CN115718969A

CN115718969A - Electromechanical equipment aided design method, device and equipment based on artificial intelligence

Info

Publication number: CN115718969A
Application number: CN202110976107.XA
Authority: CN
Inventors: 华荣伟; 请求不公布姓名
Original assignee: Jiuling Jiangsu Digital Intelligent Technology Co Ltd
Current assignee: Jiuling Jiangsu Digital Intelligent Technology Co Ltd
Priority date: 2021-08-24
Filing date: 2021-08-24
Publication date: 2023-02-28

Abstract

The application relates to an electromechanical device aided design method, device and equipment based on artificial intelligence. The method comprises the steps of deriving an electromechanical layout for the building according to a three-dimensional building model, wherein the electromechanical layout is at least an electromechanical related design drawing of one floor; the electromechanical layout comprises one or more of electromechanical equipment, equipment wiring, fire fighting equipment and air conditioning equipment; inputting the electromechanical layout into a neural network model for recognition, forming a design strong rule of the equipment according to a recognition result, comparing the design strong rule with a preset design rule base, and giving a prompt according to a comparison result. Therefore, the electromechanical equipment model can be adjusted according to the identification and evaluation result without depending on manual experience, so that the adjustment efficiency is high and accurate.

Description

Electromechanical equipment aided design method, device and equipment based on artificial intelligence

Technical Field

The application relates to the technical field of building aided design, in particular to an electromechanical equipment aided design method, device and equipment based on artificial intelligence.

Background

Along with the development of the times, scientific technologies gradually tend to specialized and comprehensive quantitative development, the wrong design of a circuit in electromechanical design can bring great disadvantages and even potential safety hazards to our lives, the quality is not guaranteed, and electric shock and fire risks can be caused. In the traditional electromechanical device design process, a design result (namely an electromechanical device model) is obtained through manual design, and after the design is finished, the design result is optimized only by depending on the personal experience of an electromechanical engineer.

However, in the conventional design optimization process, the electromechanical device model is checked purely by means of manual experience, and the problems of low adjustment efficiency and incomplete optimization may exist, and the quality of the design result is not high.

Disclosure of Invention

In view of the above, it is necessary to provide an electromechanical device aided design method, apparatus, and device based on artificial intelligence.

In a first aspect, an embodiment of the present application provides an auxiliary design method for electromechanical devices based on artificial intelligence, where the method includes:

deriving an electromechanical layout for the building according to the three-dimensional building model, wherein the electromechanical layout is at least an electromechanical related design drawing of one floor; the electromechanical layout comprises one or more of electromechanical equipment, equipment wiring, fire fighting equipment and air conditioning equipment;

inputting the electromechanical layout into a neural network model for recognition, forming a design strong rule of the equipment according to a recognition result, comparing the design strong rule with a preset design rule base, and giving a prompt according to a comparison result.

In one embodiment, the deriving the electromechanical layout for the building from the three-dimensional building model includes:

screening out a three-dimensional model of equipment and wiring related to electromechanics in the three-dimensional building model by utilizing an electromechanical screening function in the three-dimensional building model;

deriving a house type structure diagram and a plane schematic diagram of equipment and wiring related to the electromechanics according to a preset rule based on the three-dimensional model;

and converting the plane schematic diagram of the equipment and the wiring related to the motor into a design symbol schematic diagram, combining the design symbol schematic diagram with the house type structure diagram to form an image file, and taking the image file as the electromechanical layout diagram.

In one embodiment, the inputting the electromechanical layout diagram into a neural network model for recognition and forming a design strong rule of the device according to a recognition result includes:

identifying the electromechanical layout by using the neural network model, and extracting scene environment characteristics of the electromechanical equipment, equipment wiring, fire fighting equipment and air conditioning equipment in the electromechanical layout;

and forming strong design rules for the electromechanical equipment, the equipment wiring, the fire fighting equipment, the air conditioning equipment and respective scene environment characteristics.

In one embodiment, the comparing the design strong rule with a preset design rule base and giving a prompt according to a comparison result includes:

constructing a design rule base according to national design specifications and building design experience knowledge, wherein the design rule base comprises electromechanical equipment placement rules, equipment wiring rules, fire-fighting equipment placement rules and air-conditioning equipment placement rules;

the design strong rule comprises a named entity, the preset design rule base comprises a named entity, and the named entity in the design strong rule is associated and compared with the named entity in the preset design rule base; and giving a prompt for the electromechanical equipment design or the electromechanical equipment wiring design which does not conform to the design rule.

