CN115526746A - Self-adaptive power transformation operation and maintenance knowledge learning and skill drilling method and system - Google Patents
Self-adaptive power transformation operation and maintenance knowledge learning and skill drilling method and system Download PDFInfo
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Abstract
The invention discloses a self-adaptive power transformation operation and maintenance knowledge learning and skill rehearsal method, which comprises the steps of constructing a power transformation operation and maintenance knowledge map; learning knowledge based on the power transformation operation and maintenance knowledge map; the invention is used for skill drilling based on a power transformation operation and maintenance knowledge map, and combines a power transformation operation and maintenance professional knowledge system to realize a learning and drilling process of continuously and adaptively adapting to individual capability level through knowledge/skill set construction, learning/drilling path planning, learning content recommendation/drilling scene generation and cyclic iterative knowledge learning/skill drilling. The method provides an effective solution for realizing the personalized training of the power transformation operation and maintenance personnel.
Description
Technical Field
The invention belongs to the technical field of simulation training learning and skill drilling, and particularly relates to a self-adaptive power transformation operation and maintenance knowledge learning and skill drilling method and system.
Background
With the development of the construction of a new generation of electric power system, a large number of digital intelligent new devices and new systems are applied to a transformer substation, higher requirements are put forward on the knowledge skills of transformer operation and maintenance personnel, and the knowledge skill level of the transformer operation and maintenance personnel in the aspects of daily maintenance of the devices, switching operation, inspection, fault and exception handling, maintenance and repair, equipment acceptance and the like needs to be rapidly improved. At present, training for power transformation operation and maintenance personnel is mainly carried out by theoretical knowledge training, master carrying on a brother, real equipment training and transformer substation simulation training. The system adopts a full-digital simulation training system to solve the difficult problem of difficult in-situ training in a real transformer substation, has low cost and high efficiency compared with other training modes, and gradually becomes a mainstream training mode of transformer operation and maintenance personnel.
However, most of the existing transformer substation simulation training systems only provide simple learning, exercise and examination functions, the learning resource management is extensive, the training content is thousands of people, and the effect is poor.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a self-adaptive power transformation operation and maintenance knowledge learning and skill drilling method and system, which can
The technical problem to be solved by the invention is realized by the following technical scheme:
in a first aspect, a self-adaptive power transformation operation and maintenance knowledge learning and skill practicing method is provided, which includes:
constructing a power transformation operation and maintenance knowledge map;
learning knowledge based on the power transformation operation and maintenance knowledge map;
and skill drilling is carried out based on the power transformation operation and maintenance knowledge graph.
With reference to the first aspect, further, the constructing a power transformation operation and maintenance knowledge graph includes:
layering the obtained power transformation operation and maintenance data according to the data object categories;
defining nodes and attributes thereof in each layer;
and establishing an incidence relation among the nodes.
With reference to the first aspect, further, the association relationship includes an inclusion relationship, a precursor relationship, and an entity relationship.
With reference to the first aspect, further, the learning knowledge based on the power transformation operation and maintenance knowledge graph includes:
according to the learning tasks of the power transformation operation and maintenance personnel, a knowledge set corresponding to the learning tasks is constructed by adopting a power transformation operation and maintenance knowledge map;
planning a learning path according to a knowledge set corresponding to the learning task;
displaying knowledge points to be learned in a map and sequence mode respectively according to the planned learning path;
entering a learning, practicing or testing link of knowledge learning by selecting knowledge points to be learned;
evaluating the capability level of power transformation operation and maintenance personnel through a testing link of knowledge learning or a small pre-school test in the learning link;
and recommending learning resources according to the capability level of the power transformation operation and maintenance personnel in a learning link.
With reference to the first aspect, further, the recommending learning resources according to the capability level of the power transformation operation and maintenance personnel includes:
calculating the distance between the power transformation operation and maintenance personnel and the learning resources according to the capability level of the power transformation operation and maintenance personnel and the learning resources;
the learning resources with smaller distance to the power transformation operation and maintenance personnel are recommended with higher priority.
