Construction method and system of power three-dimensional model database

Abstract

The invention provides a construction method and system of an electric power three-dimensional model database. The method comprises the steps of obtaining a plurality of model feature parameters; constructing a model characteristic parameter sequence and an association relationship according to each model characteristic parameter; respectively judging whether each model characteristic parameter sequence meets a preset warehousing condition, and if any first model characteristic parameter sequence meets the warehousing condition, storing the first model characteristic parameter sequence and a plurality of corresponding first association relationships into a preset power three-dimensional model database; otherwise, updating the first model feature parameter sequence and a plurality of corresponding first association relationships based on a preset updating rule to obtain an updated second model feature parameter sequence and at least one second association relationship, and storing the second model characteristic parameter sequence, the plurality of corresponding first association relationships and the plurality of corresponding second association relationships into the power three-dimensional model database, thereby improving the space utilization rate of the power three-dimensional model database.

Description

Technical Field

[0001] The present application relates to the technical field of database construction, and in particular to a method and system for constructing a three-dimensional electric power model database. Background Art

[0002] In the power system, corresponding power 3D models can be constructed for power equipment and power scenarios. The power 3D models can provide detailed information and features of power equipment and power scenarios, allowing managers and technicians to understand the substation situation more intuitively. This can greatly improve management efficiency and reduce the possibility of misunderstanding and misoperation.

[0003] However, there are a large number of identical or similar power equipment in the substation. If the model characteristic parameters of their power three-dimensional models are collected and saved in the database, a large amount of redundant data will be generated, which may make the database space insufficient. In addition, when the model characteristic parameters are obtained later, the data search speed may be slowed down due to the large amount of data. Summary of the invention

[0004] In response to the above technical problems, the present application provides a method and system for constructing a three-dimensional electric power model database, which reduces redundant data in the three-dimensional electric power model database and improves the space utilization rate of the three-dimensional electric power model database.

[0005] In a first aspect, an embodiment of the present application provides a method for constructing a three-dimensional power model database, comprising:

[0006] Acquire several model characteristic parameters of each three-dimensional power model in the target power system;

[0007] At least one model characteristic parameter sequence and a plurality of association relationships are constructed according to the model characteristic parameters, wherein the model characteristic parameters in any of the model characteristic parameter sequences are model characteristic parameters of the same data type in each of the three-dimensional power models, and any of the association relationships are association relationships between the model characteristic parameters in a corresponding three-dimensional power model;

[0008] Determining whether each of the model characteristic parameter sequences meets a preset storage condition, if any first model characteristic parameter sequence among the model characteristic parameter sequences meets the storage condition, storing the first model characteristic parameter sequence and the corresponding first association relationships in a preset power three-dimensional model database;

[0009] If the first model characteristic parameter sequence does not meet the storage condition, the first model characteristic parameter sequence and the corresponding first association relationships are updated based on a preset update rule to obtain an updated second model characteristic parameter sequence and at least one second association relationship, and the second model characteristic parameter sequence, the corresponding first association relationships and the corresponding second association relationships are stored in the power three-dimensional model database, wherein the second association relationship is obtained by re-association of the first association relationships that meet the preset re-association condition;

[0010] When all the model characteristic parameter sequences are stored in the power three-dimensional model database, the construction of the power three-dimensional model database is completed.

[0011] The embodiment of the present application provides a method for constructing a three-dimensional power model database. By constructing a model feature parameter sequence and an association relationship, each three-dimensional power model is converted into low-dimensional data that is easier to store and process, and data preparation is made for the construction of the three-dimensional power model database. At the same time, the embodiment of the present application extracts the model feature parameters of the same data type in each of the three-dimensional power models into the same model feature parameter sequence, which is convenient for subsequent optimization of the data in the model feature parameter sequence. Further, since there are a large number of identical or similar power equipment in the power system, if the three-dimensional power model database is constructed directly by the model feature parameter sequence and the association relationship, a large amount of redundant data will be generated. Therefore, the embodiment of the present application performs a preliminary screening of each of the model feature parameter sequences by the preset storage conditions, and only stores the model feature parameter sequences and the corresponding several association relationships that meet the preset conditions. For the data that does not meet the preset conditions, update processing is performed, and the redundant data in the first model feature parameter sequence is reduced by the preset update rules, and the corresponding several first association relationships are re-associated to generate the second association relationship, while eliminating the redundant data and ensuring the integrity of the data by the second association relationship. When all model feature parameter sequences are stored in the database, the construction of the power three-dimensional model database is completed. Compared with the prior art, the embodiment of the present application effectively reduces redundant data in the power three-dimensional model database and improves the space utilization rate of the power three-dimensional model database.

[0012] Furthermore, the constructing of at least one model feature parameter sequence and a plurality of association relationships according to the respective model feature parameters includes:

[0013] Taking each of the three-dimensional power models as a unit, clustering each of the model characteristic parameters to obtain a cluster set corresponding to each of the three-dimensional power models;

[0014] Constructing at least one model feature parameter sequence according to each of the cluster sets, wherein when constructing any first model feature parameter sequence in each of the model feature parameter sequences, extracting a first model feature parameter of the same data type from each of the cluster sets, and sorting each of the first model feature parameters based on numerical values ​​to obtain the first model feature parameter sequence;

[0015] The model feature parameters corresponding to each of the cluster sets are associated to obtain the association relationship corresponding to each of the cluster sets.

