Method and device for dividing mechanical module

Abstract

The invention discloses a mechanical module dividing method and device, and belongs to the technical field of pipeline installation. The method comprises the steps that in design model data to be divided, serial numbers and target parameters of equipment and connecting pieces and the mapping relation between the serial numbers and the target parameters are extracted, and the target parameters comprise feature point coordinates; performing clustering analysis on the target parameter to obtain a clustering analysis result; according to the clustering analysis result and the mapping relation, a mechanical module division result is obtained, and the mechanical module division result comprises the number of the mechanical modules and the serial numbers of the devices and the connecting pieces in all the mechanical modules. According to the method, the problems of low mechanical module division efficiency and inaccurate division result in the prior art can be solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of pipeline installation, and in particular relates to a method and device for dividing a mechanical module. Background Art

[0002] With the development of nuclear power technology, higher requirements are put forward for the economy of each stage of nuclear power, especially the resource input and construction cycle in the construction stage. At the same time, nuclear power construction is also faced with the difficulty of structural shortage of labor. In order to effectively cope with the economic and human resource challenges of nuclear power construction, the concept of modular construction is introduced to reduce the human resource input in the nuclear power construction stage and shorten the construction cycle. In particular, the modular concept is considered to be applied to the relatively centralized arrangement of process equipment and pipelines in nuclear power plants. Mechanical modules are formed by reasonably combining process equipment such as pumps and valves and pipelines. Such mechanical modules are prefabricated in the factory to reduce the manpower requirements for on-site construction, installation, welding, and testing, improve the working environment of personnel, and shorten the construction period of the nuclear island.

[0003] Engineering practice has proven the significance of mechanical modules in shortening construction period and improving the economic efficiency of nuclear power plant construction. However, the existing mechanical module division method requires designers to carry out mechanical module division based on the established division requirements and criteria, on the basis of the completed design plan, and taking into account the transportation and installation conditions on site. Due to the large number of process systems and complicated pipelines in nuclear power plants, and considering the possible iterative improvements of nuclear power plant plans, this division method has a long construction period and a large design workload, and the accuracy of the division results depends on the design experience of the designers, which restricts the large-scale application of mechanical modules in nuclear power plants. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a method and device for dividing a mechanical module in view of the above-mentioned deficiencies in the prior art, which can improve the efficiency of mechanical module division and the accuracy of the division results.

[0005] In a first aspect, the present invention provides a method for dividing a mechanical module, comprising: extracting the numbers, target parameters, and mapping relationships between the numbers and the target parameters of devices and connectors in design model data to be divided, wherein the target parameters include feature point coordinates; performing cluster analysis on the target parameters to obtain cluster analysis results; and obtaining mechanical module division results based on the cluster analysis results and the mapping relationship, wherein the mechanical module division results include the number of mechanical modules and the numbers of the devices and connectors in each mechanical module.

[0006] Preferably, before extracting the numbers, target parameters, and mapping relationship between numbers and target parameters of equipment and connectors, the mechanical module division method also includes: receiving design model data to be divided, wherein the design model data includes a civil structure design plan, and an equipment and connector layout design plan.

[0007] Preferably, cluster analysis is performed on the target parameters to obtain cluster analysis results, specifically including: according to preset parameters, a density clustering method is used to perform multiple cluster analyses on the target parameters to obtain at least one cluster analysis result, wherein the preset parameters include a limit range of a cluster neighborhood.

[0008] Preferably, after obtaining at least one cluster analysis result and before obtaining the mechanical module division result based on the cluster analysis result and the mapping relationship, the mechanical module division method also includes: calculating the weld reduction ratio based on the number of feature point coordinates and the number of clusters in the cluster analysis result; and screening out the best cluster analysis result from at least one cluster analysis result based on the weld reduction ratio.

