CN117111792A

CN117111792A - Method and device for determining automobile disassembly training evaluation mode and readable storage medium

Info

Publication number: CN117111792A
Application number: CN202311131651.XA
Authority: CN
Inventors: 王玉彪; 旋艳静; 金健; 杨俊伟; 刘琪; 覃桂蕊; 曾志; 王佩伟
Original assignee: Fxb Co ltd
Current assignee: Fxb Co ltd
Priority date: 2023-09-04
Filing date: 2023-09-04
Publication date: 2023-11-24

Abstract

The invention discloses a method and a device for determining an automobile disassembly training evaluation mode and a readable storage medium, which are applied to the field of data processing systems, wherein the method comprises the following steps: determining a history training module according to the identity information associated with the automobile disassembly training terminal; determining a history training result and/or a history training duration corresponding to the history training module; recommending a first target evaluation module and/or a second target evaluation module based on the historical training result and/or the historical training time; determining a target evaluation mode according to the first target evaluation module and/or the second target evaluation module; the target evaluation mode is recommended to the automobile disassembly and assembly practical training terminal, the limitation of the traditional evaluation mode of the automobile virtual disassembly and assembly system is broken, the problem that corresponding evaluation modes cannot be recommended for different practical training objects is solved, the limitation exists in the evaluation mode, and the matched evaluation modes can be recommended for practical training experiences of different practical training objects.

Description

Method and device for determining automobile disassembly training evaluation mode and readable storage medium

Technical Field

The invention relates to the field of data processing systems, in particular to a method and a device for determining an automobile disassembly and assembly training evaluation mode and a readable storage medium.

Background

With the continuous improvement of the modernization degree of automobiles in China, higher requirements are put forward on the technological content of the automobile maintenance industry, the modernization of automobile maintenance means, the scientization of the automobile maintenance means and the like, and the development of the automobile maintenance profession is not kept away. For the whole gas repair professional construction, the investment of gas repair professional practical training equipment is increased year by year, and a teaching mode of 'virtual-real fusion' is basically formed.

In the related art, the VR technology is applied to the training of automobile disassembly and assembly teaching, and the blank of the VR technology in the automobile disassembly and assembly training field, especially the new energy automobile disassembly and assembly training field is filled. Through VR glasses, the students can see the virtual three-dimensional automobile repair training environment, and the students can conduct interactive operation with the virtual environment through the operating handle. The system can show the automobile structural details which cannot be shown in the practical training, is not limited by space, has good interactivity and deep immersion, can greatly increase actual combat experience of students, reduces abrasion of practical training equipment, reduces training cost and improves practical training safety.

However, the assessment and evaluation modes adopted by the VR technology automobile virtual dismounting system are single and are generally fixed, and the practical training experiences of different practical training objects are different, so that the corresponding evaluation modes cannot be recommended for the different practical training objects, and the limitation exists in the evaluation modes.

Disclosure of Invention

The embodiment of the application aims to break the limitation of the traditional evaluation mode of the automobile virtual dismounting system by providing the method, the device and the readable storage medium for determining the automobile dismounting practical training evaluation mode, and can recommend the matched evaluation mode aiming at practical training experience of different practical training objects.

The embodiment of the application provides a method for determining an automobile disassembly and assembly practical training evaluation mode, which is applied to an automobile disassembly and assembly evaluation terminal, wherein the automobile disassembly and assembly evaluation terminal is connected with the automobile disassembly and assembly practical training terminal, and the method for determining the automobile disassembly and assembly practical training evaluation mode comprises the following steps:

determining a history training module according to the identity information associated with the automobile disassembly training terminal;

determining a history training result and/or a history training duration corresponding to the history training module;

recommending a first target evaluation module and/or a second target evaluation module based on the historical training result and/or the historical training time;

determining a target evaluation mode according to the first target evaluation module and/or the second target evaluation module;

and recommending the target evaluation mode to the automobile disassembly training terminal.

Optionally, recommending the first target evaluation module or the second target evaluation module based on the historical training result or the historical training time length of each historical training module comprises:

From all the history training modules, a first history training module with a history training result smaller than a preset training result is determined;

determining a first preset training module with highest similarity with the first historical training module from a training module database, and determining the first preset training module as the first target evaluation module;

determining a second historical training module with the historical training time length longer than the preset time length from all the historical training modules;

and determining a second preset training module with highest similarity with the second historical training module from a training module database, and determining the second preset training module as the second target evaluation module.

Optionally, the first history training module includes at least two first history training tasks of different types, the second history training module includes at least two second history training tasks of different types, and determining, from a training module database, a first preset training module having the highest similarity with the first history training module includes:

determining a first preset training task with highest similarity with each first historical training task from the training module database, and combining each first preset training task to obtain a first preset training module;

The step of determining a second preset training module with highest similarity with the second historical training module from the training module database comprises the following steps:

and determining a second preset training task with highest similarity with each second historical training task from the training module database, and combining each second preset training task to obtain the second preset training module.

