Three-dimensional visual intelligent auxiliary operation system for 10kV switch cabinet

Abstract

The invention discloses a three-dimensional visual intelligent auxiliary operation system for a 10kV switch cabinet, and relates to the technical field of three-dimensional visual auxiliary of switch cabinets. The content import unit is used for transmitting operation items including operation names reflecting names of related operation of the switch cabinet and operation execution information fusion used for reflecting corresponding execution steps to the self-modeling unit, and the self-modeling unit is used for establishing a corresponding three-dimensional teaching model according to each operation item and guiding user operation; meanwhile, a fuzzy associated keyword retrieval method constructed by the index construction unit can adapt to the situation that many people are not good at describing the problem, and consequently the problem cannot be accurately positioned, so that the operation of the method is more convenient, and the method is simple, effective and easy to use.

Description

Technical Field

[0001] The present invention belongs to the technical field of three-dimensional visualization auxiliary operation of switch cabinets, and specifically is a three-dimensional visualization intelligent auxiliary operation system for 10kV switch cabinets. Background Art

[0002] The patent with publication number CN116505401A discloses a high-visualization high-voltage switch cabinet, which belongs to the technical field of high-voltage switch cabinets, including a device housing and a working mechanism installed inside the device housing, wherein the working mechanism includes a support assembly and a mounting assembly; the support assembly includes a horizontal frame, a vertical frame, a mounting frame, a fastening bolt, and an adjusting horizontal plate, and a horizontal frame is installed inside the device housing; the high-visualization high-voltage switch cabinet provided by the present invention, when in use, when the moving frame is extended and retracted inside the square frame, the double plates will be translated in the front-back direction inside the device, and when the translation is performed, the clamping frame will rotate with the double plates through the third rotating shaft, and when the rotation is performed, the arc frame will extend and retract to clamp the wires inside the device, and at the same time, when the rotation is adjusted, the springs at both ends will extend and retract with the fixed axis, and the clamping force comes from the spring during the clamping process. Due to the setting of the spring, the clamping force remains almost unchanged, making the device more stable and convenient to use.

[0003] For switch cabinets, how to develop an auxiliary operating system that can help users operate quickly is a difficult problem. After all, sometimes it involves some professional issues. When it is rarely involved, professional operators may also make mistakes. For novices, there is a situation where they cannot master all operations proficiently. So how to provide an auxiliary system that can have a teaching nature is a problem. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes a three-dimensional visual intelligent auxiliary operating system for a 10kV switch cabinet, comprising:

[0005] The content import unit is used to transmit the operation name including the name of the switch cabinet related operation and the operation item for reflecting the fusion of the operation execution information of the corresponding execution step to the self-modeling unit, and the self-modeling unit is used to establish a corresponding three-dimensional teaching model according to each operation item to guide the user operation;

[0006] The index construction unit is used to construct retrieval information according to the operation name and the corresponding index address that can jump to the teaching model, segment the operation name, obtain the associated phrases by obtaining synonyms for each segment, and all the operation segments and their corresponding associated phrases constitute fuzzy retrieval phrases; the operation name and its corresponding index address and the fuzzy retrieval phrase are merged to form retrieval information; the index construction unit is also used to save the retrieval information.

[0007] Furthermore, it also includes

[0008] The demand import unit is used for users to input teaching requirements. Teaching requirements are descriptive texts of related operations. The demand import unit automatically transmits the teaching requirements to the self-calling unit. The self-calling unit receives the teaching requirements transmitted by the demand import unit and automatically combines the index building unit and calls the model. The specific calling method is:

[0009] The teaching needs are obtained, and then when the teaching needs are similar to the fuzzy search phrases in the search information and the similarity exceeds X1, the index address and operation name corresponding to the fuzzy search phrases are automatically marked as potential selection information, and all potential selection information is obtained;

[0010] With the help of the operator, a potential selection information is designated as teaching information. At this time, the corresponding teaching model will be automatically called through the index address and displayed through the display unit; if the administrator does not make a selection, it means that the currently recommended potential selection information is wrong.

[0011] Furthermore, the content import unit is used to import all operation items, which include operation names and operation execution information. The operation name refers to the name of the corresponding operation to be performed, or the description of the problem during the problem handling process. The operation execution information is the specific operation steps corresponding to the operation name.

[0012] Furthermore, the content import unit is used to transfer operating items to the self-modeling unit, which is used to establish a three-dimensional model of the 10kV switchgear and automatically import all operating items. A corresponding three-dimensional operation model is established for each operating item and marked as a teaching model. The teaching model is named after the operation name. At the same time, the self-modeling unit is also used to store the teaching model.

[0013] Furthermore, the index building unit is synchronized with the self-modeling unit, and will automatically obtain the jump address of the teaching model corresponding to different operation items and the operation name of the corresponding operation item, and automatically perform index building analysis. The specific method of index building analysis is as follows:

[0014] First, get all the operation names and their corresponding index addresses. The index address is the jump address mentioned above.

