Teaching evaluation simulation training system based on simulation deduction

Abstract

The invention discloses a teaching evaluation simulation training system based on simulation deduction, relates to the field of aircraft maintenance, and solves the problem that an existing teaching evaluation simulation training system is poor in training effect. The step evaluation module is used for carrying out sequence monitoring on operation steps of a target student, obtaining sequence correctness corresponding to each to-be-trained knowledge point according to a monitoring result, obtaining operation sequence evaluation data and sending the operation sequence evaluation data to the step evaluation module, and the step evaluation module is used for carrying out step evaluation on the operation sequence of the target student according to the sequence correctness corresponding to each to-be-trained knowledge point. The operation evaluation module is used for carrying out component installation accuracy evaluation on the target student and obtaining installation accuracy evaluation data according to an evaluation result, and the evaluation feedback module is used for carrying out operation sequence scoring and installation accuracy scoring on the target student to obtain teaching evaluation data, and the accuracy of the evaluation result can be improved.

Description

Technical Field

[0001] The invention belongs to the field of aircraft maintenance, relates to simulation deduction technology, and specifically is a teaching and evaluation simulation training system based on simulation deduction. Background Art

[0002] The existing teaching and assessment simulation training system has the following specific defects when performing virtual maintenance on aircraft: The existing teaching assessment simulation training system cannot automatically screen the knowledge points to be trained in the students' historical assessment records, and cannot repeat the assessment training of the corresponding knowledge points to be trained and the new teaching knowledge points, which leads to the lack of comprehensive assessment in the assessment simulation training process; The existing teaching assessment simulation training system is unable to analyze the sequence correctness of the specific operation steps during the student assessment process, and is unable to comprehensively analyze the analysis results with the assessment results of component installation accuracy, resulting in a lack of accuracy in the assessment results.

[0003] To this end, we propose a teaching and assessment simulation training system based on simulation deduction. Summary of the invention

[0004] In view of the deficiencies in the prior art, the purpose of the present invention is to provide a teaching assessment simulation training system based on simulation deduction, and the present invention aims to improve the comprehensiveness of the content of the teaching assessment simulation training system and the accuracy of the assessment results.

[0005] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: a teaching assessment simulation training system based on simulation deduction, comprising: Data collection module: used to obtain teaching evaluation data, select knowledge points to be trained from the knowledge points being taught by analyzing the teaching evaluation data, and obtain historical knowledge point screening data; Step evaluation module: used to evaluate the teaching of knowledge points to be trained for target students based on the screening data of historical knowledge points, obtain the correctness of the sequence corresponding to each knowledge point to be trained based on the evaluation results, and obtain the operation sequence evaluation data; Operation evaluation module: used to evaluate the component installation accuracy of target trainees based on the operation sequence evaluation data, and obtain installation accuracy evaluation data based on the evaluation results; Evaluation feedback module: used to score the target students' operation sequence according to the operation sequence evaluation data, and to score the target students' installation accuracy according to the installation accuracy evaluation data, so as to obtain teaching evaluation data.

[0006] Furthermore, historical knowledge points are screened and data is obtained, as follows: Select a target student from the system students served by the teaching evaluation simulation training system, and obtain the teaching evaluation data corresponding to the target student; Acquire the teaching knowledge points involved in the history assessment according to the teaching assessment data to obtain a plurality of history teaching knowledge points, and select a sample teaching knowledge point from the plurality of history teaching knowledge points obtained; Comprehensively analyze the multiple teaching evaluation scores corresponding to the sample teaching knowledge points, and obtain the evaluation score analysis coefficients corresponding to the sample teaching knowledge points according to the analysis results; Obtain the assessment score analysis coefficient corresponding to each system student, calculate the average of the obtained assessment score analysis coefficients to obtain a first assessment verification index value, calculate the standard deviation of the obtained assessment score analysis coefficients to obtain a second assessment verification index value, and calculate the first assessment verification index value and the second assessment verification index value to obtain a third assessment verification index value; The third evaluation verification index value is calculated, and the specific formula is as follows: ; Among them, Kyx3 is the third assessment verification index value, Kyx2 is the second assessment verification index value, and Kyx1 is the first assessment verification index value; The value 0 is used as the left endpoint of the interval, and the third evaluation verification index value is used as the right endpoint of the interval to obtain the knowledge point to-be-trained interval corresponding to the sample teaching knowledge point. If the evaluation score analysis coefficient is in the knowledge point to-be-trained interval, the corresponding sample teaching knowledge point is marked as a knowledge point to-be-trained. If the evaluation score analysis coefficient is not in the knowledge point to-be-trained interval, the corresponding sample teaching knowledge point is marked as a training completed knowledge point. Repeat the process of evaluating and analyzing the sample teaching knowledge points, obtain the evaluation score analysis coefficient corresponding to each teaching knowledge point, and screen the training knowledge points according to the evaluation score analysis coefficient to obtain the historical knowledge point screening data.