[0009] Preferably, the calculating the weld reduction ratio according to the number of the feature point coordinates and the number of clusters in the cluster analysis result comprises: calculating the weld reduction ratio according to the following formula:

[0010]

[0011] Among them, N initial is the number of feature point coordinates, N m is the number of clusters in the cluster analysis results.

[0012] Preferably, the feature point coordinates include center point coordinates or endpoint coordinates, and the target parameters also include one or more combinations of the following: grade, diameter, and the system to which the connector belongs.

[0013] The target parameters are clustered multiple times using a density clustering method, specifically including: constructing a feature representation scheme for equipment and connectors based on the target parameters, wherein the feature representation scheme represents the target parameters of equipment and connectors based on a multidimensional array; and the feature representation scheme is clustered multiple times using a mean-shift clustering method.

[0014] Preferably, the mechanical module division result also includes the installation sequence between the mechanical modules.

[0015] The obtaining of mechanical module division results according to the cluster analysis results and the mapping relationship includes: generating virtual bodies corresponding to the mechanical modules according to the cluster analysis results; and generating installation sequences between the mechanical modules according to connection relationships and projection relationships between the virtual bodies.

[0016] Preferably, after obtaining the mechanical module division result, the mechanical module division method further comprises: displaying a three-dimensional visualization display result corresponding to the mechanical module division result.

[0017] In a second aspect, the present invention also provides a device for dividing a mechanical module, comprising: an extraction module for extracting the numbers, target parameters, and mapping relationships between the numbers and the target parameters of the equipment and connectors in the design model data to be divided, wherein the target parameters include feature point coordinates.

[0018] The analysis module is connected to the extraction module and is used to perform cluster analysis on the target parameters to obtain cluster analysis results.

[0019] The acquisition module is connected to the analysis module and is used to obtain the mechanical module division result according to the cluster analysis result and the mapping relationship, wherein the mechanical module division result includes the number of mechanical modules and the number of devices and connectors in each mechanical module.

[0020] In a third aspect, the present invention further provides a device for dividing a mechanical module, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, computer instructions are stored in the memory, and the processor executes the method for dividing the mechanical module described in the first aspect by executing the computer instructions.

[0021] The mechanical module division method and device provided by the present invention extracts the numbers and feature point coordinates of all devices and connectors in the design model data to be divided, performs cluster analysis on all feature point coordinates, maps the cluster analysis results with the numbers of the devices and connectors, and obtains the mechanical module division results, and the division results include the numbers of the devices and connectors in each mechanical module. Since the mechanical module division method of this embodiment can be automatically implemented, the workload of designers in carrying out mechanical module division can be reduced, thereby improving the efficiency of mechanical module division and the accuracy of the division results. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a schematic flow chart of a method for dividing a mechanical module according to Embodiment 1 of the present invention;

[0023] Figure 2 This is a schematic structural diagram of a mechanical module division device according to Embodiment 2 of the present invention;

[0024] Figure 3This is a schematic structural diagram of a mechanical module division device according to Embodiment 3 of the present invention;

[0025] Figure 4 Schematic diagram of a flow chart of a method for dividing a mechanical module according to Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the technical solution of the present invention, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0027] It should be understood that the specific embodiments and drawings described herein are only used to explain the present invention rather than to limit the present invention.

[0028] It can be understood that, in the absence of conflict, the various embodiments of the present invention and the various features in the embodiments can be combined with each other.

[0029] It can be understood that, for the convenience of description, the drawings of the present invention only show the parts related to the present invention, while the parts irrelevant to the present invention are not shown in the drawings.

[0030] It can be understood that each unit and module involved in the embodiments of the present invention may correspond to only one physical structure, or may be composed of multiple physical structures, or multiple units and modules may be integrated into one physical structure.

[0031] It can be understood that, without conflict, the functions and steps marked in the flowcharts and block diagrams of the present invention may occur in an order different from that marked in the drawings.