[0016] In an embodiment of the present application, the model characteristic parameters that meet the conditions are clustered by clustering to obtain each cluster set based on the power three-dimensional model, and then the corresponding association relationships and at least one model characteristic parameter sequence are constructed, so as to prepare data for the construction of the power three-dimensional model database. The embodiment of the present application realizes the automatic classification of each model characteristic parameter by clustering, and improves the efficiency and accuracy of the construction of the model characteristic parameter sequence and the association relationship. The first model characteristic parameters are sorted based on the numerical value to obtain the first model characteristic parameter sequence, which facilitates the subsequent judgment of the storage conditions of each model characteristic parameter sequence and improves the efficiency of database construction.

[0017] In a possible implementation, when determining whether any first model feature parameter sequence among the model feature parameter sequences satisfies a preset storage condition, determining whether each of the model feature parameter sequences satisfies the preset storage condition includes:

[0018] Determining whether there are at least two repeated model characteristic parameters with the same value in the first model characteristic parameter sequence, and if not, determining that the first model characteristic parameter sequence meets the storage condition;

[0019] If there are at least two repeated model characteristic parameters with the same value in the first model characteristic parameter sequence, determining whether the association relationships corresponding to the repeated model characteristic parameters are completely consistent, and if they are completely consistent, determining that the first model characteristic parameter sequence meets the storage condition;

[0020] If the association relationships corresponding to the repeated model feature parameters are not completely consistent, it is determined that the first model feature parameter sequence does not meet the storage condition.

[0021] In the embodiment of the present application, taking the first model characteristic parameter sequence as an example, by sequentially judging the repeatability of the first model characteristic parameter sequence and several first associations, it is judged whether the first model characteristic parameter sequence can be directly stored. Among them, the first model characteristic parameter sequence is firstly judged for repeatability to judge whether there are at least two repeated model characteristic parameters with the same value in the first model characteristic parameter sequence. When there are at least two repeated model characteristic parameters, it means that there may be two corresponding identical power three-dimensional models. At this time, a secondary judgment is made by the association relationship corresponding to the repeated model characteristic parameters. Only when the model characteristic parameters are repeated and the corresponding association relationships are completely consistent, it can be determined that the power three-dimensional models corresponding to these model characteristic parameters are the same. At this time, the first model characteristic parameter sequence and several first association relationships can be directly stored, and the deduplication function of the database can automatically process duplicate data. If the model characteristic parameters are repeated but the association relationships are different, it means that there are two similar power three-dimensional models, and deduplication cannot be directly performed. Then the first model characteristic parameter sequence does not meet the storage conditions, and the data needs to be further optimized and updated. The embodiment of the present application avoids storing the same three-dimensional power model data through two judgments during the database construction process, and at the same time screens out data that needs to be further optimized and updated, thereby improving the space utilization rate of the three-dimensional power model database.

[0022] Furthermore, the determining whether the association relationships corresponding to the characteristic parameters of each repeated model are completely consistent includes:

[0023] Determining whether the data types of the model feature parameters of the association relationship corresponding to each of the repeated model feature parameters are completely consistent;

[0024] It is determined whether the values ​​of the association relationships corresponding to the characteristic parameters of each repeated model are completely consistent.

[0025] In a possible implementation, storing the first model characteristic parameter sequence and the corresponding first association relationships in a preset power three-dimensional model database includes:

[0026] Storing the first model characteristic parameter sequence in a first data sub-database in the power three-dimensional model database;

[0027] The corresponding plurality of first association relationships are stored in a second data sub-database in the power three-dimensional model database.

[0028] In the process of constructing the electric power three-dimensional model database, the embodiment of the present application constructs a first data sub-library and a second data word library, wherein the first data word library is used to store the model feature parameter sequence, and the second data word library is used to store the association relationship. This is because the model feature parameter sequence is a numerical type of data, and the association relationship mainly represents the corresponding relationship between each numerical type of data. Therefore, different databases need to be used to process the model feature parameter sequence and the association relationship, thereby improving the space utilization and management efficiency of the electric power three-dimensional model database.

[0029] In a possible implementation, updating the first model feature parameter sequence and the corresponding plurality of first association relationships based on a preset update rule to obtain an updated second model feature parameter sequence and the corresponding plurality of second association relationships includes:

[0030] Determine each repeated model characteristic parameter with the same value in the first model characteristic parameter sequence and a first association relationship corresponding to each repeated model characteristic parameter, and obtain at least one set of repeated model characteristic parameter groups and an association relationship group corresponding to the repeated model characteristic parameter groups;

[0031] De-duplication operation is performed on the first model characteristic parameter sequence according to each of the repeated model characteristic parameters to obtain a second model characteristic parameter sequence without identical values;

[0032] For each of the association relationship groups, the first association relationships in the association relationship group are associated to obtain a second association relationship corresponding to the association relationship group, and then obtain second association relationships corresponding to each of the association relationship groups.