In one embodiment, the method further comprises: the derived electromechanical layout for the building is used as geographical position marking information, and a corresponding neural network model is selected according to the geographical position marking information;

and the adaptive neural network model is selected according to the geographical position marking information, and is trained by the electromechanical layout drawing for the building in the south or is trained by the electromechanical layout drawing for the building in the north.

In a second aspect, an embodiment of the present application provides an artificial intelligence-based electromechanical device aided design apparatus, where the apparatus includes:

In one embodiment, the derivation module comprises:

the screening unit is used for screening out three-dimensional models of electromechanical related equipment and wiring in the three-dimensional building model by utilizing an electromechanical screening function in the three-dimensional building model;

the deriving unit is used for deriving the house type structure diagram, the plane schematic diagram of the electromechanical related equipment and the wiring according to a preset rule based on the three-dimensional model;

and the combination unit is used for converting the plane schematic diagram of the equipment and the wiring related to the motor into a design symbol schematic diagram, combining the design symbol schematic diagram with the house type structure diagram to form an image file, and taking the image file as the electromechanical layout diagram.

The auxiliary module includes:

the extraction unit is used for identifying the electromechanical layout by using the neural network model and extracting the scene environment characteristics of the electromechanical equipment, equipment wiring, fire fighting equipment and air conditioning equipment in the electromechanical layout;

and the acquisition unit is used for forming strong design rules of the electromechanical equipment, the equipment wiring, the fire fighting equipment, the air conditioning equipment and respective scene environment characteristics.

The auxiliary module further comprises:

In a third aspect, an embodiment of the present application provides a computer device, including a memory and a processor, where the memory stores a computer program, and the processor implements the following steps when executing the computer program:

In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the following steps:

deriving an electromechanical layout for a building according to the three-dimensional building model, wherein the electromechanical layout is at least an electromechanical related design drawing of one floor; the electromechanical layout comprises one or more of electromechanical equipment, equipment wiring, fire fighting equipment and air conditioning equipment;

According to the electromechanical equipment aided design method, device and equipment based on artificial intelligence, the electromechanical layout for the building is derived according to the electromechanical equipment system model, the electromechanical equipment design image layout is input into the preset neural network model for recognition, the design strong rule of the equipment is formed according to the recognition result, the design strong rule is compared with the preset design rule base, and the prompt is given according to the comparison result. The layout of the electromechanical equipment is identified by utilizing the neural network, the strong design rule of the electromechanical equipment is extracted, and the design rule is compared based on the strong rule, so that the electromechanical equipment model can be checked without depending on artificial experience, design adjustment reminding can be automatically given, and the adjustment efficiency is high and accurate.

Drawings

FIG. 1 is a diagram illustrating an internal structure of a computer device according to an embodiment;

FIG. 2 is a schematic flow chart illustrating a method for aided design of an electromechanical device based on artificial intelligence in one embodiment;

FIG. 3 is a schematic flow chart illustrating the step of refining step S210 in one embodiment;

FIG. 4 is a schematic flow chart illustrating the step of refining step S220 in one embodiment;

FIG. 5 is a schematic structural diagram of an apparatus for aided design of electromechanical devices based on artificial intelligence in one embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

The electromechanical device intelligent design evaluation method provided by the embodiment of the application can be applied to the computer device shown in FIG. 1. The computer device comprises a processor, a memory, a network interface, a database, a display screen and an input device which are connected through a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operating system and the computer program to run on the non-volatile storage medium. The database of the computer device is used to store the neural network in the following embodiments, and the specific description of the neural network refers to the specific description in the following embodiments. The network interface of the computer device may be used to communicate with other external devices via a network connection. Optionally, the computer device may be a server, a desktop, a personal digital assistant, other terminal devices such as a tablet computer, a mobile phone, and the like, or a cloud or a remote server, and the specific form of the computer device is not limited in the embodiment of the present application. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on a shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like. Of course, the input device and the display screen may not belong to a part of the computer device, and may be external devices of the computer device.

It will be appreciated by those skilled in the art that the configuration shown in fig. 1 is a block diagram of only a portion of the configuration associated with the present application, and is not intended to limit the computing device to which the present application may be applied, and that a particular computing device may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

The following describes the technical solutions of the present application and how to solve the above technical problems with specific examples. These several specific embodiments may be combined with each other below, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.