[0032] It is understood that the flowcharts and block diagrams of the present invention illustrate the possible architectures, functions, and operations of the systems, devices, equipment, and methods according to the various embodiments of the present invention. Each box in the flowchart or block diagram may represent a unit, module, program segment, or code, which contains executable instructions for implementing the specified functions. Moreover, each box or combination of boxes in the block diagram and flowchart may be implemented by a hardware-based system that implements the specified functions, or may be implemented by a combination of hardware and computer instructions.

[0033] It can be understood that the units and modules involved in the embodiments of the present invention can be implemented by software or hardware. For example, the units and modules can be located in a processor.

[0034] Embodiment 1:

[0035] like Figure 1As shown, this embodiment provides a method for dividing a mechanical module, which is applied to the design of various types of plants (such as chemical plants, food processing plants, power plants, and nuclear power plants) with a large number of equipment or connectors. Since there are many process systems in nuclear power plants and the pipelines are complicated, the division method of this embodiment is particularly suitable for the scenario of designing the process system of nuclear power plants. Taking the scenario of the process system of a nuclear power plant as an example, the method for dividing a mechanical module is described, and the method for dividing a mechanical module includes:

[0036] Step 101 , extracting the numbers, target parameters, and mapping relationship between the numbers and the target parameters of the devices and connectors from the design model data to be divided, wherein the target parameters include the coordinates of the feature points.

[0037] In this embodiment, the design model data to be divided refers to the design model data that needs to be processed by mechanical module division. For example, if the design model data in a process workshop in a factory needs to be divided into mechanical modules, the format of the design model data includes the FBX format and the format based on the output of PDMS (Plant Design Management System). Equipment includes process system equipment, such as pumps and valves. Connectors include pipes, elbows, tees, welding points, etc., and connectors are used to connect at least one device. The number refers to an identifier that uniquely identifies the equipment and connector. The feature point coordinates refer to the center point coordinates or endpoint coordinates of the equipment and connector. For example, the center point coordinates of the pump are selected as the feature point coordinates of the pump, and the coordinates of the two endpoints / three endpoints of the L-shaped pipe are selected as the feature point coordinates of the L-shaped pipe.

[0038] Optionally, before extracting the numbers, target parameters, and mapping relationship between the numbers and target parameters of the equipment and connectors, the mechanical module division method also includes: receiving design model data to be divided, wherein the design model data includes a civil structure design plan, and an equipment and connector layout design plan.

[0039] In this embodiment, if the equipment and connector layout design includes coordinates, volume, seismic category, quality assurance level, safety level, specification level, number, etc., the number, target parameters, and mapping relationship between the number and the target parameters of the equipment and connector are directly extracted from the data. If the equipment and connector layout design does not include coordinates, the same coordinate system is constructed for the design model, and the feature point coordinates of the equipment and connector are extracted in the same coordinate system. In one embodiment, if the design model data of the entire plant is received, and only the equipment and connectors of one of the process workshops (i.e., the divided area) need to be divided into mechanical modules, before extracting the number, target parameters, and mapping relationship between the number and the target parameters of the equipment and connector, the mechanical module division method also includes: receiving the design model data and the divided area of ​​the entire plant; determining the design model data to be divided according to the divided area. Specifically, receiving the divided area input in a box selection manner, such as receiving the user to box select some equipment and connectors in the three-dimensional design model to determine the design model to be divided.

[0040] Step 102: Perform cluster analysis on the target parameters to obtain cluster analysis results.