[0033] The embodiment of the present application provides a method for updating a model feature parameter sequence and an association relationship. For a first model feature parameter sequence that does not meet the storage conditions, a second association relationship is generated by performing numerical deduplication processing on the first model feature parameter sequence and re-association processing on the corresponding association relationship. Such processing enables a plurality of first association relationships to be quickly retrieved through the second association relationship when a subsequent user inputs a model feature parameter value, thereby reducing the amount of data while not affecting the user's acquisition of other feature parameter values. In the process of constructing a database, the embodiment of the present application not only effectively reduces redundant data, but also ensures the integrity of the data, and improves the database retrieval speed when subsequently acquiring model feature parameters. It is particularly suitable for the storage of model feature parameters of a large number of identical or similar power equipment corresponding to a three-dimensional power model in a substation.

[0034] In a possible implementation, storing the second model characteristic parameter sequence, the corresponding plurality of first association relationships, and the corresponding plurality of second association relationships in the power three-dimensional model database includes:

[0035] storing the second model characteristic parameter sequence in the first data sub-database of the power three-dimensional model database;

[0036] Storing the corresponding plurality of first association relationships in a second data sub-database in the power three-dimensional model database;

[0037] The corresponding plurality of second association relationships are stored in a third data sub-database in the power three-dimensional model database.

[0038] Furthermore, the method further includes: encrypting the second data sub-base and the third data sub-base.

[0039] The embodiment of the present application improves the data security of the electric power three-dimensional model by encrypting the second data sub-library and the third data sub-library.

[0040] In the second aspect, accordingly, an embodiment of the present application provides a system for constructing a three-dimensional power model database, including an acquisition module, a first construction module, a judgment module, an update module, and a second construction module;

[0041] Wherein, the acquisition module is used to acquire several model characteristic parameters of each power three-dimensional model in the target power system;

[0042] The first construction module is used to construct at least one model characteristic parameter sequence and a plurality of association relationships according to the model characteristic parameters, wherein the model characteristic parameters in any of the model characteristic parameter sequences are model characteristic parameters of the same data type in each of the three-dimensional power models, and any of the association relationships are association relationships between the model characteristic parameters in a corresponding three-dimensional power model;

[0043] The judgment module is used to judge whether each of the model characteristic parameter sequences meets the preset storage conditions, and if any first model characteristic parameter sequence among the model characteristic parameter sequences meets the storage conditions, the first model characteristic parameter sequence and the corresponding first association relationships are stored in the preset power three-dimensional model database;

[0044] The updating module is used for updating the first model characteristic parameter sequence and the corresponding first association relationships based on a preset updating rule if the first model characteristic parameter sequence does not meet the storage condition, obtaining an updated second model characteristic parameter sequence and at least one second association relationship, and storing the second model characteristic parameter sequence, the corresponding first association relationships and the corresponding second association relationships in the power three-dimensional model database, wherein the second association relationship is obtained by re-association of the first association relationships that meet the preset re-association condition;

[0045] The second construction module is used to complete the construction of the power three-dimensional model database after all the model characteristic parameter sequences are stored in the power three-dimensional model database.

[0046] Furthermore, the first construction module includes a clustering unit, a model feature parameter sequence construction unit and an association relationship construction unit;

[0047] The clustering unit is used to cluster the characteristic parameters of each model based on each of the three-dimensional power models to obtain a cluster set corresponding to each of the three-dimensional power models;

[0048] The model feature parameter sequence construction unit is used to construct at least one model feature parameter sequence according to each of the cluster sets, wherein when constructing any first model feature parameter sequence in each of the model feature parameter sequences, a first model feature parameter of the same data type is extracted from each of the cluster sets, and each of the first model feature parameters is sorted based on the numerical value to obtain the first model feature parameter sequence;

[0049] The association relationship building unit is used to associate each model feature parameter corresponding to each cluster set to obtain an association relationship corresponding to each cluster set. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 : A flow chart of a method for constructing a three-dimensional power model database provided in an embodiment of the present application.

[0051] Figure 2 : A flow chart of constructing a model feature parameter sequence and association relationship in a method for constructing a three-dimensional power model database provided in an embodiment of the present application.

[0052] Figure 3 : A structural diagram of a system for constructing a three-dimensional power model database provided in an embodiment of the present application.

[0053] Figure 4 : A structural diagram of the first construction module in a system for constructing a three-dimensional power model database provided in an embodiment of the present application.

[0054] Figure 5 : A structural schematic diagram of an electronic device for implementing a method for constructing a three-dimensional power model database provided in an embodiment of the present application. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0056] It should be noted that the step numbers in the text are only for the convenience of explanation of the specific embodiments and do not serve to limit the order in which the steps are executed. In the description of this application, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features.