It should be noted that the execution subject of the method embodiments described below may be an intelligent design evaluation apparatus for electromechanical devices, and the apparatus may be implemented as part of or all of the computer device described above by software, hardware, or a combination of software and hardware. The following method embodiments are described by taking the execution subject as the computer device as an example.

FIG. 2 is a flowchart illustrating an example of a method for evaluating an aided design of an electromechanical device based on artificial intelligence. The embodiment relates to a process for aided design of a system model of electromechanical equipment by adopting a neural network by computer equipment. As shown in fig. 2, includes:

step S210, deriving an electromechanical layout for the building according to the three-dimensional building model, wherein the electromechanical layout is at least an electromechanical related design drawing of one floor.

Building Information Modeling (Building Information Modeling), referred to as BIM for short, can construct a three-dimensional model of a Building. The three-dimensional building model can contain three-dimensional models of various electromechanical devices in the building, and a two-dimensional electromechanical layout of the electromechanical devices can be derived from the three-dimensional models; the electromechanical layout comprises one or more of electromechanical equipment, equipment wiring, fire fighting equipment and air conditioning equipment.

It will be appreciated that a building is a multi-storey structure with multiple floors, and that the electromechanical layout of each floor may be different or partially different, and therefore the electromechanical layout derived based on the three-dimensional building model should be an electromechanically relevant design with respect to the floor.

The electromechanical layout includes one or more of a building structure, such as a wall, and an electromechanical device. Such as motors and wiring, fire hydrants, air conditioners, etc.

Specifically, the electromechanical device objects may include motors of the power supply system, motor cabling, air conditioners, air conditioner cabling, fire hydrants, fire fighting cabling, optical cable joints, optical cable cabling, and so forth.

Step S220, inputting the electromechanical layout into a neural network model for recognition, forming a design strong rule of the equipment according to a recognition result, comparing the design strong rule with a preset design rule base, and giving a prompt according to a comparison result.

In the embodiment of the invention, the neural network model is trained by using an electromechanical layout for building, has the functions of extracting and identifying the electromechanical layout information, and forms the design strong rule of electromechanical equipment according to the extracted electromechanical layout information. The design strong rules can be understood as characteristic information, position information, association information and the like about the position placement of the electromechanical device in the building design.

In other embodiments of the present invention, the extensible technique is: the design rule may further include a routing relationship between the motor and the motor, a relationship between attributes (for example, a circuit selected by the motor) or assignments (voltage, current, power, redundancy, inner diameter of the wire) of different electromechanical devices, and other design reference information related to the electromechanical device, which is not limited in this embodiment.

The preset design rule base is a knowledge base constructed according to national building design standards, such as building electromechanical engineering seismic design specifications GB 50981-2014 (2014 edition), building electrical construction quality acceptance specifications GB 50303-2002, civil building electrical design specifications JGJ T16-2008, and design experience of electromechanical design layout engineers.

Comparing the design strong rule extracted by the neural network model with a preset design rule base can obtain which electromechanical layout designs in the electromechanical layout drawings do not meet the requirements or have hidden dangers, so that a prompt can be given according to the comparison result. For example, a reminder not conforming to a design habit, a reminder of easily causing a fire, a reminder of a layout position to be modified, and the like; the reminding mode can be changed according to design requirements.

In the embodiment of the invention, the layout of the electromechanical equipment is identified by utilizing the neural network to obtain the layout relation of the electromechanical equipment, and whether the layout relation meets the design requirement is evaluated, so that the system model of the electromechanical equipment can be adjusted.

According to the electromechanical equipment intelligent design evaluation method, the electromechanical equipment intelligent design evaluation device, the computer equipment and the storage medium, the electromechanical layout for the building is derived according to the electromechanical equipment system model, the electromechanical design image layout is input into the preset neural network model for recognition, the design strong rule of the equipment is formed according to the recognition result, the design strong rule is compared with the preset design rule base, and the prompt is given according to the comparison result. The layout of the electromechanical equipment is identified by utilizing the neural network, the strong design rule of the electromechanical equipment is extracted, and the design rule is compared based on the strong rule, so that the electromechanical equipment model can be checked without relying on manual experience, a design adjustment prompt can be automatically given, and the adjustment efficiency is high and accurate.

