CN112686773B - Electric power metering all-link key business anomaly positioning model construction method based on fusion business topology - Google Patents
Electric power metering all-link key business anomaly positioning model construction method based on fusion business topology Download PDFInfo
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Abstract
The invention relates to a method for constructing an electric power metering full-link key business anomaly positioning model based on fusion business topology, and belongs to the technical field of anomaly management. The method comprises the following steps: s1: preprocessing the full-link abnormal information; s2: analyzing the abnormal weight of the whole link; s3: and (5) curing the full-link abnormal positioning rule. According to the invention, abnormal data in key business of the metering link is adopted to perform preprocessing such as topology dimension reduction and abnormal digitization on the metering business link, a link with large weight area is excavated by introducing a metering link abnormal weight analysis algorithm, the abnormality on the link is subjected to root cause positioning, and finally the positioning result and rules are solidified, so that a set of metering full-link key business abnormal positioning model is constructed, the power company can be effectively assisted to more accurately find the root cause abnormality on the metering business link, the abnormality on the metering business link is efficiently detected and solved, and the stable operation of the power grid is ensured.
Description
Technical Field
The invention belongs to the technical field of electric power metering management, and particularly relates to a method for constructing an electric power metering full-link key business anomaly positioning model based on a fusion business topology.
Background
In a power grid system, a large number of anomalies are generated on metering service links, and the anomalies are generated in links such as network communication, data loading and terminal data acquisition; secondly, continuity, and abnormality of the system alarms in time sequence; thirdly, the relevance is that the anomalies on the whole link of the metering master station are generated on the nodes which are mutually connected in a ring, and the data flow and the call instruction generated by the anomalies are related to the link topological relation. However, these anomalies need to be located and resolved, and the lack of a method for searching the root cause from the link logic in processing these anomalies results in problems of large operation and maintenance workload, low efficiency, and the like. Therefore, the abnormal data in the metering service needs to be combined, and a set of metering full-link key service abnormal positioning model is urgently needed based on an abnormal weight area algorithm.
Disclosure of Invention
In view of the above, the present invention aims to provide a method for constructing an electric power metering all-link key business anomaly positioning model based on a converged business topology, which can overcome the problems existing in the prior art by constructing a set of metering all-link key business anomaly positioning models.
The invention aims at realizing the following technical scheme:
the method for constructing the electric power metering all-link key business anomaly positioning model based on the fusion business topology comprises the following steps:
step S1: preprocessing the full-link abnormal information;
step S2: constructing a full link abnormal weight analysis;
step S3: and (5) curing the full-link abnormal positioning rule.
In particular, in the step S1, the full link anomaly information preprocessing includes: constructing a metering full-link key service topological graph, metering full-link key service topological dimension reduction, metering full-link key service abnormal item acquisition, noise abnormal filtering and time sequence cutting, and finally normalizing to obtain an abnormal link for locating a root cause.
In particular, the step S2 specifically includes: and combining the key business abnormal items of the metering full link, and taking four core dimension reduction links as examples to analyze the abnormal weight of the full link.
In particular, the step S3 is specifically:
Repeatedly carrying out weight area calculation on the anomalies on the links through historical data, searching the source anomalies on the links in the links with high priority, and reserving a full-link path;
and comparing and verifying the root abnormality result with the abnormality investigation result in the daily operation and maintenance, and solidifying the matched abnormality positioning rule into a rule base.
In particular, the drawing of the metering all-link key service topological graph is based on two types of key service topological graphs of instruction issuing and task collecting according to a research and carding operation and maintenance manual and a front design instruction.
Particularly, the measurement full-link key service topology dimension reduction is divided into 4 core links of main mining task instruction issuing, main mining task information acquisition, supplementary mining task instruction issuing and supplementary mining task information acquisition.
In particular, the metering full link critical traffic anomaly item includes a full link state evaluation anomaly value and an operation and maintenance log anomaly item.