With reference to the first aspect, further, the constructing a knowledge set corresponding to a learning task includes:
matching a knowledge point with the closest node name and a learning task in the power transformation operation and maintenance knowledge graph according to the voltage level and the task name, and searching all child generation knowledge points connected with the knowledge point in an 'inclusion' relationship by taking the knowledge point as an initial knowledge point;
if the knowledge point closest to the learning task does not contain the child knowledge point, searching a precursor knowledge point connected with the knowledge point in a precursor relation, forming a knowledge set by the knowledge point and the precursor knowledge point, and finishing the construction of the knowledge set;
if the knowledge point closest to the learning task contains the child knowledge point, searching a pilot knowledge point connected with the child knowledge point in a pilot relationship, forming a knowledge set by the initial knowledge point, the child knowledge point of the initial knowledge point and the pilot knowledge point of the child knowledge point, and finishing the construction of the knowledge set.
With reference to the first aspect, further, the planning of the learned path includes:
the leading knowledge point takes precedence over the following knowledge point;
the child knowledge points have precedence over the parent knowledge points;
the child knowledge points containing more child knowledge points are preferentially learned;
the leading knowledge points which are the same as a certain knowledge point have the same priority, and the learning sequence is randomly arranged.
With reference to the first aspect, further, the performing skill drill based on the power transformation operation and maintenance knowledge base includes:
according to the drilling tasks of the power transformation operation and maintenance personnel, a skill set corresponding to the drilling tasks is constructed by adopting a power transformation operation and maintenance knowledge map;
planning a skill drill path according to the skill set;
displaying skill points to be exercised in a map and sequence mode respectively according to the skill set and the skill exercise path;
and entering a learning, practicing or testing link of skill drilling by selecting the skill point to be drilled.
In a second aspect, an adaptive power transformation operation and maintenance knowledge learning and skill drilling system is provided, including:
the map construction module is used for constructing a power transformation operation and maintenance knowledge map;
the knowledge learning module is used for learning knowledge based on the power transformation operation and maintenance knowledge map;
and the skill drill module is used for performing skill drill based on the power transformation operation and maintenance knowledge map.
The invention has the beneficial effects that: the invention combines a power transformation operation and maintenance professional knowledge system, and realizes a learning and practicing process of continuously self-adapting individual ability level through knowledge/skill set construction, learning/practicing path planning, learning content recommendation/practicing scene generation and cyclic iterative knowledge learning/skill practicing. The method provides an effective solution for realizing the personalized training of the power transformation operation and maintenance personnel.
Drawings
FIG. 1 is a schematic diagram of a power transformation operation and maintenance knowledge graph structure in the present invention;
FIG. 2 is a flow chart of the learning of power transformation operation and maintenance knowledge in the present invention;
fig. 3 is a flow chart of the power transformation operation and maintenance skill drill in the present invention.
Detailed Description
To further describe the technical features and effects of the present invention, the present invention will be further described with reference to the accompanying drawings and detailed description.
Example 1
As shown in fig. 1-3, an adaptive power transformation operation and maintenance knowledge learning and skill practicing method includes the following steps:
step one, constructing a power transformation operation and maintenance knowledge map
According to the primary and secondary equipment, OMIS and PMIS systems, operation tickets and work tickets, power transformation operation and maintenance professional ability training standard teaching materials, power transformation operation and maintenance post ability training standards and other related materials in the actual transformer substation, combing the related contents of power transformation operation and maintenance according to 3 levels of a physical layer, a business layer and a base layer:
1) Physical layer: the physical layer comprises all the primary and secondary devices in the transformer substation and business related contents such as actual operation tickets, work tickets, operation rules, management regulations and the like. The data of the physical layer is derived from real equipment and work tasks in the substation in the physical world.
