A method, device and electronic device for reviewing model data rules

Abstract

The present invention discloses a rule review method, device and electronic device for model data, the method comprising: receiving a review task for reviewing model data, splitting the review task into at least one review rule, and converting each review rule into a specific instruction in a specific language, each feature instruction corresponding to at least one keyword; converting at least one keyword corresponding to each specific instruction into an executable expression according to a logical framework, wherein a plurality of the specific instructions form an executable expression set after conversion; and using the executable expression set to review the model data to obtain a review result of the review task. This method converts each review rule into a specific instruction in a specific language, thereby enabling modification, editing and customization of specific review content without the need to redefine or edit review specifications, thus avoiding manual development of review specifications, saving costs and improving review efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of computer-aided design, and in particular to a method, device and electronic equipment for reviewing rules of model data. Background Art

[0002] During the review of construction drawings, whether it is reviewing two-dimensional construction drawings or three-dimensional Building Information Modeling (BIM) models, they need to be reviewed item by item in accordance with the requirements of the corresponding construction and design specifications, either manually or by writing a special review program. This results in the inability of two-dimensional construction drawings or three-dimensional BIM models to be quickly applied to the construction process, and also brings heavy clause review and development work to developers. For example, if an enterprise wants to customize the review logic of proprietary rules and clauses, one method that can be adopted is to contact professional reviewers to review the construction drawings to be reviewed one by one, or to review the BIM models one by one; another method is to invest a large number of developers to carry out customized development for custom clauses, which greatly affects the use of two-dimensional and three-dimensional models in the entire construction model.

[0003] Therefore, during the construction process, in order to avoid investing additional manpower and material resources, construction drawing review is no longer mandatory. However, this will bring great safety and quality risks to the subsequent construction process and project acceptance. Based on this, a fast and flexible model data review system is needed. Summary of the Invention

[0004] The embodiments of the present invention provide a method, device and electronic device for reviewing rules of model data, thereby providing a method, device and electronic device for video synthesis.

[0005] In a first aspect, an embodiment of the present invention discloses a rule review method for model data, the method comprising: receiving a review task for reviewing model data, the model data being data representing information of various components of a building derived from a two-dimensional drawing or a three-dimensional model; splitting the review task into at least one review rule, and converting each of the review rules into a specific instruction in a specific language, each of the feature instructions corresponding to at least one keyword; converting at least one keyword corresponding to each of the specific instructions into an executable expression according to a logical framework, wherein a plurality of the specific instructions form an executable expression set after conversion; and using the executable expression set to review the model data to obtain a review result of the review task.

[0006] Optionally, in a possible implementation of the first aspect, converting each of the review rules into a specific instruction in a specific language includes: converting each of the review rules into a specific instruction in the specific language based on a correspondence between the review rules and the specific language.

[0007] Optionally, in another possible implementation of the first aspect, at least one keyword corresponding to each of the specific instructions is converted into an executable expression according to a logical framework, including: performing word segmentation processing on each of the feature instructions to obtain at least one keyword corresponding to each feature instruction; filtering at least one keyword corresponding to each of the feature instructions according to the word segmentation logical framework structure to obtain a conditional statement set and a review statement set; and converting the conditional statement set and the review statement set into the executable expression.

[0008] Optionally, in another possible implementation of the first aspect, converting into the executable expression based on the conditional statement set and the review statement set includes: generating a set of expressions to be executed based on the conditional statement set and the review statement set; and performing structured processing on the set of expressions to be executed to generate the executable expression.

[0009] Optionally, in another possible implementation of the first aspect, the statement format of the set of expressions to be executed is:

[0010] If the preset conditions are met, the review statement is executed

[0011] The preset condition can be expressed by a conditional expression, and the execution statement can be expressed by a review logic statement.

[0012] Optionally, in another possible implementation of the first aspect, performing word segmentation processing on each of the feature instructions includes: performing word segmentation processing on each of the feature instructions using a word segmenter, wherein the word segmenter is a word segmenter developed based on the Antlr framework.

[0013] Optionally, the at least one keyword includes: component keyword, component attribute keyword, review function keyword, function parameter keyword and logical operation keyword.

