Model construction method, device, computer equipment and medium for unit project

Abstract

The present invention relates to the technical field of water conservancy and hydropower engineering, and discloses a method, device, computer equipment and medium for constructing a model of a unit project. The method for constructing a model of a unit project includes: constructing an initial contour model of a target unit project according to the construction process information of a dam project; classifying the edges of the initial contour model to obtain multiple types of feature lines, and different groups of feature lines correspond to different line categories; based on the multiple types of feature lines, segmenting the initial contour model to obtain a segmentation result; and obtaining a target model of the target unit project according to the segmentation result and the attribute information of the target unit project. It can realize automatic modeling, and the target model of the unit project is constructed based on the construction process information of the dam project, so that the obtained target model is more general and more helpful for improving the efficiency of constructing the target model.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy and hydropower engineering, and particularly relates to a method, device, computer equipment and medium for constructing a model of a unit project. Background Art

[0002] In the related art, for the model construction of the unit project of a dam project, it is mainly obtained by an artificial construction method based on the modeling level and modeling experience of modelers.

[0003] However, when using this method for modeling, due to excessive dependence on the modeling experience of modelers, the obtained model is prone to have a large deviation from the actual engineering quantity. Moreover, the different modeling and quantity calculations of project stakeholders (such as owners, supervisors, and construction units, etc.) will also result in the need to repeatedly invest manpower and material resources to carry out quantity calculation work in the later stage, which is time-consuming and laborious.

[0004] In view of this, for the dam unit project, there is an urgent need for a model construction method that can improve the modeling efficiency. Summary of the Invention

[0005] In view of this, the present invention provides a method, device, computer equipment and medium for constructing a model of a unit project to solve the problem of low modeling efficiency.

[0006] In a first aspect, the present invention provides a method for constructing a model of a unit project, the method comprising:

[0007] Construct an initial contour model of a target unit project according to the construction process information of a dam project;

[0008] Classify the edges of the initial contour model by feature to obtain multiple types of feature lines, and different groups of feature lines correspond to different line categories;

[0009] Based on the multiple types of feature lines, segment the initial contour model to obtain a segmentation result;

[0010] Obtain a target model of the target unit project according to the segmentation result and the attribute information of the target unit project.

[0011] In this way, automated modeling can be realized, and the target model of the unit project is constructed based on the construction process information of the dam project, so that the obtained target model is more general and more helpful for improving the efficiency of constructing the target model.

[0012] In an optional implementation manner, classifying the edges of the initial contour model by feature to obtain multiple types of feature lines includes:

[0013] Identify the edges of the initial contour model to obtain multiple contour lines;

[0014] According to the z - coordinate of the mid - point of each contour line, multiple contour lines are divided in direction to obtain a horizontal direction line group and a vertical direction line group;

[0015] Perform a first classification process on the horizontal direction line group to obtain multiple groups of first feature lines;

[0016] Perform a second classification process on the vertical direction line group to obtain a second feature line group;

[0017] Take the multiple groups of first feature lines and the second feature line group as multiple types of feature lines.

[0018] In an alternative embodiment, performing a first classification process on the horizontal direction line group to obtain multiple groups of first feature lines includes:

[0019] According to the positions of each horizontal direction line in the initial contour model, the horizontal direction line group is divided to obtain an upper - surface horizontal line group and a lower - surface horizontal line group;

[0020] Based on the included - angle between every two upper - surface horizontal lines in the upper - surface horizontal line group, the upper - surface horizontal line group is divided to obtain a first transverse - stitch line group, a first upstream horizontal line group, and a first downstream horizontal line group;

[0021] Based on the included - angle between every two lower - surface horizontal lines in the lower - surface horizontal line group, the lower - surface horizontal line group is divided to obtain a second transverse - stitch line group, a second upstream horizontal line group, and a second downstream horizontal line group;

[0022] Take the first transverse - stitch line group, the first upstream horizontal line group, the first downstream horizontal line group, the second transverse - stitch line group, the second upstream horizontal line group, and the second downstream horizontal line group as multiple groups of first feature lines.

[0023] In an alternative embodiment, performing a second classification process on the vertical direction line group to obtain a second feature line group includes:

[0024] Compare the distance between each vertical direction line and the first upstream horizontal line group, the first downstream horizontal line group, the second upstream horizontal line group, and the second downstream horizontal line group respectively to obtain a comparison result;

[0025] According to the comparison result, obtain the second feature line group;

[0026] The second feature line is the vertical direction line in the vertical direction line group with the shortest distance compared to the target horizontal line group, and the target horizontal line group includes: the first upstream horizontal line group and the first downstream horizontal line group, or the second upstream horizontal line group and the second downstream horizontal line group.

