CN112487789B - Operation ticket scheduling logic validity verification method based on knowledge graph - Google Patents
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Abstract
The application discloses a method for verifying the legitimacy of operation ticket dispatching logic based on a knowledge graph, which comprises the steps of constructing a knowledge graph, a dispatching command and an operation term professional corpus by utilizing original data generated by a dispatching system; performing real-time voice recognition on the scheduling voice and converting the scheduling voice into scheduling words; extracting entities and relations in the scheduling words by using the professional corpus; and verifying the state of the current equipment by combining with the graph matching strategy to finish the verification of the validity of the scheduling logic. According to the application, the dispatching command and operation term professional corpus is constructed, the power grid dispatching command knowledge graph is used for monitoring the dispatching conversation content of the duty dispatcher in real time through voice recognition and other technologies, the entity-machine relationship is extracted from the dispatching conversation content, and the accuracy and normalization of the dispatching content of the dispatcher are verified through a graph matching algorithm.
Description
Technical Field
The application relates to the technical field of scheduling operation, in particular to an operation ticket scheduling logic validity verification method based on a knowledge graph.
Background
The standardization and legitimacy of dispatching operation in the current power grid dispatching flow business are comprehensively taken care of by mainly relying on a series of administrative management means, the mode needs that an on-duty dispatcher verifies the equipment state according to the requirement of five verifications before filling out dispatching operation tickets, namely, verification with an on-site verification and verification with a dispatching automation system, verification with a dispatching maintenance application form, verification with a related dispatching operation ticket and verification with a dispatching record, and then the on-duty dispatcher can execute after self-checking signature of the operation ticket filling person, checking signature of a checking person (guardian) and review signature of an on-duty responsible person.
In order to ensure the standardization and effectiveness of the dispatching operation ticket, a series of administrative management means are mainly adopted to carry out multiple comprehensive management, and when a duty dispatcher issues a dispatching command, attention must be focused and the regulation filling and issuing of the safety work process in the store of the limited responsible company of the south China grid are strictly followed. Meanwhile, before filling the dispatch operation ticket, the state needs to be verified according to the requirement of five verifications, and then the dispatch operation ticket also needs to be signed and executed after three verifications, but human negligence or errors are unavoidable in the process.
The current mode has lower execution efficiency for the dispatching service, if a dispatcher has skip or miss or even misreading in the call process, the dispatcher can not find and correct the skip or miss or even misreading in time, and at the moment, the human error can possibly generate potential safety hazard.
Disclosure of Invention
This section is intended to outline some aspects of embodiments of the application and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section as well as in the description of the application and in the title of the application, which may not be used to limit the scope of the application.
The present application has been made in view of the above-described problems occurring in the prior art.
Therefore, the application provides the operation ticket scheduling logic validity verification method based on the knowledge graph, which can improve the execution efficiency and the safety of the current scheduling service.
In order to solve the technical problems, the application provides the following technical scheme: the method comprises the steps of constructing a knowledge graph, a scheduling command and an operation term specialized corpus by utilizing original data generated by a scheduling system; performing real-time voice recognition on the scheduling voice and converting the scheduling voice into scheduling words; extracting entities and relations in the scheduling words by using the professional corpus; and verifying the state of the current equipment by combining with the graph matching strategy to finish the verification of the validity of the scheduling logic.
As a preferable scheme of the operation ticket scheduling logic validity verification method based on the knowledge graph, the application comprises the following steps: the verification comprises the step of establishing a Lagrange differential equation of a target state verification model by using an energy method, wherein the Lagrange differential equation is as follows:
wherein T: total kinetic energy of the scheduling system, U: scheduling system potential energy, D: scheduling System dissipation energy, Q i : generalized coordinate q i Corresponding generalized forces.
As a preferable scheme of the operation ticket scheduling logic validity verification method based on the knowledge graph, the application comprises the following steps: the verification is of a match error rate, including,
f 3 (X)＝f 2 (X)/f 1 (X)×100％
wherein f 1 (X): the current equipment is in the state frequency weighted root mean square value, f 2 (X): matched frequency weighted root mean square value, f 3 (X): matching error rate.