2) And (4) a service layer: in the service layer, devices, tools, systems and work tasks (switching, inspection, maintenance, exception handling, accident handling and the like) in the transformer substation are abstracted and extracted, and are classified according to different voltage levels. Knowledge in the service layer corresponds to entities in the physical layer one to one, such as: "moyagh transform #1 main transformer" in the physical layer corresponds to "transformer" in the service layer, and "moyagh transform 7510 circuit breaker full patrol" in the physical layer corresponds to "circuit breaker full patrol" in the service layer. And the data of the business layer is derived from professional teaching materials such as power transformation operation and maintenance professional ability training specifications and power transformation operation and maintenance post ability training specifications.
3) Base layer: the basic layer comprises basic concepts, principles and the like related to power transformation operation and maintenance, and the basic concepts, the principles and the like are used as general knowledge to support professional knowledge skills of the power transformation operation and maintenance contained in the business layer. The data of the basic layer is derived from basic teaching materials such as electric power system analysis, power electronic technology, electrical engineering foundation, high voltage technology foundation, electrical knowledge and drawing foundation, mechanical drawing and the like.
On the basis, the nodes and the attributes thereof in each level are further defined, wherein the nodes comprise node types, node names and node name types. The node types are divided into knowledge class nodes, skill class nodes and entity class nodes (hereinafter referred to as knowledge points, skill points and entity points), the knowledge points mainly comprise concepts, principles and theoretical class knowledge, and for example, the "working principle of the circuit breaker" is the knowledge point. The skill points are mainly operation skills corresponding to power transformation operation and maintenance, for example, "breaker operation transfer hot standby" is the skill point. The physical points are actually existing equipment, operation tickets, operation and maintenance operation contents and the like of the transformer substation, for example, the 'moho station #1 main transformer' and the 'moho station #1 main transformer moisture absorber replacement' are both physical points. According to the definition, all the nodes in the physical layer are entity points, all the nodes in the service layer comprise knowledge points and skill points, and all the nodes in the basic layer are knowledge points. The node name is the name of the node, and the type of the node name can be divided into devices, protections, loops, components, tools, instruments, tasks, and the like according to the content represented by the node name.
Further defining the association relationship among 3 nodes, as shown in fig. 1:
1) The inclusion relationship: if the content of the node A contains the content of the node B, the relationship between the node A and the node B is 'containing', the node A points to the node B, the node A is called a parent node of the node B, and the node B is called a child node of the node A. For example, the skill point "circuit breaker patrol" is a parent skill point of the skill points "circuit breaker comprehensive patrol", "circuit breaker routine patrol", "circuit breaker special patrol", and "circuit breaker lights-off patrol";
2) Leading relation: if the content of the node A is the premise of learning or practicing the content of the node B, the relationship between the node A and the node B is a leader, the node A points to the node B, the node A is called a leader node of the node B, and the node B is called a successor node of the node A. For example, the knowledge point "operation rule of circuit breaker" is a leading knowledge point of the skill point "circuit breaker operation";
3) Entity relationship: the instantiated relationship exists between the contents represented by the nodes, if the content of the node a is an instantiated object or event of the content of the node B, the relationship between the node a and the node B is an "entity", the node B points to the node a, the node a is called an instance node of the node B, and the node B is called an abstract node of the node a, such as: the entity point "moyagh transformer #1 main transformer" is an example entity point of the knowledge point "transformer", and the entity point "moyagh transformer 7510 circuit breaker comprehensive inspection" is an example entity point of the skill point "circuit breaker comprehensive inspection".
And connecting power transformation operation and maintenance related knowledge points, skill points and entity points which are combed by a physical layer, a service layer and a base layer by adopting a 'containing', 'leading' and 'entity' relationship to complete the construction of the power transformation operation and maintenance knowledge map.
Step two, learning knowledge based on power transformation operation and maintenance knowledge graph
And designing a continuous self-adaptive power transformation operation and maintenance knowledge learning method based on the constructed power transformation operation and maintenance knowledge map, as shown in the attached figure 2.