[0027] In an alternative embodiment, based on multiple types of feature lines, the initial contour model is segmented to obtain a segmentation result, including:

[0028] Read the segmentation parameters corresponding to each type of feature line from the preset configuration file respectively;

[0029] Determine the position information of each type of feature line according to the attribute information;

[0030] Segment the initial contour model respectively according to the segmentation parameters and the corresponding position information of each type of feature line to obtain the segmentation result.

[0031] In an alternative implementation, segment the initial contour model respectively according to the segmentation parameters and the corresponding position information of each type of feature line to obtain the segmentation result, including:

[0032] Determine the offset distance of each type of feature line according to the segmentation parameters of each type of feature line;

[0033] Segment the initial contour model according to the position information of each type of feature line according to the corresponding offset distance, and generate a cutting surface by stretching to obtain the model bodies corresponding to each type of feature line;

[0034] Perform modeling based on each model body to obtain an intermediate model;

[0035] Take the intermediate model as the segmentation result.

[0036] In an alternative implementation, the segmentation result includes multiple target model bodies;

[0037] Obtain the target model of the target unit project according to the segmentation result and the attribute information of the target unit project, including:

[0038] Statistically identify the volume of each target model body according to the attribute information of the target unit project;

[0039] Determine the gradation type of each target model body respectively according to the attribute information;

[0040] According to the corresponding relationship between multiple preset gradation types and colors, and the gradation type of each target model body, configure the corresponding color for each target model body respectively;

[0041] Respond to the completion of the color configuration corresponding to each target model body to obtain the target model of the target unit project.

[0042] In a second aspect, the present invention provides a model construction device for a unit project, and the device includes:

[0043] An acquisition module, configured to construct an initial contour model of a target unit project according to the construction process information of a dam project;

[0044] A classification module, configured to classify the edges of the initial contour model to obtain multiple types of feature lines, where different groups of feature lines correspond to different line categories;

[0045] A splitting module, configured to split the initial contour model based on the multiple types of feature lines to obtain a splitting result;

[0046] A processing module, configured to obtain the target model of the target unit project according to the splitting result and the attribute information of the target unit project.

[0047] In a third aspect, the present invention provides a computer device, including: a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to execute the model construction method of the unit project in the first aspect or any corresponding embodiment thereof.

[0048] In a fourth aspect, the present invention provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to cause a computer to execute the model construction method of the unit project in the first aspect or any corresponding embodiment thereof. Description of the Drawings

[0049] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the description of the specific embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0050] Figure 1 is a flowchart of the model construction method of the unit project according to an embodiment of the present invention;

[0051] Figure 2 is a schematic diagram of the model of the initial contour model according to an embodiment of the present invention;

[0052] Figure 3 is a flowchart of another model construction method of the unit project according to an embodiment of the present invention;

[0053] Figure 4 is a schematic diagram of the feature line division result according to an embodiment of the present invention;

[0054] Figure 5 is a flowchart of yet another model construction method of the unit project according to an embodiment of the present invention;

[0055] Figure 6 is a schematic diagram of the splitting effect according to an embodiment of the present invention;

[0056] Figure 7 It is another schematic diagram of the segmentation effect according to an embodiment of the present invention;

[0057] Figure 8 It is another schematic diagram of the segmentation effect according to an embodiment of the present invention;

[0058] Figure 9 It is another schematic diagram of the segmentation effect according to an embodiment of the present invention;

[0059] Figure 10 It is another schematic diagram of the segmentation effect according to an embodiment of the present invention;

[0060] Figure 11 It is another schematic diagram of the segmentation effect according to an embodiment of the present invention;

[0061] Figure 12 It is another schematic diagram of the segmentation effect according to an embodiment of the present invention;

[0062] Figure 13 It is a schematic diagram of the target model according to an embodiment of the present invention;

[0063] Figure 14 It is a flowchart of the model construction method for another unit project according to an embodiment of the present invention;

[0064] Figure 15 It is a structural block diagram of the model construction device for the unit project according to an embodiment of the present invention;

[0065] Figure 16 It is a schematic diagram of the hardware structure of the computer device according to an embodiment of the present invention. Detailed implementation manners

[0066] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0067] For the dam project, for the convenience of measurement, it is necessary to model the unit project and conduct in-depth design. Among them, the unit project may include any one of the following projects: earth-rock excavation, concrete works, drilling and grouting, foundation and foundation treatment, etc.

[0068] However, in the prior art, the model of the unit project is constructed manually, resulting in low modeling efficiency. Moreover, due to the limited experience of the modeling personnel and the inconsistent quantity calculation of the model by the project stakeholders, the obtained model is not universal, affecting the accuracy of quantity calculation.