[0057] Embodiment 1:

[0058] like Figure 1 As shown, the first embodiment provides a method for constructing a three-dimensional power model database, including steps S1-S5:

[0059] Step S1, obtaining several model characteristic parameters of each three-dimensional power model in the target power system;

[0060] Step S2: constructing at least one model characteristic parameter sequence and a plurality of association relationships according to the model characteristic parameters, wherein the model characteristic parameters in any of the model characteristic parameter sequences are model characteristic parameters of the same data type in each of the three-dimensional power models, and any of the association relationships are association relationships between the model characteristic parameters in a corresponding three-dimensional power model;

[0061] Step S3, respectively judging whether each of the model characteristic parameter sequences meets the preset storage conditions, if any first model characteristic parameter sequence among the model characteristic parameter sequences meets the storage conditions, storing the first model characteristic parameter sequence and the corresponding first association relationships in a preset power three-dimensional model database;

[0062] Step S4: if the first model characteristic parameter sequence does not meet the storage condition, then based on a preset update rule, the first model characteristic parameter sequence and the corresponding first association relationships are updated to obtain an updated second model characteristic parameter sequence and at least one second association relationship, and the second model characteristic parameter sequence, the corresponding first association relationships and the corresponding second association relationships are stored in the power three-dimensional model database, wherein the second association relationship is obtained by re-association of the first association relationships that meet the preset re-association condition;

[0063] Step S5: After all the model characteristic parameter sequences are stored in the power three-dimensional model database, the construction of the power three-dimensional model database is completed.

[0064] The embodiment of the present application provides a method for constructing a three-dimensional power model database. By constructing a model feature parameter sequence and an association relationship, each three-dimensional power model is converted into low-dimensional data that is easier to store and process, and data preparation is made for the construction of the three-dimensional power model database. At the same time, the embodiment of the present application extracts the model feature parameters of the same data type in each of the three-dimensional power models into the same model feature parameter sequence, which is convenient for subsequent optimization of the data in the model feature parameter sequence. Further, since there are a large number of identical or similar power equipment in the power system, if the three-dimensional power model database is constructed directly by the model feature parameter sequence and the association relationship, a large amount of redundant data will be generated. Therefore, the embodiment of the present application performs a preliminary screening of each of the model feature parameter sequences by the preset storage conditions, and only stores the model feature parameter sequences and the corresponding several association relationships that meet the preset conditions. For the data that does not meet the preset conditions, update processing is performed, and the redundant data in the first model feature parameter sequence is reduced by the preset update rules, and the corresponding several first association relationships are re-associated to generate the second association relationship, while eliminating the redundant data and ensuring the integrity of the data by the second association relationship. When all model feature parameter sequences are stored in the database, the construction of the power three-dimensional model database is completed. Compared with the prior art, the embodiment of the present application effectively reduces redundant data in the power three-dimensional model database and improves the space utilization rate of the power three-dimensional model database.

[0065] In step S1, the target power system may be any power system. The target power system may include multiple power entities, for example, multiple power equipment. A corresponding power three-dimensional model may be constructed for each of the multiple power entities. For example, a three-dimensional power equipment model of each power equipment may be constructed for the power equipment. The model characteristic parameters may be geometric dimensions, angles, curvatures, etc.

[0066] Furthermore, in step S2, at least one model feature parameter sequence and a plurality of association relationships are constructed according to the various model feature parameters, such as Figure 2 As shown, steps S201-S203 are included:

[0067] Step S201: clustering each of the model characteristic parameters with each of the three-dimensional power models as a unit to obtain a cluster set corresponding to each of the three-dimensional power models;

[0068] Step S202: construct at least one model feature parameter sequence according to each of the cluster sets, wherein when constructing any first model feature parameter sequence in each of the model feature parameter sequences, extract a first model feature parameter of the same data type from each of the cluster sets, and sort each of the first model feature parameters based on numerical values ​​to obtain the first model feature parameter sequence;

[0069] Step S203: Associating each model feature parameter corresponding to each cluster set to obtain an association relationship corresponding to each cluster set.

[0070] In a preferred embodiment, taking power equipment A and power equipment B as examples, the corresponding power three-dimensional models are model A and model B. In step S201, clustering is performed on each of the model feature parameters to obtain cluster set A and cluster set B corresponding to model A and model B. Cluster set A includes feature parameters: geometric dimension a, angle b and curvature c, and cluster set B includes feature parameters: geometric dimension d and angle e. In step S202, the first model feature parameters of the same data type are extracted from each of the cluster sets, and the first model feature parameters are sorted based on the numerical value to obtain the first model feature parameter sequence. The model feature parameter sequence that can be obtained is {geometric dimension a, geometric dimension d} and {angle b, angle e}. In step S203, the model feature parameters corresponding to each of the cluster sets are associated to obtain the association relationship corresponding to each of the cluster sets. The association relationship that can be obtained is association relationship A: geometric dimension a-angle b-curvature c, and association relationship B: geometric dimension d-angle e.

[0071] In an embodiment of the present application, the model characteristic parameters that meet the conditions are clustered by clustering to obtain each cluster set based on the power three-dimensional model, and then the corresponding association relationships and at least one model characteristic parameter sequence are constructed, so as to prepare data for the construction of the power three-dimensional model database. The embodiment of the present application realizes the automatic classification of each model characteristic parameter by clustering, and improves the efficiency and accuracy of the construction of the model characteristic parameter sequence and the association relationship. The first model characteristic parameters are sorted based on the numerical value to obtain the first model characteristic parameter sequence, which facilitates the subsequent judgment of the storage conditions of each model characteristic parameter sequence and improves the efficiency of database construction.