[0007] Furthermore, the evaluation score analysis coefficients corresponding to the sample teaching knowledge points are obtained, as follows: According to the teaching evaluation data, multiple teaching evaluations involving sample teaching knowledge points are obtained, and the obtained multiple teaching evaluations are named K1 sample teaching evaluation to Ka sample teaching evaluation in chronological order; In the K1 sample teaching assessment, the assessment questions involving the sample teaching knowledge points are scored, and the scores of the multiple assessment questions are averaged to obtain the K1 teaching assessment score; The average score of the students in the K1 sample teaching evaluation of the evaluation questions corresponding to the sample teaching knowledge points is obtained to obtain the K1 teaching evaluation average score, and the ratio of the K1 teaching evaluation score to the K1 teaching evaluation average score is calculated to obtain the K1 teaching evaluation average score ratio; Calculate the average total score of multiple assessment questions corresponding to the sample teaching knowledge points to obtain the total score of K1 teaching assessment, calculate the ratio of the K1 teaching assessment score to the K1 teaching assessment total score, and obtain the K1 teaching assessment score ratio; Obtain the ratio of the average score of K2 teaching assessment to the average score of Ka teaching assessment and the ratio of the score of K2 teaching assessment to the score of Ka teaching assessment respectively; The evaluation score analysis coefficient corresponding to the sample teaching knowledge points is obtained by calculating the ratio of the K1 teaching evaluation average score to the Ka teaching evaluation average score and the ratio of the K1 teaching evaluation score to the Ka teaching evaluation score; The evaluation score analysis coefficient corresponding to the sample teaching knowledge points is calculated. The specific formula is as follows: ; Among them, Cpd is the evaluation score analysis coefficient corresponding to the sample teaching knowledge point, Dfki is the Ki teaching evaluation score ratio, Jfki is the Ki teaching evaluation average score ratio, and a is the quantitative value corresponding to the sample teaching evaluation.

[0008] Furthermore, the operation sequence evaluation data is obtained as follows: Obtain historical knowledge point screening data, and obtain multiple knowledge points to be trained based on the historical knowledge point screening data; Mark the interval between the current assessment and the last assessment of the target student as a characteristic assessment interval, and add the teaching knowledge points learned by the target student in the characteristic assessment interval as knowledge points to be trained; Select a characteristic knowledge point from the acquired multiple knowledge points to be trained, and mark the maintenance steps involved in the characteristic knowledge point as the first priority step to the bth priority step in order of operation priority; Acquire a monitoring image of a target student completing a characteristic knowledge point assessment in a characteristic scenario model, acquire the aircraft maintenance steps performed by the target student in the characteristic scenario model according to the monitoring image, and name the acquired multiple aircraft maintenance steps as the first practical operation step to the cth practical operation step in chronological order; Conduct an operation sequence analysis on the evaluation process of target students completing characteristic knowledge points, and obtain the correctness of the step sequence corresponding to the characteristic knowledge points based on the analysis results; The process of obtaining the correctness of the step sequence corresponding to the characteristic knowledge points is repeated, and the correctness of the step sequence corresponding to each knowledge point to be trained is obtained respectively to obtain the operation sequence evaluation data.

[0009] Furthermore, the correctness of the step sequence corresponding to the characteristic knowledge point is obtained, as follows: The first practical operation step to the cth practical operation step are recorded as a practical operation step sequence: Sactual=[s1,s2,…,sc]; Wherein, s1 to sc are the first practical operation step to the cth practical operation step respectively; The first priority step to the bth priority step are recorded as a priority step sequence: Spriority=[p1,p2,……,pb]; Among them, p1 to pb are the first priority step to the bth priority step respectively; In the priority step sequence, the step sequence score corresponding to each priority step in the priority step sequence and the total step evaluation score corresponding to the characteristic knowledge point are obtained according to the evaluation rules corresponding to the characteristic knowledge point, and the ratio of each step sequence score to the total step evaluation score of the characteristic knowledge point is calculated to obtain the step weight corresponding to each priority step; For each actual operation step sj, get its position pos in the priority step sequence Spriority std (sj); If sj is at position pos in the actual operation step sequence Sactual actual (sj), then the step offset corresponding to sj is ; According to the penalty value Penalty(△j) corresponding to the actual operation step sj is calculated; The details are as follows: ; Among them, a1 and a2 are the set offset weight coefficients, wj is the step weight corresponding to the actual operation step sj1, and a1 involved here is set to 0.2 and a2 is set to 0.5; If the priority step does not appear in the actual operation steps, the deduction value is the sum of the step weights corresponding to the missing priority steps, and the priority step missing deduction value Yqz is obtained; The correctness of the step sequence corresponding to the feature knowledge point is obtained by calculating the penalty value of each actual operation step offset, the penalty value of the priority step missing, and the step weight corresponding to each priority step; The correctness of the step sequence corresponding to the characteristic knowledge points is calculated. The specific formula is as follows: ; Among them, Szd is the correctness of the step sequence corresponding to the feature knowledge point, Penalty(△j) is the penalty value of the jth actual operation step offset, wi is the step weight corresponding to the ith priority step, Yqz is the missing penalty for the priority step, b is the quantity value corresponding to the priority step, and c is the quantity value corresponding to the actual operation step.

[0010] Furthermore, the installation accuracy evaluation data is obtained, as follows: Acquire operation sequence evaluation data, acquire multiple knowledge points to be trained according to the operation sequence evaluation data, and select a knowledge point Fi to be trained from the acquired multiple knowledge points to be trained; Use 3D modeling technology to model the aircraft maintenance scene required for the assessment of the knowledge points to be trained, and obtain a feature scene model; Acquire the fuselage components involved in the knowledge point to be trained Fi, and select a characteristic fuselage component from the acquired fuselage components; Create a component position space coordinate system, and obtain the actual position coordinates corresponding to the characteristic fuselage component according to the component position space coordinate system; Deviation monitoring is performed on the component installation positions corresponding to the knowledge points Fi to be trained, and the component installation deviation values ​​corresponding to the knowledge points Fi to be trained are obtained according to the monitoring results to obtain the installation accuracy evaluation data.