[0069] In view of this, the present invention provides a method for constructing a model of a unit project, including: constructing an initial contour model of a target unit project according to the construction process information of a dam project; classifying the edges of the initial contour model to obtain multiple types of feature lines, where different groups of feature lines correspond to different line categories; based on the multiple types of feature lines, dividing the initial contour model to obtain a division result; and obtaining a target model of the target unit project according to the division result and the attribute information of the target unit project. Through the method for constructing a model of a unit project provided by the present invention, automated modeling can be achieved, and the target model of the unit project is constructed based on the construction process information of the dam project, so that the obtained target model is more general and more conducive to improving the efficiency of constructing the target model.

[0070] According to an embodiment of the present invention, an embodiment of a method for constructing a model of a unit project is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0071] In this embodiment, a method for constructing a model of a unit project is provided, which can be used for the above-mentioned terminals, such as notebooks, desktop computers, etc. Figure 1 is a flowchart of a method for constructing a model of a unit project according to an embodiment of the present invention, as Figure 1 shown, and the process includes the following steps:

[0072] Step S101, construct an initial contour model of a target unit project according to the construction process information of a dam project.

[0073] In an embodiment of the present invention, to improve the effectiveness of modeling, an initial contour model of a target unit project is constructed according to the construction process information of a dam project, and the attribute information of the initial contour model is determined. Among them, the construction process information is information shared by all project stakeholders of the dam project. Through the construction process information, the quantity calculation standards of all project stakeholders can be clarified, which is helpful for ensuring the timeliness, authority, and accuracy of constructing the target model. For example: through the construction process information, data such as the elevation, specific dimensions, and measurement units of the actual building can be determined, and then the initial contour model of the target unit project can be constructed using a unified standard.

[0074] In an example, the constructed initial contour model can be as Figure 2 shown.

[0075] Step S102, classify the edges of the initial contour model to obtain multiple types of feature lines.

[0076] In the embodiments of the present invention, different sets of feature lines correspond to different line categories. By classifying the edges of the initial contour model, different cutting methods can be adopted for different feature lines in the subsequent process, thereby improving the cutting accuracy.

[0077] Step S103: Based on multiple types of feature lines, cut the initial contour model to obtain a cutting result.

[0078] In the embodiments of the present invention, based on multiple types of feature lines, the initial contour model is cut to clarify different partitions involved in the initial contour model, and then a cutting result is obtained.

[0079] Step S104: According to the cutting result and the attribute information of the target unit project, obtain the target model of the target unit project.

[0080] In the embodiments of the present invention, according to the cutting result and the attribute information of the target unit project, the attribute information corresponding to each region in the cutting result can be clarified, so as to obtain the target model of the target unit project. When the relevant parties of each subsequent project perform quantity calculation based on this target model, they can use the same standard for calculation.

[0081] The model construction method of the unit project provided in this embodiment can realize automatic modeling, and the target model of the unit project is constructed based on the construction process information of the dam project. Therefore, the obtained target model is more general and more helpful for improving the efficiency of target model construction.

[0082] In this embodiment, a model construction method of a unit project is provided, which can be used in terminals such as notebooks and desktop computers. Figure 3 It is a flowchart of the model construction method of the unit project according to the embodiments of the present invention. As Figure 3 shown, this process includes the following steps:

[0083] Step S301: According to the construction process information of the dam project, construct the initial contour model of the target unit project. For details, please refer to Figure 1 Step S101 of the shown embodiment, which will not be elaborated here.

[0084] Step S302: Classify the features of the edges of the initial contour model to obtain multiple types of feature lines.

[0085] Specifically, the above step S302 includes:

[0086] Step S3021: Identify the edges of the initial contour model to obtain multiple contour lines.

[0087] In the embodiment of the present invention, the initial contour model is placed horizontally to improve the segmentation efficiency. The edges of the initial contour model are recognized to obtain multiple contour lines, so that subsequent targeted segmentation can be performed based on the categories of each contour line.

[0088] Step S3022: According to the z-axis coordinates of the midpoints of each contour line, the multiple contour lines are divided in terms of direction to obtain a horizontal direction line group and a vertical direction line group.

[0089] In the embodiment of the present invention, to improve the division efficiency, the multiple contour lines are divided in terms of direction according to the z-axis coordinates of the midpoints of each contour line to obtain a horizontal direction line group and a vertical direction line group.

[0090] Step S3023: Perform a first classification process on the horizontal direction line group to obtain multiple groups of first feature lines.

[0091] In the embodiment of the present invention, to refine the classification, a first classification process is performed on the horizontal direction line group to obtain multiple groups of first feature lines.

[0092] In some alternative embodiments, the above step S3023 includes:

[0093] Step a1: According to the positions of the horizontal direction lines in the initial contour model, the horizontal direction line group is divided to obtain an upper surface horizontal line group and a lower surface horizontal line group.

[0094] Step a2: Based on the included angle between every two upper surface horizontal lines in the upper surface horizontal line group, the upper surface horizontal line group is divided to obtain a first transverse stitch line group, a first upstream horizontal line group, and a first downstream horizontal line group.