[0072] In a possible implementation, in step S3, when determining whether any first model feature parameter sequence in each of the model feature parameter sequences satisfies a preset storage condition, the step of determining whether each of the model feature parameter sequences satisfies the preset storage condition comprises:

[0073] Determining whether there are at least two repeated model characteristic parameters with the same value in the first model characteristic parameter sequence, and if not, determining that the first model characteristic parameter sequence meets the storage condition;

[0074] If there are at least two repeated model characteristic parameters with the same value in the first model characteristic parameter sequence, determining whether the association relationships corresponding to the repeated model characteristic parameters are completely consistent, and if they are completely consistent, determining that the first model characteristic parameter sequence meets the storage condition;

[0075] If the association relationships corresponding to the repeated model feature parameters are not completely consistent, it is determined that the first model feature parameter sequence does not meet the storage condition.

[0076] In the embodiment of the present application, taking the first model characteristic parameter sequence as an example, by sequentially judging the repeatability of the first model characteristic parameter sequence and several first associations, it is judged whether the first model characteristic parameter sequence can be directly stored. Among them, the first model characteristic parameter sequence is firstly judged for repeatability to judge whether there are at least two repeated model characteristic parameters with the same value in the first model characteristic parameter sequence. When there are at least two repeated model characteristic parameters, it means that there may be two corresponding identical power three-dimensional models. At this time, a secondary judgment is made by the association relationship corresponding to the repeated model characteristic parameters. Only when the model characteristic parameters are repeated and the corresponding association relationships are completely consistent, it can be determined that the power three-dimensional models corresponding to these model characteristic parameters are the same. At this time, the first model characteristic parameter sequence and several first association relationships can be directly stored, and the deduplication function of the database can automatically process duplicate data. If the model characteristic parameters are repeated but the association relationships are different, it means that there are two similar power three-dimensional models, and deduplication cannot be directly performed. Then the first model characteristic parameter sequence does not meet the storage conditions, and the data needs to be further optimized and updated. The embodiment of the present application avoids storing the same three-dimensional power model data through two judgments during the database construction process, and at the same time screens out data that needs to be further optimized and updated, thereby improving the space utilization rate of the three-dimensional power model database.

[0077] Furthermore, the determining whether the association relationships corresponding to the characteristic parameters of each repeated model are completely consistent includes:

[0078] Determining whether the data types of the model feature parameters of the association relationship corresponding to each of the repeated model feature parameters are completely consistent;

[0079] It is determined whether the values ​​of the association relationships corresponding to the characteristic parameters of each repeated model are completely consistent.

[0080] In a preferred embodiment, taking association relationship A and association relationship B as an example, it is determined whether association relationship A and association relationship B have the same number and type of model characteristic parameters, and whether the values ​​of the model characteristic parameters corresponding to association relationship A and association relationship B are completely consistent. Specifically, if association relationship A is: geometric dimension a-angle b-curvature c; when association relationship B is also: geometric dimension a-angle b-curvature c, then it is determined that association relationship A and association relationship B are consistent, if association relationship B is: geometric dimension a-angle b, then association relationship A and first association relationship B are inconsistent, and further, if association relationship B is: geometric dimension a-angle b-curvature d, then association relationship A and association relationship B are also inconsistent.

[0081] In a possible implementation, in step S3, storing the first model characteristic parameter sequence and the corresponding first association relationships in a preset power three-dimensional model database includes:

[0082] Storing the first model characteristic parameter sequence in a first data sub-database in the power three-dimensional model database;

[0083] The corresponding plurality of first association relationships are stored in a second data sub-database in the power three-dimensional model database.

[0084] In the process of constructing the electric power three-dimensional model database, the embodiment of the present application constructs a first data sub-library and a second data word library, wherein the first data word library is used to store the model feature parameter sequence, and the second data word library is used to store the association relationship. This is because the model feature parameter sequence is a numerical type of data, and the association relationship mainly represents the corresponding relationship between each numerical type of data. Therefore, different databases need to be used to process the model feature parameter sequence and the association relationship, thereby improving the space utilization and management efficiency of the electric power three-dimensional model database.

[0085] In a possible implementation, in step S4, updating the first model feature parameter sequence and the corresponding first association relationships based on a preset update rule to obtain an updated second model feature parameter sequence and the corresponding second association relationships includes:

[0086] Determine each repeated model characteristic parameter with the same value in the first model characteristic parameter sequence and a first association relationship corresponding to each repeated model characteristic parameter, and obtain at least one set of repeated model characteristic parameter groups and an association relationship group corresponding to the repeated model characteristic parameter groups;

[0087] De-duplication operation is performed on the first model characteristic parameter sequence according to each of the repeated model characteristic parameters to obtain a second model characteristic parameter sequence without identical values;

[0088] For each of the association relationship groups, the first association relationships in the association relationship group are associated to obtain a second association relationship corresponding to the association relationship group, and then the second association relationships corresponding to each of the association relationship groups are obtained.