[0014] In a second aspect, an embodiment of the present invention further discloses a rule review device for model data, the device comprising:

[0015] A receiving unit, configured to receive a review task for reviewing model data, wherein the model data is data representing information of various building components derived from a two-dimensional drawing or a three-dimensional model;

[0016] a processing unit, configured to split the review task into at least one review rule, and convert each review rule into a specific instruction in a specific language, wherein each feature instruction corresponds to at least one keyword;

[0017] a conversion unit, configured to convert at least one keyword corresponding to each of the specific instructions into an executable expression according to a logical framework, wherein a plurality of the specific instructions form an executable expression set after conversion;

[0018] The review unit is used to review the model data using the executable expression set to obtain a review result of the review task.

[0019] In addition, the rule review device provided in this aspect is also used to implement the method steps in various possible implementations of the first aspect mentioned above.

[0020] In a third aspect, an embodiment of the present invention further discloses an electronic device, comprising: at least one processor; and a memory connected to the at least one processor.

[0021] In which, the memory stores instructions that can be executed by the at least one processor. When the instructions in the memory are executed by the at least one processor, the at least one processor executes the rule review method for model data as described in the first aspect or any optional embodiment of the first aspect.

[0022] In addition, an embodiment of the present invention further discloses a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the rule review method for model data as described in the first aspect or any optional embodiment of the first aspect is implemented.

[0023] The rule review method, device and electronic device provided in this embodiment split the review task into at least one review rule, and then convert each review rule into a specific instruction in a specific language. The specific instruction can be modified, edited, and customized for specific review content without the need to redefine and edit the review specifications. The specification clauses of the specific instruction can be reused and edited, thereby avoiding manual development of review specifications, saving manual review costs and development costs, and improving the system's review efficiency for model data. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0025] Figure 1 A schematic structural diagram of a processing device provided in an embodiment of the present invention;

[0026] Figure 2A flowchart of a rule review method for model data provided by an embodiment of the present invention;

[0027] Figure 3 A signaling flow chart of a rule review method provided by an embodiment of the present invention;

[0028] Figure 4 An example diagram of a grammar configuration file in a partial review engine interpreter provided by an embodiment of the present invention;

[0029] Figure 5 A flowchart of an interpreter interpreting statements provided by an embodiment of the present invention;

[0030] Figure 6 An example diagram of an inspection result provided by an embodiment of the present invention;

[0031] Figure 7 A structural block diagram of a rule review device provided by an embodiment of the present invention;

[0032] Figure 8 A schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0034] The technical solution provided by the implementation of the present invention belongs to the application of three-dimensional information models in the entire process of engineering construction, especially in the compliance review of construction drawings and BIM models during the construction drawing review stage.

[0035] At present, the review tools or systems for rules and clauses on the market are basically customized and developed for specific clauses and are not reusable. As a result, companies are unable to quickly review various regulatory clauses, and are unable to flexibly customize their own rules and clauses. They are unable to increase the application scope of rule checking, and require a lot of manual review costs and development costs, making it impossible for the value of the model to be truly realized in the construction process.

[0036] In order to improve the review efficiency of building model data and save manual review costs, this embodiment provides a rule review method for model data, which can be applied to an electronic device or processing device, such as a processing chip or terminal device.

[0037] Among them, such as Figure 1As shown, the apparatus or device 100 includes a tasker 110, an audit engine 120, and a library 130. Furthermore, the tasker 110 can be a task worker or task module. The audit engine 120 includes an interpreter and an executor, which interpret and execute model data based on the model data and output the execution results. The library 130 includes a model library and a rule library, which stores various components, models, and other information used for rule auditing. The audit engine 120 then calls upon various audit components and information in the library 130 during auditing.

[0038] The model repository is a basic service for storing model data. This service standardizes various types of model data into a storage model that can be directly used by the review engine system and provides export functionality. Optionally, the model repository can be SQLite, a lightweight database.

[0039] Rule Base: A system where users maintain audit rules. This system allows the execution of rules to be entered into the rule base, making it easier for the audit engine to use.

[0040] The aforementioned device also includes a model space and memory space. The model space can be used to process model data developed in C++ / C#, while the memory space can be used to store component data in a data format, such as code logic modules stored in an octree structure. Furthermore, all underlying model data logic can execute rule review processes by calling the code logic modules in the memory control.

[0041] It should be understood that the above Figure 1 The device or apparatus shown may further include more or fewer other models or units, which is not limited in this embodiment.