[0095] Step a3: Based on the included angle between every two lower surface horizontal lines in the lower surface horizontal line group, the lower surface horizontal line group is divided to obtain a second transverse stitch line group, a second upstream horizontal line group, and a second downstream horizontal line group.

[0096] Step a4: Based on the included angle between every two lower surface horizontal lines in the lower surface horizontal line group, the lower surface horizontal line group is divided to obtain a second transverse stitch line group, a second upstream horizontal line group, and a second downstream horizontal line group.

[0097] Step a5: Take the first transverse stitch line group, the first upstream horizontal line group, the first downstream horizontal line group, the second transverse stitch line group, the second upstream horizontal line group, and the second downstream horizontal line group as the multiple groups of first feature lines.

[0098] Specifically, since the number of the upstream horizontal line group and the downstream horizontal line group is large and they are approximately tangent, the upstream horizontal line group and the lower surface horizontal line group are divided in the same way respectively.

[0099] Taking the upstream horizontal line group as an example: for the convenience of distinction, it is judged based on the included angle between every two upper surface horizontal lines. If the included angle is less than the specified angle, the two are divided into the same group. The specified angle is the maximum critical value for determining the intersection of the upper surface horizontal lines. After traversing all the upper surface horizontal lines, multiple intermediate groups are obtained, and the upper surface horizontal lines in the intermediate group with the largest number are connected. Since there is only one left horizontal seam and one right horizontal seam. Therefore, based on the quantity, the intermediate groups are classified. If there is only one upper surface horizontal line in the intermediate group, it is determined that the intermediate group is the first horizontal seam group. If there are multiple upper surface horizontal lines in the intermediate group, according to the distribution of the upper surface horizontal lines in the intermediate group on the y-axis, each intermediate group is determined to be the first upstream horizontal line group or the first downstream horizontal line group.

[0100] Similarly, the downstream horizontal line group is divided in the same way to obtain the second horizontal seam group, the second upstream horizontal line group, and the second downstream horizontal line group.

[0101] Taking the first horizontal seam group, the first upstream horizontal line group, the first downstream horizontal line group, the second horizontal seam group, the second upstream horizontal line group, and the second downstream horizontal line group as the multiple groups of first feature lines.

[0102] Dividing the horizontal direction line group in the above way helps to improve the division efficiency and avoid misclassification.

[0103] Step S3024, perform a second classification process on the vertical direction line group to obtain a second feature line group.

[0104] In some alternative embodiments, the above step S3024 includes:

[0105] Step b1, respectively compare the distance between each vertical direction line and the first upstream horizontal line group, the first downstream horizontal line group, the second upstream horizontal line group, and the second downstream horizontal line group to obtain a comparison result.

[0106] Step b2, according to the comparison result, obtain a second feature line group, where the second feature line is the vertical direction line in the vertical direction line group with the shortest distance compared with the target horizontal line group. The target horizontal line group includes: the first upstream horizontal line group and the first downstream horizontal line group, or the second upstream horizontal line group and the second downstream horizontal line group.

[0107] Specifically, for the vertical line group, each vertical line is respectively compared with the first upstream horizontal line group, the first downstream horizontal line group, the second upstream horizontal line group, and the second downstream horizontal line group in terms of distance. The vertical lines with the shortest distances to the first upstream horizontal line group and the first downstream horizontal line group, as well as the vertical lines with the shortest distances to the second upstream horizontal line group and the second downstream horizontal line group, are respectively retained, thereby obtaining the second feature line group. Other vertical lines with non-shortest distances are deleted, which can easily avoid interfering with subsequent model segmentation.

[0108] Step S3025: Use multiple groups of first feature lines and the second feature line group as multiple types of feature lines.

[0109] In an implementation scenario, by classifying the edges of the initial contour model, obtaining multiple types of feature lines can include, for example Figure 4 the multiple feature line groups shown. Among them, the upstream horizontal line, the downstream horizontal line, the left horizontal seam, and the right horizontal seam are obtained by classifying the horizontal line group. The vertical line is obtained by classifying the vertical line group.

[0110] Step S303: Based on the multiple types of feature lines, segment the initial contour model to obtain a segmentation result. For details, please refer to Figure 1 Step S103 of the embodiment shown, which will not be elaborated here.

[0111] Step S304: According to the segmentation result and the attribute information of the target unit project, obtain the target model of the target unit project. For details, please refer to Figure 1 Step S104 of the embodiment shown, which will not be elaborated here.

[0112] The method for constructing a model of a unit project provided in this embodiment, by classifying the edges of the initial contour model and then segmenting and constructing the target model based on the classification result, helps to improve the model construction efficiency and thus reduce the time cost.