Firstly, according to the learning task of power transformation operation and maintenance personnel, a knowledge set corresponding to the learning task is constructed by adopting a power transformation operation and maintenance knowledge map, and the construction method comprises the following steps:
1) In the power transformation operation and maintenance knowledge graph, matching a knowledge point with the closest node name and a learning task according to the voltage level and the task name, and searching all child generation knowledge points connected with the knowledge point in a 'including' relationship by taking the knowledge point as an initial knowledge point;
2) If the knowledge points close to the learning task do not contain children knowledge points, searching precursor knowledge points connected with the knowledge points in a precursor relation, forming a knowledge set by the knowledge points and the precursor knowledge points, and finishing the construction of the knowledge set;
3) If the knowledge points close to the learning task comprise child knowledge points, searching for a leader knowledge point connected with the child knowledge points in a leader relation, and forming a knowledge set by the initial knowledge point, the child knowledge points of the initial knowledge point and the leader knowledge points of the child knowledge points, wherein the knowledge set is established.
On the basis of constructing a knowledge set corresponding to a learning task, a knowledge learning path is planned, and the planning method comprises the following steps:
1) The leading knowledge point takes precedence over the following knowledge point;
2) The child knowledge points have precedence over the parent knowledge points;
3) The child knowledge points containing more child knowledge points are preferentially learned while being child knowledge points of a certain knowledge point;
4) The leading knowledge points which are the same as a certain knowledge point have the same priority, and the learning sequence is randomly arranged.
And displaying the knowledge points to be learned in a map and sequence mode respectively according to the knowledge set and the learning path. In the knowledge point display link, the graph display mode emphasizes representing the logic venation among knowledge, and the structure of the power transformation operation and maintenance knowledge graph related to the knowledge set is determined. And the sequence display mode emphasizes the sequence of representing knowledge learning and learns the path according to the planned power transformation operation and maintenance knowledge. And further, two different control modes of system selection and autonomous selection are provided, in the system selection mode, the first knowledge point to be learned is actively selected according to the learning path to start learning, and in the autonomous selection mode, the power transformation operation and maintenance personnel can automatically select any one knowledge point in the knowledge point set to be learned to start learning.
After the knowledge points to be learned are selected, the power transformation operation and maintenance personnel can directly enter the links of learning, practicing and testing. Wherein, practice and test are carried out by answering theoretical test questions. After the power transformation operation and maintenance personnel enter into learning, whether the preschool survey is needed or not is judged according to whether the knowledge point is learned for the first time or not. The small pre-study tests are carried out by adopting a mode of answering 5 theoretical test questions corresponding to the knowledge points to be learned:
if answer is not less than 4, recording the capability level of the transformer operation and maintenance personnel as 0, 0, 1;
if the answer is 2 or 3, recording the capability level of the power transformation operation and maintenance personnel as 0, 1, 0;
if the answer is 1 question and below, the capacity level of the power transformation operation and maintenance personnel is recorded as [1, 0, 0].
After entering a learning link, recommending matched learning resources for power transformation operation and maintenance personnel according to the capability level of the power transformation operation and maintenance personnel, wherein the learning resource recommending method comprises the following steps:
first, parameters of learning resources are defined as shown in the following table:
TABLE 1 learning resource parameters
| Parameter(s) | Description of parameters |
| Difficulty of | Using difficulty vector s, m, d]Characterization, s + m + d =1, standard values for simple resources of [1, 0, 0]medium is [0, 1, 0]Difficulty is [0, 0, 1]]Difficulty of resources by domain experts The quantitative component is evaluated |
| Format | Video class =1, text class =0 |
And extracting all learning resources corresponding to the knowledge points to be learned, and calculating the Distance between the operation and maintenance personnel and the learning resources, namely Distance = 1/((U-s) 2 + (L-M) 2 + (M-d) 2) on the assumption that the capability level of the operation and maintenance personnel obtained according to the pre-school short-term test or the previous test result is [ U, L, M ], and the difficulty of the learning resources is [ s, M, d), wherein the lower the Distance value is, the higher the recommendation degree of the learning resources is, and the higher the recommendation degree is, the higher the priority is to recommend. And preferentially recommending the video learning resources on the premise of the same recommendation degree. Where U = unbwn (don't understand), L = low (low), M = middle (medium); s = simple, m = midle (medium), d = difficult (hard).