[0042] The technical solution provided in this embodiment is described in detail below.

[0043] See also Figure 2 , is a flow chart of a method for reviewing model data rules provided by an embodiment of the present invention. The method can be executed by the above-mentioned apparatus or device, and specifically includes:

[0044] Step 101: Receive a review task for reviewing model data.

[0045] The model data is data representing information about building components derived from two-dimensional drawings or three-dimensional Building Information Modeling (BIM) models. The review task is to review whether the model data complies with industry and building regulations.

[0046] In a possible implementation, the task worker in the tasker 110 receives the review task issued by the user and starts a review process for the model data.

[0047] Step 102: split the review task into at least one review rule, and convert each review rule into a specific instruction in a specific language, where each feature instruction corresponds to at least one keyword.

[0048] Specifically, the process of splitting at least one review rule can be determined based on the rule information passed by the review task. For example, the review task can be split into an equal number of review rules based on the number of rule information passed. A review task includes at least one review rule to be processed.

[0049] Alternatively, the specific language may be a domain-specific language (DSL), which is a computer language focused on a specific application domain. In this embodiment, the split review rules are converted into a DSL, thereby enabling a standardized review of each model data item.

[0050] In step 102, converting each review rule into a specific instruction in a specific language includes converting each review rule into a specific instruction in the specific language based on a correspondence between the review rule and the specific language. In this embodiment, the correspondence is a correspondence between the review rule and the DSL language.

[0051] In addition, each characteristic instruction includes at least one keyword: component keyword, component attribute keyword, review function keyword, function parameter keyword and logical operation keyword. In addition, other keywords may also be included, which is not limited in this embodiment.

[0052] For example, the component keyword can be the name of any component, such as beam, house, column, etc.; the component attribute keyword can be a feature describing the component, such as "area", "volume", "size", etc.; the "function parameter keyword" can be a feature describing the specific size of the component, such as the function parameter keyword corresponding to area is 4.5 square meters (m 2 ), length size 10 centimeters (cm), etc.

[0053] After converting the review rules into specific instructions, users can modify and update specific keywords, such as "component attribute keywords" and "function parameter keywords" can be freely set and edited, thereby avoiding a lot of manpower to physically modify and edit the review specification clauses.

[0054] Step 103: Convert at least one keyword corresponding to each of the specific instructions into an executable expression according to a logical framework, wherein a plurality of the specific instructions form an executable expression set after conversion.

[0055] Specifically, the at least one keyword converted in step 102 is converted into a logical statement that is recognizable or executable by the executor according to the logical framework, thereby enabling review in the executor.

[0056] Among them, the logical framework can be an Antlr (Another Tool for Language Recognition) framework. The Antlr framework is an open source framework for analyzing grammar. In this embodiment, Antlr4 is used. Antlr4 is an open source grammar analyzer generation tool developed based on Java. It can generate corresponding grammar analyzers according to grammar rule files and is widely used in DSL construction, language lexical syntax analysis and other fields. Users can create grammar rule files by themselves, and then use Antlr4 to generate class files. These class files can realize the segmentation of sentences according to keywords, and then construct the segmentation into a tree structure, for example, constructing a grammar tree based on the segmentation form of the Antlr4 framework. After the grammar tree is generated, the Antlr4 technical framework can be used for grammar segmentation processing to obtain the corresponding keyword information, and finally generate an expression set executable by the executor based on the keyword information.

[0057] Step 104: review the model data using the executable expression set to obtain a review result of the review task.

[0058] Among them, each executable expression can be used to review whether a part of the model data complies with the building specifications or is compliant. Then, reviewing all the model data requires multiple different executable expressions (i.e., executable expression sets) to review. Each executable expression reviews a part of the model data and obtains a review result. After all the model data are reviewed by the executable expression set, multiple review results are obtained, i.e., the review result set. After summarizing, the final review result of the review task is obtained.

[0059] The method provided in this embodiment splits the review task into at least one review rule, and then converts each review rule into a specific instruction in a specific language. The specific instruction can be modified, edited, and customized for specific review content without the need to redefine and edit the review specifications. The specification clauses of the specific instruction can be reused and edited, thereby avoiding manual development of review specifications, saving manual review costs and development costs, and improving the system's review efficiency for model data.