Optionally, recommending the first target evaluation module and the second target evaluation module based on the historical training result and the historical training time length of each historical training module comprises:

determining a third historical training module with a historical training result smaller than a preset training result from all the historical training modules, determining a third preset training module with highest similarity with the third historical training module from a training module database, and determining the third preset training module as the first target evaluation module;

when the number of the first target evaluation modules is smaller than a first preset value, the first target evaluation modules are used as the second target evaluation modules, and the first preset value is an integer;

when the number of the first target evaluation modules is greater than or equal to the first preset value, determining a fourth historical training module with the historical training time longer than the preset time from all the first target evaluation modules, determining a fourth preset training module with highest similarity with the fourth historical training module from a training module database, and determining the fourth preset training module as the second target evaluation module.

determining a fifth historical training module with a historical training result smaller than a preset training result from all the historical training modules, and determining the fifth historical training module as the first target evaluation module;

when the number of the first target evaluation modules is smaller than a second preset value, the first target evaluation modules are used as the second target evaluation modules, and the second preset value is an integer;

and when the number of the first target evaluation modules is greater than or equal to the second preset value, determining a sixth history training module with the history training time longer than the preset time length from all the first target evaluation modules, and determining the sixth history training module as the second target evaluation module.

Optionally, the step of determining a target evaluation mode according to the first target evaluation module and/or the second target evaluation module includes:

determining a preset evaluation mode corresponding to the first target evaluation module and/or a preset evaluation mode corresponding to the second target evaluation module, wherein the preset evaluation modes corresponding to the first target evaluation module and the second target evaluation module are the same or different;

When the preset evaluation mode corresponding to the first target evaluation module is the same as the preset evaluation mode corresponding to the second target evaluation module, determining the preset evaluation mode as the target evaluation mode;

when the preset evaluation mode corresponding to the first target evaluation module and the preset evaluation mode corresponding to the second target evaluation module are different, determining the historical recommendation times of the preset evaluation mode corresponding to the first target evaluation module and the preset evaluation mode corresponding to the second target evaluation module, and determining the preset evaluation mode with the highest historical recommendation times as the target evaluation mode.

Optionally, the target evaluation mode includes at least one module to be disassembled, the module to be disassembled includes at least one task to be disassembled, and after the step of determining the target evaluation mode according to the first target evaluation module and/or the second target evaluation module, the method further includes:

determining a virtual automobile disassembly and assembly tool associated with the target evaluation mode;

and sending the virtual automobile disassembly tool and the target evaluation mode to the automobile disassembly training terminal.

Optionally, after the step of sending the virtual vehicle disassembly tool and the target evaluation mode to the vehicle disassembly training terminal, the method further includes:

The method comprises the steps that an assessment result and an assessment time length of a task to be assembled and disassembled, which are corresponding to a target assessment mode, are received by the automobile assembly and disassembly training terminal, the target assessment mode sent by the automobile assembly and disassembly assessment terminal is received by the automobile assembly and disassembly training terminal, at least one task to be assembled and disassembled, which is corresponding to the target assessment mode, is obtained, a rendering interface corresponding to the task to be assembled and disassembled is displayed, and automobile assembly and disassembly assessment of the task to be assembled and disassembled is carried out on the basis of the rendering interface, so that the assessment result and the assessment time length corresponding to the task to be assembled and disassembled are obtained;

determining an evaluation result corresponding to the module to be disassembled and assembled according to the assessment result and the assessment time;

and determining the automobile disassembly and assembly evaluation result of the automobile disassembly and assembly practical training terminal according to the evaluation result and the difficulty coefficient of the module to be disassembled and assembled.

In addition, in order to achieve the above object, the present invention further provides an apparatus for determining an evaluation mode of practical training for disassembly and assembly of an automobile, comprising: the method comprises the steps of a memory, a processor and an automobile disassembly and assembly training evaluation mode determining program which is stored in the memory and can run on the processor, wherein the automobile disassembly and assembly training evaluation mode determining program is executed by the processor to realize the automobile disassembly and assembly training evaluation mode determining method.

In addition, in order to achieve the above object, the present application further provides a computer readable storage medium storing a real training evaluation mode determination program for car disassembly and assembly, wherein the real training evaluation mode determination program for car disassembly and assembly is executed by a processor to implement the steps of the real training evaluation mode determination method for car disassembly and assembly.

The embodiment of the application provides a method and a device for determining an automobile disassembly training evaluation mode and a technical scheme of a readable storage medium. Compared with the limitation of single evaluation mode of the automobile virtual disassembly and assembly system in the related art, the method can recommend the matched target evaluation mode for the practical training experience of different practical training objects, and recommend the target evaluation mode to the practical training object, so that the practical training object can carry out automobile disassembly and assembly practical training evaluation based on the target evaluation mode, and the practical training evaluation effect is improved.

Drawings

FIG. 1 is a flow chart of a first embodiment of the present application;

FIG. 2 is a schematic diagram of a refinement flow chart according to a first embodiment of the present application;

FIG. 3 is a schematic diagram of another refinement flow chart of the first embodiment of the present application;

FIG. 4 is a schematic diagram of another refinement flow chart of the first embodiment of the present application;

FIG. 5 is a schematic diagram of another refinement flow chart of the first embodiment of the present application;

FIG. 6 is a schematic diagram of a device for determining an evaluation mode of an automobile disassembly training according to the present application.

The achievement of the objects, functional features and advantages of the present application will be further described with reference to embodiments, with reference to the accompanying drawings, which are only illustrations of one embodiment, but not all of the applications.

