CN112182242A - Safety control knowledge graph construction method for whole process of electric power operation - Google Patents
Safety control knowledge graph construction method for whole process of electric power operation Download PDFInfo
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Abstract
The invention relates to a safety control knowledge graph construction method facing to the whole process of electric power operation, which is based on a knowledge graph and a case graph, firstly, dividing collected information into dynamic data and static data and extracting knowledge; then, establishing a power event affair map by using the four logic relations; then establishing a static knowledge map; and finally, connecting the knowledge graph and the affair graph through a common entity. The invention utilizes the relevance between people and equipment to analyze the dynamic and static relevance, and is beneficial to the improvement of the safety control level of the electric power operation.
Description
Technical Field
The invention belongs to the field of electric power operation safety control, and particularly relates to a safety control method for the whole operation process of an electric power system based on a knowledge graph.
Background
With the expansion of the scale of the power grid, the power safety problem occurs more frequently and the fault types are more complicated. The occurrence of safety production accidents affects the normal operation of equipment slightly, and personal casualty accidents are caused seriously.
The existing safety control method firstly depends on-line and off-line safety training for operators and secondly utilizes a target detection algorithm to carry out dress inspection and identity authentication for workers. The current security management and control has the following problems: (1) only the 'two ends' of the operation are detected, and the safety control of the operation main body is lacked, namely, the preparation work and the fine work are only monitored by target detection and face recognition, and the risk assessment and the correlation analysis of illegal operation in formal operation are lacked. (2) Dynamic interaction analysis is lacked in people and equipment, human-computer interaction is limited to monitoring the space distance of an operator relative to the electrified equipment, and state detection data of the electrified equipment cannot be fed back to an operation site in time and cannot assist construction operation of related personnel.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a construction method of the whole process of electric power operation safety control based on a knowledge graph and a case graph method and an association graph established among people, equipment and events.
The design principle is as follows: the knowledge graph is used as a branch of cognitive intelligence, static attributes of the entities and relationships among the entities can be visually represented, and the event graph taking the events as a basic unit can well represent the evolution relationship among the events. The development of the knowledge graph provides possibility for constructing a dynamic supervision system, accurate associated personnel information and equipment state information of the whole operation process, and has important significance for improving the safety control level. Based on the design, the static knowledge map of the operation affair map and the personnel and equipment is formed, and the two maps are connected through a common entity such as an operator and electrical equipment.
The design scheme is as follows: a safety control knowledge graph construction method for the whole process of power operation comprises the following steps:
step 1, data acquisition, namely acquiring operation process data, personnel dressing data, equipment working state data, violation accident data and safety control algorithm data.
And 2, classifying the acquired data and extracting knowledge.
And 3, establishing a matter map according to the electric power event information.
And 4, establishing a static knowledge graph of the personnel and equipment, and establishing the knowledge graph in an owl standard triple form according to the extracted personnel clothes, identity information and equipment state monitoring data.
And 5, connecting the knowledge graph and the affair graph according to the common entity.
Preferably, the classifying and knowledge extracting of the acquired data in step 2 includes: the collected data are divided into two categories of event information and personnel and equipment state information, and the triples are used for respectively carrying out knowledge extraction so as to carry out normalized representation on the operation events.
Preferably, the triad is specifically: the triple e is { a, O, V }, and describes an operation event in the power job, where O is a specific action, a is an operation object element, and V is an operation environment.
Preferably, in step 3, the relationship between the operation events is logically connected by four kinds of events, and the four kinds of logical relationships include: the transitive probability is defined as the necessity of a transition from a previous event to a subsequent event, and this relationship is transitive. And in the causal relationship, the two events before and after the causal relationship have obvious causality, and after the causal event, the specific causal strength is assigned according to the frequency of the conventional power accident. The upper and lower relationship is based on the upper and lower relationship of the noun. Mutual exclusion relationship: two events are prohibited from occurring in succession.
Preferably, the common entities include power equipment and an operator.
Compared with the prior art, the invention has the beneficial effects that: according to the invention, through the fusion analysis of the affair map and the knowledge map, scattered personnel information and power equipment information are systematized, and the safety control level of the whole process of power operation is improved.
Drawings
FIG. 1 is a knowledge graph construction flow diagram for the overall process of power operations;
FIG. 2 is a case map and knowledge map of an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
A knowledge graph construction method for the whole switching operation process is disclosed, and a case graph and a knowledge graph are established by referring to fig. 1 and fig. 2.
Step 1, data acquisition: searching relevant requirements of switching operation based on words such as 'switching' and 'electrified' in a safety regulation manual; recording the operation pictures of the workers from the transformer substation site; collecting state monitoring data of relevant equipment of the transformer substation; collecting teaching videos of equipment manufacturers such as switch cabinets and the like; and entering a safety control algorithm and the like.
Step 2, classifying and extracting knowledge of the acquired data: the collected data are divided into two categories of event information and personnel and equipment state information, and the knowledge is extracted by using the triples respectively. For example, for collected operation videos, specific operation videos are intercepted according to corresponding operation ticket items of 'switching the A switch handle from the working position to the breaking locking position', and the short videos are described as 'handle rotating to the right at switch cabinet' by a triad with reference to the specific operation videos.
Further, the specific operation of step 2 is.
And 2.1, classifying the collected information into dynamic data and static data, namely event information and personnel equipment state information.