In one embodiment, as shown in fig. 3, a flowchart of the refining step of step S210 includes:

step S211, utilizing the electromechanical screening function in the three-dimensional building model, screening out the three-dimensional model of the electromechanical related equipment and wiring in the three-dimensional building model.

The traditional BIM model has no some automatic functions, so that electromechanical equipment can be selected from the three-dimensional building model based on self-developed three-dimensional design software, and the method can be understood as displaying only the electromechanical equipment and hiding other unnecessary building related models. In the embodiment of the invention, model information of electromechanical first-closing equipment and wiring in the three-dimensional building model is screened, and the wiring can be understood as rules and connection relations among all electromechanics, such as position relations among fire hydrants, pipeline communication relations and the like.

Therefore, a corresponding three-dimensional model needs to be screened out from the three-dimensional building models.

And step S212, deriving a house type structure diagram and a plane schematic diagram of equipment and wiring related to the electromechanics according to a preset rule based on the three-dimensional model.

It will be appreciated that the electromechanical related devices, wiring, etc. are building structure dependent, with the building structure being the reference target as the basis for the evaluation. Therefore, when deriving a two-dimensional layout from a three-dimensional building model, it is necessary to construct derivation rules in the three-dimensional building model and derive floor plan views of the building, the electromechanical devices, and the wiring.

The plan is similar to the design drawing of the architecture design institute when designing buildings.

Step S213, converting the plan schematic diagram of the device and the wiring related to the motor into a design symbol schematic diagram, combining the design symbol schematic diagram with the house type structure diagram to form an image file, and using the image file as the electromechanical layout diagram.

In the embodiment of the invention, since the two-dimensional graph derived from the three-dimensional building model is mostly a projection graph, namely a projection of a perspective graph of the electromechanical device, and the symbolic language of the electromechanical device is adopted in the general design process, the electromechanical related graph in the two-dimensional graph is different from the actual design language. To make the use of design language symbols more convenient, it is necessary to convert the associated drawings in the plan view into design symbols.

In one embodiment, the derived two-dimensional map is provided with labeled information, for example, if the lead of a fire hydrant is labeled "hydrant", the labeled wire frame may be replaced with a representative symbol of an air conditioner. It can be understood that the schematic design symbols are replaced, the schematic design symbols are formed and combined with the house type structure diagram to form an image file, the image file is exported to form the electromechanical layout diagram, and the electromechanical and wiring forms in the electromechanical layout diagram meet the requirements of the design drawing.

In the embodiment of the invention, the electromechanical device model is converted from three dimensions to two dimensions to obtain the electromechanical device and wiring design images. The computer equipment can traverse in the three-dimensional building model, and the electromechanical correlation model is converted from three dimensions to two dimensions according to the electromechanical correlation system model obtained by traversing. Therefore, the electromechanical device design image can be automatically acquired from the complete design model, the requirements of a design drawing are met, the neural network model can conveniently identify and extract information, the automation degree is higher, and the identification efficiency and the accuracy are further improved.

In an embodiment, as shown in fig. 4, the flowchart of the step of refining in step S220 is shown, and step S220 specifically includes:

step S221, a design rule base is constructed according to national design specifications and building design experience knowledge, and the design rule base comprises electromechanical equipment placement rules, equipment wiring rules, fire fighting equipment placement rules and air conditioning equipment placement rules.

For example, "building electromechanical engineering seismic design specification GB 50981-2014 (2014 edition)," building electrical construction quality acceptance specification GB 50303-2002 ", civil building electrical design specification JGJ T16-2008", etc. are all experience of national building design rules related to electromechanics; on the basis of meeting the basic design rule, a better design rule is constructed by combining years of work experience of a senior designer.

Relevant rules of the electromechanical equipment and the routing included in the construction design rule base include but are not limited to rules of placement positions of the equipment and rules of routing design; the collocation of the mechatronic devices may also be selected based on this extension. Such as the model of the mechatronic device, the degree of power matching, etc.

The method comprises at least one of the rules of constructing and designing rule base equipment and circuits, the rules of circuits and materials, the rules of equipment and load capacity, the rules of equipment and electric energy quality, the rules of electromechanical and air-conditioning wind systems, the control modes of electromechanical equipment and control modes, the rules of strong and weak electricity rooms and public pipe wells, and the rules of strong and weak electricity buses and facilities.