[0011] Furthermore, the actual coordinates of the position corresponding to the characteristic fuselage component are as follows: In the feature scene model, a spatial point is randomly selected as the coordinate origin, and a straight line parallel to the ground is drawn through the coordinate origin to obtain the first feature straight line. The plane where the first feature straight line is located is marked as the first feature plane. In the first feature plane, a straight line perpendicular to the first feature straight line is drawn through the coordinate origin to obtain the second feature straight line. A straight line perpendicular to the first feature plane is drawn through the coordinate origin to obtain the third feature straight line. The first feature straight line is marked as the coordinate x-axis, the second feature straight line is marked as the coordinate y-axis, and the third feature straight line is marked as the coordinate z-axis to obtain the component position space coordinate system. In the component position space coordinate system, multiple feature position points are selected from the feature fuselage component, and the selected feature position points are named as the first position feature point to the mth position feature point, and the three-dimensional coordinates corresponding to the first position feature point to the mth position feature point are obtained respectively to obtain the actual coordinates of the first position to the mth position.

[0012] Furthermore, the component installation deviation value corresponding to the knowledge point to be trained in Fi is obtained, as follows: In the feature scene model, the reference position coordinates corresponding to the first position feature point to the mth position feature point are respectively acquired to obtain the first position reference coordinates to the mth position reference coordinates; The installation position deviation corresponding to the characteristic fuselage component is obtained by calculating the actual coordinates of the first position to the actual coordinates of the mth position and the reference coordinates of the first position to the reference coordinates of the mth position; The installation position deviation corresponding to the characteristic fuselage component is calculated, and the specific formula is as follows: ; Wherein, Wpc is the installation position deviation corresponding to the characteristic fuselage component, (Xsi, Ysi, Zsi) is the actual coordinate of the i-th position, (Xji, Yji, Zji) is the reference coordinate of the i-th position, and m is the quantity value corresponding to the characteristic position point; The installation position deviation corresponding to each fuselage component is obtained respectively to obtain multiple installation position deviations, and the average of the obtained multiple installation position deviations is calculated to obtain the installation deviation value of the Fi component; Obtain the component installation benchmark deviation corresponding to the Fi knowledge point to be trained, obtain the Fi component installation benchmark deviation, calculate the Fi component installation deviation value and the Fi component installation benchmark deviation to obtain the component installation deviation degree corresponding to each knowledge point to be trained, and obtain the installation accuracy evaluation data; Calculate the component installation deviation, the specific formula is as follows: ; Among them, Zpc is the component installation deviation, Fapi is the Fi component installation deviation value, and Fjpi is the Fi component installation benchmark deviation.

[0013] Furthermore, the teaching evaluation data is obtained as follows: Acquire operation sequence assessment data, and select Si knowledge points to be trained from the acquired multiple knowledge points to be trained; Obtain the correctness of the step sequence corresponding to the Si knowledge point to be trained, obtain the total score of the step assessment corresponding to the Si knowledge point to be trained, calculate the product of the correctness of the step sequence and the total score of the step assessment, and obtain the operation sequence score corresponding to the Si knowledge point to be trained; Obtain installation accuracy evaluation data, and score the installation accuracy of the Si knowledge points to be trained according to the installation accuracy evaluation data; The operation sequence score and the installation accuracy score are summed to obtain the teaching evaluation score corresponding to the Si knowledge points to be trained; The teaching evaluation scores corresponding to each knowledge point to be trained are obtained respectively to obtain the teaching evaluation data.

[0014] Furthermore, the installation accuracy score of the Si knowledge points to be trained is as follows: Obtain installation accuracy evaluation data, and obtain component installation deviation corresponding to Si knowledge point to be trained according to the installation accuracy evaluation data; If the component installation deviation is greater than 1, the installation accuracy score corresponding to the Si knowledge point to be trained is 0; If the component installation deviation is less than 1, the total score of the operation evaluation corresponding to the Si knowledge point to be trained is obtained, and the component installation deviation and the total score of the operation evaluation are calculated to obtain the installation accuracy score corresponding to the Si knowledge point to be trained; Calculate the installation accuracy score corresponding to the Si knowledge point to be trained. The specific formula is as follows: ; Among them, Ckz is the installation accuracy score corresponding to the Si knowledge point to be trained, Czf is the total score of the operation evaluation corresponding to the Si knowledge point to be trained, and Zpc is the component installation deviation corresponding to the Si knowledge point to be trained.

[0015] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: 1. The present invention automatically screens the knowledge points to be trained in the students' historical assessment records, and repeats the assessment training of the corresponding knowledge points to be trained and the new knowledge points, which can effectively improve the comprehensiveness of the assessment simulation training system.

[0016] 2. The present invention can analyze the sequence correctness of specific operation steps in the student assessment process, and comprehensively analyze the analysis results with the assessment results of component installation accuracy, thereby improving the accuracy of the assessment results. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0018] Figure 1 is the overall system block diagram of the present invention; Figure 2 It is a schematic diagram of the sequence of steps in the present invention; Figure 3 It is a schematic diagram of the characteristic scene model in the present invention. DETAILED DESCRIPTION

[0019] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] Example 1: Please refer to Figure 1The present invention provides a technical solution: a teaching assessment simulation training system based on simulation deduction, comprising a data acquisition module, a step assessment module, an operation assessment module, an assessment feedback module and a server, wherein the data acquisition module, the step assessment module, the operation assessment module and the assessment feedback module are respectively connected to the server, and the server controls the data acquisition module, the step assessment module, the operation assessment module and the assessment feedback module respectively; The data collection module obtains the teaching evaluation data of the target students, selects the knowledge points to be trained from the knowledge points taught by analyzing the teaching evaluation data, and obtains the historical knowledge point screening data; The details are as follows: a target student is selected from the system students served by the teaching evaluation simulation training system, and the teaching evaluation data corresponding to the target student is obtained; It should be noted here that: in this application, the system students involved here can all complete the fault repair involved in the teaching knowledge points.