[0041] In this embodiment, there are a large number of devices and connectors, so the target parameter is a set of feature point coordinates. Cluster analysis methods include density clustering methods, K-means clustering methods, hierarchical clustering methods, etc. In this embodiment, the density clustering method is preferably used to perform cluster analysis on the target parameters. Examples of density clustering methods include Mean Shift and DBSCAN (Density-Based Spatial Clustering of Applications with Noise): by setting the minimum number of data points and radius in the neighborhood to find high-density areas and group them into a cluster, this method can find clusters of any shape and can handle noise points. AUTOCLUST: An adaptive density clustering algorithm that can automatically adjust parameters to adapt to the characteristics of the data set while maintaining the accuracy and interpretability of the clustering. Since the density clustering method shows good performance when processing data sets with complex shapes and irregular density distributions, this embodiment uses the density clustering method to perform cluster analysis on the feature point coordinate set of devices and connectors, which can improve the accuracy of the mechanical module division results. The cluster analysis results include the number of classes (i.e., the number of cluster centers, or the number of clusters), the location coordinates of the cluster centers, and the cluster boundaries. It should be noted that the feature point coordinates of the example equipment and connectors are three-dimensional data, and the cluster boundaries are also three-dimensional, and the dimension of the cluster boundaries is consistent with the dimension of the target parameters.

[0042] Specifically, cluster analysis is performed on the target parameters to obtain cluster analysis results, including: according to preset parameters, a density clustering method is used to perform multiple cluster analyses on the target parameters to obtain at least one cluster analysis result, wherein the preset parameters include a limit range of a cluster neighborhood.

[0043] In this embodiment, the number of cluster analysis results obtained in step 102 can be one or more. The preset parameters refer to pre-set parameters. The limit value of the cluster neighborhood affects the number of clusters obtained by the cluster analysis. The limit value range of the cluster neighborhood includes the limit values ​​of at least two cluster neighborhoods. A cluster analysis needs to be performed once for the limit value of a cluster neighborhood, so multiple cluster analysis results can be obtained according to the limit value range of the cluster neighborhood. Obtaining multiple cluster analysis results is conducive to screening out the optimal cluster analysis results from multiple cluster analysis results, thereby obtaining the optimal mechanical module division result. Preferably, the preset parameters also include the limit values ​​of the mechanical module size (such as length, width, and height). For example, cluster analysis is performed according to the limit value range of the cluster neighborhood to obtain multiple cluster analysis results, and the cluster analysis results that meet the mechanical module size limit value are screened out from the multiple cluster analysis results. Preferably, the preset parameters also include the mechanical module division form, which includes the division of small pipeline modules in the form of a single process system equipment and connectors, and the division of mechanical modules in the form of a combination of multiple process system equipment and connectors, so as to complete the mechanical module division of all process system equipment and connectors in a process workshop. The preset parameters can be determined according to the actual needs of the design model data to be divided.

[0044] Step 103, obtaining a mechanical module division result according to the cluster analysis result and the mapping relationship, wherein the mechanical module division result includes the number of mechanical modules and the numbers of the devices and connectors in each mechanical module.

[0045] In this embodiment, since cluster analysis is performed on the feature point coordinate set, the cluster analysis result includes the feature point coordinates, and then the mechanical module division result is obtained based on the mapping relationship between the feature point coordinates and the numbers, that is, the number of mechanical modules and the number list of equipment and connectors in each mechanical module are obtained. The mechanical module division result also includes the pipeline length, etc.

[0046] Optionally, after obtaining at least one cluster analysis result and before obtaining the mechanical module division result based on the cluster analysis result and the mapping relationship, the mechanical module division method also includes: calculating the weld reduction ratio based on the number of feature point coordinates and the number of clusters in the cluster analysis results; and screening out the optimal cluster analysis result from at least one cluster analysis result based on the weld reduction ratio.

[0047] In this embodiment, the larger the weld reduction ratio is, the less welding workload is in the on-site installation process corresponding to the division result. Therefore, the best cluster analysis result is selected from multiple cluster analysis results according to the weld reduction ratio, which is beneficial to reducing the labor cost of on-site construction, installation, and welding, and shortening the construction period. There are two methods for calculating the weld reduction ratio. One is the ratio of the number of feature point coordinates to the number of clusters, multiplied by a predetermined coefficient, such as the predetermined coefficient is 0.001.

[0048] The other is to calculate the weld reduction ratio according to the following formula:

[0049]

[0050] Among them, N initial is the number of feature point coordinates, N m is the number of clusters in the cluster analysis results.