[0060] In a specific embodiment, if Figure 3The figure shows a signaling flow chart of a rule review method provided in this embodiment. The method can be executed by a task worker, an interpreter, an executor, and a model library / rule library. Specifically, the method includes:

[0061] Step 201: The task worker obtains model data.

[0062] The model data is the model data in the aforementioned step 101. The model data can be obtained from the outside, or from a model library / rule library, which is not limited in this embodiment.

[0063] Specifically, the task worker can obtain an SQLite file package or data package from the model library, perform data localization processing based on the SQLite file package or data package, and obtain model data. This process is the data preparation stage. In this data preparation stage, the task worker also loads the original data into the system operation environment.

[0064] Step 202: The task worker obtains a review task, where the review task is used to review the standardization of the model data.

[0065] The review task includes information such as building specifications, industry specifications, etc. The review task can be determined based on the model data to be reviewed.

[0066] Step 203: The task worker splits the building specification for reviewing the model data into multiple rules according to the review task, and each rule corresponds to a rule ID.

[0067] Specifically, the splitting process can be referred to the description of step 102 of the above embodiment, which will not be described in detail here. The review task is split into multiple execution units, each of which is used to interpret the rule DI statement, adapt the algorithm, and prepare the review statement.

[0068] Step 204: The task worker converts the multiple rule IDs into multiple DSL instructions based on the correspondence between the rule IDs and the DSL, wherein each rule ID may correspond to one DSL instruction.

[0069] Optionally, the DSL instruction is a feature instruction in the aforementioned embodiment.

[0070] Step 205: The task worker sends multiple DSL instructions to the interpreter. Correspondingly, the interpreter receives the multiple DSL instructions sent by the task worker.

[0071] This embodiment is based on DSL theory. The audit rule statement format designed in this embodiment is:

[0072] If the preset conditions are met, the review statement is executed

[0073] It is expressed through program code as: If conditions, Then expresses;

[0074] The preset conditions can be expressed as conditional expressions, and the execution statements can be expressed as review logic statements. Furthermore, conditions represents conditional expressions that require filtering by the system executor. Based on these conditional expressions, the system (executor) filters out the original data to be reviewed from the review data. Expresses represents review logic statement expressions that require the system (executor) to execute based on the conditional original model data. Based on these expressions, the system filters out model data that does not meet the execution statement expression from the conditional original model data, thereby outputting abnormal model data.

[0075] Optionally, conditions can be composed of several sub-expressions connected by logical operation keywords, such as:

[0076] [Room].Name=Bedroom and [Room].Area=100

[0077] The "Room" in the "[]" brackets represents the main component keyword, and the English dot (".") is used to connect the component keyword and the attribute keyword; the "Name" position represents the component attribute keyword, and "Name" itself represents the component name attribute; the equal sign ("=") represents an equality function keyword, which is also called the review function keyword. In addition, the system also supports various other types of custom review function keywords, such as "+" and "-". "Bedroom" and "100" represent function parameter keywords; "and" represents a logical operation keyword.

[0078] The "conditions" conditional expression is located between the fixed keywords "if" and "then", indicating that it is expected to filter out component objects that meet the expression conditions.

[0079] Similarly, the expresses execution review statement can also be composed of several sub-expressions, connected and spliced ​​through logical operation keywords. It should be noted that expresses comes after the keyword "then" and represents a list of components filtered based on the conditional expression. The component objects that do not meet the expression conditions are expected to be reviewed, thereby obtaining the review results.

[0080] In a specific example, a DSL instruction, namely a review statement, is expressed as follows:

[0081] if[Room].Name≈front room then[Room].Area≥4.5;

[0082] The review semantics represented by this DSL instruction (review statement) is: the area of ​​all rooms in the model data whose names contain "front room" should be greater than or equal to 4.5 square meters.

[0083] Otherwise, the room is a room component that does not meet the rules, and the component information of the room (that does not meet the rules) needs to be output, that is, a review result is obtained.

[0084] Step 206: The interpreter performs word segmentation processing on each of the multiple DSL instructions to obtain multiple keyword information.

[0085] The word segmentation process can use a word segmenter developed based on the Antlr framework. The Antlr framework will be based on the grammar configuration file (such as Figure 4 As shown in the example above, an executable file class is generated and executed by the system to split the input text into a keyword list. Figure 4 This is a sample diagram of a grammar configuration file in the partial review engine interpreter.

