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CN118195425A - Teaching task scoring method and system based on three-dimensional modeling - Google Patents

Teaching task scoring method and system based on three-dimensional modeling Download PDF

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CN118195425A
CN118195425A CN202410594473.2A CN202410594473A CN118195425A CN 118195425 A CN118195425 A CN 118195425A CN 202410594473 A CN202410594473 A CN 202410594473A CN 118195425 A CN118195425 A CN 118195425A
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CN118195425B (en
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吴瑜
张绍军
胡盛
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Chengdu Vocational and Technical College of Industry
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Abstract

The invention belongs to the field of data processing, and provides a teaching task scoring method and system based on three-dimensional modeling, wherein the main scheme is as follows: acquiring first operation flow information for three-dimensional modeling in an operation terminal and constructed three-dimensional model information, transmitting the first operation flow information and first operation time to a cloud platform, and simultaneously transmitting the three-dimensional model information to a 3D printing terminal; yun Pingtai calculating a first score according to the first workflow information, the first working time and the first weight; acquiring second operation flow information and assembly result information of assembling all the entity parts, and sending the second operation flow information and second operation time to the cloud platform; yun Pingtai calculates a second score according to the second workflow information, the second working time and the second weight, calculates a third score according to the assembly result information and the third weight, and takes the sum of the three scores as a final score. The method and the device can accurately evaluate the learning condition of the user in the whole three-dimensional modeling process.

Description

Teaching task scoring method and system based on three-dimensional modeling
Technical Field
The invention relates to the technical field of data processing, in particular to a teaching task scoring method and system based on three-dimensional modeling.
Background
Because of the teaching requirements of BIM and three-dimensional modeling, the BIM and three-dimensional modeling courses are required to be operated and tested at ordinary times by Revit software, works which are completed by students according to the operation requirements or the test requirements of teachers are required to be checked one by teachers, the workload is huge, and corresponding data statistics and analysis are difficult to be achieved rapidly. According to a grade, 150 people calculate, each person provides 5 models, the workload is 750 models, and each model needs to compare the overall effect graph with three views. Corresponding teaching and operation modification are needed to be provided for two grades, the normal teaching time is 12 weeks, the examination is 2 times, a teacher is needed to compare 750 x2 = 1500 images and give scores, the workload is huge, and the problem distribution cannot be automatically counted, and a score list and teaching difficulty statistics cannot be formed. Moreover, for the homework provided by the students, the teacher needs to check whether the problems of plagiarism, copying and the like exist by manually comparing the file sizes, generating time or checking specific parameters.
BIM model course achievements can be used for three-dimensional model design; the part module designed by the three-dimensional model can be used for soft-packaged courses, but at present, the means for unified management of the BIM model and the part module is lacking, the number of parts to be processed, the inventory condition, the use condition and the soft-packaged entity model management are lacking in tools and means, effective closed-loop management cannot be formed, and effective trend analysis cannot be completed. The design of students cannot be linked with actual demands, so that on one hand, resource waste is caused, on the other hand, market needs to be truly fed back to a teaching stage, and the teaching is disjointed from actual application, so that the students cannot master the real technology.
Thus, the following teaching difficulties may be encountered when performing BIM, soft-pack and model design related courses in schools:
1. Separation between theory and practice: these courses often require students to understand complex architectural and design concepts, as well as requiring them to master the relevant software skills. However, neither theory nor practice alone can fully meet the needs of students. Therefore, in course design, a scheme needs to be found to ensure that students can grasp basic principles, proficiency apply related software, grasp various business processes in actual work, improve employment practice of students through interaction of the students and end users, and provide guidance for optimization of important directions of teaching.
2. Quality of data and information: in the process of designing BIM or physical three-dimensional models, the accuracy of data and information is important. If the data or information used by students is inaccurate, their design may also be problematic. Therefore, in the teaching process, the quality of data and information needs to be emphasized, the method for processing and verifying the data by students is strictly checked, and the examination and analysis of the homework and examination results are important constituent links in the work of teachers. Due to the fact that the number of students is large, the workload of the teacher in reviewing homework is large due to the staged homework and examination; part of students copy or directly copy homework, and teachers need abundant experience to distinguish; student homework problem statistics lacks a quick and effective means.
3. Time and resource constraints: BIM, soft-pack, and model design related courses require significant time and resources to complete. However, in a school environment, both time and resources tend to be limited. Thus, in educational design, it is desirable to find a solution to maximize the available time and resources to ensure that the student is able to obtain sufficient knowledge and skill at the end of the course.
Disclosure of Invention
The invention aims to provide a teaching task scoring method and system based on three-dimensional modeling, which can accurately evaluate the learning condition of a user on the whole process of the three-dimensional modeling.
The invention solves the technical problems and adopts the following technical scheme:
on the one hand, the invention provides a teaching task scoring method based on three-dimensional modeling, which comprises the following steps:
The cloud platform acquires the operation requirements of three-dimensional modeling, generates standard operation flow information and standard operation result information under the operation requirements of different three-dimensional modeling, distributes a first weight for the three-dimensional modeling process, a second weight for the solid part assembling process and a third weight for an assembling result;
The learning terminal acquires the operation requirement of the current three-dimensional modeling, and acquires standard operation flow information and standard operation result information corresponding to the operation requirement of the current three-dimensional modeling from the cloud platform;
acquiring user learning time under the current three-dimensional modeling operation requirement, and transmitting the current three-dimensional modeling operation requirement to an operation terminal through a cloud platform after the user learning time reaches the specified learning time;
Acquiring first operation flow information for three-dimensional modeling in an operation terminal, and three-dimensional model information constructed in a first operation time under the first operation flow information, and sending the first operation flow information and the first operation time to a cloud platform, and simultaneously sending the three-dimensional model information to a 3D printing terminal;
Yun Pingtai calculating a first score according to the first workflow information and the first operation time and in combination with the first weight;
All the entity parts corresponding to the three-dimensional model information are manufactured through the 3D printing terminal, second operation flow information for assembling all the entity parts and assembly result information assembled in a second operation time under the second operation flow information are obtained, and the second operation flow information, the second operation time and the assembly result information are sent to the cloud platform;
yun Pingtai calculating a second score according to the second workflow information and the second working time by combining the second weight, calculating a third score according to the assembly result information by combining the third weight, and adding the sum of the first score, the second score and the third score as a final score.