[0021] Acquire the teaching knowledge points involved in the history assessment according to the teaching assessment data to obtain a plurality of history teaching knowledge points, and select a sample teaching knowledge point from the plurality of history teaching knowledge points obtained; It should be noted here that: in this application, the historical teaching knowledge points involved here are specifically knowledge points related to aircraft maintenance, and the historical teaching knowledge points involved here include but are not limited to fuselage structure maintenance, aircraft power plant maintenance, and aircraft electrical system maintenance; Comprehensively analyze the multiple teaching evaluation scores corresponding to the sample teaching knowledge points, and obtain the evaluation score analysis coefficients corresponding to the sample teaching knowledge points according to the analysis results; Specifically, multiple teaching evaluations involving sample teaching knowledge points are obtained according to the teaching evaluation data, and the obtained multiple teaching evaluations are named K1 sample teaching evaluation to Ka sample teaching evaluation in chronological order; It should be noted here that a is the quantitative value corresponding to the sample teaching evaluation, and a is an integer greater than 1.

[0022] In the K1 sample teaching assessment, the assessment questions involving the sample teaching knowledge points are scored, and the scores of the multiple assessment questions are averaged to obtain the K1 teaching assessment score; The average score of the students in the K1 sample teaching evaluation of the evaluation questions corresponding to the sample teaching knowledge points is obtained to obtain the K1 teaching evaluation average score, and the ratio of the K1 teaching evaluation score to the K1 teaching evaluation average score is calculated to obtain the K1 teaching evaluation average score ratio; Calculate the average total score of multiple assessment questions corresponding to the sample teaching knowledge points to obtain the total score of K1 teaching assessment, calculate the ratio of the K1 teaching assessment score to the K1 teaching assessment total score, and obtain the K1 teaching assessment score ratio; Obtain the ratio of the average score of K2 teaching assessment to the average score of Ka teaching assessment and the ratio of the score of K2 teaching assessment to the score of Ka teaching assessment respectively; The evaluation score analysis coefficient corresponding to the sample teaching knowledge points is obtained by calculating the ratio of the K1 teaching evaluation average score to the Ka teaching evaluation average score and the ratio of the K1 teaching evaluation score to the Ka teaching evaluation score; The evaluation score analysis coefficient corresponding to the sample teaching knowledge points is calculated. The specific formula is as follows: ; Among them, Cpd is the evaluation score analysis coefficient corresponding to the sample teaching knowledge point, Dfki is the Ki teaching evaluation score ratio, Jfki is the Ki teaching evaluation average score ratio, and a is the quantitative value corresponding to the sample teaching evaluation; It should be noted here that: in the present application, the Ki teaching assessment score ratio involved here can be any teaching assessment score ratio from K1 teaching assessment score ratio to Ka teaching assessment score ratio, and the Ki teaching assessment average score ratio involved here can be any teaching assessment average score ratio from K1 teaching assessment average score ratio to Ka teaching assessment average score ratio.

[0023] In the specific implementation, there are the following experimental data: Dfk1 is 0.88, Dfk2 is 0.78, Dfk3 is 0.61, Jfk1 is 1.2, Jfk2 is 0.9, Jfk3 is 1.3, and a=3. The evaluation score analysis coefficient can be calculated to be 7.94.

[0024] Obtain the assessment score analysis coefficient corresponding to each system student, calculate the average of the obtained assessment score analysis coefficients to obtain a first assessment verification index value, calculate the standard deviation of the obtained assessment score analysis coefficients to obtain a second assessment verification index value, and calculate the first assessment verification index value and the second assessment verification index value to obtain a third assessment verification index value; The third evaluation verification index value is calculated, and the specific formula is as follows: ; Among them, Kyx3 is the third assessment verification index value, Kyx2 is the second assessment verification index value, and Kyx1 is the first assessment verification index value; The value 0 is used as the left endpoint of the interval, and the third evaluation verification index value is used as the right endpoint of the interval to obtain the knowledge point to-be-trained interval corresponding to the sample teaching knowledge point. If the evaluation score analysis coefficient is in the knowledge point to-be-trained interval, the corresponding sample teaching knowledge point is marked as a knowledge point to-be-trained. If the evaluation score analysis coefficient is not in the knowledge point to-be-trained interval, the corresponding sample teaching knowledge point is marked as a training completed knowledge point. It should be noted that: in this application, the knowledge points to be trained involved herein include the interval boundaries corresponding to the intervals of the knowledge points to be trained; Repeat the process of evaluating and analyzing the sample teaching knowledge points, obtain the evaluation score analysis coefficient corresponding to each teaching knowledge point, and screen the training knowledge points according to the evaluation score analysis coefficient to obtain the historical knowledge point screening data; The step evaluation module evaluates the target students’ knowledge points to be trained based on the historical knowledge point screening data, obtains the correctness of the sequence corresponding to each knowledge point to be trained based on the evaluation results, and obtains the operation sequence evaluation data; The details are as follows: obtaining historical knowledge point screening data, and obtaining multiple knowledge points to be trained according to the historical knowledge point screening data; Mark the interval between the current assessment and the last assessment of the target student as a characteristic assessment interval, and add the teaching knowledge points learned by the target student in the characteristic assessment interval as knowledge points to be trained; A characteristic knowledge point is selected from the acquired multiple knowledge points to be trained, and an operation sequence analysis is performed on the evaluation process of the target students completing the characteristic knowledge point, and the correctness of the operation sequence corresponding to the characteristic knowledge point is obtained according to the analysis result; Specifically, the maintenance steps involved in the characteristic knowledge points are marked as the first priority step to the bth priority step in order of operation priority; It should be noted here that: in this application, the b involved here is the quantity value corresponding to the priority step, and b is an integer greater than 1; In this application, assuming that the characteristic knowledge point is specifically replacing the main wheel of the aircraft landing gear, the first priority step may be jacking up the aircraft, the second priority step may be installing the safety pin on the landing gear, the third priority step may be removing the old wheel, the fourth priority step may be checking the wheel hub, the fifth priority step may be installing the new wheel, and the sixth priority step may be tightening the nut; Acquire a monitoring image of a target student completing a characteristic knowledge point assessment in a characteristic scenario model, acquire the aircraft maintenance steps performed by the target student in the characteristic scenario model according to the monitoring image, and name the acquired multiple aircraft maintenance steps as the first practical operation step to the cth practical operation step in chronological order; It should be noted here that: in the present application, C involved here is the quantity value corresponding to the actual operation steps, and c is an integer greater than 0.