In the above embodiment, the inputting the electromechanical layout diagram into the neural network model for recognition, and forming a design strong rule of the device according to the recognition result specifically includes:

identifying the electromechanical layout by using the neural network model, and extracting scene environment characteristics of the electromechanical equipment, equipment wiring, fire fighting equipment and air conditioning equipment in the electromechanical layout; and forming strong design rules for the electromechanical equipment, the equipment wiring, the fire fighting equipment, the air conditioning equipment and respective scene environment characteristics.

In the embodiment of the invention, the characteristics of the electromechanical environment and the environment between the wiring and the wall body can be simply understood; further, scene environment characteristics between electromechanics and building characteristics can be understood; such as an open air environment, a semi-open air environment, an enclosed environment, and the like. Strong rules in the electromechanical layout can be better obtained according to the extraction rules.

Furthermore, different devices use different circuits, and design errors or improper selection of the circuits can bring disadvantages and even potential safety hazards to life; the rules of the circuit and the material (seeking economic and poor quality electric wires or other equipment are selected, even if no problem exists in the selection of the circuit, a great potential safety hazard exists, according to different provided circuits, corresponding voltage, current, power and redundancy are identified, the rules of the equipment and the load capacity (meeting the requirement of electric equipment on the load capacity), the rules of the equipment and the electric energy quality, the insulation distance of an electromechanical circuit and the insulation strength (prompting to design a lightning protection device, such as important electromechanics and important machines also need to prompt static electricity prevention and surge prevention), the rules of an electromechanical and air conditioning system (an air conditioning system in a building electromechanical system adopts a full-air conditioning system and does not adopt a fan coil system), the control modes of the electromechanical equipment and the control modes (frequency conversion regulation control mode which is adaptive to the control equipment is adopted to control the frequency of a chilled water pump and set the lowest frequency of the chilled water pump, the non-uniformity of the electric load is adopted, when the utilization rate of the air conditioner is low, the power consumption is reduced by the frequency conversion mode, the rules of a strong electricity load and a public conduit well (rules of strong electricity and weak electricity and a conduit without water accumulation in a wet public conduit or a wet heat dissipation pipeline, and other facilities nearby a strong and weak conduit of a public conduit in a bathroom, and a hot water bus in other places are not adopted to prompt.

Step S222, the strong design rule comprises a named entity, the preset design rule base comprises a named entity, and the named entity in the strong design rule is associated and compared with the named entity in the preset design rule base; and giving a prompt for the electromechanical equipment design or the electromechanical equipment wiring design which does not conform to the design rule.

In the embodiment of the invention, the design rule extracted by the neural network model contains the named entity of the electromechanical device, and can be understood as the name of the electromechanical device. In the process, simple name association can be carried out, and association identification and processing can also be carried out by utilizing a natural language processing technology; specific natural language processing techniques are not described in detail herein. And further realizing giving prompt for electromechanical equipment design or electromechanical equipment wiring design which does not accord with design rules.

Furthermore, in order to better distinguish the design difference between the south and the north, the neural network model can be trained respectively according to the design difference between the south and the north so as to improve the recognition accuracy.

The vast width of our country is influenced by factors such as geographical natural conditions, political economic culture and the like, different south and north building differences and building style laws are bred through thousands of years of accumulation and evolution, and the north building atmosphere is stable and slightly has concave-convex transformation. In the south, due to hot climate, the whole style belongs to fresh, transparent and flexible layout. The lighting design in the south and the north is different, the atmosphere in the north, the top grade, the south more pay attention to environmental protection, which waste energy, the unreasonable electromechanical design scheme of overall arrangement need abandon in the data mining, give the most environmental protection, the design scheme of energy can be saved.

The method of the invention also comprises the following steps:

and (4) taking the derived electromechanical layout drawing for the building as geographical position marking information, and selecting a corresponding neural network model according to the geographical position marking information.

Specifically, a neural network model for north is trained by utilizing a north electromechanical layout; the electromechanical layout map for the south is used to train the neural network model for the south.

And when the auxiliary design is carried out, the adaptive neural network model is selected and trained by the electromechanical layout drawing for the building in the south or the electromechanical layout drawing for the building in the north according to the geographical position marking information.