As a further optimization, the first weight is at least 0.5, and the sum of the second weight and the third weight is at most 0.5;
the sum of the first weight, the second weight and the third weight is 1.
As a further optimization, before the acquiring the learning time of the user under the requirement of the current three-dimensional modeling operation, the method comprises the following steps:
the method comprises the steps that a specified learning time, a learning terminal identification information list and a user identity information list under the operation requirement of current three-dimensional modeling are stored in a cloud platform in advance;
the cloud platform is also pre-stored with a preset first operation time and an operation terminal identification information list;
the cloud platform is also pre-stored with a preset second operation time;
Standard assembly result image information is also stored in the cloud platform in advance.
As further optimization, the acquiring the user learning time under the current three-dimensional modeling operation requirement, when the user learning time reaches the specified learning time, sending the current three-dimensional modeling operation requirement to the operation terminal through the cloud platform, including the following steps:
The method comprises the steps that in user learning time, a learning terminal collects real-time identity information of a user, and when the user learning time reaches a specified time, the learning terminal sends current learning terminal identification information and the real-time identity information of the user to a cloud platform;
The cloud platform judges whether the current learning terminal identification information exists in a pre-stored learning terminal identification information list, and when the current learning terminal identification information exists, the cloud platform inquires a user identity information list according to the real-time identity information of the user;
if the real-time identity information of the user can be queried in the user identity information list, the current three-dimensional modeling operation requirement is sent to the operation terminal through the cloud platform.
As further optimization, the method includes the steps of obtaining first operation flow information for three-dimensional modeling in the operation terminal, and three-dimensional model information constructed in a first operation time under the first operation flow information, and sending the first operation flow information and the first operation time to the cloud platform, and simultaneously sending the three-dimensional model information to the 3D printing terminal, and includes the following steps:
in a first operation time, the operation terminal acquires real-time identity information of a user and acquires first operation flow information for three-dimensional modeling in the operation terminal;
the operation terminal sends the identification information of the current operation terminal, the first operation time, the real-time identity information of the user and the first operation flow information to the cloud platform;
The cloud platform judges whether the current operation terminal identification information exists in a pre-stored operation terminal identification information list, and when the current operation terminal identification information exists, the cloud platform inquires a user identity information list according to the real-time identity information of a user;
If the real-time identity information of a single user can be queried in the user identity information list, the three-dimensional model information is sent to the 3D printing terminal, the first score is allowed to be calculated, and if the real-time identity information of the user cannot be queried in the user identity information list, or the real-time identity information of a plurality of users can be queried in the user identity information list, the first score is directly judged to be 0 score.
As a further optimization, when the calculation of the first score is allowed, the cloud platform calculates the first score according to the first workflow information and the first working time and by combining the first weight, which means that:
Distributing a first score for the three-dimensional modeling process, dividing the first score into a first sub-score and a second sub-score, and dividing the first weight into a first sub-weight and a second sub-weight;
Multiplying the first sub-score by a first sub-weight if the first operation time is smaller than or equal to a preset first operation time, obtaining a first sub-score, obtaining a first difference value between the first operation time and the preset first operation time if the first operation time is larger than the preset first operation time, reducing the first sub-score according to the ratio of the first difference value to the preset first operation time, and multiplying the reduced first sub-score by the first sub-weight, thus obtaining the first sub-score;
acquiring a part modeling procedure of the first operation flow information and a part modeling procedure of the standard operation flow information, judging whether the parts modeling procedures are consistent, multiplying the second sub-score by a second sub-weight to obtain a second sub-score if the parts modeling procedures are consistent, acquiring a second difference value between the part modeling procedure of the first operation flow information and the part modeling procedure of the standard operation flow information if the parts modeling procedures are inconsistent, reducing the second sub-score according to a ratio of the second difference value to the number of the parts modeling procedure of the standard operation flow information, and multiplying the reduced second sub-score by the second sub-weight to obtain the second sub-score;
the first sub-score is added to the second sub-score to obtain a first score.
As further optimization, the method includes the steps of creating all the physical parts corresponding to the three-dimensional model information through the 3D printing terminal, acquiring second operation flow information for assembling all the physical parts, and assembling result information assembled in a second operation time under the second operation flow information, and sending the second operation flow information, the second operation time and the assembling result information to the cloud platform, wherein the method includes the following steps:
in the second operation time, acquiring first image information when all the solid parts are assembled through an image acquisition device, and sending the first image information to a cloud platform;
the cloud platform analyzes the first image information to obtain real-time identity information of a user and second operation flow information for assembling all the entity parts;
The cloud platform queries a user identity information list according to the real-time identity information of the user, if the real-time identity information of a single user can be queried in the user identity information list, the cloud platform is allowed to calculate a second score and a third score, and if the real-time identity information of the user cannot be queried in the user identity information list, or the real-time identity information of a plurality of users can be queried in the user identity information list, the cloud platform directly judges that the second score and the third score are both 0 score.