In particular, the full link anomaly weight analysis is performed by the following steps:
Step S21: abnormal link digital processing: and carrying out abstract processing on the abnormal chain after the sequence adjustment by combining the abnormal chain of the service information and the time information, deleting redundant service information and time information, using 1 to represent abnormal nodes, and 0to represent non-abnormal nodes to obtain an abstract 01 abnormal chain.
Step S22: and the calculation accuracy of the abnormal link is further improved by adding the weight to the special multiplying power assignment. The key business of the whole link is analyzed and measured and is adjusted by using an abnormal weight algorithm of three special links;
Step S23: the abnormal link weight area algorithm calculates the link abnormal association degree by the abnormal quantity and the abnormal density degree on the link links, and provides reference for abnormal positioning;
Step S24: abnormal link weight area calculation: evaluating and calculating links corresponding to abnormal items recorded by a log, displaying the links through a time stamp, digitizing abnormal information into standard chains represented by 0 and 1, obtaining the area of each chain through a weight area algorithm, and representing the abnormal priority of different chains so as to fulfill the aim of assisting operation and maintenance abnormality investigation;
Step S25: metering full link root cause anomaly location: setting link priority, and determining the source abnormality according to the time stamp sequence in the priority range.
In particular, in the step S22, the specific rules are as follows:
Single-node exception chains where the full chain has only a single exception node: multiplying c=1+abnormal node sequence/total node number;
There is a single abnormally dense segment and at the last post-exception chain of the chain: multiplying c=10 times the overall anomaly weight;
full exception chain in which each node of the full chain is abnormal: multiplying c=the overall anomaly weight is 10 times amplified.
In particular, in the step S24, the specific steps for calculating the link abnormality association degree are as follows:
step S231: the abnormal number is expressed as a width, and if the abnormal link node number N=1, the width a=1; if the number of abnormal links N >1, the width a=max (the number of abnormal links connected);
step S232: the degree of abnormal density is expressed in terms of length: if the abnormal number of the links N=1, the length b=1+the serial number of the link where the alarm node is located/the total number of the links, if the abnormal number of the links N >1, the length
Step S233: calculating the abnormal link weight area by using the following abnormal link weight area formula:
S＝a*b*100*c。
the beneficial effects of the invention are as follows:
The invention can construct a set of electric power metering full-link key business anomaly positioning model based on fusion business topology based on metering link anomaly data. In the practical process, the abnormality information on the link is preprocessed, then the weight area algorithm is used for quantitatively calculating the abnormality relevance of the abnormal link, the abnormality of the root cause is positioned by sequencing the priority of the abnormality relevance of the link, and finally the method for positioning the abnormality of the key business of the metering full link is determined by rule solidification, so that an electric company can be assisted to more accurately find the abnormality of the root cause on the metering link, the abnormality detection and processing efficiency of daily operation and maintenance work is improved, and the stable operation of the power grid is ensured.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof.
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For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings, in which:
FIG. 1 is a flow chart of the construction of the present invention;
FIG. 2 is a schematic diagram of a full link critical traffic topology;
FIG. 3 is a schematic diagram of topology dimension reduction of a metered full link critical service;
FIG. 4 is a schematic diagram of acquiring a metering full-link key business exception;
FIG. 5 is a diagram of an abnormal link digitizing process;
FIG. 6 is a comparison table of link location accuracy verification according to an embodiment;
FIG. 7 is an interface display diagram of an anomaly localization example.
Detailed Description
Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. It should be understood that the preferred embodiments are presented by way of illustration only and not by way of limitation.
As shown in fig. 1, the method for constructing the electric power metering all-link key business anomaly positioning model based on the fusion business topology comprises the following steps:
step S1: preprocessing the full-link abnormal information;
the full link anomaly information preprocessing comprises the following steps: constructing a metering full-link key service topological graph, metering full-link key service topological dimension reduction, metering full-link key service abnormal item acquisition, noise abnormal filtering and time sequence cutting, and finally normalizing to obtain an abnormal link for locating a root cause.