The intelligent design evaluation method of the electromechanical equipment derives the electromechanical layout for the building according to the electromechanical equipment system model, inputs the electromechanical design image layout into a preset neural network model for recognition, forms a design strong rule of the equipment according to a recognition result, compares the design strong rule with a preset design rule base, and gives a prompt according to a comparison result. The layout of the electromechanical equipment is identified by utilizing the neural network, the strong design rule of the electromechanical equipment is extracted, and the design rule is compared based on the strong rule, so that the electromechanical equipment model can be checked without relying on manual experience, a design adjustment prompt can be automatically given, and the adjustment efficiency is high and accurate. In addition, electromechanical projection is converted into a design symbol according to the conversion from the three-dimensional graph to the two-dimensional graph, so that the recognition accuracy is improved; different neural network models are constructed according to the difference between the south and the north, so that electromechanical design can be better guided, and the layout of the flat air conditioner routing, the cable routing and the like can be intelligently recommended.

It should be understood that although the various steps in the flow charts of fig. 2-4 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-4 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternating with other steps or at least some of the sub-steps or stages of other steps.

In one embodiment, as shown in fig. 5, there is provided an electromechanical device intelligent design evaluation apparatus, including:

electromechanical device aided design device based on artificial intelligence, characterized in that the device comprises:

a deriving module 510, configured to derive an electromechanical layout for a building according to a three-dimensional building model, where the electromechanical layout is an electromechanical related design drawing of at least one floor; the electromechanical layout comprises one or more of electromechanical equipment, equipment wiring, fire fighting equipment and air conditioning equipment;

and the auxiliary module 520 is used for inputting the electromechanical layout into the neural network model for identification, forming a design strong rule of the equipment according to an identification result, comparing the design strong rule with a preset design rule base, and giving a prompt according to a comparison result.

Further, the derivation module 510 includes:

Further, the auxiliary module 520 includes:

The auxiliary module 520 further comprises:

the design strong rule contains a named entity, the preset design rule base contains a named entity, and the named entity in the design strong rule and the named entity in the preset design rule base are subjected to correlation comparison; and giving a prompt for the electromechanical equipment design or the electromechanical equipment wiring design which does not accord with the design rule.

In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:

It should be clear that the process of executing the computer program by the processor in the above embodiments is consistent with the process of executing the steps in the above method, and specific reference may be made to the description above.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by hardware instructions of a computer program, which may be stored in a non-volatile computer-readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, and these are all within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims

1. An electromechanical device aided design method based on artificial intelligence is characterized by comprising the following steps:

2. The method of claim 1, wherein deriving the electromechanical layout for the building from the three-dimensional model of the building comprises:

screening out a three-dimensional model of electromechanical related equipment and wiring in the three-dimensional building model by utilizing an electromechanical screening function in the three-dimensional building model;

and converting the plan schematic diagram of the equipment and the wiring related to the motor into a design symbol schematic diagram, combining the design symbol schematic diagram with the house type structure diagram to form an image file, and taking the image file as the electromechanical layout diagram.

3. The method of claim 1, wherein inputting the electromechanical layout into a neural network model for recognition and forming a design strong rule of the device according to the recognition result comprises:

4. The method according to claim 1, wherein the comparing the design strong rule with a preset design rule base and giving a prompt according to a comparison result comprises:

the design strong rule comprises a named entity, the preset design rule base comprises a named entity, and the named entity in the design strong rule is associated and compared with the named entity in the preset design rule base; and giving a prompt for the electromechanical equipment design or the electromechanical equipment wiring design which does not accord with the design rule.

5. The method as recited in claim 1, further comprising: the derived electromechanical layout for the building is used as geographical position marking information, and a corresponding neural network model is selected according to the geographical position marking information;

6. An electromechanical device aided design apparatus based on artificial intelligence, the apparatus comprising:

the system comprises a deriving module, a calculating module and a calculating module, wherein the deriving module is used for deriving an electromechanical layout chart for the building according to a three-dimensional building model, and the electromechanical layout chart is at least an electromechanical related design chart of one floor; the electromechanical layout comprises one or more of electromechanical equipment, equipment wiring, fire fighting equipment and air conditioning equipment;

and the auxiliary module is used for inputting the electromechanical layout into the neural network model for recognition, forming a design strong rule of the equipment according to a recognition result, comparing the design strong rule with a preset design rule base, and giving a prompt according to a comparison result.

7. The apparatus of claim 6, wherein the derivation module comprises:

8. The apparatus of claim 6, wherein the assistance module comprises:

9. The apparatus of claim 6, wherein the assistance module further comprises:

10. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor when executing the computer program performs the steps of the method according to any of claims 1 to 5.

11. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 5.