[0089] In a preferred embodiment, taking the first model feature parameter sequence {geometric dimension a, geometric dimension b, geometric dimension b, geometric dimension c} as an example, the corresponding first association relationships are association relationship A, association relationship B1, association relationship B2, and association relationship C. When it is found that the first model feature parameter sequence has a repeated value geometric dimension b, it is determined that the repeated model feature parameter group is {geometric dimension b, geometric dimension b} and the corresponding association relationship group is {association relationship B1, association relationship B2}. Then, the first model feature parameter sequence is deduplicated to obtain the second model feature parameter sequence {geometric dimension a, geometric dimension b, geometric dimension c}, and the association relationships in the association relationship group are associated to obtain the second association relationship: geometric dimension b-{association relationship B1, association relationship B2}. By establishing the second association relationship, when the subsequent user enters the geometric dimension b for query, the association relationship B1 and the association relationship B2 can be queried at the same time.

[0090] The embodiment of the present application provides a method for updating a model feature parameter sequence and an association relationship. For a first model feature parameter sequence that does not meet the storage conditions, a second association relationship is generated by performing numerical deduplication processing on the first model feature parameter sequence and re-association processing on the corresponding association relationship. Such processing enables a plurality of first association relationships to be quickly retrieved through the second association relationship when a subsequent user inputs a model feature parameter value, thereby reducing the amount of data while not affecting the user's acquisition of other feature parameter values. In the process of constructing a database, the embodiment of the present application not only effectively reduces redundant data, but also ensures the integrity of the data, and improves the database retrieval speed when subsequently acquiring model feature parameters. It is particularly suitable for the storage of model feature parameters of a large number of identical or similar power equipment corresponding to a three-dimensional power model in a substation.

[0091] In a possible implementation, in step S4, storing the second model characteristic parameter sequence, the corresponding first association relationships, and the corresponding second association relationships in the power three-dimensional model database includes:

[0092] storing the second model characteristic parameter sequence in the first data sub-database of the power three-dimensional model database;

[0093] Storing the corresponding plurality of first association relationships in a second data sub-database in the power three-dimensional model database;

[0094] The corresponding plurality of second association relationships are stored in a third data sub-database in the power three-dimensional model database.

[0095] Furthermore, the method further includes: encrypting the second data sub-base and the third data sub-base.

[0096] The embodiment of the present application improves the data security of the electric power three-dimensional model by encrypting the second data sub-library and the third data sub-library.

[0097] Embodiment 2:

[0098] like Figure 3 As shown, accordingly, the second embodiment provides a system for constructing a three-dimensional power model database, including an acquisition module 10, a first construction module 20, a judgment module 30, an update module 40 and a second construction module 50;

[0099] The acquisition module 10 is used to acquire several model characteristic parameters of each three-dimensional power model in the target power system;

[0100] The first construction module 20 is used to construct at least one model characteristic parameter sequence and a plurality of association relationships according to the model characteristic parameters, wherein the model characteristic parameters in any of the model characteristic parameter sequences are model characteristic parameters of the same data type in each of the three-dimensional power models, and any of the association relationships are association relationships between the model characteristic parameters in a corresponding three-dimensional power model;

[0101] The judging module 30 is used to judge whether each of the model characteristic parameter sequences meets the preset storage conditions. If any first model characteristic parameter sequence among the model characteristic parameter sequences meets the storage conditions, the first model characteristic parameter sequence and the corresponding first association relationships are stored in the preset power three-dimensional model database;

[0102] The updating module 40 is used for updating the first model characteristic parameter sequence and the corresponding first association relationships based on a preset updating rule if the first model characteristic parameter sequence does not meet the storage condition, obtaining an updated second model characteristic parameter sequence and at least one second association relationship, and storing the second model characteristic parameter sequence, the corresponding first association relationships and the corresponding second association relationships in the power three-dimensional model database, wherein the second association relationship is obtained by re-association of the first association relationships that meet the preset re-association condition;

[0103] The second construction module 50 is used to complete the construction of the power three-dimensional model database after all the model characteristic parameter sequences are stored in the power three-dimensional model database.

[0104] Further, such as Figure 4 As shown, the first construction module 20 includes a clustering unit 201, a model feature parameter sequence construction unit 202, and an association relationship construction unit 203;

[0105] The clustering unit 201 is used to cluster the characteristic parameters of each model based on each of the three-dimensional power models to obtain a cluster set corresponding to each of the three-dimensional power models;

[0106] The model feature parameter sequence construction unit 202 is used to construct at least one model feature parameter sequence according to each of the cluster sets, wherein when constructing any first model feature parameter sequence in each of the model feature parameter sequences, a first model feature parameter of the same data type is extracted from each of the cluster sets, and each of the first model feature parameters is sorted based on the numerical value to obtain the first model feature parameter sequence;

[0107] The association relationship building unit 203 is used to associate each model feature parameter corresponding to each cluster set to obtain an association relationship corresponding to each cluster set.