[0025] The first practical operation step to the cth practical operation step are recorded as a practical operation step sequence: Sactual=[s1,s2,…,sc]; Wherein, s1 to sc are the first practical operation step to the cth practical operation step respectively; The first priority step to the bth priority step are recorded as a priority step sequence: Spriority=[p1,p2,……,pb]; Among them, p1 to pb are the first priority step to the bth priority step respectively; In the priority step sequence, the step sequence score corresponding to each priority step in the priority step sequence and the total step evaluation score corresponding to the characteristic knowledge point are obtained according to the evaluation rules corresponding to the characteristic knowledge point, and the ratio of each step sequence score to the total step evaluation score of the characteristic knowledge point is calculated to obtain the step weight corresponding to each priority step; It should be noted here that: in this application, the scoring of the step sequence involved here is specifically the score of each priority step in the evaluation process.

[0026] For each actual operation step sj, get its position pos in the priority step sequence Spriority std (sj); It should be noted here that: in the present application, the actual operation step sj involved here can be any actual operation step from the first actual operation step to the cth actual operation step; If sj is at position pos in the actual operation step sequence Sactual actual (sj), then the step offset corresponding to sj is ; It is important to note that: Please refer to Figure 2 In this application, if the Sj step in the Sactual step sequence is the same as the p2 step in the Spriority sequence, then ; According to the penalty value Penalty(△j) corresponding to the actual operation step sj is calculated; The details are as follows: ; Among them, a1 and a2 are the set offset weight coefficients, wj is the step weight corresponding to the actual operation step sj1, and a1 involved here is set to 0.2 and a2 is set to 0.5; It should be noted here that: in the specific implementation, the following experimental data were measured: It is known that the step weight corresponding to the actual operation step sj1 is 0.4. If △j is 2, then Penalty(△j) can be calculated to be 0.08. If △j is 4, then Penalty(△j) can be calculated to be 0.2. If △j is 0, then Penalty(△j) can be calculated to be 0. If the priority step does not appear in the actual operation steps, the deduction value is the sum of the step weights corresponding to the missing priority steps, and the priority step missing deduction value Yqz is obtained; The correctness of the step sequence corresponding to the feature knowledge point is obtained by calculating the penalty value of each actual operation step offset, the penalty value of the priority step missing, and the step weight corresponding to each priority step; The correctness of the step sequence corresponding to the characteristic knowledge points is calculated. The specific formula is as follows: ; Among them, Szd is the correctness of the step sequence corresponding to the feature knowledge point, Penalty(△j) is the penalty value of the jth actual operation step offset, wi is the step weight corresponding to the i-th priority step, Yqz is the missing penalty for the priority step, b is the number value corresponding to the priority step, and c is the number value corresponding to the actual operation step; Repeat the process of obtaining the correctness of the step sequence corresponding to the characteristic knowledge point, and obtain the correctness of the step sequence corresponding to each knowledge point to be trained respectively; The correctness of the knowledge points to be trained and the sequence of steps are defined as the operation sequence assessment data; The operation assessment module assesses the target trainees' component installation accuracy based on the operation sequence assessment data, and obtains installation accuracy assessment data based on the assessment results; Specifically, the following steps are performed: obtaining operation sequence evaluation data, obtaining a plurality of knowledge points to be trained according to the operation sequence evaluation data, and selecting a knowledge point Fi to be trained from the plurality of knowledge points to be trained obtained; It should be noted here that: the Fi to-be-trained knowledge point involved here can be any one of the multiple to-be-trained knowledge points; In this application, the maintenance contents corresponding to the multiple knowledge points to be trained involved here all involve the installation of aircraft fuselage components; Perform deviation monitoring on the component installation position corresponding to the knowledge point Fi to be trained, and obtain the component installation deviation value corresponding to the knowledge point Fi to be trained according to the monitoring result; The details are as follows: 3D modeling technology is used to model the aircraft maintenance scene required for the assessment of the knowledge points to be trained, and a feature scene model is obtained; Acquire the fuselage components involved in the knowledge point to be trained Fi, and select a characteristic fuselage component from the acquired fuselage components; See also Figure 3 , randomly select a space point in the feature scene model as the coordinate origin, draw a straight line parallel to the ground through the coordinate origin to obtain the first feature straight line, mark the plane where the first feature straight line is located as the first feature plane, in the first feature plane, draw a straight line perpendicular to the first feature straight line through the coordinate origin to obtain the second feature straight line, draw a straight line perpendicular to the first feature plane through the coordinate origin to obtain the third feature straight line, mark the first feature straight line as the coordinate x-axis, the second feature straight line as the coordinate y-axis, and the third feature straight line as the coordinate z-axis to obtain the component position space coordinate system; In the component position space coordinate system, multiple feature position points are selected from the feature fuselage component, and the selected feature position points are named as the first position feature point to the mth position feature point, respectively, and the three-dimensional coordinates corresponding to the first position feature point to the mth position feature point are obtained respectively, so as to obtain the actual coordinates of the first position to the mth position; It should be noted here that: in the present application, the m involved here is the quantity value corresponding to the feature position point, and m is an integer greater than 1.