[0113] In this embodiment, a method for constructing a model of a unit project is provided, which can be used in terminals such as notebooks and desktop computers. Figure 5 is a flowchart of the method for constructing a model of a unit project according to an embodiment of the present invention. As Figure 5 shown, this process includes the following steps:

[0114] Step S501: According to the construction process information of the dam project, construct the initial contour model of the target unit project.

[0115] Step S502: Classify the edges of the initial contour model to obtain multiple types of feature lines. For details, please refer to Figure 2 Step S202 of the embodiment shown, which will not be elaborated here.

[0116] Step S503: Based on multiple types of feature lines, segment the initial contour model to obtain a segmentation result.

[0117] Specifically, the above step S503 includes:

[0118] Step S5031: Read the segmentation parameters corresponding to each type of feature line from a preset configuration file.

[0119] In the embodiment of the present invention, to facilitate clarifying the segmentation parameters corresponding to each type of feature line, they are obtained from a preset configuration file.

[0120] Step S5032: Determine the position information of each type of feature line according to the attribute information.

[0121] In the embodiment of the present invention, to facilitate accurate segmentation, the position information of each type of feature line is determined according to the attribute information of the target model.

[0122] Step S5033: Segment the initial contour model respectively according to the segmentation parameters and the corresponding position information of each type of feature line to obtain a segmentation result.

[0123] In some alternative embodiments, the above step S5033 includes:

[0124] Step c1: Determine the offset distance of each type of feature line according to the segmentation parameters of each type of feature line.

[0125] Step c2: Segment the initial contour model according to the position information of each type of feature line at the corresponding offset distance, and generate a cutting surface by stretching to obtain the model bodies corresponding to each type of feature line.

[0126] Step c3: Perform modeling based on each model body to obtain an intermediate model.

[0127] Step c4: Use the intermediate model as the segmentation result.

[0128] Specifically, when segmenting the initial contour model, it is segmented according to the position of each type of feature line and its corresponding offset distance, and then a cutting surface is generated by stretching to obtain the model bodies corresponding to each type of feature line. For example: Combining Figure 2 with the shown initial contour model, according to the position information and offset distance of the lower horizontal sewing line, the initial contour model is segmented, and the effect diagram after generating a cutting surface by stretching can be as Figure 6 shown, and the corresponding model body obtained is model body 1.

[0129] Then, perform modeling based on each model body to obtain an intermediate model for in-depth division of the initial contour model, and then use the intermediate model as the segmentation result.

[0130] In an implementation scenario, in combination with the partitioning result as shown in Figure 6 , by performing slicing on the downstream upper surface horizontal line and the downstream upper surface horizontal line, the model bodies 2 and 3 as shown in Figure 7 can be obtained.

[0131] By performing slicing on the upstream upper surface horizontal line and the upstream upper surface horizontal line, the model body 4 as shown in Figure 8 can be obtained.

[0132] By performing slicing on the right-side transverse seam line, the model body 5 as shown in Figure 9 can be obtained. In combination with the slicing of the upstream horizontal plane, the model body 6 as shown in Figure 9 can be obtained.

[0133] During the cutting process, the model body 5 is merged back into the model body 1, and the model body 6 is merged back into the model body 4, obtaining the slicing schematic diagram as shown in Figure 10 .

[0134] In combination with Figure 10 the initial intermediate model as shown in, by performing slicing on the upstream transverse seam line, the intermediate part as shown in Figure 11 is obtained. Modeling it, the models of each model body as shown in Figure 12 are obtained. The models of each model body are merged, obtaining the target model as shown in Figure 13 , and the target model is used as the slicing result.

[0135] Step S504: According to the slicing result and the attribute information of the target unit project, obtain the target model of the target unit project.

[0136] The method for constructing the model of the unit project provided in this embodiment can automatically complete the detailed design of the target unit project, so that the relevant parties of the project can clarify the structural details of the target unit project through the obtained target model.

[0137] In some optional implementation manners, to facilitate the relevant parties of the project to quickly clarify the structural details of the target unit project and the distribution of each gradation, obtaining the target model of the target unit project according to the slicing result and the attribute information of the target unit project includes: according to the attribute information of the target unit project, counting and identifying the volume of each target model body. Wherein, the slicing result includes multiple target model bodies. According to the attribute information, determine the gradation type of each target model body respectively. According to the corresponding relationship between the preset multiple gradation types and colors, and the gradation type of each target model body, configure the corresponding color for each target model body respectively. After the color configuration corresponding to each target model body is completed, the target model of the target unit project is obtained. For example: as shown in Figure 13As shown, the target model includes three target model bodies, corresponding to gradation a, gradation b, and gradation c respectively. Among them, gradation a, gradation b, and gradation c represent different gradation types, and different gradation types correspond to different colors.

[0138] In an implementation scenario, taking the division of the whiteboard bin as an example, the model construction method of the unit project provided by the present invention can be executed through a Building Information Modeling simulation tool, such as Figure 14 shown, including:

[0139] Division preparation stage: The modeler opens the cad template and calls the sat format file of the initial contour model of the target unit project. If it exists, the division initialization link is executed. If it does not exist, an error is prompted.