Detailed Description

At present, the VR technology is applied to the training of automobile disassembly and assembly teaching, and fills the blank of the VR technology in the automobile disassembly and assembly training field, especially the new energy automobile disassembly and assembly training field. Through VR glasses, the students can see the virtual three-dimensional automobile repair training environment, and the students can conduct interactive operation with the virtual environment through the operating handle. The system can show the automobile structural details which cannot be shown in the practical training, is not limited by space, has good interactivity and deep immersion, can greatly increase actual combat experience of students, reduces abrasion of practical training equipment, reduces training cost and improves practical training safety. However, the assessment and evaluation modes adopted by the VR technology automobile virtual dismounting system are single and are generally fixed, and the practical training experiences of different practical training objects are different, so that the corresponding evaluation modes cannot be recommended for the different practical training objects, and the limitation exists in the evaluation modes.

Based on the defects, the application provides a method for determining an automobile disassembly and assembly training evaluation mode, which comprises the following steps: determining a plurality of history training modules according to the identity information associated with the automobile disassembly training terminal; determining a historical training result and/or a historical training duration of each historical training module; recommending a first target evaluation module and/or a second target evaluation module based on the historical training result and/or the historical training time; determining a target evaluation mode according to the first target evaluation module and/or the second target evaluation module; and recommending the target evaluation mode to the automobile disassembly training terminal. Compared with the limitation of single evaluation mode of the automobile virtual disassembly and assembly system in the related art, the method can recommend the matched target evaluation mode for the practical training experience of different practical training objects, and recommend the target evaluation mode to the practical training object, so that the practical training object can carry out automobile disassembly and assembly practical training evaluation based on the target evaluation mode, and the practical training evaluation effect is improved.

In addition, the application adopts the virtual terminal to carry out the practical training teaching and evaluation of the disassembly and assembly of the automobile. The method has good interactivity and deep immersion, can greatly increase actual combat experience of students, reduces abrasion to automobile parts, reduces training cost and assessment cost, and improves practical training safety. Solves the problems of high risk, easy abrasion and loss of parts and the like of the traditional practical training.

In order to better understand the above technical solution, exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

As shown in fig. 1, in a first embodiment of the present application, the method for determining an automobile disassembly training evaluation mode is applied to an automobile disassembly evaluation terminal, where the automobile disassembly evaluation terminal may be a terminal device such as a mobile phone, a computer, or an intelligent wearable device, for example, an intelligent glasses such as VR glasses and MR glasses. The method for determining the practical training evaluation method for the disassembly and assembly of the automobile further comprises the following steps:

and step S110, determining a history training module according to the identity information associated with the automobile disassembly training terminal.

Optionally, the identity information of the training object is bound to the automobile disassembly training terminal, and the identity information can be the identity information currently input by the training object or the identity information historically bound to the automobile disassembly training terminal by the training object. The real standard object uses the real standard terminal of car dismouting to carry out car dismouting examination. At this time, identity information is input first and identity verification is performed, so that the training object can successfully log in the automobile virtual dismounting system, the identity information includes but is not limited to a user name, an account number, a password and the like, and after the identity information is successfully verified, the fact that the training object can successfully log in the automobile dismounting training terminal is indicated.

Optionally, the history training module can be determined according to biological information associated with the automobile disassembly training terminal. After the biological information is input and the biological information is successfully verified, the fact that the training object can successfully log in the automobile disassembly training terminal is indicated. Or binding the biological information with the identity information of the training object, quickly acquiring the identity information of the training object associated with the biological information after the biological information is input, and indicating that the training object can successfully log in the automobile disassembly training terminal after the identity information is successfully verified.

Optionally, in order to improve the security of the login system of the training object and avoid the disclosure of the identity information of the training object, the identity information of the training object can be doubly verified. For example, firstly inputting identity information of a training object of a training terminal assembled and disassembled by a current automobile; after the identity information is successfully verified, the identity information of the training object is verified again according to the biological information, such as fingerprint information, face information, iris information and the like, input by the training object of the automobile disassembly training terminal. After the biological information is successfully verified, the fact that the training object can successfully log in the automobile disassembly training terminal is indicated.

Optionally, the identity information may be identity information of a training object, which is suitable for a training and checking scene of disassembly and assembly of a single automobile; the identity information can also be the identity information of a plurality of practical training objects, and is suitable for a practical training assessment scene of disassembly and assembly of the multi-person automobile.

Optionally, after the training object successfully logs in the automobile disassembly training terminal based on the operation, determining the history training module according to the identity information associated with the automobile disassembly training terminal. The identity information is associated with a plurality of history training modules, each history training module associated with the identity information can be one or even a plurality of history training modules associated with the identity information, the history training modules associated with the identity information are modules adopted when a training object corresponding to the identity information is trained through the automobile virtual disassembly and assembly system, namely the automobile virtual disassembly and assembly system comprises a training mode and an assessment mode, the training module of the automobile virtual disassembly and assembly system can be used for carrying out ordinary automobile disassembly and assembly simulation training, the training modules trained by the history of the training object, namely the history training modules are summarized and counted, and the history training modules are bound with the identity information of the training object, so that the history training modules associated with the identity information can be quickly determined based on the identity information of the training object in the subsequent automobile disassembly and assembly training evaluation mode determining process, and the automobile disassembly and assembly training evaluation mode is determined based on the history training modules.