In this embodiment, as shown in fig. 2, the drawing of the metered full-link key service topology map is based on two types of key service topology maps, namely, instruction issuing and task acquisition, by researching and combing operation and maintenance manuals and pre-design description;
as shown in fig. 3, the measurement of the topology dimension reduction of the full-link key service is divided into 4 core links of issuing a main mining task instruction, acquiring main mining task information, issuing a supplementary mining task instruction and acquiring supplementary mining task information;
the acquisition of the key business abnormal item of the metering full link comprises the abnormal value of the full link state evaluation and the abnormal item of the operation and maintenance log, noise abnormality is removed, and the abnormal item is cut according to a time sequence to obtain the abnormal item with important attention of abnormality positioning, as shown in fig. 4.
Step S2: constructing a full link abnormal weight analysis; the method comprises the following steps:
and combining the key business abnormal items of the metering full link, and taking four core dimension reduction links as examples to analyze the abnormal weight of the full link.
In this embodiment, the full link anomaly weight analysis is performed by the following steps:
Step S21: abnormal link digital processing: and carrying out abstract processing on the abnormal chain after the sequence adjustment by combining the abnormal chain of the service information and the time information, deleting redundant service information and time information, using 1 to represent abnormal nodes, and 0 to represent non-abnormal nodes to obtain an abstract 01 abnormal chain. As shown in particular in fig. 5.
Step S22: and the calculation accuracy of the abnormal link is further improved by adding the weight to the special multiplying power assignment. The key business of the whole link is analyzed and measured and is adjusted by using an abnormal weight algorithm of three special links;
Step S23: the abnormal link weight area algorithm calculates the link abnormal association degree by the abnormal quantity and the abnormal density degree on the link links, and provides reference for abnormal positioning;
Step S24: abnormal link weight area calculation: evaluating and calculating links corresponding to abnormal items recorded by a log, displaying the links through a time stamp, digitizing abnormal information into standard chains represented by 0 and 1, obtaining the area of each chain through a weight area algorithm, and representing the abnormal priority of different chains so as to fulfill the aim of assisting operation and maintenance abnormality investigation;
Step S25: metering full link root cause anomaly location: setting link priority, and determining the source abnormality according to the time stamp sequence in the priority range.
In step S22, the specific rules are as follows:
(1) Single-node exception chains where the full chain has only a single exception node: multiplying c=1+abnormal node sequence/total node number;
(2) There is a single abnormally dense segment and at the last post-exception chain of the chain: multiplying c=10 times the overall anomaly weight;
(3) Full exception chain in which each node of the full chain is abnormal: multiplying c=the overall anomaly weight is 10 times amplified.
In step S23, the specific steps for calculating the link abnormality association degree are as follows:
The specific steps for calculating the link abnormality association degree are as follows:
step S231: the abnormal number is expressed as a width, and if the abnormal link node number N=1, the width a=1; if the number of abnormal links N >1, the width a=max (the number of abnormal links connected);
step S232: the degree of abnormal density is expressed in terms of length: if the abnormal number of the links N=1, the length b=1+the serial number of the link where the alarm node is located/the total number of the links, if the abnormal number of the links N >1, the length
Step S233: calculating the abnormal link weight area by using the following abnormal link weight area formula:
S＝a*b*100*c。
step S3: and (5) curing the full-link abnormal positioning rule. The method comprises the following steps:
Firstly, repeatedly carrying out weight area calculation on the anomalies on the links through historical data, searching the source anomalies on the links in the links with high priority for the anomalies, and reserving a full-link path;
and comparing and verifying the root abnormality result with the abnormality investigation result in the daily operation and maintenance, and solidifying the matched abnormality positioning rule into a rule base.