As a preferable scheme of the operation ticket scheduling logic validity verification method based on the knowledge graph, the application comprises the following steps: the original data comprises structured data and unstructured data set semi-structured data.
As a preferable scheme of the operation ticket scheduling logic validity verification method based on the knowledge graph, the application comprises the following steps: and establishing a triplet of the entity, the relation and the entity by utilizing the original data.
As a preferable scheme of the operation ticket scheduling logic validity verification method based on the knowledge graph, the application comprises the following steps: the structured data is converted into the entity, the relation and the triplet of the entity through a graph mapping or a D2R conversion strategy.
As a preferable scheme of the operation ticket scheduling logic validity verification method based on the knowledge graph, the application comprises the following steps: the semi-structured data needs to be subjected to certain preprocessing, and is converted into knowledge based on entity identification and entity association and stored in the knowledge graph.
As a preferable scheme of the operation ticket scheduling logic validity verification method based on the knowledge graph, the application comprises the following steps: and the unstructured data is processed based on natural language, is combined with the professional corpus to perform entity recognition and relation extraction, is stored as the knowledge, and is utilized to search new words and is updated into the professional corpus.
As a preferable scheme of the operation ticket scheduling logic validity verification method based on the knowledge graph, the application comprises the following steps: the device is in only one state, and each state is only associated with nodes which are connected together in a wired mode, and the states among the nodes cannot be converted.
The application has the beneficial effects that: according to the application, the dispatching command and operation term professional corpus is constructed, the power grid dispatching command knowledge graph is used for monitoring the dispatching conversation content of the duty dispatcher in real time through voice recognition and other technologies, the entity-machine relationship is extracted from the dispatching conversation content, and the accuracy and normalization of the dispatching content of the dispatcher are verified through a graph matching algorithm.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. Wherein:
fig. 1 is a flow chart of a method for verifying validity of operation ticket scheduling logic based on a knowledge graph according to a first embodiment of the present application;
fig. 2 is a schematic diagram of a process for constructing a knowledge graph and a specialized corpus by using the method for verifying the validity of operation ticket scheduling logic based on the knowledge graph according to the first embodiment of the present application;
FIG. 3 is a schematic diagram of entity identification and extraction flow of a method for verifying the validity of operation ticket scheduling logic based on a knowledge graph according to a first embodiment of the present application;
fig. 4 is a schematic diagram of an experimental comparative output curve of a method for verifying the legitimacy of operation ticket scheduling logic based on a knowledge graph according to a second embodiment of the present application.
Detailed Description
So that the manner in which the above recited objects, features and advantages of the present application can be understood in detail, a more particular description of the application, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, but the present application may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present application is not limited to the specific embodiments disclosed below.
Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the application. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
While the embodiments of the present application have been illustrated and described in detail in the drawings, the cross-sectional view of the device structure is not to scale in the general sense for ease of illustration, and the drawings are merely exemplary and should not be construed as limiting the scope of the application. In addition, the three-dimensional dimensions of length, width and depth should be included in actual fabrication.
Also in the description of the present application, it should be noted that the orientation or positional relationship indicated by the terms "upper, lower, inner and outer", etc. are based on the orientation or positional relationship shown in the drawings, are merely for convenience of describing the present application and simplifying the description, and do not indicate or imply that the apparatus or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present application. Furthermore, the terms "first, second, or third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
The terms "mounted, connected, and coupled" should be construed broadly in this disclosure unless otherwise specifically indicated and defined, such as: can be fixed connection, detachable connection or integral connection; it may also be a mechanical connection, an electrical connection, or a direct connection, or may be indirectly connected through an intermediate medium, or may be a communication between two elements. The specific meaning of the above terms in the present application will be understood in specific cases by those of ordinary skill in the art.