[0108] The embodiment of the present application provides a system for constructing a three-dimensional power model database. By constructing a model feature parameter sequence and an association relationship, each three-dimensional power model is converted into low-dimensional data that is easier to store and process, and data preparation is made for the construction of the three-dimensional power model database. At the same time, the embodiment of the present application extracts the model feature parameters of the same data type in each of the three-dimensional power models into the same model feature parameter sequence, which is convenient for the subsequent optimization of the data in the model feature parameter sequence. Further, since there are a large number of identical or similar power equipment in the power system, if the three-dimensional power model database is constructed directly by the model feature parameter sequence and the association relationship, a large amount of redundant data will be generated. Therefore, the embodiment of the present application performs a preliminary screening of each of the model feature parameter sequences by the preset storage conditions, and only stores the model feature parameter sequences and the corresponding several association relationships that meet the preset conditions. For the data that does not meet the preset conditions, the update processing is performed, and the redundant data in the first model feature parameter sequence is reduced by the preset update rules, and the corresponding several first association relationships are re-associated to generate the second association relationship, and the data integrity is ensured by the second association relationship while eliminating the redundant data. When all model feature parameter sequences are stored in the database, the construction of the power three-dimensional model database is completed. Compared with the prior art, the embodiment of the present application effectively reduces redundant data in the power three-dimensional model database and improves the space utilization rate of the power three-dimensional model database.

[0109] The more detailed working principle and step flow of this embodiment can refer to, but are not limited to, the relevant records of Embodiment 1.

[0110] Embodiment three:

[0111] Embodiment 3 provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the processor executes any one of the methods for constructing a three-dimensional power model database described in the embodiments of the present application.

[0112] The computer-readable storage medium may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the power three-dimensional model database construction system, etc. In addition, the computer-readable storage medium may include a high-speed random access memory, and may also include a memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the computer-readable storage medium may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the power three-dimensional model database construction system via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0113] Figure 5 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application, such as Figure 5 As shown, the device includes: a processor 310 and a memory 320. The electronic device may also include: an input device 330 and an output device 340. The processor 310, the memory 320, the input device 330 and the output device 340 may be connected via a bus or other means. Figure 5 The example of the bus connection is taken. The memory 320 is the above-mentioned computer-readable storage medium. The processor 310 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions and modules stored in the memory 320, that is, the method for constructing a three-dimensional model database of the power in the above-mentioned method embodiment is realized. The input device 330 can receive input digital or character information, and generate key signal input related to user settings and function control of the power three-dimensional model database construction system. The output device 340 may include display devices such as display screens.

[0114] The electronic device can execute the method provided in the embodiment of the present application, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not described in detail in this embodiment, please refer to the method provided in the first embodiment of the present invention.

[0115] As an embodiment, the above-mentioned electronic device is applied to a power three-dimensional model database construction system, used for a client, and includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor so that at least one processor can execute any one of the power three-dimensional model database construction methods described in the embodiments of the present application.

[0116] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or some parts of the embodiment.

[0117] The specific embodiments described above further describe the purpose, technical solutions and beneficial effects of the present application in detail. It should be understood that the above description is only a specific embodiment of the present application and is not intended to limit the scope of protection of the present application. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of protection of the present application.

Claims

1. A method for constructing a three-dimensional power model database, characterized in that: include: Acquire several model characteristic parameters of each three-dimensional power model in the target power system; At least one model characteristic parameter sequence and a plurality of association relationships are constructed according to the model characteristic parameters, wherein the model characteristic parameters in any of the model characteristic parameter sequences are model characteristic parameters of the same data type in each of the three-dimensional power models, and any of the association relationships are association relationships between the model characteristic parameters in a corresponding three-dimensional power model; Determining whether each of the model characteristic parameter sequences meets a preset storage condition, if any first model characteristic parameter sequence among the model characteristic parameter sequences meets the storage condition, storing the first model characteristic parameter sequence and the corresponding first association relationships in a preset power three-dimensional model database; If the first model characteristic parameter sequence does not meet the storage condition, the first model characteristic parameter sequence and the corresponding first association relationships are updated based on a preset update rule to obtain an updated second model characteristic parameter sequence and at least one second association relationship, and the second model characteristic parameter sequence, the corresponding first association relationships and the corresponding second association relationships are stored in the power three-dimensional model database, wherein the second association relationship is obtained by re-association of the first association relationships that meet the preset re-association condition; When all the model characteristic parameter sequences are stored in the power three-dimensional model database, the construction of the power three-dimensional model database is completed.

2. The method for constructing a three-dimensional power model database according to claim 1, characterized in that: The step of constructing at least one model feature parameter sequence and a plurality of association relationships according to each model feature parameter comprises: Taking each of the three-dimensional power models as a unit, clustering each of the model characteristic parameters to obtain a cluster set corresponding to each of the three-dimensional power models; Constructing at least one model feature parameter sequence according to each of the cluster sets, wherein when constructing any first model feature parameter sequence in each of the model feature parameter sequences, extracting a first model feature parameter of the same data type from each of the cluster sets, and sorting each of the first model feature parameters based on numerical values ​​to obtain the first model feature parameter sequence; The model feature parameters corresponding to each of the cluster sets are associated to obtain the association relationship corresponding to each of the cluster sets.