[0140] Initialization stage: Read the division parameter file from the preset configuration file and save it. Import the sat format file of the called initial contour model into the current template file to obtain the initial contour model. Determine the total volume of the initial contour model according to the attribute information of the target unit project. Classify the features of the edges of the initial contour model to obtain multiple types of feature lines.

[0141] Division stage: Based on the multiple types of feature lines, divide the initial contour model to obtain the division result.

[0142] Processing stage: Configure corresponding colors for different target model bodies, and according to the construction process information of the dam project, count and identify the volume of each target model body, and save it in text. Save each target model body in a separate txt format text, and identify the volume of each target model body and the corresponding gradation.

[0143] Through the model construction method of the unit project provided by the present invention, the automatic construction of the model can be realized, so that personnel with different modeling experiences can obtain the LOD400 model according to the set parameters, realizing automation and standardization. Furthermore, it overcomes the stubborn problems of traditional unit deepening design such as inaccurate engineering quantity calculation and repetitive verification of modeling caused by the dependence on the experience of modelers, making the design simple and not varying from person to person, with strong practical value and promotion value.

[0144] In this embodiment, a model construction device for a unit project is also provided. This device is used to implement the above embodiments and preferred implementation manners, and those that have been described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that realizes a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0145] This embodiment provides a model construction device for a unit project, as Figure 15 shown, including:

[0146] An acquisition module 1501, configured to construct an initial contour model of a target unit project according to the construction process information of a dam project;

[0147] A classification module 1502, configured to perform feature classification on the edges of the initial contour model to obtain multiple types of feature lines, and different groups of feature lines correspond to different line categories;

[0148] A segmentation module 1503, configured to segment the initial contour model based on multiple types of feature lines to obtain a segmentation result;

[0149] A processing module 1504, configured to obtain a target model of the target unit project according to the segmentation result and the attribute information of the target unit project.

[0150] In some alternative embodiments, the classification module 1502 includes:

[0151] An identification unit, configured to identify the edges of the initial contour model to obtain multiple contour lines;

[0152] A division unit, configured to perform direction division on the multiple contour lines according to the z-direction coordinates of the midpoints of each contour line to obtain a horizontal direction line group and a vertical direction line group;

[0153] A first classification unit, configured to perform a first classification process on the horizontal direction line group to obtain multiple groups of first feature lines;

[0154] A second classification unit, configured to perform a second classification process on the vertical direction line group to obtain a second feature line group;

[0155] A first execution unit, configured to use the multiple groups of first feature lines and the second feature line group as multiple types of feature lines.

[0156] In some alternative embodiments, the first classification unit includes:

[0157] A first processing unit, configured to divide the horizontal direction line group according to the positions of the horizontal direction lines in the initial contour model to obtain an upper surface horizontal line group and a lower surface horizontal line group;

[0158] A second processing unit, configured to divide the upper surface horizontal line group based on the included angle between every two upper surface horizontal lines in the upper surface horizontal line group to obtain a first transverse seam line group, a first upstream horizontal line group, and a first downstream horizontal line group;

[0159] A third processing unit, configured to divide the lower surface horizontal line group based on the included angle between every two lower surface horizontal lines in the lower surface horizontal line group, so as to obtain a second transverse seam line group, a second upstream horizontal line group, and a second downstream horizontal line group;

[0160] A second execution unit, configured to use the first transverse seam line group, the first upstream horizontal line group, the first downstream horizontal line group, the second transverse seam line group, the second upstream horizontal line group, and the second downstream horizontal line group as multiple groups of first feature lines.

[0161] In some optional embodiments, the second classification unit includes:

[0162] A fourth processing unit, configured to respectively compare the distance between each vertical direction line and the first upstream horizontal line group, the first downstream horizontal line group, the second upstream horizontal line group, and the second downstream horizontal line group to obtain a comparison result;

[0163] A fifth processing unit, configured to obtain a second feature line group according to the comparison result;

[0164] A third execution unit, where the second feature line is the vertical direction line in the vertical direction line group that has the shortest distance compared with the target horizontal line group, and the target horizontal line group includes: the first upstream horizontal line group and the first downstream horizontal line group, or the second upstream horizontal line group and the second downstream horizontal line group.

[0165] In some optional embodiments, the segmentation module includes:

[0166] A reading unit, configured to respectively read the segmentation parameters corresponding to each type of feature line from a preset configuration file;

[0167] A determination unit, configured to determine the position information of each type of feature line according to the attribute information;

[0168] A segmentation unit, configured to respectively segment the initial contour model according to the segmentation parameters of each type of feature line and the corresponding position information to obtain a segmentation result.