Optionally, each historical training module is associated with one or even more training tasks. For example, the virtual dismounting system of the new energy automobile mainly comprises: the device comprises a charging system, a power battery system, a driving system and four training modules of an air conditioning system, wherein each training module comprises a specific part dismounting part, and a training object can select tasks corresponding to different training modules to simulate dismounting and training. And each training module comprises a plurality of training tasks, for example, the training tasks corresponding to the training module of the charging system comprise replacement of a charging assembly, replacement of an alternating-current charging port, replacement of a direct-current charging port and the like. The training tasks corresponding to the training module of the power battery system comprise power battery replacement, storage battery replacement, replacement and maintenance of the switch lamp. The training tasks corresponding to the training module of the driving system comprise power assembly replacement, left front half shaft replacement and the like. When the training object performs virtual disassembly and assembly training of the automobile, training tasks corresponding to any training module can be selected for training, and the trained training module and the corresponding training tasks are associated with identity information of the training object.

Step S120, determining a history training result and/or a history training duration corresponding to the history training module.

Optionally, each history training module is associated with a corresponding history training result and/or history training duration, and the corresponding relationship thereof is stored in the database. After the historical training module is determined, the historical training result and/or the historical training duration corresponding to the historical training module can be searched according to the corresponding relation. The historical training results can be training progress of the historical training module, scoring results of the historical training module, error operation matters of the historical training module and the like. The history training time period refers to the time period spent completing the history training module.

Further, the historical training results corresponding to each historical training module can be obtained from the training results of the training tasks in each historical training module. For example, there are 3 history training tasks of a certain history training module, and each history training task has a corresponding training result, and the training results corresponding to each history training task are summed to obtain a history training result corresponding to the history training module.

Further, the history training module is associated with a training task, a history training result and a history training duration corresponding to each training task, and a difficulty coefficient or a difficulty level of each training task. The historical training results can be training progress of training tasks, scoring results of the training tasks, error operation matters of the training tasks and the like. The historical training results corresponding to the historical training modules can be training results corresponding to training tasks associated with the historical training modules, the training tasks are effective tasks which are trained by the practical training objects in a historical mode, and the practical training objects can generate corresponding training results after training of the training tasks. And when the training result is a scoring result, the scoring results corresponding to the effective tasks can be summed, so that the historical training result corresponding to the historical training module is obtained.

Under an application scene, after a training object selects a corresponding training module to train, the automobile virtual dismounting system main interface simulates an automobile dismounting training workshop scene, can realize 360-degree rotation in the scene and a scene scaling function, and helps the training object to more accurately observe and know the automobile structure and the part position while operating according to a standard flow of dismounting of a new energy automobile. During the training process, the operation required by each step of the training object is prompted, for example, the operation mode of a keyboard and a mouse is prompted, and the current mode, for example, an observation mode, a disassembly mode and an installation mode, is displayed. For example, clicking a mouse left button popup menu to enter a detach mode or an install mode; clicking the right button popup menu of the mouse can enter the tool box, the part car, the task details and the submitting task, and can also exit to the mode selection page. The tool box comprises a sleeve synthesis tool or a common tool. The parts cart includes detached parts or new parts. In the training process, the task can be checked, for example, a task checking button is clicked to enter a task detail interface, and vehicle information, task details, operation steps and completion conditions are checked.

Further, under an application scenario, the training process includes the following steps:

firstly, a practical training mode and a task are selected, a practical training mode main interface is displayed, the structure of the whole vehicle can be observed, and the whole vehicle is disassembled and assembled according to an operation prompt.

Secondly, adjusting to a proper visual angle, clicking a mouse left button pop-up menu when the mouse moves to a part from a green frame to a yellow frame, and selecting to dismount; after clicking and dismantling, the disassembly mode view is entered, the green frame is displayed on the part, and the part can be dismantled.

Thirdly, clicking a right button popup menu of the mouse to select and open the tool box; after clicking to open the tool box, selecting a proper sleeve tool synthesis tool or a direct tool according to the operation prompt; after the tool is selected, clicking the part to be disassembled, and disassembling the visible part from the green frame to the yellow frame.

Fourthly, adjusting to a proper visual angle, clicking a mouse left button pop-up menu when the mouse moves to a part from a green frame to a yellow frame, and selecting and installing; after clicking the installation, the installation mode view is entered, the green frame is displayed on the part, and the part installation can be carried out.

Fifth, clicking the right button popup menu of the mouse to select the part car. Clicking the part list interface displayed after the part vehicle, and selecting a proper sleeve tool synthesis tool or a direct selection tool according to the operation prompt. And selecting a part in the part vehicle, clicking the part to be disassembled, and installing the visible part from a green frame to a yellow frame.

Step S130, recommending the first target evaluation module and/or the second target evaluation module based on the historical training result and/or the historical training time.

Optionally, because the training experience of each training object is different, when the training of the training object is finished and the assessment is performed, the corresponding assessment mode is recommended for different training objects to perform the assessment, so that the conventional assessment mode is single, each training object performs the assessment based on the uniform assessment mode, and the assessment result is limited and not representative. Therefore, the application recommends the target evaluation mode after determining the historical training result and/or the historical training duration of each training task. And the target evaluation mode is formed by combining one or even a plurality of evaluation modules. Therefore, after determining the target evaluation mode, the corresponding evaluation module needs to be recommended according to the training experience of the different training objects.