In the example, through historical abnormal data and operation and maintenance investigation logs, 5.32 ten thousand pieces of data from 10 days in 4 months in 2020 to 24 days in 4 months in 2020 are selected as training sample sets, and errors with higher importance degree in links of 5 types in 15 days are selected as abnormal information, which comprises the following steps: failure report of the task generation link, communication delay report of the front service link, low state evaluation of the task scheduling link and abnormal report of the group specification link. The anomaly information within 10 minutes before and after the anomaly information is selected, the anomaly information is acquired every 2 minutes, the link with the priority of the anomaly association degree set to be 3 in the ranking is finally analyzed, the proportion of the coverage root anomalies of the link exceeds 50%, the positioning accuracy of the 5 types of key anomalies is higher than 75%, and the accuracy and the effectiveness of the positioning rules of the key business anomalies of the electric power metering full link are verified, as shown in fig. 6.
In the abnormal positioning example, positioning information is visually displayed, positioning nodes and link information are displayed, operation and maintenance personnel are helped to check the source of abnormality, and an interface is shown in fig. 7.
It should be appreciated that embodiments of the invention may be implemented or realized by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer readable memory. The methods may be implemented in a computer program using standard programming techniques, including a non-transitory computer readable storage medium configured with a computer program, where the storage medium so configured causes a computer to operate in a specific and predefined manner, in accordance with the methods and drawings described in the specific embodiments. Each program may be implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the program(s) can be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language. Furthermore, the program can be run on a programmed application specific integrated circuit for this purpose.
Furthermore, the operations of the processes described herein may be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The processes (or variations and/or combinations thereof) described herein may be performed under control of one or more computer systems configured with executable instructions, and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications), by hardware, or combinations thereof, collectively executing on one or more processors. The computer program includes a plurality of instructions executable by one or more processors.
Further, the method may be implemented in any type of computing platform operatively connected to a suitable computing platform, including, but not limited to, a personal computer, mini-computer, mainframe, workstation, network or distributed computing environment, separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, and so forth. Aspects of the invention may be implemented in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, optical read and/or write storage medium, RAM, ROM, etc., such that it is readable by a programmable computer, which when read by a computer, is operable to configure and operate the computer to perform the processes described herein. Further, the machine readable code, or portions thereof, may be transmitted over a wired or wireless network. When such media includes instructions or programs that, in conjunction with a microprocessor or other data processor, implement the steps described above, the invention described herein includes these and other different types of non-transitory computer-readable storage media. The invention also includes the computer itself when programmed according to the methods and techniques of the present invention.
The computer program can be applied to the input data to perform the functions described herein, thereby converting the input data to generate output data that is stored to the non-volatile memory. The output information may also be applied to one or more output devices such as a display. In a preferred embodiment of the invention, the transformed data represents physical and tangible objects, including specific visual depictions of physical and tangible objects produced on a display.
Finally, it is noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made thereto without departing from the spirit and scope of the present invention, which is intended to be covered by the claims of the present invention.
Claims (8)
1. A method for constructing an electric power metering all-link key business anomaly positioning model based on a converged business topology is characterized by comprising the following steps: the method comprises the following steps:
step S1: preprocessing the full-link abnormal information;
Step S2: constructing a full link abnormal weight analysis; the step S2 specifically comprises the following steps: and combining with metering the key business abnormal items of the full link, wherein the analysis of the abnormal weights of the full link is carried out by adopting the following steps:
Step S21: abnormal link digital processing: carrying out abstract processing on the abnormal chain after the sequence adjustment by combining the abnormal chain of the service information and the time information, deleting redundant service information and time information, using 1 to represent abnormal nodes, and 0to represent non-abnormal nodes to obtain an abstract 01 abnormal chain;
Step S22: the special multiplying power assignment further improves the calculation accuracy of the abnormal link by adding weights, and the calculation accuracy is adjusted by analyzing and metering the abnormal weight algorithm of the all-link key business by using three special links;
Step S23: the abnormal link weight area algorithm calculates the link abnormal association degree by the abnormal quantity and the abnormal density degree on the link links, and provides reference for abnormal positioning;
Step S24: abnormal link weight area calculation: evaluating and calculating links corresponding to abnormal items recorded by a log, displaying the links through a time stamp, digitizing abnormal information into standard chains represented by 0 and 1, obtaining the area of each chain through a weight area algorithm, and representing the abnormal priority of different chains so as to fulfill the aim of assisting operation and maintenance abnormality investigation;
step S25: metering full link root cause anomaly location: setting link priority, and determining root cause abnormality according to time stamp sequence in priority range;
step S3: and (5) curing the full-link abnormal positioning rule.