[0169] In some optional embodiments, the segmentation unit includes:

[0170] A distance determination unit, configured to determine the offset distance of each type of feature line according to the segmentation parameters of each type of feature line;

[0171] A first segmentation processing unit, configured to segment the initial contour model according to the position information of each type of feature line according to the corresponding offset distance, and generate a cutting surface by stretching to obtain a model body corresponding to each type of feature line;

[0172] A construction unit, configured to perform modeling based on each model body to obtain an intermediate model;

[0173] The second segmentation processing unit is used to take the intermediate model as the segmentation result.

[0174] In some alternative embodiments, the segmentation result includes multiple target model bodies;

[0175] The processing module includes:

[0176] The statistics unit is used to statistically calculate and identify the volume of each target model body according to the attribute information of the target unit project;

[0177] The type determination unit is used to respectively determine the gradation type of each target model body according to the attribute information;

[0178] The rendering unit is used to respectively configure a corresponding color for each target model body according to the corresponding relationship between multiple preset gradation types and colors, and the gradation type of each target model body;

[0179] The fourth execution unit is used to obtain the target model of the target unit project in response to the completion of the color configuration corresponding to each target model body.

[0180] The model construction device of the unit project in this embodiment is presented in the form of functional units. Here, the unit refers to an ASIC circuit, a processor and a memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0181] The further function descriptions of the above-mentioned various modules and units are the same as those in the corresponding embodiments above, and will not be repeated here.

[0182] The embodiment of the present invention further provides a computer device having the above Figure 15 shown model construction device of the unit project.

[0183] Please refer to Figure 16 , Figure 16 which is a schematic structural diagram of a computer device provided by an alternative embodiment of the present invention. As Figure 16As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting the components, including a high-speed interface and a low-speed interface. Each component communicates with each other using different buses and can be installed on a common motherboard or in other ways as needed. The processor can process instructions executed within the computer device, including instructions stored in the memory or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some alternative embodiments, if needed, multiple processors and / or multiple buses can be used with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a set of blade servers, or a multi-processor system). Figure 16 In the figure, a processor 10 is taken as an example.

[0184] The processor 10 can be a central processing unit, a network processor, or a combination thereof. Among them, the processor 10 can further include a hardware chip. The above hardware chip can be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The above programmable logic device can be a complex programmable logic device, a field programmable gate array, a generic array logic, or any combination thereof.

[0185] Among them, the memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiments.

[0186] The memory 20 can include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the computer device presented by a kind of mini-program landing page, etc. In addition, the memory 20 can include a high-speed random access memory and can also include a non-transitory memory, such as at least one disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some alternative embodiments, the memory 20 can optionally include a memory remotely set relative to the processor 10, and these remote memories can be connected to the computer device through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0187] The memory 20 can include a volatile memory, such as a random access memory; the memory can also include a non-volatile memory, such as a flash memory, a hard disk, or a solid-state drive; the memory 20 can also include a combination of the above types of memories.

[0188] The computer device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30, and the output device 40 may be connected through a bus or other means. Figure 14 Taking the connection through the bus as an example.

[0189] The input device 30 can receive input digital or character information, and generate key signal inputs related to the user settings and function controls of the computer device, such as a touch screen, a keypad, a mouse, a trackpad, a touchpad, a pointing stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 may include a display device, an auxiliary lighting device (e.g., an LED), and a haptic feedback device (e.g., a vibration motor), etc. The above display device includes but is not limited to a liquid crystal display, a light-emitting diode, a display, and a plasma display. In some alternative embodiments, the display device may be a touch screen.

[0190] The embodiments of the present invention also provide a computer-readable storage medium. The methods according to the embodiments of the present invention can be implemented in hardware, firmware, or be implemented as computer code that can be recorded on a storage medium, or be implemented by downloading through a network the original computer code stored in a remote storage medium or a non-transitory machine-readable storage medium and to be stored in a local storage medium, so that the methods described herein can be stored as such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium may be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid-state drive, etc.; further, the storage medium may further include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code, and when the software or computer code is accessed and executed by the computer, the processor, or the hardware, the methods shown in the above embodiments are implemented.

[0191] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for constructing a model of a unit project, characterized in that, the method includes: Construct an initial contour model of the target unit project according to the construction process information of the dam project; Classify the edges of the initial contour model to obtain multiple types of feature lines, and different groups of feature lines correspond to different line categories; Based on the multiple types of feature lines, divide the initial contour model to obtain a division result; According to the division result and the attribute information of the target unit project, obtain the target model of the target unit project; The classifying the edges of the initial contour model to obtain multiple types of feature lines includes: Identify the edges of the initial contour model to obtain multiple contour lines; According to the z-direction coordinates of the midpoints of each contour line, divide the multiple contour lines in terms of direction to obtain a horizontal direction line group and a vertical direction line group; Perform a first classification process on the horizontal direction line group to obtain multiple groups of first feature lines; Perform a second classification process on the vertical direction line group to obtain a second feature line group; Take the multiple groups of first feature lines and the second feature line group as the multiple types of feature lines; The dividing the initial contour model based on the multiple types of feature lines to obtain a division result includes: Read the division parameters corresponding to each type of feature line from a preset configuration file respectively; Determine the position information of each type of feature line according to the attribute information; Divide the initial contour model respectively according to the division parameters of each type of feature line and the corresponding position information to obtain a division result.