Optionally, the application adopts a recommendation algorithm to determine the evaluation module so as to recommend a proper evaluation module for the training experience of each training object. The assessment module may be recommended based on historical training results. The assessment module may also be recommended based on historical training time periods. The evaluation module may also be recommended based on the historical training results and the historical training time period. Further, a first target evaluation module may be recommended based on the historical training results; or recommending a second target evaluation module based on the historical training time period; alternatively, the first and second goal assessment modules are recommended based on the historical training results and the historical training time period.

Optionally, referring to fig. 2, recommending the first goal module based on the historical training results of each historical training module includes:

step S131, determining a first history training module with a history training result smaller than a preset training result from all the history training modules;

step S132, determining a first preset training module with highest similarity to the first historical training module from a training module database, and determining the first preset training module as the first target evaluation module.

Further, each history training module has a corresponding history training result, and all history training modules which are subjected to history training of the training object can be ranked based on the corresponding history training results, so that a first history training module with the history training result smaller than a preset training result is determined. Because the first historical training module is a training module with a historical training result smaller than the preset training result, the first historical training module is a weak module or an unskilled module relative to the training object. According to the first history training module, the target evaluation module is determined, the unskilled module of the practical training object can be checked, and the situation that the practical training object masters the unskilled module can be evaluated conveniently.

After the first history training module is obtained, the first history training module can be directly used as a first target evaluation module, so that the training object can be checked based on the first target evaluation module, and the mastering condition of the training object on the unskilled module can be conveniently evaluated. Alternatively, after the first historical training module is obtained, a first target assessment module is determined from a training module database. The training module database stores a plurality of training modules, the stored training modules can be modules which are trained by the history of the training object, or can be modules which are not trained by a new training object, and a first preset training module with highest similarity with the first history training module is used as a first target evaluation module, so that the determined first target evaluation module is more representative, the training object carries out assessment based on the first target evaluation module, and the mastering condition of the unskilled module by the training object can be conveniently evaluated.

Further, the first history training module includes at least two different types of first history training tasks, and each training module stored in the training module database has a corresponding preset training task, that is, the training module database stores the corresponding preset training task of each training module. The determining, from the training module database, a first preset training module having the highest similarity with the first historical training module includes: and determining a preset training task with the highest similarity with each first historical training task, namely a first preset training task, from a training module database, thereby obtaining a plurality of first preset training tasks. And combining each first preset training task to obtain a first preset training module, namely, the first preset training module is obtained by combining a plurality of first preset training tasks.

Optionally, referring to fig. 3, recommending the second target evaluation result based on the historical training time period of each historical training module includes:

step S231, determining a second history training module with a history training time longer than a preset time from all the history training modules;

step S232, determining a second preset training module with highest similarity to the second historical training module from the training module database, and determining the second preset training module as the second target evaluation module.

Further, each history training module has a corresponding history training duration, and all history training modules which are subjected to history training of the training object can be ordered based on the corresponding history training durations, so that a second history training module with the history training duration longer than the preset duration is determined. Because the second historical training module is a training module with a historical training time longer than a preset time, the second historical training module is a weak module or an unskilled module relative to the training object. And determining a target evaluation module according to the second history training module, and checking an unskilled module of the practical training object, so that the situation that the practical training object grasps the unskilled module can be evaluated conveniently.

After the second history training module is obtained, the second history training module can be directly used as a second target evaluation module, so that the training object can be checked based on the second target evaluation module, and the mastering condition of the training object on the unskilled module can be conveniently evaluated. Alternatively, after the second historical training module is obtained, a second target evaluation module is determined from the training module database. The training module database stores a plurality of training modules, the stored training modules can be modules which are trained by the history of the training object, or can be modules which are not trained by a new training object, and a second preset training module with highest similarity with a second history training module is used as a second target evaluation module, so that the determined second target evaluation module is more representative, the training object carries out assessment based on the second target evaluation module, and the mastering condition of the unskilled module by the training object can be conveniently evaluated.

Further, the second history training module includes at least two second history training tasks of different types, and each training module stored in the training module database has a corresponding preset training task, that is, the training module database stores the corresponding preset training task of each training module. The determining, from the training module database, a second preset training module having the highest similarity with the second historical training module includes: and determining a preset training task with the highest similarity with each second historical training task, namely a second preset training task, from the training module database, thereby obtaining a plurality of second preset training tasks. And combining each second preset training task to obtain a second preset training module, namely, the second preset training module is obtained by combining a plurality of second preset training tasks.

Optionally, referring to fig. 4, recommending the first target evaluation module and the second target evaluation module based on the historical training result and the historical training time period of each of the historical training modules includes:

step S331, determining a third history training module with a history training result smaller than a preset training result from all the history training modules, determining a third preset training module with highest similarity with the third history training module from a training module database, and determining the third preset training module as the first target evaluation module;

step S332, when the number of the first target evaluation modules is smaller than a first preset value, the first target evaluation module is used as the second target evaluation module, and the first preset value is an integer;

step S333, when the number of the first target evaluation modules is greater than or equal to the first preset value, determining a fourth history training module with a history training time longer than a preset time from all the first target evaluation modules, determining a fourth preset training module with highest similarity with the fourth history training module from a training module database, and determining the fourth preset training module as the second target evaluation module.