[0051] Optionally, the target parameter further includes one or more combinations of the following: grade, diameter, and the system to which the connector belongs.

[0052] The density clustering method is used to perform multiple clustering analyses on the target parameters, specifically including: constructing a feature representation scheme for devices and connectors based on the target parameters, wherein the feature representation scheme is based on a multidimensional array to characterize the target parameters of the devices and connectors; and the mean-shift clustering method is used to perform multiple clustering analyses on the feature representation scheme.

[0053] In this embodiment, constructing a characteristic representation scheme of equipment and connectors according to target parameters specifically includes: constructing a characteristic representation scheme using a multidimensional array according to the target parameters. For example, the target parameters of the pump include characteristic point coordinates (three-dimensional), safety level (one-dimensional), diameter (one-dimensional), and the system to which it belongs (one-dimensional). The characteristic representation scheme of the constructed pump is a six-dimensional array, which represents a discrete data point in a six-dimensional space. Cluster analysis is performed on many discrete data points, and cluster analysis is performed from multiple dimensions such as the coordinates, level, and diameter of the equipment and connectors, thereby ensuring the accuracy of the subsequent mechanical module division results. For example, the preset parameters include the limit range of the cluster neighborhood and the limit of the mechanical module size (such as length, width, and height). The mechanical module size limit is determined according to the size of the transportation channel, and the mean-shift clustering method is used to perform multiple cluster analyses on the characteristic representation scheme. The cluster analysis results obtained can ensure that the mechanical module can enter the factory through the transportation channel for installation, avoiding the mechanical module size that cannot enter the factory through the transportation channel for installation due to human error. Therefore, the cluster analysis of the dimensions such as feature point coordinates, diameter, and size taken into consideration in this embodiment can avoid transportation difficulties, thereby improving the accuracy of the mechanical module division results.

[0054] Optionally, the mechanical module division result also includes the installation sequence between the mechanical modules.

[0055] Specifically, according to the cluster analysis results and the mapping relationship, obtaining the mechanical module division results includes: generating virtual bodies corresponding to each mechanical module according to the cluster analysis results; and generating the installation sequence between each mechanical module according to the connection relationship and projection relationship between the virtual bodies.

[0056] In this embodiment, the installation order between mechanical modules may affect each other, which will affect the accuracy of the mechanical module division results. Therefore, a virtual body corresponding to each mechanical module is generated based on the cluster analysis results (such as three-dimensional or multi-dimensional cluster boundaries). For example, the combination of objects (i.e., equipment, connectors) corresponding to the coordinates of the feature points within the cluster boundary is a virtual body. Based on the connection relationship and projection relationship between the virtual bodies, the installation order between the mechanical modules is generated. For example, if virtual body C blocks virtual body D in space, it is recommended to install virtual body D first, and then install virtual body C.

[0057] Optionally, after obtaining the mechanical module division result, the mechanical module division method further includes: displaying a three-dimensional visualization display result corresponding to the mechanical module division result.

[0058] In this embodiment, the three-dimensional visualization display result corresponding to the mechanical module division result is displayed, which is conducive to conveniently displaying the mechanical module division result to designers, making the result more intuitive and easy to understand. At the same time, the number of mechanical modules and the number list of equipment and connectors in each mechanical module are output.