[0027] In the feature scene model, the reference position coordinates corresponding to the first position feature point to the mth position feature point are respectively acquired to obtain the first position reference coordinates to the mth position reference coordinates; The installation position deviation corresponding to the characteristic fuselage component is obtained by calculating the actual coordinates of the first position to the actual coordinates of the mth position and the reference coordinates of the first position to the reference coordinates of the mth position; The installation position deviation corresponding to the characteristic fuselage component is calculated, and the specific formula is as follows: ; Wherein, Wpc is the installation position deviation corresponding to the characteristic fuselage component, (Xsi, Ysi, Zsi) is the actual coordinate of the i-th position, (Xji, Yji, Zji) is the reference coordinate of the i-th position, and m is the quantity value corresponding to the characteristic position point; It should be noted here that: In the present application, the i-th position actual coordinates involved here may be any one of the first position actual coordinates to the m-th position actual coordinates, and the i-th position reference coordinates involved here may be any one of the first position reference coordinates to the m-th position reference coordinates; The installation position deviation corresponding to each fuselage component is obtained respectively to obtain multiple installation position deviations, and the average of the obtained multiple installation position deviations is calculated to obtain the installation deviation value of the Fi component; Obtain the component installation benchmark deviation corresponding to the Fi knowledge point to be trained, obtain the Fi component installation benchmark deviation, calculate the Fi component installation deviation value and the Fi component installation benchmark deviation to obtain the component installation deviation degree corresponding to each knowledge point to be trained, and obtain the installation accuracy evaluation data; Calculate the component installation deviation, the specific formula is as follows: ; Among them, Zpc is the component installation deviation, Fapi is the Fi component installation deviation value, and Fjpi is the Fi component installation benchmark deviation; It should be noted here that: in the present application, the Fi component installation deviation value involved here can be a component installation deviation value corresponding to any knowledge point to be trained, and the Fi component installation reference deviation involved here can be a component installation reference deviation corresponding to any knowledge point to be trained; The component installation reference deviation involved here is the maximum deviation within the qualified range of component installation; In the specific implementation, the following experimental data were measured: the component installation deviation corresponding to fuselage component A is 1.3 cm, the component installation reference deviation corresponding to fuselage component A is 1.5 cm, the component installation deviation corresponding to fuselage component B is 1.7 cm, the component installation reference deviation corresponding to fuselage component B is 2.0, the component installation deviation corresponding to fuselage component C is 1.8, and the component installation reference deviation corresponding to fuselage component C is 2.0. It can be calculated that the component installation deviation degree is 0.87.

[0028] The evaluation feedback module scores the target students on the operation sequence according to the operation sequence evaluation data, and scores the target students on the installation accuracy according to the installation accuracy evaluation data, thereby obtaining the teaching evaluation data; The details are as follows: obtaining operation sequence assessment data, and selecting one Si knowledge point to be trained from the obtained multiple knowledge points to be trained; It should be noted that: in the present application, the Si to-be-trained knowledge point involved here can be any one of the multiple to-be-trained knowledge points; Obtain the correctness of the step sequence corresponding to the Si knowledge point to be trained, obtain the total score of the step assessment corresponding to the Si knowledge point to be trained, calculate the product of the correctness of the step sequence and the total score of the step assessment, and obtain the operation sequence score corresponding to the Si knowledge point to be trained; Obtain installation accuracy evaluation data, and score the installation accuracy of the Si knowledge points to be trained according to the installation accuracy evaluation data; The details are as follows: obtaining installation accuracy evaluation data, and obtaining the component installation deviation corresponding to the Si knowledge point to be trained according to the installation accuracy evaluation data; If the component installation deviation is greater than 1, the installation accuracy score corresponding to the Si knowledge point to be trained is 0; If the component installation deviation is less than 1, the total score of the operation evaluation corresponding to the Si knowledge point to be trained is obtained, and the component installation deviation and the total score of the operation evaluation are calculated to obtain the installation accuracy score corresponding to the Si knowledge point to be trained; Calculate the installation accuracy score corresponding to the Si knowledge point to be trained. The specific formula is as follows: ; Among them, Ckz is the installation accuracy score corresponding to the knowledge point Si to be trained, Czf is the total score of the operation evaluation corresponding to the knowledge point Si to be trained, and Zpc is the component installation deviation corresponding to the knowledge point Si to be trained; The operation sequence score and the installation accuracy score are summed to obtain the teaching evaluation score corresponding to the Si knowledge points to be trained; The teaching evaluation scores corresponding to each knowledge point to be trained are obtained respectively to obtain the teaching evaluation data.