[0086] Among them, the syntax configuration file specifically includes: defining the overall format of the statement, defining the terminator as a semicolon, the gif keyword, the gthen keyword, defining the conditional expression format, executing the expression set, and configuring the simple function expression set, basic simple function expression format, simple function keywords, attribute keywords, component keywords, operator keywords, logical operator keywords, keyword definitions, defining pure numeric constants, defining uppercase and lowercase character constants and Chinese character constants and other information.

[0087] By using a predefined keyword list, the word segmentation results can return information according to different dimensions. For example, by using the conditions keyword and iterative word segmentation, you can get a list of all condition clauses, that is, a set of conditional statement strings (referred to as the conditional statement set). Similarly, by using the expresses keyword, you can also get a set of all split review statement strings, that is, a review statement set. For example Figure 5 As shown, after the DSL instruction is word segmented, M keywords are obtained, where M ≥ 2 and is a positive integer.

[0088] Optionally, M=5, and the M keywords include: component keywords, component attribute keywords, review function keywords, function parameter keywords and logical operation keywords.

[0089] In this embodiment, the execution / review process of M keywords corresponding to a DSL instruction is described in detail.

[0090] according to Figure 3 As shown, the method of this embodiment also includes:

[0091] Step 207: The interpreter filters the M keywords corresponding to a DSL instruction according to the word segmentation logic framework structure to obtain a conditional statement set if and a review statement set then.

[0092] Step 208: The interpreter merges the conditional statement set and the review statement set and converts them into expressions executable by the executor.

[0093] Step 209: The interpreter performs structured processing on the executable expressions to obtain an executable expression set.

[0094] The structured processing shown here refers to converting the executable expression into a structured expression that can be executed by the executor.

[0095] Specifically, after the interpreter obtains the conditional statement set if and the review statement set then, it can obtain a string set specific to the component keyword, attribute keyword, function keyword, and other dimensions through cyclic word segmentation. Then, it can generate the corresponding language object, such as Java Object, to obtain a structured expression object set. For example, this example gives a Json representation Demo. For example, a structured conditional object expression set is:

[0096] {"dslAttributeExprList":[{"attributeList":["Name"],"object":"Room","operator":"≈","value":"front room"}],"operatorList":[]},

[0097] A structured set of execution object expressions:

[0098] {"dslAttributeExprList":[{"attributeList":["Area"],"object":"Room","operator":"≥","value":"4.5"}],"operatorList":[]}.

[0099] It should be understood that different interpreter syntax configuration files can be used to parse different conditional statements if and review statements then, thereby obtaining different structured conditional object expressions and structured execution object expressions. This embodiment does not limit the syntax configuration file in the interpreter.

[0100] Step 210: The interpreter sends the executable expression set to the executor. Correspondingly, the executor receives the executable expression set sent by the interpreter.

[0101] In addition, the method further includes: the executor obtains the model data, which can be obtained in the aforementioned step 201, such as obtaining the original model data from a model library.

[0102] Step 211: The executor uses the executable structured expression set to review the model data and obtain a review result.

[0103] Specifically, the executor generates a first set of executable structured expressions based on a DSL instruction, examines a portion of the model data, and obtains a first examination result. Similarly, the executor uses other DSL instructions to generate a second, third, ..., and Nth set of structured expressions, respectively, and filters / examines the model data to obtain N examination results.

[0104] Step 212: The executor sends all review results to the task worker, for example, N review results are sent to the task worker.

[0105] Step 213: The task worker receives all review results and summarizes all review results to obtain the review result of the review task.

[0106] In this embodiment, the executor uses a plurality of executable structured expression sets to filter, review and calculate the original model data, and finally outputs the component information that does not meet the rules and returns the task review result.

[0107] For example Figure 6 The following is an example of the review result, which is expressed in Json data format. The example found that the original data entry with ID number 2 and name "front room" does not comply with the rules / articles, and the visual Figure 4 (viewList4) is displayed.

[0108] The rule review method provided in this embodiment has the following beneficial effects:

[0109] 1. This method combines a self-developed model data conversion system to split the review task specifications into multiple specific languages, so that it can perform review tasks based on model data rules that meet the Industry Foundation Classes (IFC), the General Foundation Classes (GFC) and the Revit format.