2. The method according to claim 1, characterized in that, the performing a first classification process on the horizontal direction line group to obtain multiple groups of first feature lines includes: Divide the horizontal direction line group according to the positions of the horizontal direction lines in the initial contour model to obtain an upper surface horizontal line group and a lower surface horizontal line group; Based on the included angle between every two upper surface horizontal lines in the upper surface horizontal line group, divide the upper surface horizontal line group to obtain a first transverse seam line group, a first upstream horizontal line group and a first downstream horizontal line group; Based on the included angle between every two lower surface horizontal lines in the lower surface horizontal line group, divide the lower surface horizontal line group to obtain a second transverse seam line group, a second upstream horizontal line group and a second downstream horizontal line group; Take the first transverse seam line group, the first upstream horizontal line group, the first downstream horizontal line group, the second transverse seam line group, the second upstream horizontal line group and the second downstream horizontal line group as the multiple groups of first feature lines.

3. The method according to claim 2, characterized in that, the performing a second classification process on the vertical direction line group to obtain a second feature line group includes: Compare the distance between each vertical direction line and the first upstream horizontal line group, the first downstream horizontal line group, the second upstream horizontal line group and the second downstream horizontal line group respectively to obtain a comparison result; Obtain a second feature line group according to the comparison result; The second characteristic line is the vertical direction line in the vertical direction line group that has the shortest distance compared to the target floating horizontal line group, where the target floating horizontal line group includes: the first upstream horizontal line group and the first downstream horizontal line group, or the second upstream horizontal line group and the second downstream horizontal line group.

4. The method according to claim 1, wherein, the step of respectively segmenting the initial contour model according to the segmentation parameters of each type of characteristic line and the corresponding position information to obtain a segmentation result includes: determining the offset distance of each characteristic line group according to the segmentation parameters of each characteristic line group; segmenting the initial contour model according to the position information of each characteristic line group at the corresponding offset distance, and generating a cutting surface by stretching to obtain the model body corresponding to each characteristic line group; performing modeling based on each model body to obtain an intermediate model; taking the intermediate model as the segmentation result.

5. The method according to claim 1, wherein, the segmentation result includes a plurality of target model bodies; the step of obtaining the target model of the target unit project according to the segmentation result and the attribute information of the target unit project includes: statistically identifying the volume of each target model body according to the attribute information of the target unit project; respectively determining the gradation type of each target model body according to the attribute information; configuring corresponding colors for each target model body respectively according to the corresponding relationship between a plurality of preset gradation types and colors and the gradation type of each target model body; responding to the completion of the color configuration corresponding to each target model body to obtain the target model of the target unit project.

6. A model construction device for a unit project, wherein, the device includes: an acquisition module, configured to construct an initial contour model of a target unit project according to the construction process information of a dam project; a classification module, configured to perform feature classification on the edges of the initial contour model to obtain multiple types of characteristic lines, where different characteristic line groups correspond to different line categories; a segmentation module, configured to segment the initial contour model based on the multiple types of characteristic lines to obtain a segmentation result; a processing module, configured to obtain the target model of the target unit project according to the segmentation result and the attribute information of the target unit project; the step of performing feature classification on the edges of the initial contour model to obtain multiple types of characteristic lines includes: identifying the edges of the initial contour model to obtain multiple contour lines; performing direction division on the multiple contour lines according to the z-direction coordinates of the midpoints of each contour line to obtain a horizontal direction line group and a vertical direction line group; performing a first classification process on the horizontal direction line group to obtain multiple groups of first characteristic lines; performing a second classification process on the vertical direction line group to obtain a second characteristic line group; taking the multiple groups of first characteristic lines and the second characteristic line group as the multiple types of characteristic lines; the step of segmenting the initial contour model based on the multiple types of characteristic lines to obtain a segmentation result includes: respectively reading the segmentation parameters corresponding to each type of characteristic line from a preset configuration file; determining the position information of each type of characteristic line according to the attribute information; The initial contour model is segmented according to the segmentation parameters of each type of feature line and the corresponding position information to obtain a segmentation result.

7. A computer device, characterized in that, it includes: 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 computer instructions to execute the model construction method of the unit project described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, the computer-readable storage medium stores computer instructions, and the computer instructions are used to cause a computer to execute the model construction method of the unit project described in any one of claims 1 to 5.

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