In the learning process, the power transformation operation and maintenance personnel can enter a training link at any time, the training is carried out in a mode of answering theoretical test questions corresponding to the knowledge points to be learned, and training results are not used as a basis for evaluating the capability of the power transformation operation and maintenance personnel.
The transformer operation and maintenance personnel enter a testing link after learning, and the testing link is developed by adopting a mode of answering 10 theoretical test questions corresponding to the knowledge points to be learned:
if answer is 8 or more, updating the capability level of the transformer operation and maintenance personnel to be 0, 0, 1;
if answer is given to the questions 4 or 7, the capability level of the power transformation operation and maintenance personnel is updated to be [0, 1, 0];
and if answer is given to the questions 3 and below, updating the capacity level of the substation operation and maintenance personnel to be [1, 0, 0].
And generating a summary report for the power transformation operation and maintenance personnel according to the updated capability level, and suggesting the next knowledge point to be learned:
if the ability level is [0, 0, 1], prompting the power transformation operation and maintenance personnel to master the knowledge point, recommending the power transformation operation and maintenance personnel to continuously learn other knowledge points in the knowledge point set to be learned, and entering a knowledge point display link to reselect;
and if the ability level is [0, 1, 0] or [1, 0, 0], prompting the power transformation operation and maintenance personnel not to master the knowledge point, recommending the power transformation operation and maintenance personnel to continuously learn the knowledge point, and entering a learning link to learn.
And performing cyclic iterative learning according to the rules to finally form a whole set of continuous self-adaptive power transformation operation and maintenance knowledge learning method.
Thirdly, skill drill is carried out based on power transformation operation and maintenance knowledge graph
And designing a continuous self-adaptive power transformation operation and maintenance skill drilling method based on the constructed power transformation operation and maintenance knowledge graph, as shown in the attached figure 3.
Firstly, according to a drilling task of a power transformation operation and maintenance worker, a skill set corresponding to the drilling task is constructed by adopting a power transformation operation and maintenance knowledge map, and the construction method comprises the following steps:
1) Matching a skill point with the most similar node name and a drilling task according to the voltage level and the task name in a power transformation operation and maintenance knowledge graph, and searching all child skill points connected with the node name by using the skill point as an initial skill point;
2) If the skill points close to the drilling task do not contain child skill points, searching example entity points connected with the skill points in an entity relationship, forming a skill set by the skill points and the example entity points, and finishing the construction of the skill set;
3) If the skill points close to the drilling task contain the child skill points, searching the instance entity points connected with the child skill points in an entity relationship, forming a skill set by the starting skill point, the child skill points of the starting skill point and the instance entity points of the child skill points, and finishing the construction of the skill set.
Planning a skill drilling path on the basis of constructing a skill set corresponding to the drilling task, wherein the planning method comprises the following steps:
the child skill points have precedence over the parent skill points;
the child skill points containing more child skill points are preferentially exercised, wherein the child skill points are the child skill points of a certain skill point;
the entity points are not planned into a drilling path, and for the skill points on the path, 1 is randomly selected from the example entity points for starting simulation cases in the subsequent drilling and testing processes.
And displaying the skill points to be exercised in a map and sequence mode respectively according to the skill sets and the exercise paths. In the skill point display link, the graph display mode emphasizes representing logic veins among skills, and the structure of the power transformation operation and maintenance knowledge graph related to the skill set is determined. And the sequence display mode emphasizes the sequence of the characteristic skill drilling and according to the planned power transformation operation and maintenance skill drilling path. Furthermore, two different control modes of system selection and autonomous selection are provided, in the system selection mode, the skill point to be performed first is actively selected according to the drilling path to start drilling, and in the autonomous selection, the power transformation operation and maintenance personnel can automatically select any one skill point in the skill point set to be performed to start drilling.