[0029] In this application, if corresponding calculation formulas appear, the above calculation formulas are all dimensionless and take their numerical calculations. The weight coefficients, proportional coefficients and other coefficients in the formulas are set to a result value obtained by quantifying each parameter. The size of the weight coefficient and the proportional coefficient can be determined as long as it does not affect the proportional relationship between the parameter and the result value.

[0030] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A teaching assessment simulation training system based on simulation deduction, characterized in that: include: Data collection module: used to obtain teaching evaluation data, analyze the teaching evaluation data, select the knowledge points to be trained from the knowledge points taught, and obtain historical knowledge point screening data; Step evaluation module: used to sequentially monitor the operation steps of target students based on historical knowledge point screening data, obtain the sequence correctness corresponding to the knowledge points to be trained based on the monitoring results, and obtain the operation sequence evaluation data; Operation evaluation module: used to evaluate the component installation accuracy of the target trainees according to the operation sequence evaluation data, and obtain the component installation deviation corresponding to the knowledge point to be trained according to the evaluation results to obtain the installation accuracy evaluation data; Evaluation feedback module: used to score the operation sequence and installation accuracy of the target students according to the operation sequence evaluation data and the installation accuracy evaluation data, and obtain teaching evaluation data.

2. According to claim 1, a teaching assessment simulation training system based on simulation deduction is characterized in that: The historical knowledge points are filtered and data is obtained as follows: Select a target student and obtain the teaching evaluation data corresponding to the target student; Select a sample teaching knowledge point from the teaching knowledge points involved in the history assessment according to the teaching assessment data; Conduct a comprehensive analysis of the teaching evaluation scores corresponding to the sample teaching knowledge points, and obtain the evaluation score analysis coefficients corresponding to the sample teaching knowledge points based on the analysis results; Obtain the assessment score analysis coefficient corresponding to each system student, calculate the average of the obtained assessment score analysis coefficients to obtain the first assessment verification index value, calculate the standard deviation of the obtained assessment score analysis coefficients to obtain the second assessment verification index value, and calculate the first assessment verification index value Kyx1 and the second assessment verification index value Kyx2 to obtain the third assessment verification index value Kyx3. The specific formula is as follows: ； The value 0 is used as the left endpoint of the interval, and the third evaluation verification index value is used as the right endpoint of the interval to obtain the knowledge point to be trained interval corresponding to the sample teaching knowledge point; If the evaluation score analysis coefficient is in the knowledge point to be trained interval, the corresponding sample teaching knowledge point is marked as a knowledge point to be trained; If the evaluation score analysis coefficient is not in the knowledge point waiting to be trained interval, the corresponding sample teaching knowledge point is marked as a training completed knowledge point; The evaluation score analysis coefficient corresponding to each teaching knowledge point is obtained respectively, and the training knowledge points are screened according to the evaluation score analysis coefficient to obtain the historical knowledge point screening data.

3. A teaching assessment simulation training system based on simulation deduction according to claim 2, characterized in that: The evaluation score analysis coefficient is obtained as follows: Obtain the average score ratio of K1 to Ka teaching assessment and the score ratio of K1 to Ka teaching assessment respectively; The details are as follows: In the K1 sample teaching assessment, the assessment questions involving the sample teaching knowledge points are scored, and the scores of the multiple assessment questions are averaged to obtain the K1 teaching assessment score; The average score of the students in the K1 sample teaching evaluation of the evaluation questions corresponding to the sample teaching knowledge points is obtained to obtain the K1 teaching evaluation average score, and the ratio of the K1 teaching evaluation score to the K1 teaching evaluation average score is calculated to obtain the K1 teaching evaluation average score ratio; Calculate the average total score of multiple assessment questions corresponding to the sample teaching knowledge points to obtain the total score of K1 teaching assessment, calculate the ratio of the K1 teaching assessment score to the K1 teaching assessment total score, and obtain the K1 teaching assessment score ratio; Calculate the evaluation score analysis coefficient corresponding to the sample teaching knowledge points: ； Among them, Cpd is the evaluation score analysis coefficient, Dfki is the Ki teaching evaluation score ratio, Jfki is the Ki teaching evaluation average score ratio, and a is the quantitative value corresponding to the sample teaching evaluation.

4. The teaching assessment simulation training system based on simulation deduction according to claim 1 is characterized in that: The operation sequence evaluation data is obtained as follows: Obtain historical knowledge point screening data, and obtain multiple knowledge points to be trained based on the historical knowledge point screening data; Mark the interval between the current assessment and the last assessment of the target student as a characteristic assessment interval, and add the teaching knowledge points learned by the target student in the characteristic assessment interval as knowledge points to be trained; Randomly select a characteristic knowledge point from the acquired multiple knowledge points to be trained, and mark the maintenance steps involved in the characteristic knowledge point as the first priority step to the bth priority step in order of operation priority; Acquire a monitoring image of a target student completing a characteristic knowledge point assessment, acquire the aircraft maintenance steps performed by the target student in the characteristic scene model according to the monitoring image, and name the acquired multiple aircraft maintenance steps as the first practical operation step to the cth practical operation step in chronological order; Conduct an operation sequence analysis on the evaluation process of target students completing characteristic knowledge points, and obtain the correctness of the step sequence corresponding to the characteristic knowledge points based on the analysis results; The correctness of the step sequence corresponding to each knowledge point to be trained is obtained respectively to obtain the operation sequence evaluation data.