[0059] The method for mechanical module division provided in this embodiment extracts the numbers and feature point coordinates of all devices and connectors in the design model data to be divided, and uses the density clustering method to perform cluster analysis on all feature point coordinates, maps the cluster analysis results with the numbers of devices and connectors, and obtains the mechanical module division results, and the division results include the numbers of devices and connectors in each mechanical module. Since the mechanical module division method of this embodiment can be automatically implemented, the workload of designers in carrying out mechanical module division can be reduced, thereby improving the efficiency of mechanical module division and the accuracy of division results. Specifically, since the density clustering method shows good performance when processing data sets with complex shapes and irregular density distributions, the density clustering method is used in this embodiment to perform cluster analysis on the feature point coordinate set of devices and connectors, which can improve the accuracy of mechanical module division results. By setting the limit range of the clustering neighborhood, multiple clustering analysis results are obtained, which is conducive to screening out the optimal clustering analysis result from multiple clustering analysis results, thereby obtaining the optimal mechanical module division result. The best cluster analysis result is selected from multiple cluster analysis results according to the weld reduction ratio, which is conducive to reducing the labor costs of on-site construction, installation, and welding, and shortening the construction period. Furthermore, cluster analysis is performed from multiple dimensions such as the coordinates, grade, and diameter of equipment and connectors to ensure the accuracy of the subsequent mechanical module division results. In addition, the three-dimensional visualization display results corresponding to the mechanical module division results are displayed to make the results more intuitive and easy to understand.

[0060] Embodiment 2:

[0061] like Figure 2 As shown, this embodiment provides a device for dividing a mechanical module, including:

[0062] The extraction module 21 is used to extract the numbers, target parameters, and mapping relationships between the numbers and the target parameters of the devices and connectors from the design model data to be divided, wherein the target parameters include the coordinates of the feature points.

[0063] The analysis module 22 is connected to the extraction module 21 and is used to perform cluster analysis on the target parameters to obtain cluster analysis results.

[0064] The acquisition module 23 is connected to the analysis module 22, and is used to obtain the mechanical module division result according to the cluster analysis result and the mapping relationship, wherein the mechanical module division result includes the number of mechanical modules and the number of devices and connectors in each mechanical module.

[0065] Optionally, the dividing device also includes a receiving module.

[0066] The receiving module is connected to the extracting module and is used to receive the design model data to be divided, wherein the design model data includes a civil structure design scheme, and an equipment and connector layout design scheme.

[0067] Optionally, the analysis module is used to perform multiple cluster analyses on the target parameters using a density clustering method according to preset parameters to obtain at least one cluster analysis result, wherein the preset parameters include a limit range of a cluster neighborhood.

[0068] Optionally, the analysis module is further used to calculate the weld reduction ratio according to the number of feature point coordinates and the number of clusters in the cluster analysis result, and to select the best cluster analysis result from at least one cluster analysis result according to the weld reduction ratio.

[0069] Optionally, the analysis module is used to calculate the weld reduction ratio according to the following formula:

[0070]

[0071] Among them, N initial is the number of feature point coordinates, N m is the number of clusters in the cluster analysis results.

[0072] Optionally, the feature point coordinates include center point coordinates or end point coordinates. The target parameters also include one or more of the following combinations: grade, diameter, and the system to which the connector belongs.

[0073] The analysis module is also used to construct a feature representation scheme for devices and connectors based on the target parameters, wherein the feature representation scheme is based on a multidimensional array to characterize the target parameters of the devices and connectors, and a mean-shift clustering method is used to perform multiple clustering analyses on the feature representation scheme.

[0074] Optionally, the mechanical module division result also includes the installation sequence between the mechanical modules.

[0075] The acquisition module is used to generate virtual bodies corresponding to various mechanical modules according to the cluster analysis results, and to generate the installation sequence between various mechanical modules according to the connection relationship and projection relationship between the virtual bodies.

[0076] Optionally, the dividing device also includes a graphics module.

[0077] The graphics module is used to display the three-dimensional visualization results corresponding to the mechanical module division results.

[0078] Embodiment 3:

[0079] like Figure 3 As shown, this embodiment provides a mechanical module division device, which is applied to the mechanical module division scenario of the nuclear power plant process system. The division device includes a data input module, a data processing module, a graphic interaction module, and a data export module.

[0080] The data input module is used to receive the nuclear power plant design model data, including the nuclear power plant civil structure design plan, process system equipment and pipeline layout design plan data, especially the process system equipment and pipeline connector data (including but not limited to: coordinates, volume, seismic category, quality assurance level, safety level, specification level, etc.). Pipeline connectors include but are not limited to pipes, elbows, tees, (virtual) welding points, etc.