3. The method for constructing a three-dimensional power model database according to claim 1, characterized in that: When determining whether any first model feature parameter sequence among the model feature parameter sequences satisfies the preset storage condition, the step of respectively determining whether each model feature parameter sequence satisfies the preset storage condition includes: Determining whether there are at least two repeated model characteristic parameters with the same value in the first model characteristic parameter sequence, and if not, determining that the first model characteristic parameter sequence meets the storage condition; If there are at least two repeated model characteristic parameters with the same value in the first model characteristic parameter sequence, determining whether the association relationships corresponding to the repeated model characteristic parameters are completely consistent, and if they are completely consistent, determining that the first model characteristic parameter sequence meets the storage condition; If the association relationships corresponding to the repeated model feature parameters are not completely consistent, it is determined that the first model feature parameter sequence does not meet the storage condition.

4. The method for constructing a three-dimensional power model database according to claim 3, characterized in that: The determining whether the association relationships corresponding to the characteristic parameters of the repeated models are completely consistent includes: Determining whether the data types of the model feature parameters of the association relationship corresponding to each of the repeated model feature parameters are completely consistent; It is determined whether the values ​​of the association relationships corresponding to the characteristic parameters of each repeated model are completely consistent.

5. The method for constructing a three-dimensional power model database according to claim 1, characterized in that: The storing of the first model characteristic parameter sequence and the corresponding first association relationships into a preset power three-dimensional model database includes: Storing the first model characteristic parameter sequence in a first data sub-database in the power three-dimensional model database; The corresponding plurality of first association relationships are stored in a second data sub-database in the power three-dimensional model database.

6. The method for constructing a three-dimensional power model database according to claim 1, characterized in that: The updating of the first model feature parameter sequence and the corresponding first association relationships based on a preset updating rule to obtain an updated second model feature parameter sequence and the corresponding second association relationships includes: Determine each repeated model characteristic parameter with the same value in the first model characteristic parameter sequence and a first association relationship corresponding to each repeated model characteristic parameter, and obtain at least one set of repeated model characteristic parameter groups and an association relationship group corresponding to the repeated model characteristic parameter groups; De-duplication operation is performed on the first model characteristic parameter sequence according to each of the repeated model characteristic parameters to obtain a second model characteristic parameter sequence without identical values; For each of the association relationship groups, the first association relationships in the association relationship group are associated to obtain a second association relationship corresponding to the association relationship group, and then obtain second association relationships corresponding to each of the association relationship groups.

7. The method for constructing a three-dimensional power model database according to claim 1, characterized in that: The storing the second model characteristic parameter sequence, the corresponding plurality of first association relationships and the corresponding plurality of second association relationships into the power three-dimensional model database includes: storing the second model characteristic parameter sequence in the first data sub-database of the power three-dimensional model database; Storing the corresponding plurality of first association relationships in a second data sub-database in the power three-dimensional model database; The corresponding plurality of second association relationships are stored in a third data sub-database in the power three-dimensional model database.

8. The method for constructing a three-dimensional power model database according to claim 7, characterized in that: The method further includes: encrypting the second data sub-base and the third data sub-base.

9. A system for constructing a three-dimensional power model database, characterized in that: It includes an acquisition module, a first construction module, a judgment module, an update module and a second construction module; Wherein, the acquisition module is used to acquire several model characteristic parameters of each power three-dimensional model in the target power system; The first construction module is used to construct at least one model characteristic parameter sequence and a plurality of association relationships according to the model characteristic parameters, wherein the model characteristic parameters in any of the model characteristic parameter sequences are model characteristic parameters of the same data type in each of the three-dimensional power models, and any of the association relationships are association relationships between the model characteristic parameters in a corresponding three-dimensional power model; The judgment module is used to judge whether each of the model characteristic parameter sequences meets the preset storage conditions, and if any first model characteristic parameter sequence among the model characteristic parameter sequences meets the storage conditions, the first model characteristic parameter sequence and the corresponding first association relationships are stored in the preset power three-dimensional model database; The updating module is used for updating the first model characteristic parameter sequence and the corresponding first association relationships based on a preset updating rule if the first model characteristic parameter sequence does not meet the storage condition, obtaining an updated second model characteristic parameter sequence and at least one second association relationship, and storing the second model characteristic parameter sequence, the corresponding first association relationships and the corresponding second association relationships in the power three-dimensional model database, wherein the second association relationship is obtained by re-association of the first association relationships that meet the preset re-association condition; The second construction module is used to complete the construction of the power three-dimensional model database after all the model characteristic parameter sequences are stored in the power three-dimensional model database.

10. A system for constructing a three-dimensional power model database as claimed in claim 9, characterized in that: The first construction module includes a clustering unit, a model feature parameter sequence construction unit and an association relationship construction unit; The clustering unit is used to cluster the characteristic parameters of each model based on each of the three-dimensional power models to obtain a cluster set corresponding to each of the three-dimensional power models; The model feature parameter sequence construction unit is used to construct at least one model feature parameter sequence according to each of the cluster sets, wherein when constructing any first model feature parameter sequence in each of the model feature parameter sequences, a first model feature parameter of the same data type is extracted from each of the cluster sets, and each of the first model feature parameters is sorted based on the numerical value to obtain the first model feature parameter sequence; The association relationship building unit is used to associate each model feature parameter corresponding to each cluster set to obtain an association relationship corresponding to each cluster set.

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