The third preset training module with the highest similarity to the third historical training module or the fourth preset training module with the highest similarity to the fourth historical training module is similar to the first preset training module with the highest similarity to the first historical training module or the second preset training module with the highest similarity to the second historical training module, and will not be described again here.

The first preset value is an integer and may be set according to practical situations, for example, the first preset value may be set to 2. And when the number of the first target evaluation modules is smaller than 2, directly taking the first target evaluation modules as second target evaluation modules. When the number of the first target evaluation modules is greater than or equal to 2, a second target evaluation module is determined from the first target evaluation modules. The method specifically comprises the steps of determining a fourth historical training module which is longer than a preset time length from all first target evaluation modules, determining a fourth preset training module which is the highest in similarity with the fourth historical training module from a training module database, and determining the fourth preset training module as the second target evaluation module.

According to the method, first target evaluation modules are determined according to the historical training results of the historical training modules, and second target evaluation modules are determined from a training module database based on the historical training time length of each first target evaluation module, so that more accurate, specific and targeted evaluation modules are determined.

Optionally, referring to fig. 5, recommending the first target evaluation module and the second target evaluation module based on the historical training result and the historical training time period of each of the historical training modules includes:

step S431, determining a fifth history training module with a history training result smaller than a preset training result from all the history training modules, and determining the fifth history training module as the first target evaluation module;

step S432, when the number of the first target evaluation modules is smaller than a second preset value, using the first target evaluation module as the second target evaluation module, where the second preset value is an integer;

and S433, when the number of the first target evaluation modules is greater than or equal to the second preset value, determining a sixth history training module with a history training time longer than a preset time length from all the first target evaluation modules, and determining the sixth history training module as the second target evaluation module.

According to the method, first target evaluation modules are determined according to the historical training results of the historical training modules, second target evaluation modules are determined based on the number of each first target evaluation module, and then more accurate, specific and targeted evaluation modules are determined.

Step S140, determining a target evaluation mode according to the first target evaluation module and/or the second target evaluation module.

Optionally, the target evaluation mode is generated or determined by the first target evaluation module and/or the second target evaluation module. The target evaluation modes corresponding to the training objects are different, and the corresponding target evaluation modes can be recommended for the training objects in a targeted manner. A target evaluation mode can be generated according to the first target evaluation module; or generating a target evaluation mode according to the second target evaluation module; or generating a target evaluation mode according to the first target evaluation module and the second target evaluation module.

Further, according to the first target evaluation module and/or the second target evaluation module, determining a target evaluation mode includes: determining a preset evaluation mode corresponding to the first target evaluation module and/or the second target evaluation module; when the preset evaluation modes corresponding to the first target evaluation module and the second target evaluation module are the same, determining the preset evaluation mode as the target evaluation mode; when the preset evaluation modes corresponding to the first target evaluation module and the second target evaluation module are different, determining the historical recommendation times of the preset evaluation modes corresponding to the first target evaluation module and the preset evaluation modes corresponding to the second target evaluation module, and determining the preset evaluation mode with the highest historical recommendation times as the target evaluation mode.

Each evaluation module is pre-associated with a corresponding preset evaluation mode. The preset evaluation modes determined by the first target evaluation module and the second target evaluation module may be the same or different. When the preset evaluation mode corresponding to the first target evaluation module is the same as the preset evaluation mode corresponding to the second target evaluation module, the preset evaluation mode is indicated to exist, and then the preset evaluation mode can be directly determined as the target evaluation mode. When the preset evaluation mode corresponding to the first target evaluation module is different from the preset evaluation mode corresponding to the second target evaluation module, the preset evaluation mode indicates that two or more different preset evaluation modes exist, and one of the preset evaluation modes needs to be selected as the target evaluation mode. The recommended times of each preset evaluation mode are different, the historical recommended times of the preset evaluation modes corresponding to the first target evaluation module can be obtained, the historical recommended times of the preset evaluation modes corresponding to the second target evaluation module are obtained, the preset evaluation mode with the highest historical recommended times is selected from the historical recommended times, and the preset evaluation mode with the highest historical recommended times is determined to be the target evaluation mode. Thereby making the determined target evaluation mode more targeted.

And S150, recommending the target evaluation mode to the automobile disassembly training terminal.

Optionally, because the automobile disassembly training terminal is in communication connection with the automobile disassembly evaluation terminal, the automobile disassembly evaluation terminal recommends the target evaluation mode to the automobile disassembly training terminal after determining the target evaluation mode.

Optionally, when there are a plurality of real standard terminals of car dismouting, still be connected with data forwarding equipment between real standard terminal of car dismouting and the car dismouting aassessment terminal, send the real standard terminal corresponding target aassessment mode of every car dismouting to each real standard terminal of car dismouting through this data forwarding equipment, reduce the data processing pressure of car dismouting aassessment terminal.

In an embodiment, after determining the target evaluation mode according to the first target evaluation module and/or the second target evaluation module, the method further includes determining a virtual vehicle dismounting tool associated with the target evaluation mode, and sending the virtual vehicle dismounting tool and the target evaluation mode to a vehicle dismounting training terminal. The target evaluation mode comprises at least one module to be disassembled and assembled, and the module to be disassembled and assembled comprises at least one task to be disassembled and assembled. The module to be disassembled may be the target evaluation module for determining the target evaluation mode, and the task to be disassembled may be a training task corresponding to the target evaluation module. The virtual automobile disassembly tools required by each task to be disassembled are different, and the virtual automobile disassembly tools required by each task to be disassembled associated with the target evaluation mode can be determined. And sending virtual automobile disassembly tools required by each task to be disassembled to the automobile disassembly training terminal.