[0015] Select any operation name and index address, process the operation name, first perform word segmentation on the operation name to obtain several operation word segments, and sort the operation word segments in the order of the operation name;

[0016] Select the first operation participle in order, then obtain all synonyms for the operation participle, and mark the synonyms as related phrases;

[0017] Then, the associated phrases of all the remaining operation participles are obtained in sequence, so as to obtain all the operation participles and their corresponding associated phrases, and mark them as fuzzy search phrases corresponding to the operation names;

[0018] The operation name and its corresponding index address and fuzzy search phrase are integrated to form search information and saved.

[0019] Furthermore, the demand import unit is used for users to input teaching requirements, which are descriptive texts of related operations. The demand import unit automatically transmits the teaching requirements to the self-calling unit. The self-calling unit receives the teaching requirements transmitted by the demand import unit and automatically combines the index building unit and calls the model. The specific calling method is:

[0020] The teaching needs are obtained, and then when the teaching needs are similar to the fuzzy search phrases in the search information and the similarity exceeds X1, the index address and operation name corresponding to the fuzzy search phrases are automatically marked as potential selection information, and all potential selection information is obtained;

[0021] With the help of the operator, a potential selection information is designated as teaching information. At this time, the corresponding teaching model will be automatically called through the index address and displayed through the display unit; if the administrator does not make a selection, it means that the currently recommended potential selection information is wrong.

[0022] Furthermore, the collection of related phrases also includes the following steps:

[0023] After collecting the relevant words input by the user, no associated operation name is found. Then, within T1 time, where T1 is the preset time, the operation execution information corresponding to any operation name executed first will mark the relevant words entered by the user at this time as the associated phrase of the operation name corresponding to the operation execution information.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] The present application transmits the operation name including the name of the switch cabinet related operation and the operation item for reflecting the operation execution information fusion of the corresponding execution step to the self-modeling unit through the content importing unit, and the self-modeling unit is used to establish a corresponding three-dimensional teaching model according to each operation item to guide the user operation;

[0026] At the same time, a fuzzy associative keyword retrieval method constructed by the index construction unit can adapt to the situation where many people are not good at describing problems, which leads to the inability to accurately locate the problems, thereby making the operation of this application more convenient. This application is simple, effective, and easy to use. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0028] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] See also Figure 1 , the present application provides a three-dimensional visual intelligent auxiliary operating system for 10kV switchgear, including:

[0030] Content import unit, index building unit, self-modeling unit, self-calling unit, demand import unit and display unit;

[0031] The content import unit is used to import all operation items, which include operation names and operation execution information. The operation name refers to the name of the operation to be performed, or the description of the problem in the process of handling the problem. The operation execution information refers to the specific operation steps corresponding to the operation name.

[0032] The content import unit is used to transfer the operation items to the self-modeling unit. The self-modeling unit is used to build a 3D model of the 10kV switchgear and automatically import all the operation items. A corresponding 3D operation model is built for each operation item. The 3D operation model will automatically display what to operate and where to operate in sequence according to the steps of the operation execution information. There will be a detailed 3D display model and it will be marked as a teaching model. The teaching model is named after the operation name. At the same time, the self-modeling unit is also used to store the teaching model.

[0033] The index building unit is synchronized with the self-modeling unit, and will automatically obtain the jump address of the teaching model corresponding to different operation items and the operation name of the corresponding operation item, and automatically perform index building analysis. The specific method of index building analysis is as follows:

[0034] First, get all the operation names and their corresponding index addresses. The index address is the jump address mentioned above.

[0035] Select any operation name and index address, process the operation name, first perform word segmentation on the operation name to obtain several operation word segments, and sort the operation word segments in the order of the operation name;

[0036] Select the first operation participle in order, then obtain all synonyms for the operation participle, and mark the synonyms as related phrases;

[0037] Then, the associated phrases of all the remaining operation participles are obtained in sequence, so as to obtain all the operation participles and their corresponding associated phrases, and mark them as fuzzy search phrases corresponding to the operation names;

[0038] The operation name and its corresponding index address and fuzzy search phrase are integrated to form search information and saved;

[0039] Of course, the present application also includes a demand import unit, which is used for users to enter teaching requirements when they do not know how to operate the switch cabinet. The teaching requirements are descriptive texts of related operations. The demand import unit automatically transmits the teaching requirements to the self-calling unit. The self-calling unit receives the teaching requirements transmitted by the demand import unit and automatically combines the index building unit and calls the model. The specific calling method is:

[0040] The teaching needs are obtained, and then when there is similarity between the teaching needs and the fuzzy search phrases in the search information, and the similarity exceeds X1, the index address and operation name corresponding to the fuzzy search phrase are automatically marked as potential selection information, and all potential selection information is obtained; the similarity is obtained by obtaining the number of characters that are the same between the teaching needs and the fuzzy search phrases in any search information, and dividing it by the total number of characters corresponding to the teaching needs.

[0041] With the help of the operator, a potential selection information is designated as teaching information. At this time, the corresponding teaching model will be automatically called through the index address and displayed through the display unit; if the administrator does not make a selection, it means that the currently recommended potential selection information is wrong.