As a further optimization, when the calculation of the second score is allowed, the cloud platform calculates the second score according to the second workflow information and the second working time and in combination with the second weight, which means that:
distributing a second score for the assembly process of the entity parts, dividing the second score into a third sub-score and a fourth sub-score, and dividing the second weight into a third sub-weight and a fourth sub-weight;
multiplying the third sub-score by a third sub-weight if the second operation time is less than or equal to the preset second operation time, obtaining a third sub-score, obtaining a third difference value between the second operation time and the preset second time if the second operation time is greater than the preset second operation time, reducing the third sub-score according to the ratio of the third difference value to the preset second operation time, and multiplying the reduced third sub-score by the third sub-weight, thereby obtaining the third sub-score;
Acquiring a part assembly procedure of the second operation flow information and a part assembly procedure of the standard operation flow information, judging whether the parts assembly procedure of the second operation flow information and the part assembly procedure of the standard operation flow information are consistent, multiplying the fourth sub-score by fourth sub-weight to obtain a fourth sub-score if the parts assembly procedure of the second operation flow information and the part assembly procedure of the standard operation flow information are consistent, acquiring a fourth difference value of the part assembly procedure of the second operation flow information and the part assembly procedure of the standard operation flow information if the parts assembly procedure of the second operation flow information and the part assembly procedure of the standard operation flow information are inconsistent, reducing the fourth sub-score according to a ratio of the fourth difference value to the number of the parts assembly procedure of the standard operation flow information, and multiplying the reduced fourth sub-score by the fourth sub-weight to obtain the fourth sub-score;
And adding the third sub-score and the fourth sub-score to obtain a second score.
As a further optimization, when the third score is allowed to be calculated, the cloud platform calculates the third score according to the assembly result information and in combination with the third weight, which means that:
Assigning a third score to the assembled result, and equally dividing the third score into a fifth sub-score, a sixth sub-score, a seventh sub-peak and an eighth sub-score, and dividing the third weight into a fifth sub-weight, a sixth sub-weight, a seventh sub-weight and an eighth sub-weight;
acquiring second image information corresponding to the assembly result information through an image acquisition device, and sending the second image information to the cloud platform;
The cloud platform analyzes the second image information to obtain a three-dimensional image, a front view, a left view and a top view of an assembly result, and invokes a CV image processing algorithm to convert the three-dimensional image, the front view, the left view and the top view into gray images;
The cloud platform analyzes the image information of the standard assembly result, analyzes a three-dimensional image, a front view, a left view and a top view of the standard assembly result, and calls a CV image processing algorithm to convert the three-dimensional image, the front view, the left view and the top view into gray images;
Comparing the gray level images of the three-dimensional image, the front view, the left view and the top view corresponding to the assembly result with the gray level images of the three-dimensional image, the front view, the left view and the top view corresponding to the standard assembly result by utilizing a calculation structural similarity index algorithm in a CV image processing algorithm to obtain four groups of comparison values;
And carrying out weighted average on the sub-scores and the sub-weights corresponding to the four groups of comparison values to obtain a third score.
On the other hand, the invention provides a teaching task scoring system based on three-dimensional modeling, which is applied to a teaching task scoring method based on three-dimensional modeling, and comprises the following steps:
the learning terminal is used for acquiring the operation requirement of the current three-dimensional modeling, and acquiring standard operation flow information and standard operation result information corresponding to the operation requirement of the current three-dimensional modeling from the cloud platform;
the user learning time acquisition unit is used for acquiring the user learning time under the current three-dimensional modeling operation requirement, and transmitting the current three-dimensional modeling operation requirement to the operation terminal through the cloud platform after the user learning time reaches the specified learning time;
The first information acquisition unit is used for acquiring first operation flow information for three-dimensional modeling in the operation terminal and three-dimensional model information constructed in a first operation time under the first operation flow information, sending the first operation flow information and the first operation time to the cloud platform, and simultaneously sending the three-dimensional model information to the 3D printing terminal;
the 3D printing terminal is used for manufacturing all the entity parts corresponding to the three-dimensional model information;
The second information acquisition unit is used for acquiring second operation flow information for assembling all the entity parts and assembly result information assembled in a second operation time under the second operation flow information, and sending the second operation flow information, the second operation time and the assembly result information to the cloud platform;
The cloud platform is used for three-dimensional modeling operation requirements, generating standard operation flow information and standard operation result information under different three-dimensional modeling operation requirements, distributing a first weight for a three-dimensional modeling process, distributing a second weight for a solid part assembling process and distributing a third weight for an assembling result;
the first scoring module is used for calculating a first score according to the first operation flow information and the first operation time and combining the first weight;
And the second score is calculated according to the second work flow information and the second work time by combining the second weight, the third score is calculated according to the assembly result information by combining the third weight, and the sum of the first score, the second score and the third score is taken as a final score.
The beneficial effects of the invention are as follows: according to the teaching task scoring method and system based on three-dimensional modeling, firstly, the learning condition of a user in three-dimensional modeling software can be evaluated, secondly, the learning condition can be further evaluated by manually assembling parts after the modeling is completed, and finally, the learning condition can be evaluated again through the assembling result, so that the learning condition of the user in the whole three-dimensional modeling process can be accurately evaluated.
Drawings
FIG. 1 is a flowchart of a teaching task scoring method based on three-dimensional modeling according to embodiment 1 of the present invention;
FIG. 2 is a three-dimensional view of the standard in example 3 of the present invention;
FIG. 3 is a front view of the standard in embodiment 3 of the present invention;
FIG. 4 is a left side view of the standard of example 3 of the present invention;
FIG. 5 is a top view of the standard of example 3 of the present invention;
FIG. 6 is a three-dimensional view showing the assembly result of classmate A in example 3 of the present invention;
FIG. 7 is a front view showing the assembly result of classmate A in example 3 of the present invention;
FIG. 8 is a left side view showing the assembly result of classmate A in example 3 of the present invention;
FIG. 9 is a top view showing the assembly result of the classmate A in example 3 of the present invention;
FIG. 10 is a three-dimensional view showing the assembly result of classmate B in example 3 of the present invention;
FIG. 11 is a front view showing the assembly result of the classmate B in the embodiment 3 of the present invention;
FIG. 12 is a left side view showing the assembly result of the classmate B in the embodiment 3 of the present invention;
FIG. 13 is a top view showing the assembly result of the classmate B in example 3 of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of 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, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Example 1
The embodiment provides a teaching task scoring method based on three-dimensional modeling, and a flow chart of the method is shown in fig. 1, wherein the method comprises the following steps:
S1, a cloud platform acquires operation requirements of three-dimensional modeling, generates standard operation flow information and standard operation result information under different operation requirements of three-dimensional modeling, distributes a first weight for a three-dimensional modeling process, distributes a second weight for a solid part assembling process and distributes a third weight for an assembling result;
S2, acquiring the operation requirement of the current three-dimensional modeling by the learning terminal, and acquiring standard operation flow information and standard operation result information corresponding to the operation requirement of the current three-dimensional modeling from the cloud platform;
s3, acquiring user learning time under the current three-dimensional modeling operation requirement, and transmitting the current three-dimensional modeling operation requirement to an operation terminal through a cloud platform after the user learning time reaches the specified learning time;
S4, acquiring first operation flow information for three-dimensional modeling in the operation terminal and three-dimensional model information constructed in a first operation time under the first operation flow information, and sending the first operation flow information and the first operation time to the cloud platform, and simultaneously sending the three-dimensional model information to the 3D printing terminal;
S5, the cloud platform calculates a first score according to the first operation flow information and the first operation time and by combining the first weight;
S6, manufacturing all the entity parts corresponding to the three-dimensional model information through the 3D printing terminal, acquiring second operation flow information for assembling all the entity parts, assembling result information assembled in a second operation time under the second operation flow information, and sending the second operation flow information, the second operation time and the assembling result information to the cloud platform;
And S7, the cloud platform calculates a second score according to the second operation flow information and the second operation time and combining the second weight, calculates a third score according to the assembly result information and combining the third weight, and takes the sum of the first score, the second score and the third score as a final score.