Optionally, after receiving the virtual vehicle disassembly tools and the target evaluation modes required by each task to be disassembled, the vehicle disassembly training terminal performs the assessment of each task to be disassembled based on the virtual vehicle disassembly tools required by each task to be disassembled.

In an embodiment, after the automobile disassembly and assembly evaluation terminal sends the virtual automobile disassembly and assembly tool and the target evaluation mode to the automobile disassembly and assembly training terminal, the automobile disassembly and assembly training terminal receives the target evaluation mode sent by the automobile disassembly and assembly evaluation terminal, obtains at least one task to be disassembled and assembled corresponding to the target evaluation mode, renders and displays a rendering interface corresponding to the task to be disassembled and assembled, performs automobile disassembly and assembly assessment of the task to be disassembled and assembled based on the rendering interface, obtains an assessment result and an assessment duration corresponding to the task to be disassembled and assembled, and sends the assessment result and the assessment duration of each task to be disassembled and assembled of the target evaluation mode to the automobile disassembly and assembly evaluation terminal. The automobile disassembly and assembly evaluation terminal receives an assessment result and an assessment duration of a task to be disassembled and assembled, which correspond to the automobile disassembly and assembly training terminal based on a target evaluation mode; the automobile disassembly and assembly evaluation terminal determines an evaluation result corresponding to the module to be disassembled and assembled according to the evaluation result and the evaluation time; and the automobile disassembly and assembly evaluation terminal determines an automobile disassembly and assembly evaluation result of the automobile disassembly and assembly training terminal according to the evaluation result and the difficulty coefficient of the module to be disassembled and assembled.

For example, each task to be disassembled has a corresponding assessment result and assessment time, and the assessment result and the assessment time corresponding to each task to be disassembled are added, so that an assessment result corresponding to each module to be disassembled is obtained. And each module to be disassembled and assembled has a corresponding difficulty coefficient, the weight values corresponding to the difficulty coefficients are different, and weighting is carried out according to the difficulty coefficient corresponding to each module to be disassembled and assembled and the evaluation result corresponding to each module to be disassembled and assembled, so that the automobile disassembly and assembly evaluation result of each practical training object is obtained.

In other embodiments, training tasks with error rate ranking greater than a preset ranking in the automobile disassembly and assembly system can be combined to obtain a target evaluation module, and then a target evaluation mode is determined based on the target evaluation module, so that the target evaluation mode is recommended to an automobile disassembly and assembly training terminal.

Further, the error rate is obtained by taking an average value after counting the error rates of the historical training tasks of different training objects. And ranking the error rate of each historical training task to obtain training tasks with the error rate ranking greater than a preset ranking. Because the training tasks with the error rate ranking being larger than the preset ranking are tasks easy to make mistakes, the training tasks easy to make mistakes are generated into the target evaluation module, and the mastering condition of training objects on the training tasks easy to make mistakes is convenient to master. For example, assuming that there are a training object a and a training object B, the training object a and the training object B perform two identical training tasks respectively, and assuming that the training object a performs task 1 error and task 2 error, and the training object B performs task 1 error and task 2 error, the error rate ranking of the training tasks is from high to low: task 1, task 2. Task 1 may be combined to obtain the target evaluation module.

Further, the error rate may also be determined by counting the cumulative number of errors per historical training task for a single training object. For example, assuming that the training object a performs 3 training tasks, and the number of accumulated errors of the training task 1 is 2, the number of accumulated errors of the training task 2 is 3, and the number of accumulated errors of the training task 3 is 2, the training tasks 2 may be combined to obtain the target evaluation module.

In other embodiments, the training task with the largest training frequency in the automobile disassembly and assembly system can be combined to obtain the target evaluation module.

In other embodiments, the part of training tasks in the target evaluation module may be training task components with the error rate ranking greater than a preset ranking according to the above-mentioned automobile disassembly and assembly system, and the part of training tasks may also be training task components determined based on the historical training results and/or the historical training duration, so that the determined target evaluation module is more representative.

According to the technical scheme, compared with the limitation of single evaluation mode of the automobile virtual dismounting system in the related art, the method and the device can recommend the matched target evaluation mode for the practical training experience of different practical training objects, and recommend the target evaluation mode to the practical training objects, so that the practical training objects can carry out automobile dismounting practical training evaluation based on the target evaluation mode, and the practical training evaluation effect is improved. In addition, the application adopts the virtual terminal to carry out the practical training teaching and evaluation of the disassembly and assembly of the automobile. The method has good interactivity and deep immersion, can greatly increase actual combat experience of students, reduces abrasion to automobile parts, reduces training cost and assessment cost, and improves practical training safety. Solves the problems of high risk, easy abrasion and loss of parts and the like of the traditional practical training.

The embodiments of the present invention provide embodiments of a method for determining an evaluation mode for an automobile disassembly training, and it should be noted that although a logic sequence is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown or described herein.