[0042] As the second embodiment of the present application, this embodiment is implemented on the basis of the first embodiment. The difference from the first embodiment is that in the process of index construction analysis, the following contents need to be supplemented for the collection of related phrases:

[0043] After collecting the relevant words input by the user, no associated operation name is found. Then, within T1 time, where T1 is the preset time, the operation execution information corresponding to any operation name executed first will mark the relevant words entered by the user at this time as the associated phrase of the operation name corresponding to the operation execution information.

[0044] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A three-dimensional visual intelligent auxiliary operating system for 10kV switchgear, characterized in that: include: The content import unit is used to transmit the operation name including the name of the switch cabinet related operation and the operation item for reflecting the fusion of the operation execution information of the corresponding execution step to the self-modeling unit, and the self-modeling unit is used to establish a corresponding three-dimensional teaching model according to each operation item to guide the user operation; The index construction unit is used to construct retrieval information according to the operation name and the corresponding index address that can jump to the teaching model, segment the operation name, obtain the associated phrases by obtaining synonyms for each segment, and all the operation segments and their corresponding associated phrases constitute fuzzy retrieval phrases; the operation name and its corresponding index address and the fuzzy retrieval phrase are merged to form retrieval information; the index construction unit is also used to save the retrieval information.

2. A three-dimensional visual intelligent auxiliary operating system for 10kV switch cabinet according to claim 1, characterized in that: Also includes The demand import unit is used for users to input teaching requirements. Teaching requirements are descriptive texts of related operations. The demand import unit automatically transmits the teaching requirements to the self-calling unit. The self-calling unit receives the teaching requirements transmitted by the demand import unit and automatically combines the index building unit and calls the model. The specific calling method is: The teaching needs are obtained, and then when the teaching needs are similar to the fuzzy search phrases in the search information and the similarity exceeds X1, the index address and operation name corresponding to the fuzzy search phrases are automatically marked as potential selection information, and all potential selection information is obtained; With the help of the operator, a potential selection information is designated as teaching information. At this time, the corresponding teaching model will be automatically called through the index address and displayed through the display unit; if the administrator does not make a selection, it means that the currently recommended potential selection information is wrong.

3. The three-dimensional visual intelligent auxiliary operating system for 10kV switch cabinet according to claim 1 is characterized in that: The content import unit is used to import all operation items. The operation items include operation name and operation execution information. The operation name refers to the name of the corresponding operation to be performed, or the description of the problem during the problem handling process. The operation execution information is the specific operation steps corresponding to the operation name.

4. The three-dimensional visual intelligent auxiliary operating system for 10kV switch cabinet according to claim 3 is characterized in that: The content import unit is used to transfer operation items to the self-modeling unit. The self-modeling unit is used to establish a three-dimensional model of the 10kV switchgear and automatically import all operation items. A corresponding three-dimensional operation model is established for each operation item and marked as a teaching model. The teaching model is named after the operation name. At the same time, the self-modeling unit is also used to store the teaching model.

5. A three-dimensional visual intelligent auxiliary operating system for 10kV switch cabinet according to claim 4, characterized in that: The index building unit is synchronized with the self-modeling unit, and will automatically obtain the jump address of the teaching model corresponding to different operation items and the operation name of the corresponding operation item, and automatically perform index building analysis. The specific method of index building analysis is as follows: First, get all the operation names and their corresponding index addresses. The index address is the jump address mentioned above. Select any operation name and index address, process the operation name, first perform word segmentation on the operation name to obtain several operation word segments, and sort the operation word segments in the order of the operation name; Select the first operation participle in order, then obtain all synonyms for the operation participle, and mark the synonyms as related phrases; Then, the associated phrases of all the remaining operation participles are obtained in sequence, so as to obtain all the operation participles and their corresponding associated phrases, and mark them as fuzzy search phrases corresponding to the operation names; The operation name and its corresponding index address and fuzzy search phrase are integrated to form search information and saved.

6. The three-dimensional visual intelligent auxiliary operating system for 10kV switch cabinet according to claim 5 is characterized in that: The demand import unit is used for users to input teaching requirements. Teaching requirements are descriptive texts of related operations. The demand import unit automatically transmits the teaching requirements to the self-calling unit. The self-calling unit receives the teaching requirements transmitted by the demand import unit and automatically combines the index building unit and calls the model. The specific calling method is: The teaching needs are obtained, and then when the teaching needs are similar to the fuzzy search phrases in the search information and the similarity exceeds X1, the index address and operation name corresponding to the fuzzy search phrases are automatically marked as potential selection information, and all potential selection information is obtained; With the help of the operator, a potential selection information is designated as teaching information. At this time, the corresponding teaching model will be automatically called through the index address and displayed through the display unit; if the administrator does not make a selection, it means that the currently recommended potential selection information is wrong.

7. The three-dimensional visual intelligent auxiliary operating system for 10kV switch cabinet according to claim 5 is characterized in that: The collection of related phrases also includes the following steps: After collecting the relevant words input by the user, no associated operation name is found. Then, within T1 time, where T1 is the preset time, the operation execution information corresponding to any operation name executed first will mark the relevant words entered by the user at this time as the associated phrase of the operation name corresponding to the operation execution information.

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