In a general three-dimensional modeling teaching process, after a task is issued, a student only needs to build a model in three-dimensional modeling software and send the built model to an auditing teacher for scoring, but for the three-dimensional modeling task, the learning process is not objective to evaluate only by a modeling result, and because the modeling process cannot be monitored, even if other people participate in cheating or directly replace the modeling process, the auditing teacher is unaware, and further the learning degree of the student on the three-dimensional modeling software can be greatly reduced. Therefore, in this embodiment, not only the modeling process is monitored, but also the students can assemble the parts after the modeling is completed, so as to further improve the mastering degree of the three-dimensional modeling process, and simultaneously, both the assembly process and the assembly result are monitored, so as to accurately evaluate the whole three-dimensional modeling learning process.
In this embodiment, since the learning of the three-dimensional modeling task is more focused on the three-dimensional modeling software, the first weight should be at most 0.5, the sum of the second weight and the third weight is at most 0.5, and the sum of the first weight, the second weight and the third weight is 1, because it is possible to further monitor whether the operation of the modeling user is the own operation of the modeling user, and to further familiarize the user with the modeling process. The lowest value of the first weight is 0.5, the second weight and the third weight can be set as required, and the sum of the three weights is 1.
In order to accurately evaluate the three-dimensional modeling process, the assembly process and the assembly result, in this embodiment, before acquiring the learning time of the user under the current operation requirement of three-dimensional modeling, the method may include: the method comprises the steps that a specified learning time, a learning terminal identification information list and a user identity information list under the operation requirement of current three-dimensional modeling are stored in a cloud platform in advance; the cloud platform is also pre-stored with a preset first operation time and an operation terminal identification information list; the cloud platform is also pre-stored with a preset second operation time; standard assembly result image information is also stored in the cloud platform in advance.
In this embodiment, after the setting of the specified learning time is completed, the user may learn, in the learning terminal, standard work flow information and standard work result information corresponding to the current task requirement of the three-dimensional modeling, and since learning and grasping efficiencies of different users are not consistent, it is ensured that most users learn and grasp the three-dimensional modeling process in the setting of the specified learning time. And, when the user finishes the learning of the three-dimensional modeling process through the learning terminal, the current three-dimensional modeling operation requirement is sent to the operation terminal through the cloud platform, and the current user performs the three-dimensional modeling operation.
Therefore, in this embodiment, the acquiring the user learning time under the current three-dimensional modeling job requirement, when the user learning time reaches the specified learning time, sends the current three-dimensional modeling job requirement to the job terminal through the cloud platform, may include the following steps:
The method comprises the steps that in user learning time, a learning terminal collects real-time identity information of a user, and when the user learning time reaches a specified time, the learning terminal sends current learning terminal identification information and the real-time identity information of the user to a cloud platform;
The cloud platform judges whether the current learning terminal identification information exists in a pre-stored learning terminal identification information list, and when the current learning terminal identification information exists, the cloud platform inquires a user identity information list according to the real-time identity information of the user;
if the real-time identity information of the user can be queried in the user identity information list, the current three-dimensional modeling operation requirement is sent to the operation terminal through the cloud platform.
In the application process, three-dimensional modeling software such as Revit software is basically installed in a desktop computer or a notebook computer, and a user can perform three-dimensional modeling operation through the Revit software installed in the computer. For different three-dimensional modeling operation requirements, the corresponding standard operation flow and standard operation result are inconsistent, so that for the current three-dimensional modeling operation requirements, the cloud platform only generates standard operation flow information and standard operation result information under the operation requirements, and different standard operation flows, when a user performs three-dimensional modeling, the number of involved parts is generally tens or even hundreds, and sequential manufacturing order requirements may exist between the different parts, namely, after one part is manufactured, the next part is allowed to be manufactured, or the next part may be parallel, namely, no sequential order requirement exists, and at this time, which part can be freely manufactured can be selected.