After the skill point to be exercised is selected, the power transformation operation and maintenance personnel can directly enter the links of learning, practicing and testing. The practice and the test are both carried out in a mode of actual operation in a transformer substation simulation scene. And when the power transformation operation and maintenance personnel enter the learning, a teaching video based on the simulation case is presented for the power transformation operation and maintenance personnel, and the power transformation operation and maintenance personnel are guided to finish the operation in the simulation scene. Wherein the presented simulation case corresponds to an instance entity point of the skill point to be exercised in the skill set.
After the power transformation operation and maintenance personnel enter the practice, a power transformation simulation scene is established for the power transformation operation and maintenance personnel for the practice exercise, and the practice result is not used as a basis for evaluating the capability of the power transformation operation and maintenance personnel. The generation mode of the simulation case is as follows: and calling and starting the pre-edited simulation case corresponding to the entity point according to the node name of the instance entity point of the skill point to be exercised.
The editing and the operation of the simulation case are supported by a power grid model and a simulation scene. Wherein the power grid model is modeled according to the steady state, quasi-steady state and electromechanical transient state processes of the whole power grid; modeling is required according to an electromagnetic transient process in a local power grid formed by a simulation transformer substation and adjacent lines, so that the operation dynamic parameters of the transformer substation are more real. The simulation scene mainly refers to transformer substation simulation, and the transformer substation simulation comprises a primary equipment three-dimensional interactive virtual scene system, a secondary equipment three-dimensional interactive virtual scene and a transformer background monitoring system, and specifically comprises detailed models of primary equipment, a control system, a measurement system, an alternating current system, a direct current system, a relay protection and automatic device and a comprehensive automatic system of a transformer substation. The simulation of the primary equipment and the secondary equipment of the transformer substation adopts a virtual reality technology to simulate, and various kinds of primary equipment and secondary equipment in the transformer substation are developed into simulation components which can be reused. And combining simulation scenes by using each simulation component, reflecting the normal, abnormal, accident states and action processes of the equipment, and considering the influence of the detailed simulation model of the transformer substation on the abstract simulation model of the power grid.
And the power transformation operation and maintenance personnel enter a testing link after practice, and are carried out in a mode of carrying out actual operation testing in a simulation scene. And according to the actual operation result, generating a summary report for the power transformation operation and maintenance personnel, and suggesting the next skill point to be exercised:
if the power transformation operation and maintenance personnel finish the actual operation test according to the correct operation steps, prompting the power transformation operation and maintenance personnel to master the skill point, recommending the power transformation operation and maintenance personnel to continue to drill other skill points in the skill point set to be drilled, and entering a skill point display link to reselect;
and if the power transformation operation and maintenance personnel do not complete the actual operation test according to the correct operation steps, prompting the power transformation operation and maintenance personnel not to master the skill point, and recommending the power transformation operation and maintenance personnel to continue practicing the skill point. And restarting the simulation case corresponding to the instance entity point of the skill point, and selecting to carry out actual exercise or actual exercise test by the power transformation operation and maintenance personnel.
And performing circulating iterative drilling according to the rule to finally form a whole set of continuous self-adaptive power transformation operation and maintenance skill drilling method.
Example 2
Still provide a self-adaptation transformer operation and maintenance knowledge learning and skill rehearsal system, include:
the map construction module is used for constructing a power transformation operation and maintenance knowledge map;
the knowledge learning module is used for learning knowledge based on the power transformation operation and maintenance knowledge map;
and the skill drill module is used for performing skill drill based on the power transformation operation and maintenance knowledge map.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (9)
1. A self-adaptive power transformation operation and maintenance knowledge learning and skill practicing method is characterized by comprising the following steps:
constructing a power transformation operation and maintenance knowledge map;
learning knowledge based on the power transformation operation and maintenance knowledge map;
and performing skill drill based on the power transformation operation and maintenance knowledge map.