Example 1
Referring to fig. 1 to 3, for a first embodiment of the present application, there is provided a method for verifying validity of operation ticket scheduling logic based on a knowledge graph, including:
s1: and constructing a knowledge graph, a scheduling command and an operation term specialized corpus by using the original data generated by the scheduling system. Referring to fig. 2, it should be noted that the original data includes:
structured data, unstructured data set semi-structured data;
establishing a triplet of entities, relations and entities by using the original data;
the structured data is converted into a triplet of entities, relations and entities through a graph mapping or D2R conversion strategy;
the semi-structured data needs to be subjected to certain preprocessing, and is converted into knowledge based on entity identification and entity association and stored in a knowledge graph;
the unstructured data is based on natural language processing, performs entity recognition and relation extraction in combination with the professional corpus, stores the information as knowledge, searches for new words by utilizing entity recognition and updates the new words into the professional corpus.
S2: and carrying out real-time voice recognition on the scheduling voice and converting the scheduling voice into scheduling words.
S3: and extracting the entity and the relation in the scheduling text by using the professional corpus. Among them, it is also to be noted that:
the Anlong-changing capacitor bank No. 10kv7 is changed from 'hot standby' to 'cold standby';
extracting an entity 'Anlong becomes a No. 10kv7 capacitor', 'hot standby', 'cold standby' and a relation 'Change' from a professional corpus;
based on the graph matching policy, it is verified whether the state "hot standby" in which the current device is located can be "switched" to "cold standby".
S4: and verifying the state of the current equipment by combining with the graph matching strategy to finish the verification of the validity of the scheduling logic. The step is to be noted, the verification includes:
and establishing a Lagrange differential equation of the target state verification model by using an energy method, wherein the Lagrange differential equation is as follows:
wherein T: total kinetic energy of the scheduling system, U: scheduling system potential energy, D: scheduling System dissipation energy, Q i : generalized coordinate q i The corresponding generalized force;
verifying that a match error rate exists includes, including,
f 3 (X)＝f 2 (X)/f 1 (X)×100％
wherein f 1 (X): the state frequency weighted root mean square value, f, of the current equipment 2 (X): matched frequency weighted root mean square value, f 3 (X): matching error rate;
the device is in only one state, and each state is only associated with nodes which are connected together in a wired way, and the state among the cross nodes cannot be converted.
Referring to fig. 3, the primary knowledge representation is completed through data integration, entity extraction, relation extraction, attribute extraction and knowledge extraction, entity disambiguation, coreference resolution and entity alignment are performed on the primary knowledge representation to obtain a standard knowledge representation, and quality assessment is further completed by combining knowledge reasoning and knowledge discovery to obtain a knowledge graph; and constructing a model on the basis of the existing knowledge, carrying out data standardization on the standard knowledge representation, and improving standardization through model revision to obtain the final knowledge graph application.
Preferably, the flow of the scheduling command initiated by the duty scheduler is as follows: for example, the command is to change 022 knife switch from hot standby to cold standby, and the condition that the equipment 022 knife switch is in the hot standby state currently is obtained through a graph matching algorithm, and the hot standby state node and the cold standby state node are directly associated, so that direct conversion is realized, and the secondary command meets the specification.
Preferably, the dispatch uttered by the duty dispatcher due to misstatement or misreading in the dispatching process is as follows: the 022 knife switch is used for hot-standby maintenance, the current state of the 022 knife switch is obtained through a graph matching algorithm to be hot standby, but the hot standby state node and the maintenance state node are directly not directly associated, so that direct conversion cannot be performed, error or non-standardization of a dispatching can be identified, and an on-duty dispatcher and a dispatched person can be timely reminded, so that unnecessary loss is avoided.
Example 2
In order to better verify and explain the technical effects adopted in the method, the embodiment selects the traditional auxiliary pre-control method of the power dispatching operation ticket to carry out comparison test with the method, and the actual effects of the method are verified by comparing test results by means of scientific demonstration.