In this embodiment, the manufacturing completion sequence of each part may be monitored to obtain first operation flow information for three-dimensional modeling in the operation terminal, and meanwhile, the first operation flow information for three-dimensional modeling in the operation terminal and the first operation time from the start of the construction to the completion of the construction of the three-dimensional model need to be obtained, so in the above method, the first operation flow information for three-dimensional modeling in the operation terminal and the three-dimensional model information constructed in the first operation time under the first operation flow information are obtained, and the first operation flow information and the first operation time are sent to the cloud platform, and meanwhile, the three-dimensional model information is sent to the 3D printing terminal, which may include the following steps:
in a first operation time, the operation terminal acquires real-time identity information of a user and acquires first operation flow information for three-dimensional modeling in the operation terminal;
the operation terminal sends the identification information of the current operation terminal, the first operation time, the real-time identity information of the user and the first operation flow information to the cloud platform;
The cloud platform judges whether the current operation terminal identification information exists in a pre-stored operation terminal identification information list, and when the current operation terminal identification information exists, the cloud platform inquires a user identity information list according to the real-time identity information of a user;
If the real-time identity information of a single user can be queried in the user identity information list, the three-dimensional model information is sent to the 3D printing terminal, the first score is allowed to be calculated, and if the real-time identity information of the user cannot be queried in the user identity information list, or the real-time identity information of a plurality of users can be queried in the user identity information list, the first score is directly judged to be 0 score.
It should be noted that, in the process of performing three-dimensional modeling learning in the learning terminal, except for the current user, even if other users participate, the process does not influence that after the learning time of the user reaches the prescribed learning time, the current three-dimensional modeling operation requirement is sent to the operation terminal through the cloud platform, but in the operation terminal, for example, the current user completes the three-dimensional modeling task by himself, at this time, if other people and cheating are present, the first score corresponding to the three-dimensional modeling process is judged to be 0, thus, even if the subsequent second score and the third score are full scores, the user can only obtain half of the integral score at most, and the relevant teacher can mark the user.
In addition, when the calculation of the first score is allowed, the cloud platform calculates the first score according to the first workflow information and the first working time and in combination with the first weight, which may be referred to as:
Distributing a first score for the three-dimensional modeling process, dividing the first score into a first sub-score and a second sub-score, and dividing the first weight into a first sub-weight and a second sub-weight;
Multiplying the first sub-score by a first sub-weight if the first operation time is smaller than or equal to a preset first operation time, obtaining a first sub-score, obtaining a first difference value between the first operation time and the preset first operation time if the first operation time is larger than the preset first operation time, reducing the first sub-score according to the ratio of the first difference value to the preset first operation time, and multiplying the reduced first sub-score by the first sub-weight, thus obtaining the first sub-score;
acquiring a part modeling procedure of the first operation flow information and a part modeling procedure of the standard operation flow information, judging whether the parts modeling procedures are consistent, multiplying the second sub-score by a second sub-weight to obtain a second sub-score if the parts modeling procedures are consistent, acquiring a second difference value between the part modeling procedure of the first operation flow information and the part modeling procedure of the standard operation flow information if the parts modeling procedures are inconsistent, reducing the second sub-score according to a ratio of the second difference value to the number of the parts modeling procedure of the standard operation flow information, and multiplying the reduced second sub-score by the second sub-weight to obtain the second sub-score;
the first sub-score is added to the second sub-score to obtain a first score.
It should be noted that, after the three-dimensional model is built, the three-dimensional model information may be sent to the 3D printing terminal to make the parts so that the user can assemble and score accurately, so in this embodiment, the method includes the steps of making all the physical parts corresponding to the three-dimensional model information by the 3D printing terminal, obtaining second operation flow information for assembling all the physical parts, and assembling result information assembled in the second operation time under the second operation flow information, and sending the second operation flow information, the second operation time and the assembling result information to the cloud platform, and may include the following steps:
in the second operation time, acquiring first image information when all the solid parts are assembled through an image acquisition device, and sending the first image information to a cloud platform;
the cloud platform analyzes the first image information to obtain real-time identity information of a user and second operation flow information for assembling all the entity parts;
The cloud platform queries a user identity information list according to the real-time identity information of the user, if the real-time identity information of a single user can be queried in the user identity information list, the cloud platform is allowed to calculate a second score and a third score, and if the real-time identity information of the user cannot be queried in the user identity information list, or the real-time identity information of a plurality of users can be queried in the user identity information list, the cloud platform directly judges that the second score and the third score are both 0 score.
Similarly, in order to avoid the cheating phenomenon, in the assembly process, if other users except the current user participate in the production, the second score and the third score are also directly judged to be 0 so as to prompt the relevant teacher to pay attention, thereby further improving the accuracy of evaluation and the mastering degree of the current user on the three-dimensional modeling process.
In addition, in this embodiment, when the calculation of the second score is allowed, the calculation of the second score by the cloud platform according to the second workflow information and the second working time and in combination with the second weight may refer to:
distributing a second score for the assembly process of the entity parts, dividing the second score into a third sub-score and a fourth sub-score, and dividing the second weight into a third sub-weight and a fourth sub-weight;
multiplying the third sub-score by a third sub-weight if the second operation time is less than or equal to the preset second operation time, obtaining a third sub-score, obtaining a third difference value between the second operation time and the preset second time if the second operation time is greater than the preset second operation time, reducing the third sub-score according to the ratio of the third difference value to the preset second operation time, and multiplying the reduced third sub-score by the third sub-weight, thereby obtaining the third sub-score;
Acquiring a part assembly procedure of the second operation flow information and a part assembly procedure of the standard operation flow information, judging whether the parts assembly procedure of the second operation flow information and the part assembly procedure of the standard operation flow information are consistent, multiplying the fourth sub-score by fourth sub-weight to obtain a fourth sub-score if the parts assembly procedure of the second operation flow information and the part assembly procedure of the standard operation flow information are consistent, acquiring a fourth difference value of the part assembly procedure of the second operation flow information and the part assembly procedure of the standard operation flow information if the parts assembly procedure of the second operation flow information and the part assembly procedure of the standard operation flow information are inconsistent, reducing the fourth sub-score according to a ratio of the fourth difference value to the number of the parts assembly procedure of the standard operation flow information, and multiplying the reduced fourth sub-score by the fourth sub-weight to obtain the fourth sub-score;
And adding the third sub-score and the fourth sub-score to obtain a second score.