[0081] The data input module is used to receive preset parameters input by the user, and the preset parameters include the limit values ​​of the mechanical module size (length, width, height) and the limit values ​​of the clustering neighborhood of the clustering algorithm.

[0082] The preset parameters also include the form and scope of mechanical module division, such as dividing the area according to a single process system pipeline and pipeline connectors, or a combination of several process system pipelines and pipeline connectors (design plans and models can also be input using a graphic interaction module).

[0083] The data input module is also used to receive output content set by the user, including but not limited to the pipeline number and length contained in each mechanical module, the number of pipeline connectors, etc., and the recommended installation order of the mechanical modules.

[0084] The graphic interaction module is used to receive the area selected by the user for mechanical module division by box selection.

[0085] The data processing module is used to construct a feature representation scheme for process system equipment and pipeline connectors based on the coordinates of feature points (center points or end points) of the process system equipment and pipeline connectors.

[0086] The data processing module is used to cluster the above feature representation schemes based on the mean-shift clustering method according to the parameters input by the user from the dimensions including various grades of pipelines, diameters, and the systems in which the pipelines are located.

[0087] The data processing module is also used to generate a mechanical module virtual body based on the clustering result parameters and the clustering boundary (three-dimensional), and to generate the installation logic relationship of the mechanical module division plan based on the mutual connection and projection relationship of the virtual bodies (for example, if virtual body A blocks virtual body B in space, it is recommended to install virtual body B first and then install virtual body A).

[0088] The data processing module is also used to calculate the reduction ratio of the number of pipeline welds according to the current division scheme. Where N initial is the number of initial feature points, N m is the number of clusters after clustering.

[0089] The graphic interaction module is used to accept the clustering scheme of the data processing module and perform three-dimensional visualization of the clustering scheme or virtual body.

[0090] The data export module is used to output the characteristics of the mechanical module division plan according to the user's formulated mechanical module division plan, and output the attributes and parameters of the mechanical module division plan, including but not limited to the number and length of the pipeline connections (parts) contained in the mechanical module, the installation order of the mechanical module, etc.

[0091] The mechanical module division device provided in this embodiment can reduce the workload of designers in mechanical module division, and can provide guidance on the installation sequence of mechanical modules and evaluate the preliminary performance of the scheme, which is of great significance to promoting the application of mechanical module and pipeline prefabrication technology.

[0092] Embodiment 4:

[0093] like Figure 4 As shown, this embodiment provides a method for dividing a mechanical module, which is applied to the mechanical module dividing device of embodiment 3, that is, the method for using the dividing device of embodiment 3. The method can pre-process the process system and pipeline data (three-dimensional model), mechanical module division requirements, and main module constraints involved in the mechanical module division, and recommend a mechanical module division scheme to the user according to the parameters specified by the user, thereby reducing the dependence of the mechanical module division on the design experience and reducing the workload of the designers, improving the efficiency of the mechanical module division (design), and promoting the large-scale application of mechanical modules.

[0094] Methods include:

[0095] S1, the user inputs the data of the nuclear power plant design model into the system in a specific format (fbx / based on PDMS), and then cooperates with the graphic interactive model to select the area to be modularized, the limit and form of the mechanical module division, etc.

[0096] S2, start the division calculation, the program data processing module establishes the model feature representation scheme according to the parameters input by the user, and then divides the input design model into module units according to the meanshift clustering method, and constructs the virtual body at the same time, and gives the order of virtual body placement (installation) according to the occlusion and collision relationship of the virtual body. And calculate the weld reduction ratio under this scheme.

[0097] S3, the user evaluates the partitioning scheme and adjusts the input parameters such as limit and form as needed, and obtains more alternatives.

[0098] S4. The user outputs the division results according to the requirements, including but not limited to the content and length of the pipelines included in the mechanical module.