[0110] 2. This rule review method supports customized review clauses for industries or enterprises. You only need to write corresponding review statements, such as conditions and / or expresses, to quickly review the rules. There is no need to repeatedly develop customized review logic. All review rules can be reviewed based on a unified underlying execution logic, which greatly reduces the human and material costs of the review.

[0111] 3. This method has the scalability of the review rule syntax, and the interpreter and executor can be continuously iterated and upgraded to improve the review efficiency and accuracy.

[0112] The embodiment of the present invention also discloses a rule review device for model data, which is used to implement the rule review method in the above embodiment, such as Figure 7 As shown, the rule review device includes: a receiving unit 701, a processing unit 702, a conversion unit 703 and a review unit 704, and may also include other more or fewer modules, such as a storage unit, a sending unit, etc.

[0113] The receiving unit 701 is used to receive a review task, where the review task is used to review model data, where the model data is data representing information of various building components derived from a two-dimensional drawing or a three-dimensional model.

[0114] The processing unit 702 is configured to split the review task into at least one review rule, and convert each review rule into a specific instruction in a specific language, where each feature instruction corresponds to at least one keyword.

[0115] The at least one keyword includes: component keyword, component attribute keyword, review function keyword, function parameter keyword and logical operation keyword, etc.

[0116] The conversion unit 703 is configured to convert at least one keyword corresponding to each of the specific instructions into an executable expression according to a logical framework, wherein a plurality of the specific instructions form an executable expression set after conversion.

[0117] The review unit 704 is configured to review the model data using the executable expression set to obtain a review result of the review task.

[0118] Optionally, the specific instruction is a DSL instruction.

[0119] Optionally, in a specific implementation of this embodiment, the conversion unit 703 is specifically used to convert each review rule into a specific instruction of the specific language according to the correspondence between the review rule and the specific language.

[0120] Optionally, in another specific implementation of this embodiment, the conversion unit 703 is further used to perform word segmentation processing on each of the feature instructions to obtain at least one keyword corresponding to each feature instruction; filter the at least one keyword corresponding to each of the feature instructions according to the word segmentation logic framework structure to obtain a conditional statement set and a review statement set; and convert the conditional statement set and the review statement set into the executable expression.

[0121] Furthermore, the conversion unit 703 is further configured to generate a set of expressions to be executed based on the set of conditional statements and the set of review statements; and perform structured processing on the set of expressions to be executed to generate the executable expressions.

[0122] The statement format of the expression set to be executed is:

[0123] If the preset conditions are met, the review statement is executed

[0124] It is expressed through program code as: If conditions, Then expresses;

[0125] The preset condition can be expressed by a conditional expression, and the execution statement can be expressed by a review logic statement.

[0126] Optionally, in another specific implementation of this embodiment, the conversion unit 703 is further configured to perform word segmentation processing on each of the feature instructions using a word segmenter, and the word segmenter is a word segmenter developed based on the Antlr framework.

[0127] It should be noted that, in combination with the above Figure 1 In the device shown in FIG. 1 , the function of the tasker 110 can be realized by the receiving unit 701 of this embodiment, the function of the review engine 120 can be realized by the processing unit 702, the conversion unit 703 and the review unit 704, and the functions of the model library and the rule library can be realized by the storage unit. Figure 7 Not shown in the figure.

[0128] The device provided in this embodiment splits the review task into at least one review rule, and then converts each review rule into a specific instruction in a specific language. The specific instruction can be modified, edited, and customized for specific review content without the need to redefine and edit the review specifications. The specification clauses of the specific instruction can be reused and edited, thereby avoiding manual development of review specifications, saving manual review costs and development costs, and improving the system's review efficiency for model data.

[0129] In addition, an embodiment of the present invention further provides an electronic device, such as Figure 8As shown, the electronic device may include a processor 801 and a memory 802, wherein the processor 801 and the memory 802 may be connected via a bus or other means. Figure 8 In addition, the electronic device further includes at least one interface 803, which may be a communication interface or other interface, and this embodiment does not limit this.

[0130] The processor 801 may be a central processing unit (CPU). Alternatively, the processor 801 may be another general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above chips.