It should be noted that, when the calculation of the third score is allowed, the cloud platform calculates the third score according to the assembly result information in combination with the third weight, which may mean that:
Assigning a third score to the assembled result, and equally dividing the third score into a fifth sub-score, a sixth sub-score, a seventh sub-peak and an eighth sub-score, and dividing the third weight into a fifth sub-weight, a sixth sub-weight, a seventh sub-weight and an eighth sub-weight;
acquiring second image information corresponding to the assembly result information through an image acquisition device, and sending the second image information to the cloud platform;
The cloud platform analyzes the second image information to obtain a three-dimensional image, a front view, a left view and a top view of an assembly result, and invokes a CV image processing algorithm to convert the three-dimensional image, the front view, the left view and the top view into gray images;
The cloud platform analyzes the image information of the standard assembly result, analyzes a three-dimensional image, a front view, a left view and a top view of the standard assembly result, and calls a CV image processing algorithm to convert the three-dimensional image, the front view, the left view and the top view into gray images;
Comparing the gray level images of the three-dimensional image, the front view, the left view and the top view corresponding to the assembly result with the gray level images of the three-dimensional image, the front view, the left view and the top view corresponding to the standard assembly result by utilizing a calculation structural similarity index algorithm in a CV image processing algorithm to obtain four groups of comparison values;
And carrying out weighted average on the sub-scores and the sub-weights corresponding to the four groups of comparison values to obtain a third score.
In a specific application process, the third scoring can be achieved by the following steps:
1. the four standard views are produced according to the operation requirements of arrangement and are respectively as follows: three-dimensional, front, left, and top views, each view invoking a CV image processing algorithm to convert to a grayscale image.
2. The homework is issued, the three-dimensional drawing, the front view, the left view and the top view are named after the students finish, the received drawing is uniformly converted in a student coding and view angle mode, and the received drawing is stored in the format of Pnum _image_D, pnum _image_FR, pnum _image_L and Pnum _image_T.
3. Converted to a corresponding grayscale image using CV image processing algorithms, pnum _gray_image_d, pnum _gray_image_fr, pnum _gray_image_l, pnum _gray_image_t.
3. Using a computational Structured Similarity Index (SSIM) algorithm in the CV image processing algorithm, four sets of comparison values (Pnum _ SSIM _score [ D ], pnum _ SSIM _score [ FR ], pnum _ SSIM _score [ L ], pnum _ SSIM _score [ T ]) were obtained, the four sets of comparison values above were recorded, and values below 70% of which were marked for manual review by a teacher.
4. The four sets of comparison values are weighted and averaged to obtain a student assessment score (ssim _score).
In addition, after the assembly result information is obtained, the photographs and the design drawings are first registered using a feature matching algorithm SFIT, ensuring that their scale, rotation and translation differences are minimized, and a transformation matrix between them is calculated to align them, once the image registration is completed, a Structural Similarity Index (SSIM) algorithm is employed to find the differences. The differences between the design drawings and the pictures can be found out by calculating the similarity scores between the design drawings and the pictures, and numerical values are counted into the system for rechecking. Then, YOLO is used to find out specific discrepant objects or areas and mark them, and the discrepant data is counted into the system for review. Finally, the found differences are visually displayed in a marking, coloring and other modes so as to be more intuitively understood and compared and used for rechecking and displaying the scoring result basis to students.
Example 2
On the basis of embodiment 1, the present embodiment provides a teaching task scoring system based on three-dimensional modeling, including:
the learning terminal is used for acquiring the operation requirement of the current three-dimensional modeling, and acquiring standard operation flow information and standard operation result information corresponding to the operation requirement of the current three-dimensional modeling from the cloud platform;
the user learning time acquisition unit is used for acquiring the user learning time under the current three-dimensional modeling operation requirement, and transmitting the current three-dimensional modeling operation requirement to the operation terminal through the cloud platform after the user learning time reaches the specified learning time;
The first information acquisition unit is used for acquiring first operation flow information for three-dimensional modeling in the operation terminal and three-dimensional model information constructed in a first operation time under the first operation flow information, sending the first operation flow information and the first operation time to the cloud platform, and simultaneously sending the three-dimensional model information to the 3D printing terminal;
the 3D printing terminal is used for manufacturing all the entity parts corresponding to the three-dimensional model information;
The second information acquisition unit is used for acquiring second operation flow information for assembling all the entity parts and assembly result information assembled in a second operation time under the second operation flow information, and sending the second operation flow information, the second operation time and the assembly result information to the cloud platform;
The cloud platform is used for three-dimensional modeling operation requirements, generating standard operation flow information and standard operation result information under different three-dimensional modeling operation requirements, distributing a first weight for a three-dimensional modeling process, distributing a second weight for a solid part assembling process and distributing a third weight for an assembling result;
the first scoring module is used for calculating a first score according to the first operation flow information and the first operation time and combining the first weight;
And the second score is calculated according to the second work flow information and the second work time by combining the second weight, the third score is calculated according to the assembly result information by combining the third weight, and the sum of the first score, the second score and the third score is taken as a final score.
According to the description of embodiment 1, the working principle and implementation process of this embodiment are the same as those of embodiment 1, and thus, a detailed description is omitted.
Example 3
In the embodiment, based on embodiment 1 and embodiment 2, in the practical application process, the teacher arranges the operation requirement of three-dimensional modeling, and sends the operation requirement to the cloud platform for the learning terminal to obtain, see fig. 2-5, which are four views of the standard under the current three-dimensional modeling operation requirement, see fig. 6-9, which are four views of the assembly result of the classmate a, and see fig. 10-13, which are four views of the assembly result of the classmate B.
The four views of the classmate A are compared with the standard four views respectively, and the bottom surface of the bridge deck in the three-dimensional view of the classmate A is wrong, the section of the bridge deck in the left view is wrong, and the front view and the top view are not wrong; comparing the four views of the classmate B with the standard four views respectively, the three-dimensional view of the classmate B is not complete in overall structure, the bridge structure in the front view is missing, and the front view and the top view do not correspond to the standard view.