2. The method for constructing the electric power metering full-link key business anomaly positioning model based on the converged business topology according to claim 1, which is characterized by comprising the following steps: in the step S1, the full link anomaly information preprocessing includes: constructing a metering full-link key service topological graph, metering full-link key service topological dimension reduction, metering full-link key service abnormal item acquisition, noise abnormal filtering and time sequence cutting, and finally normalizing to obtain an abnormal link for locating a root cause.
3. The method for constructing the electric power metering full-link key business anomaly positioning model based on the converged business topology according to claim 1, which is characterized by comprising the following steps: the step S3 specifically comprises the following steps:
Repeatedly carrying out weight area calculation on the anomalies on the links through historical data, searching the source anomalies on the links in the links with high priority, and reserving a full-link path;
and comparing and verifying the root abnormality result with the abnormality investigation result in the daily operation and maintenance, and solidifying the matched abnormality positioning rule into a rule base.
4. The method for constructing the electric power metering full-link key business anomaly positioning model based on the converged business topology according to claim 2, which is characterized by comprising the following steps: the construction of the metering all-link key service topological graph is based on two key service topological graphs of instruction issuing and task acquisition according to a study-carding operation and maintenance manual and a front design instruction drawing.
5. The method for constructing the electric power metering full-link key business anomaly positioning model based on the converged business topology according to claim 2, which is characterized by comprising the following steps: the measurement full-link key service topology dimension reduction is divided into 4 core links of main acquisition task instruction issuing, main acquisition task information acquisition, supplementary acquisition task instruction issuing and supplementary acquisition task information acquisition.
6. The method for constructing the electric power metering full-link key business anomaly positioning model based on the converged business topology according to claim 2, which is characterized by comprising the following steps: and the business abnormal item in the acquisition of the metering full-link key business abnormal item comprises a full-link state evaluation abnormal value and an operation and maintenance log abnormal item.
7. The method for constructing the electric power metering full-link key business anomaly positioning model based on the converged business topology according to claim 1, which is characterized by comprising the following steps: in the step S22, specific rules are as follows:
Single-node exception chains where the full chain has only a single exception node: multiplying c=1+abnormal node number/total number of links;
there is a single abnormally dense segment and at the last post-exception chain of the chain: multiplying c=10 times the overall anomaly weight;
Full exception chain in which each node of the full chain is abnormal: multiplying c=the overall anomaly weight is 10 times amplified.
8. The method for constructing the electric power metering full-link key business anomaly positioning model based on the converged business topology according to claim 1, which is characterized by comprising the following steps: in the step S23, the specific steps for calculating the link abnormality association degree are as follows:
step S231: the abnormal number is expressed as a width, and if the abnormal link node number N=1, the width a=1; if the number of abnormal links N >1, the width a=max (the number of abnormal links connected);
step S232: the degree of abnormal density is expressed in terms of length: if the abnormal number of the links N=1, the length b=1+the serial number of the link where the alarm node is located/the total number of the links, if the abnormal number of the links N >1, the length
N=the number of non-abnormally dense segments;
step S233: calculating the abnormal link weight area by using the following abnormal link weight area formula:
S=a*b*100*c。
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