The conventional power dispatching operation ticket auxiliary pre-control method realizes dispatching operation ticket verification based on the risk quantification value, has low accuracy and standardability, and has high accuracy and safety standardability compared with the conventional method for verification, and in the embodiment, the conventional method and the method are adopted to respectively carry out real-time measurement and comparison on the operation ticket verification of the simulation dispatching system.
Test environment: operating the simulation scheduling system on a simulation platform to simulate operation and simulate scenes of operation of different equipment in different states, taking historical equipment operation data as a test sample, and respectively testing by using risk quantized value operation of a traditional method to obtain test result data; by adopting the method, automatic test equipment is started, MATLB is used for realizing the simulation test of the method, and simulation data are obtained according to experimental results; each method tests 100 groups of data, calculates and obtains an error value of each group of data, compares and calculates with an actual prediction error value input by simulation, and outputs a final curve comparison graph.
Referring to fig. 4, a schematic diagram of a final result output curve for test comparison, wherein a solid line is a curve output by the method, a dotted line is a curve output by a traditional method, according to the schematic diagram of fig. 4, it can be intuitively seen that the solid line and the dotted line are gradually pulled apart along with the increase of time, the dotted line always presents an unstable fluctuation trend, and is always lower than the safety increase of the solid line, and the solid line basically tends to be stable and is kept at the rising position of the dotted line more always, so that the accuracy of the method is far higher than that of the traditional method, and the true effect of the method is verified.
It should be noted that the above embodiments are only for illustrating the technical solution of the present application and not for limiting the same, and although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present application may be modified or substituted without departing from the spirit and scope of the technical solution of the present application, which is intended to be covered in the scope of the claims of the present application.
Claims (7)
1. A method for verifying the legitimacy of operation ticket scheduling logic based on a knowledge graph is characterized by comprising the following steps: comprising the steps of (a) a step of,
constructing a knowledge graph, a scheduling command and an operation term specialized corpus by using the original data generated by the scheduling system;
performing real-time voice recognition on the scheduling voice and converting the scheduling voice into scheduling words;
extracting entities and relations in the scheduling words by using the professional corpus;
verifying the state of the current equipment by combining with a graph matching strategy to finish the validity verification of the scheduling logic;
wherein the verification includes the steps of,
and establishing a Lagrange differential equation of the target state verification model by using an energy method, wherein the Lagrange differential equation is as follows:
wherein T: total kinetic energy of the scheduling system, U: scheduling system potential energy, D: scheduling System dissipation energy, Q i : generalized coordinate q i The corresponding generalized force;
verifying that a match error rate exists includes, including,
f 3 (X)＝f 2 (X)/f 1 (X)×100％
wherein f 1 (X): the current equipment is in the state frequency weighted root mean square value, f 2 (X): matched frequency weighted root mean square value, f 3 (X): matching error rate.
2. The knowledge-graph-based operation ticket scheduling logic validity verification method according to claim 1, wherein: the original data includes structured data, unstructured data, and semi-structured data.
3. The knowledge-graph-based operation ticket scheduling logic validity verification method according to claim 2, wherein: and establishing a triplet of the entity, the relation and the entity by utilizing the original data.
4. The knowledge-graph-based operation ticket scheduling logic validity verification method according to claim 3, wherein: the structured data is converted into the entity, the relation and the triplet of the entity through a graph mapping or a D2R conversion strategy.
5. The knowledge-graph-based operation ticket scheduling logic validity verification method according to claim 4, wherein: the semi-structured data needs to be subjected to certain preprocessing, and is converted into knowledge based on entity identification and entity association and stored in the knowledge graph.
6. The knowledge-graph-based operation ticket scheduling logic validity verification method according to claim 5, wherein: and the unstructured data is processed based on natural language, is combined with the professional corpus to perform entity recognition and relation extraction, is stored as the knowledge, and is utilized to search new words and is updated into the professional corpus.
7. The knowledge-graph-based operation ticket scheduling logic validity verification method according to claim 6, wherein: the device is in only one state, and each state is only associated with nodes which are connected together in a wired mode, and the states among the nodes cannot be converted.
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