Assuming that the whole three-dimensional design process and the assembly process are independently completed, the score of the classmate A is obviously higher than that of the classmate B, if the accurate scores of the classmates B are to be calculated accurately, the operation time, the modeling process, the assembly process and the like are combined, and based on the assembly result of the classmate B, the classmate B belongs to a study object focused on, the classmate B can be marked through a cloud platform, and the classmate B is reminded to score again after relearning.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. The teaching task scoring method based on three-dimensional modeling is characterized by comprising the following steps of:
The cloud platform acquires the operation requirements of three-dimensional modeling, generates standard operation flow information and standard operation result information under the operation requirements of different three-dimensional modeling, distributes a first weight for the three-dimensional modeling process, a second weight for the solid part assembling process and a third weight for an assembling result;
The learning terminal acquires the operation requirement of the current three-dimensional modeling, and acquires standard operation flow information and standard operation result information corresponding to the operation requirement of the current three-dimensional modeling from the cloud platform;
acquiring user learning time under the current three-dimensional modeling operation requirement, and transmitting the current three-dimensional modeling operation requirement to an operation terminal through a cloud platform after the user learning time reaches the specified learning time;
Acquiring first operation flow information for three-dimensional modeling in an operation terminal, and three-dimensional model information constructed in a first operation time under the first operation flow information, and sending the first operation flow information and the first operation time to a cloud platform, and simultaneously sending the three-dimensional model information to a 3D printing terminal;
Yun Pingtai calculating a first score according to the first workflow information and the first operation time and in combination with the first weight;
All the entity parts corresponding to the three-dimensional model information are manufactured through the 3D printing terminal, second operation flow information for assembling all the entity parts and assembly result information assembled in a second operation time under the second operation flow information are obtained, and the second operation flow information, the second operation time and the assembly result information are sent to the cloud platform;
yun Pingtai calculating a second score according to the second workflow information and the second working time by combining the second weight, calculating a third score according to the assembly result information by combining the third weight, and adding the sum of the first score, the second score and the third score as a final score.
2. The three-dimensional modeling-based teaching task scoring method of claim 1, wherein the first weight is at least 0.5, and the sum of the second weight and the third weight is at most 0.5;
the sum of the first weight, the second weight and the third weight is 1.
3. The teaching task scoring method based on three-dimensional modeling according to claim 1, wherein before the learning time of the user under the task requirement of the current three-dimensional modeling is obtained, the method comprises:
the method comprises the steps that a specified learning time, a learning terminal identification information list and a user identity information list under the operation requirement of current three-dimensional modeling are stored in a cloud platform in advance;
the cloud platform is also pre-stored with a preset first operation time and an operation terminal identification information list;
the cloud platform is also pre-stored with a preset second operation time;
Standard assembly result image information is also stored in the cloud platform in advance.
4. The teaching task scoring method based on three-dimensional modeling according to claim 3, wherein the step of obtaining the user learning time under the current three-dimensional modeling job requirement, and when the user learning time reaches the prescribed learning time, sending the current three-dimensional modeling job requirement to the job terminal through the cloud platform comprises the following steps:
The method comprises the steps that in user learning time, a learning terminal collects real-time identity information of a user, and when the user learning time reaches a specified time, the learning terminal sends current learning terminal identification information and the real-time identity information of the user to a cloud platform;
The cloud platform judges whether the current learning terminal identification information exists in a pre-stored learning terminal identification information list, and when the current learning terminal identification information exists, the cloud platform inquires a user identity information list according to the real-time identity information of the user;
if the real-time identity information of the user can be queried in the user identity information list, the current three-dimensional modeling operation requirement is sent to the operation terminal through the cloud platform.
5. The teaching task scoring method based on three-dimensional modeling according to claim 3, wherein the steps of obtaining the first workflow information for three-dimensional modeling in the operation terminal and the three-dimensional model information constructed in the first operation time under the first workflow information, and sending the first workflow information and the first operation time to the cloud platform, and simultaneously sending the three-dimensional model information to the 3D printing terminal, comprise the following steps:
in a first operation time, the operation terminal acquires real-time identity information of a user and acquires first operation flow information for three-dimensional modeling in the operation terminal;
the operation terminal sends the identification information of the current operation terminal, the first operation time, the real-time identity information of the user and the first operation flow information to the cloud platform;
The cloud platform judges whether the current operation terminal identification information exists in a pre-stored operation terminal identification information list, and when the current operation terminal identification information exists, the cloud platform inquires a user identity information list according to the real-time identity information of a user;
If the real-time identity information of a single user can be queried in the user identity information list, the three-dimensional model information is sent to the 3D printing terminal, the first score is allowed to be calculated, and if the real-time identity information of the user cannot be queried in the user identity information list, or the real-time identity information of a plurality of users can be queried in the user identity information list, the first score is directly judged to be 0 score.
6. The teaching task scoring method based on three-dimensional modeling according to claim 5, wherein when the calculation of the first score is allowed, the cloud platform calculates the first score according to the first workflow information and the first working time in combination with the first weight, which means:
Distributing a first score for the three-dimensional modeling process, dividing the first score into a first sub-score and a second sub-score, and dividing the first weight into a first sub-weight and a second sub-weight;
Multiplying the first sub-score by a first sub-weight if the first operation time is smaller than or equal to a preset first operation time, obtaining a first sub-score, obtaining a first difference value between the first operation time and the preset first operation time if the first operation time is larger than the preset first operation time, reducing the first sub-score according to the ratio of the first difference value to the preset first operation time, and multiplying the reduced first sub-score by the first sub-weight, thus obtaining the first sub-score;
acquiring a part modeling procedure of the first operation flow information and a part modeling procedure of the standard operation flow information, judging whether the parts modeling procedures are consistent, multiplying the second sub-score by a second sub-weight to obtain a second sub-score if the parts modeling procedures are consistent, acquiring a second difference value between the part modeling procedure of the first operation flow information and the part modeling procedure of the standard operation flow information if the parts modeling procedures are inconsistent, reducing the second sub-score according to a ratio of the second difference value to the number of the parts modeling procedure of the standard operation flow information, and multiplying the reduced second sub-score by the second sub-weight to obtain the second sub-score;
the first sub-score is added to the second sub-score to obtain a first score.