As shown in fig. 6, fig. 6 is a schematic structural diagram of a hardware operating environment of an automobile disassembly training evaluation mode determining device according to an embodiment of the present invention. The real standard evaluation mode determination device of car dismouting can include: a processor 1001, such as a CPU, memory 1005, user interface 1003, network interface 1004, communication bus 1002. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a display, an input unit such as a keyboard, and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface. The memory 1005 may be a high-speed RAM memory or a stable memory such as a disk memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.

It will be appreciated by those skilled in the art that the configuration of the vehicle disassembly training evaluation mode determination device illustrated in fig. 6 is not limiting of the vehicle disassembly training evaluation mode determination device and may include more or fewer components than illustrated, or may be combined with certain components, or may be arranged with different components.

As shown in fig. 6, the memory 1005, which is a storage medium, may include an operating system, a network communication module, a user interface module, and an automobile disassembly training evaluation mode determination program. The operating system is a program for managing and controlling hardware and software resources of the automobile disassembly training evaluation mode determining device, and the automobile disassembly training evaluation mode determining program and other software or program runs.

In the car disassembly training evaluation mode determining device shown in fig. 6, the user interface 1003 is mainly used for connecting a terminal and performing data communication with the terminal; the network interface 1004 is mainly used for a background server and is in data communication with the background server; the processor 1001 may be configured to invoke the car disassembly training assessment mode determination program stored in the memory 1005.

In this embodiment, the device for determining the training evaluation mode of the disassembly and assembly of the automobile includes: memory 1005, processor 1001 and store on the memory and can be on the real standard evaluation mode determination procedure of car dismouting of running on the processor, wherein:

when the processor 1001 calls the car disassembly training evaluation mode determination program stored in the memory 1005, the following operations are performed:

When the processor 1001 calls the car disassembly training evaluation mode determination program stored in the memory 1005, the following operations are also performed:

Based on the same inventive concept, the embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores an automobile disassembly and assembly practical training evaluation mode determining program, and the automobile disassembly and assembly practical training evaluation mode determining program realizes each step of the automobile disassembly and assembly practical training evaluation mode determining method when being executed by a processor, and can achieve the same technical effect, and in order to avoid repetition, the description is omitted.

Because the storage medium provided by the embodiment of the present application is a storage medium used for implementing the method of the embodiment of the present application, based on the method introduced by the embodiment of the present application, a person skilled in the art can understand the specific structure and the modification of the storage medium, and therefore, the description thereof is omitted herein. All storage media adopted by the method of the embodiment of the application belong to the scope of protection of the application.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.

The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.

From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as described above, comprising instructions for causing an automobile disassembly training evaluation mode determining apparatus (which may be a mobile phone, a computer, a server, a television, or a network device, etc.) to perform the method according to the embodiments of the present invention.

The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.

Claims

1. The method for determining the practical training evaluation mode of the automobile disassembly and assembly is characterized by being applied to an automobile disassembly and assembly evaluation terminal, wherein the automobile disassembly and assembly evaluation terminal is connected with the practical training terminal of the automobile disassembly and assembly, and the method for determining the practical training evaluation mode of the automobile disassembly and assembly comprises the following steps:

2. The method of determining an automotive disassembly training assessment model according to claim 1, wherein recommending the first objective assessment module or the second objective assessment module based on the historical training results or the historical training time period of each of the historical training modules comprises:

3. The method for determining the training evaluation mode of the disassembly and assembly of the automobile according to claim 2, wherein the first historical training module comprises at least two different types of first historical training tasks, the second historical training module comprises at least two different types of second historical training tasks, and the determining the first preset training module with the highest similarity with the first historical training module from the training module database comprises:

4. The method of determining an automotive disassembly training assessment model according to claim 1, wherein recommending the first target assessment module and the second target assessment module based on the historical training results and the historical training time period of each of the historical training modules comprises:

5. The method of determining an automotive disassembly training assessment model according to claim 1, wherein recommending the first target assessment module and the second target assessment module based on the historical training results and the historical training time period of each of the historical training modules comprises:

6. The method for determining an evaluation mode of practical training for disassembly and assembly of a vehicle according to any one of claims 1 to 5, wherein the step of determining the evaluation mode of the object according to the first object evaluation module and/or the second object evaluation module comprises:

7. The method for determining an evaluation mode of practical training for disassembly and assembly of an automobile according to claim 1, wherein the target evaluation mode includes at least one module to be disassembled and assembled, the module to be disassembled and assembled includes at least one task to be disassembled and assembled, and the step of determining the target evaluation mode according to the first target evaluation module and/or the second target evaluation module further includes:

8. The method for determining the training evaluation mode for the disassembly and assembly of the automobile according to claim 7, wherein after the step of transmitting the virtual disassembly and assembly tool and the target evaluation mode to the training terminal for the disassembly and assembly of the automobile, further comprises:

9. The utility model provides a real standard evaluation mode determining means of car dismouting, its characterized in that, real standard evaluation mode determining means of car dismouting includes: memory, processor and store on the memory and the real standard evaluation mode determination procedure of car dismouting of operation on the processor, the real standard evaluation mode determination procedure of car dismouting is executed by the processor and realizes the step of the real standard evaluation mode determination method of car dismouting of any one of claims 1-8.

10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores an automobile disassembly training evaluation mode determination program, which when executed by a processor, implements the steps of the automobile disassembly training evaluation mode determination method according to any one of claims 1 to 8.