[0131] Memory 802, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as the program instructions / modules corresponding to the rule review method in the embodiments of the present invention. Processor 801 executes the non-transitory software programs, instructions, and modules stored in memory 802 to perform various processor functions and data processing, thereby implementing the rule review method in the above method embodiments.

[0132] The memory 802 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created by the processor 801, etc. In addition, the memory 802 may include a high-speed random access memory, and may also include a non-volatile 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 memory 802 may optionally include a memory remotely located relative to the processor 801, and these remote memories may be connected to the processor 801 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.

[0133] In addition, at least one interface 803 is used for communication between the electronic device and external devices, such as communication with a server, etc. Optionally, at least one interface 803 can also be used to connect to external input and output devices, such as a keyboard, a display screen, etc.

[0134] The non-transitory computer-readable storage medium stores computer program instructions, and when the instructions are executed by the processor 801, the rule review method in the aforementioned embodiment can be implemented.

[0135] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD), or a solid-state drive (SSD). The storage medium can also include a combination of the above-mentioned types of memory.

[0136] Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention. Such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A rule review method for model data, characterized in that: The method comprises: receiving a review task for reviewing model data, wherein the model data is data representing information of various components of a building derived from a two-dimensional drawing or a three-dimensional model; Splitting the review task into at least one review rule, and converting each review rule into a specific instruction in a specific language, each specific instruction corresponding to at least one keyword; Converting at least one keyword corresponding to each of the specific instructions into an executable expression according to a logical framework, wherein a plurality of the specific instructions form an executable expression set after conversion; Reviewing the model data using the executable expression set to obtain a review result of the review task; Converting at least one keyword corresponding to each of the specific instructions into an executable expression according to a logical framework, including: Performing word segmentation processing on each of the specific instructions to obtain at least one keyword corresponding to each specific instruction; Filtering at least one keyword corresponding to each of the specific instructions according to the word segmentation logic framework structure to obtain a conditional statement set and a review statement set; According to the conditional statement set and the review statement set, it is converted into the executable expression.

2. The method according to claim 1, characterized in that Convert each of the review rules into specific instructions in a specific language, including: According to the correspondence between the examination rules and the specific language, each of the examination rules is converted into a specific instruction of the specific language.

3. The method according to claim 1, characterized in that Converting the conditional statement set and the review statement set into the executable expression includes: Generate a set of expressions to be executed according to the conditional statement set and the review statement set; The set of expressions to be executed is structured to generate the executable expressions.

4. The method according to claim 3, characterized in that The statement format of the expression set to be executed is: If the preset conditions are met, the review statement is executed Among them, the preset condition is expressed by a conditional expression, and the review statement is expressed by a review logic statement.

5. The method according to claim 1, wherein Perform word segmentation processing on each of the specific instructions, including: A word segmenter is used to perform word segmentation processing on each of the specific instructions, and the word segmenter is a word segmenter developed based on the Antlr framework.

6. The method according to any one of claims 1 to 3, characterized in that The at least one keyword includes: component keywords, component attribute keywords, review function keywords, function parameter keywords and logical operation keywords.

7. A rule review device for model data, characterized in that: The device comprises: A receiving unit, configured to receive a review task for reviewing model data, wherein the model data is data representing information of various building components derived from a two-dimensional drawing or a three-dimensional model; a processing unit, configured to split the review task into at least one review rule, and convert each review rule into a specific instruction in a specific language, each specific instruction corresponding to at least one keyword; a conversion unit, configured to convert at least one keyword corresponding to each of the specific instructions into an executable expression according to a logical framework, wherein a plurality of the specific instructions form an executable expression set after conversion; A review unit, configured to review the model data using the executable expression set to obtain a review result of the review task; The conversion unit is also used to perform word segmentation processing on each of the specific instructions to obtain at least one keyword corresponding to each specific instruction; filter the at least one keyword corresponding to each of the specific instructions according to the word segmentation logic framework structure to obtain a conditional statement set and a review statement set; and convert the conditional statement set and the review statement set into the executable expression.

8. An electronic device, characterized in that: comprising a processor and a memory, said memory being coupled to said processor; The memory stores computer-readable program instructions, and when the instructions are executed by the processor, the rule review method for model data according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the rule review method for model data according to any one of claims 1 to 6 is implemented.

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