7. The teaching task scoring method based on three-dimensional modeling according to claim 3, wherein the steps of creating all the physical parts corresponding to the three-dimensional model information by the 3D printing terminal, acquiring second operation flow information for assembling all the physical parts, and assembling result information assembled in a second operation time under the second operation flow information, and transmitting the second operation flow information, the second operation time and the assembling result information to the cloud platform, include the steps of:
in the second operation time, acquiring first image information when all the solid parts are assembled through an image acquisition device, and sending the first image information to a cloud platform;
the cloud platform analyzes the first image information to obtain real-time identity information of a user and second operation flow information for assembling all the entity parts;
The cloud platform queries a user identity information list according to the real-time identity information of the user, if the real-time identity information of a single user can be queried in the user identity information list, the cloud platform is allowed to calculate a second score and a third score, and if the real-time identity information of the user cannot be queried in the user identity information list, or the real-time identity information of a plurality of users can be queried in the user identity information list, the cloud platform directly judges that the second score and the third score are both 0 score.
8. The teaching task scoring method based on three-dimensional modeling according to claim 7, wherein when the calculation of the second score is allowed, the cloud platform calculates the second score according to the second workflow information and the second working time in combination with the second weight, which means:
distributing a second score for the assembly process of the entity parts, dividing the second score into a third sub-score and a fourth sub-score, and dividing the second weight into a third sub-weight and a fourth sub-weight;
multiplying the third sub-score by a third sub-weight if the second operation time is less than or equal to the preset second operation time, obtaining a third sub-score, obtaining a third difference value between the second operation time and the preset second time if the second operation time is greater than the preset second operation time, reducing the third sub-score according to the ratio of the third difference value to the preset second operation time, and multiplying the reduced third sub-score by the third sub-weight, thereby obtaining the third sub-score;
Acquiring a part assembly procedure of the second operation flow information and a part assembly procedure of the standard operation flow information, judging whether the parts assembly procedure of the second operation flow information and the part assembly procedure of the standard operation flow information are consistent, multiplying the fourth sub-score by fourth sub-weight to obtain a fourth sub-score if the parts assembly procedure of the second operation flow information and the part assembly procedure of the standard operation flow information are consistent, acquiring a fourth difference value of the part assembly procedure of the second operation flow information and the part assembly procedure of the standard operation flow information if the parts assembly procedure of the second operation flow information and the part assembly procedure of the standard operation flow information are inconsistent, reducing the fourth sub-score according to a ratio of the fourth difference value to the number of the parts assembly procedure of the standard operation flow information, and multiplying the reduced fourth sub-score by the fourth sub-weight to obtain the fourth sub-score;
And adding the third sub-score and the fourth sub-score to obtain a second score.
9. The teaching task scoring method based on three-dimensional modeling according to claim 7, wherein when the third score is allowed to be calculated, the cloud platform calculates the third score according to the assembly result information in combination with the third weight, which means:
Assigning a third score to the assembled result, and equally dividing the third score into a fifth sub-score, a sixth sub-score, a seventh sub-peak and an eighth sub-score, and dividing the third weight into a fifth sub-weight, a sixth sub-weight, a seventh sub-weight and an eighth sub-weight;
acquiring second image information corresponding to the assembly result information through an image acquisition device, and sending the second image information to the cloud platform;
The cloud platform analyzes the second image information to obtain a three-dimensional image, a front view, a left view and a top view of an assembly result, and invokes a CV image processing algorithm to convert the three-dimensional image, the front view, the left view and the top view into gray images;
The cloud platform analyzes the image information of the standard assembly result, analyzes a three-dimensional image, a front view, a left view and a top view of the standard assembly result, and calls a CV image processing algorithm to convert the three-dimensional image, the front view, the left view and the top view into gray images;
Comparing the gray level images of the three-dimensional image, the front view, the left view and the top view corresponding to the assembly result with the gray level images of the three-dimensional image, the front view, the left view and the top view corresponding to the standard assembly result by utilizing a calculation structural similarity index algorithm in a CV image processing algorithm to obtain four groups of comparison values;
And carrying out weighted average on the sub-scores and the sub-weights corresponding to the four groups of comparison values to obtain a third score.
10. A three-dimensional modeling-based teaching task scoring system applied to the three-dimensional modeling-based teaching task scoring method according to any one of claims 1 to 9, characterized by comprising:
the learning terminal is used for acquiring the operation requirement of the current three-dimensional modeling, and acquiring standard operation flow information and standard operation result information corresponding to the operation requirement of the current three-dimensional modeling from the cloud platform;
the user learning time acquisition unit is used for acquiring the user learning time under the current three-dimensional modeling operation requirement, and transmitting the current three-dimensional modeling operation requirement to the operation terminal through the cloud platform after the user learning time reaches the specified learning time;
The first information acquisition unit is used for acquiring first operation flow information for three-dimensional modeling in the operation terminal and three-dimensional model information constructed in a first operation time under the first operation flow information, sending the first operation flow information and the first operation time to the cloud platform, and simultaneously sending the three-dimensional model information to the 3D printing terminal;
the 3D printing terminal is used for manufacturing all the entity parts corresponding to the three-dimensional model information;
The second information acquisition unit is used for acquiring second operation flow information for assembling all the entity parts and assembly result information assembled in a second operation time under the second operation flow information, and sending the second operation flow information, the second operation time and the assembly result information to the cloud platform;
The cloud platform is used for three-dimensional modeling operation requirements, generating standard operation flow information and standard operation result information under different three-dimensional modeling operation requirements, distributing a first weight for a three-dimensional modeling process, distributing a second weight for a solid part assembling process and distributing a third weight for an assembling result;
the first scoring module is used for calculating a first score according to the first operation flow information and the first operation time and combining the first weight;
And the second score is calculated according to the second work flow information and the second work time by combining the second weight, the third score is calculated according to the assembly result information by combining the third weight, and the sum of the first score, the second score and the third score is taken as a final score.
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