictive of the scope of the application, which is defined by the appended claims.
It is noted that relational terms such as first and second, and the like, if any, are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
It should be understood that, in various embodiments of the present application, the sequence numbers of the foregoing processes do not mean the order of execution, and the order of execution of the processes should be determined by the functions and internal logic thereof, and should not constitute any limitation on the implementation process of the embodiments of the present application.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application.
Claims (7)
1. The communication state monitoring and managing method for power communication is characterized by comprising the following steps:
step one: collecting transmission information of the communication node, generating a node data transmission state index, monitoring the data state transmitted by the communication node, and generating a risk data transmission node grade;
in the first step, the information collected by the data collection module comprises the efficiency of node data transmission and the quality of node transmission, the quality of node transmission comprises the frequency of node data transmission errors and the frequency of node data transmission packet loss, and after the information collection, the data collection module marks the collected efficiency of node data transmission asThe quality of the collected node transmission is marked as +.>The frequency of the data transmission error of the collected nodeSub-nominal +.>Marking the frequency of packet loss of node data transmission as +.>；
Will be、/>、/>、/>Carrying out normalization formula processing after dimensionless processing to obtain a node data transmission state index, which is marked as +.>The specific formula of the treatment is as follows:
；
in the method, in the process of the application,is an efficiency parameter of node data transmission, wherein +.>Data quantity transmitted for data node, +.>Time required for transmitting the data quantity, +.>For the quality parameters transmitted by the nodes, e1 and e2 are the efficiency parameters of the data transmission of the nodes and the preset proportionality coefficients of the quality parameters transmitted by the nodes, and e1 and e2 are both larger than 0;
step two: collecting self information of the communication node, generating a node self state index, monitoring the communication node self state index, and generating a risk node grade;
in the second step, the acquired information comprises the change amplitude of the node throughput and the node load, and after the information is acquired, the data acquisition module respectively marks the change amplitude of the acquired node throughput and the node load as、/>Will->、/>Carrying out normalization formula processing after dimensionless processing to obtain a node self state index, and marking the node self state index as +.>The specific formula of the treatment is as follows:
；
wherein b1 and b2 are weight coefficients of node throughput and node load respectively, and b1 and b2 are both greater than 0;
step three: acquiring risk data transmission node grades and risk node grades of n nodes, comprehensively analyzing the risk data transmission node grades and the risk node grades, and determining the comprehensive risk grade of the nodes;
step four: and re-analyzing the nodes, generating a risk index, and judging the risk of the nodes in the comprehensive risk level.
2. The method for monitoring and managing communication status for power communication according to claim 1, wherein the node data transmission status index isComparing with preset node data transmission state indexes YZ1 and YZ2, wherein YZ1<YZ2, when node data transmission status index +.>When the data transmission state index is larger than YZ2, the data acquisition module generates low-risk data transmission node grade, and when the node data transmission state index +.>When YZ1 and YZ2 are larger than or equal to each other, the node data transmission state index is indicated to be poor, the data acquisition module generates a risk data transmission node grade, and when the node data transmission state index is +.>And when the data transmission state index is smaller than YZ1, indicating that the node data transmission state index is worst, and generating a high-risk data transmission node grade by the data acquisition module.
3. The method for monitoring and managing communication states for power communication according to claim 1, wherein the node's own state index is used for the communicationComparing with preset node data transmission state indexes YZ3 and YZ4, wherein YZ3<YZ4, when node self State index +.>When the state index of the node is larger than YZ4, the state index of the node is shown to be optimal, and the data acquisition module generatesAt low risk node level, when node self state index +.>When YZ3 and YZ4 are larger than or equal to each other, the node self state index is not good, the data acquisition module generates a risk node grade, and when the node self state index is +.>And when the node state index is smaller than YZ3, indicating that the node state index is worst, and generating a high risk node grade by the data acquisition module.
4. A communication status monitoring and managing method for electric power communication according to claim 3, wherein in step three, if any node has both a high risk data transmission node level and a high risk node level, the first analysis module identifies the node as an integrated high risk level; if any node has a high risk data transmission node level and a medium risk node level, a medium risk data transmission node level and a high risk node level, and a medium risk data transmission node level and a medium risk node level, the first analysis module identifies the node as a comprehensive medium risk level; the remaining cases the first analysis module identifies the node as an integrated low risk level.
5. The method for monitoring and managing a communication state for power communication according to claim 4, wherein in the fourth step, a risk index is generated for the nodes of the integrated risk level as follows, and the analysis formula is:
；
in the method, in the process of the application,is an efficiency parameter of node data transmission, wherein +.>Data quantity transmitted for data node, +.>Time required for transmitting the data quantity, +.>Quality parameters transmitted for nodes, < >>、/>The change amplitude of the node throughput and the node load are respectively +.>For node data transmission status parameter->And f1 and f2 are preset proportionality coefficients of the node data transmission state parameter and the node self state parameter, and f1 and f2 are both larger than 0.
6. The method for monitoring and managing power communication according to claim 5, wherein the analysis results inComparing with a set threshold YZ, if yes>The risk index of the node is high, which indicates that the risk index of the node is close to the comprehensive high risk level, when the risk index of the node is smaller than or equal to the threshold YZ, the second analysis module marks the node through the marking module in the second analysis module, and the marking module marks the node according to the risk index from small to small through the ordering module in the second analysis moduleThe large order is ordered and recorded, if yes +.>Above threshold YZ, a node risk index indicating a risk level in the aggregate is low, at which point the second analysis module does not flag the node.
7. The communication state monitoring and management system for power communication according to any one of claims 1 to 6, comprising a first data acquisition module, a second data acquisition module, a first analysis module, and a second analysis module;
the first data acquisition module acquires transmission information of the communication node, generates a node data transmission state index, monitors the data state transmitted by the communication node and generates a risk data transmission node grade;
the second data acquisition module acquires self information of the communication node, generates a node self state index, monitors the communication node self state index and generates a risk node grade;
the first analysis module comprehensively analyzes the acquired risk data transmission node grades and risk node grades of the n nodes, and determines the comprehensive risk grade of the node;
and the second analysis module re-analyzes the nodes, generates a risk index and judges the risk of the nodes in the comprehensive risk level.
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