And 2.2, extracting the information by using a specialist method. The basic standard for the division of the operation process of the related operator is to divide the specific operation process into a plurality of key behaviors, namely operation events, based on the operation items in the operation ticket. The operation event is represented in a normalized mode, and the specific normalized naming rule is as follows: the operation event in the power job is described by a triplet e ═ { a, O, V }. Wherein: o is a specific action that may include the tool used, and an action descriptive adjective such as "slowly pull apart with an insulating rod"; a is an operation object element, such as a control insurance and a disconnecting link; v is an operating environment, such as "work-over", "distribution room"; where the operating environment may be omitted depending on the conditions.
And 3, establishing a matter map according to the electric power event information.
Further, the specific operation of step 3 is: the invention uses four kinds of affair logic to connect the relationship between operation events, which is as follows:
(1) the sequential relationship is: transition probability is defined as the necessity of a transition from a previous event to a subsequent event, and this relationship is transitive. The transition probability is defined to be between 0 and 1, and 1 represents that the next event is necessary to be worked after the previous event according to the safety regulation requirement. From 1 to 0, the necessary degree of occurrence of subsequent events decreases in order. The assignment of the specific transition probability is adjudicated according to the low, medium and high risk values of the corresponding violation operation.
(2) Cause and effect relationship: the two events have obvious causality, and after the result event, the specific causality intensity can be assigned according to the frequency of the conventional power accident. If a certain violation operation causes a certain accident, the two can be considered as a cause-and-effect relationship.
(3) The upper and lower relation: the first and the second relations are named as "checking the switch status" and "checking the switch position".
(4) Mutual exclusion relationship: two events are prohibited from occurring in succession. For example, "handle is turned right at the switch cabinet" and "handle is turned left at the switch cabinet".
In the specific embodiment of step 3, a case map is established according to switching operation information: four logic relations are used for connecting corresponding events, for example, the 'three-phase electrified display lamp inspection of the switch cabinet' and the 'safety removal of the switch cabinet' are in a sequential bearing relation, the step of 'display lamp inspection' is important, and the transition probability is set to be 1. The 'shielding plate is taken down from the switch cabinet' and 'human body electric shock coma' are in a strong causal relationship, and the causal strength can be set to be 1.
Step 4, establishing a personnel and equipment static knowledge map: and constructing a knowledge graph in an owl standard triple form t ═ { subject, predict, object } according to the extracted personnel clothing, identity information and equipment state monitoring data, wherein the object can be an individual or a specific data value.
In a specific embodiment, the step 4 of establishing the static knowledge graph of the personnel equipment specifically includes: the node attribute of the switching operator can be considered to be that the switching operator wears a safety helmet, the switching operator safety test score and the like. The attributes of the side include 'switching operator working place distribution room', 'human face recognition algorithm verification personal code' and the like.
And 5: the knowledge map and the affair map are connected according to a common entity, such as a transformer, a switching operator and the like, namely the switching operator and the switch cabinet in the knowledge map are connected with the switching operation affair map.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention 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 solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (5)
1. A safety control knowledge graph construction method for the whole process of power operation is characterized by comprising the following steps:
step 1, data acquisition, namely acquiring operation process data, personnel dressing data, equipment working state data, violation accident data and safety control algorithm data;
step 2, classifying the acquired data and extracting knowledge;
step 3, establishing a matter map according to the electric power event information;
step 4, establishing a static knowledge map of personnel and equipment, and establishing the knowledge map in an owl standard triple form according to the extracted personnel clothes, identity information and equipment state monitoring data;
and 5, connecting the knowledge graph and the affair graph according to the common entity.
2. The method according to claim 1, wherein classifying and knowledge extracting the acquired data in step 2 comprises: the collected data are divided into two categories of event information and personnel and equipment state information, and the triples are used for respectively carrying out knowledge extraction so as to carry out normalized representation on the operation events.
3. The method according to claim 2, characterized in that the triplets are in particular: the triple e is { a, O, V }, and describes an operation event in the power job, where O is a specific action, a is an operation object element, and V is an operation environment.
4. The method of claim 1, wherein: in step 3, the relationships between the operation events are logically connected by four kinds of events, and the four kinds of logical relationships include:
a cis-bearing relationship, in which the transition probability is defined as the necessity of transforming the previous event to the next event and the relationship is transitive;
the causal relationship is that the two events have obvious causality, and after the causal event, the specific causal strength is assigned according to the frequency of the conventional power accident;
the upper and lower relation is based on the upper and lower relation of the noun;
mutual exclusion relationship: two events are prohibited from occurring in succession.
5. The method of claim 1, wherein: the common entities include power equipment and operators.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113191740A (en) * | 2021-05-19 | 2021-07-30 | 广东电网有限责任公司 | Measurement asset management system |
| CN113220903A (en) * | 2021-05-19 | 2021-08-06 | 云南电网有限责任公司电力科学研究院 | Power accident visual analysis system and method based on knowledge graph |
| CN113379214A (en) * | 2021-06-02 | 2021-09-10 | 国网福建省电力有限公司 | Method for automatically filling and assisting decision of power grid accident information based on affair map |
| CN114722974A (en) * | 2022-06-07 | 2022-07-08 | 国网浙江省电力有限公司信息通信分公司 | Multi-dimensional map fusion method based on matter logic and entity knowledge |
| CN114817575A (en) * | 2022-06-24 | 2022-07-29 | 国网浙江省电力有限公司信息通信分公司 | Large-scale electric power affair map processing method based on extended model |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114817575B (en) * | 2022-06-24 | 2022-09-02 | 国网浙江省电力有限公司信息通信分公司 | Large-scale electric power affair map processing method based on extended model |
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