2. The adaptive power transformation operation and maintenance knowledge learning and skill drilling method according to claim 1, wherein the constructing of the power transformation operation and maintenance knowledge graph comprises:
layering the obtained power transformation operation and maintenance data according to the data object categories;
defining nodes and attributes thereof in each layer;
and establishing an incidence relation among the nodes.
3. The method of claim 1, wherein the association comprises an inclusion relationship, a lead relationship, and an entity relationship.
4. The adaptive power transformation operation and maintenance knowledge learning and skill practicing method according to claim 2, wherein the learning knowledge based on the power transformation operation and maintenance knowledge graph comprises:
according to the learning tasks of the power transformation operation and maintenance personnel, a knowledge set corresponding to the learning tasks is constructed by adopting a power transformation operation and maintenance knowledge map;
planning a learning path according to a knowledge set corresponding to the learning task;
displaying knowledge points to be learned in a map and sequence mode respectively according to the planned learning path;
entering a learning, practicing or testing link of knowledge learning by selecting knowledge points to be learned;
evaluating the capability level of power transformation operation and maintenance personnel through a testing link of knowledge learning or a small pre-school test in the learning link;
and recommending learning resources according to the capability level of the power transformation operation and maintenance personnel in a learning link.
5. The adaptive power transformation operation and maintenance knowledge learning and skill practicing method according to claim 2, wherein the recommending learning resources according to the capability level of the power transformation operation and maintenance personnel comprises:
calculating the distance between the power transformation operation and maintenance personnel and the learning resources according to the capability level of the power transformation operation and maintenance personnel and the learning resources;
the learning resources with smaller distance to the power transformation operation and maintenance personnel are recommended with higher priority.
6. The adaptive power transformation operation and maintenance knowledge learning and skill practicing method according to claim 4, wherein the constructing the knowledge set corresponding to the learning task comprises:
matching a knowledge point with the closest node name and a learning task in the power transformation operation and maintenance knowledge graph according to the voltage level and the task name, and searching all child generation knowledge points connected with the knowledge point in an 'inclusion' relationship by taking the knowledge point as an initial knowledge point;
if the knowledge point closest to the learning task does not contain the child knowledge point, searching a precursor knowledge point connected with the knowledge point in a precursor relation, forming a knowledge set by the knowledge point and the precursor knowledge point, and finishing the construction of the knowledge set;
if the knowledge point closest to the learning task contains the child knowledge point, searching a pilot knowledge point connected with the child knowledge point in a pilot relationship, forming a knowledge set by the initial knowledge point, the child knowledge point of the initial knowledge point and the pilot knowledge point of the child knowledge point, and finishing the construction of the knowledge set.
7. The adaptive power transformation operation and maintenance knowledge learning and skill practicing method according to claim 6, wherein:
the planning of the learned path includes:
the leading knowledge point takes precedence over the following knowledge point;
the child knowledge points have precedence over the parent knowledge points;
the child knowledge points containing more child knowledge points are preferentially learned while being child knowledge points of a certain knowledge point;
the leading knowledge points which are the same as a certain knowledge point have the same priority, and the learning sequence is randomly arranged.
8. The adaptive power transformation operation and maintenance knowledge learning and skill drilling method according to claim 2, wherein the performing skill drilling based on the power transformation operation and maintenance knowledge map comprises:
according to the drilling tasks of the power transformation operation and maintenance personnel, a skill set corresponding to the drilling tasks is constructed by adopting a power transformation operation and maintenance knowledge map;
planning a skill drilling path according to the skill set;
displaying skill points to be exercised in a map and sequence mode respectively according to the skill set and the skill exercise path;
and entering a learning, practicing or testing link of skill drilling by selecting a skill point to be drilled.
9. An adaptive power transformation operation and maintenance knowledge learning and skill drilling system is characterized by comprising:
the map construction module is used for constructing a power transformation operation and maintenance knowledge map;
the knowledge learning module is used for learning knowledge based on the power transformation operation and maintenance knowledge map;
and the skill drill module is used for performing skill drill based on the power transformation operation and maintenance knowledge map.
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