[0099] Embodiment 5:

[0100] This embodiment provides a device for dividing a mechanical module, including: a memory and a processor, the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for dividing the mechanical module of Example 1 by executing the computer instructions.

[0101] It is to be understood that the above embodiments are merely exemplary embodiments used to illustrate the principles of the present invention, but the present invention is not limited thereto. For those of ordinary skill in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. A method for dividing a mechanical module, characterized in that: include: Extracting the numbers, target parameters, and mapping relationships between the numbers and the target parameters of the devices and connectors from the design model data to be divided, wherein the target parameters include the coordinates of the feature points; Performing cluster analysis on the target parameters to obtain cluster analysis results; According to the cluster analysis result and the mapping relationship, a mechanical module division result is obtained, wherein the mechanical module division result includes the number of mechanical modules and the numbers of devices and connectors in each mechanical module.

2. The method according to claim 1, characterized in that Before extracting the numbers, target parameters, and mapping relationship between the numbers and target parameters of the devices and connectors, the following is also included: The design model data to be divided is received, wherein the design model data includes a civil structure design scheme and an equipment and connector arrangement design scheme.

3. The method according to claim 1, characterized in that Performing cluster analysis on the target parameters to obtain cluster analysis results, specifically including: According to preset parameters, a density clustering method is used to perform multiple clustering analyses on the target parameters to obtain at least one clustering analysis result, wherein the preset parameters include a limit range of a cluster neighborhood.

4. The method according to claim 3, characterized in that After obtaining at least one cluster analysis result and before obtaining a mechanical module division result according to the cluster analysis result and the mapping relationship, the method further includes: Calculating the weld reduction ratio according to the number of the feature point coordinates and the number of clusters in the cluster analysis result; An optimal cluster analysis result is selected from at least one cluster analysis result according to the weld reduction ratio.

5. The method according to claim 4, characterized in that The calculating the weld reduction ratio according to the number of the feature point coordinates and the number of clusters in the cluster analysis result includes: The weld reduction ratio is calculated according to the following formula: Among them, N initial is the number of feature point coordinates, N m is the number of clusters in the cluster analysis results.

6. The method according to claim 3, characterized in that The feature point coordinates include center point coordinates or endpoint coordinates, and the target parameters also include one or more of the following combinations: grade, diameter, system to which the connector belongs, The density clustering method is used to perform multiple clustering analyses on the target parameters, specifically including: According to the target parameters, construct a characteristic representation scheme of the device and the connector, wherein the characteristic representation scheme represents the target parameters of the device and the connector based on a multi-dimensional array; The mean-shift clustering method is used to perform multiple clustering analyses on the feature representation scheme.

7. The method according to claim 1, characterized in that The mechanical module division result also includes the installation sequence between the mechanical modules. The obtaining of mechanical module division results according to the cluster analysis results and the mapping relationship includes: Generating a virtual body corresponding to each mechanical module according to the cluster analysis result; According to the connection relationship and projection relationship between virtual bodies, the installation sequence between various mechanical modules is generated.

8. The method according to claim 1, characterized in that After obtaining the mechanical module division result, the method further includes: Display the three-dimensional visualization results corresponding to the mechanical module division results.

9. A device for dividing a mechanical module, characterized in that: include: The extraction module is used to extract the numbers and target parameters of the equipment and connectors from the design model data to be divided, as well as the mapping relationship between the numbers and the target parameters, wherein the target parameters include the coordinates of the feature points. The analysis module is connected to the extraction module and is used to perform cluster analysis on the target parameters to obtain cluster analysis results. The acquisition module is connected to the analysis module and is used to obtain the mechanical module division result according to the cluster analysis result and the mapping relationship, wherein the mechanical module division result includes the number of mechanical modules and the number of devices and connectors in each mechanical module.

10. A device for dividing a mechanical module, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for dividing the mechanical modules according to any one of claims 1 to 8 by executing the computer instructions.

Images