5. A teaching assessment simulation training system based on simulation deduction according to claim 4, characterized in that: The correctness of the step sequence corresponding to the characteristic knowledge points is obtained as follows: The first practical operation step to the cth practical operation step are recorded as a practical operation step sequence: Sactual=[s1,s2,……,sc]; Wherein, s1 to sc are the first practical operation step to the cth practical operation step respectively; The first priority step to the bth priority step are recorded as a priority step sequence: Spriority=[p1,p2,……,pb]; Among them, p1 to pb are the first priority step to the bth priority step respectively; In the priority step sequence, obtain the step sequence score corresponding to each priority step in the priority step sequence and the total step evaluation score corresponding to the characteristic knowledge point, calculate the ratio of each step sequence score to the total step evaluation score of the characteristic knowledge point, and obtain the step weight corresponding to each priority step; For each actual operation step sj, get its position pos in the priority step sequence Spriority std (sj); If sj is at position pos in the actual operation step sequence Sactual actual (sj), then the step offset corresponding to sj is ; According to the penalty value Penalty(△j) corresponding to the actual operation step sj is calculated; The details are as follows: ; Among them, a1 and a2 are the set offset weight coefficients, and wj is the step weight corresponding to the actual operation step sj1; If the priority step does not appear in the actual operation steps, the deduction value is the sum of the step weights corresponding to the missing priority steps, and the priority step missing deduction value Yqz is obtained; Calculate the correctness of the step sequence corresponding to the characteristic knowledge points: ； Among them, Szd is the correctness of the step sequence corresponding to the feature knowledge point, Penalty(△j) is the penalty value of the jth actual operation step offset, wi is the step weight corresponding to the ith priority step, Yqz is the missing penalty for the priority step, b is the quantity value corresponding to the priority step, and c is the quantity value corresponding to the actual operation step.

6. The teaching assessment simulation training system based on simulation deduction according to claim 1 is characterized in that: The installation accuracy evaluation data is obtained as follows: Acquire operation sequence evaluation data, acquire multiple knowledge points to be trained according to the operation sequence evaluation data, and select a knowledge point Fi to be trained from the acquired multiple knowledge points to be trained; Use 3D modeling technology to model the aircraft maintenance scene required for the assessment of the knowledge points to be trained, and obtain a feature scene model; Acquire the fuselage components involved in the knowledge point Fi to be trained, and select a characteristic fuselage component from the acquired fuselage components; Create a component position space coordinate system, and obtain the actual position coordinates corresponding to the characteristic fuselage component according to the component position space coordinate system; Deviation monitoring is performed on the component installation positions corresponding to the knowledge points Fi to be trained, and the component installation deviation values ​​corresponding to the knowledge points Fi to be trained are obtained according to the monitoring results to obtain the installation accuracy evaluation data.

7. The teaching assessment simulation training system based on simulation deduction according to claim 6 is characterized in that: The actual coordinates of the position corresponding to the characteristic fuselage component are obtained as follows: In the feature scene model, a spatial point is randomly selected as the coordinate origin, and a straight line parallel to the ground is drawn through the coordinate origin to obtain the first feature straight line. The plane where the first feature straight line is located is marked as the first feature plane. In the first feature plane, a straight line perpendicular to the first feature straight line is drawn through the coordinate origin to obtain the second feature straight line. A straight line perpendicular to the first feature plane is drawn through the coordinate origin to obtain the third feature straight line. The first feature straight line is marked as the coordinate x-axis, the second feature straight line is marked as the coordinate y-axis, and the third feature straight line is marked as the coordinate z-axis to obtain the component position space coordinate system. In the component position space coordinate system, m position feature points are selected, and the three-dimensional coordinates corresponding to the first position feature point to the m-th position feature point are obtained respectively, so as to obtain the actual coordinates of the first position to the m-th position.

8. The teaching assessment simulation training system based on simulation deduction according to claim 6 is characterized in that: Obtain the component installation deviation value as follows: In the feature scene model, the reference position coordinates corresponding to the first position feature point to the mth position feature point are respectively acquired to obtain the first position reference coordinates to the mth position reference coordinates; Calculate the installation position deviation corresponding to the characteristic fuselage component: ； Wherein, Wpc is the installation position deviation corresponding to the characteristic fuselage component, (Xsi, Ysi, Zsi) is the actual coordinate of the i-th position, (Xji, Yji, Zji) is the reference coordinate of the i-th position, and m is the quantity value corresponding to the characteristic position point; The installation position deviation corresponding to each fuselage component is obtained to obtain multiple installation position deviations, and the average of the obtained multiple installation position deviations is calculated to obtain the installation deviation value of the Fi component; Obtain the component installation benchmark deviation corresponding to the Fi knowledge point to be trained, obtain the Fi component installation benchmark deviation, calculate the Fi component installation deviation value and the Fi component installation benchmark deviation to obtain the component installation deviation degree corresponding to each knowledge point to be trained, and obtain the installation accuracy evaluation data; Calculate the component installation deviation, the specific formula is as follows: ； Among them, Zpc is the component installation deviation, Fapi is the Fi component installation deviation value, and Fjpi is the Fi component installation benchmark deviation.

9. The teaching assessment simulation training system based on simulation deduction according to claim 1 is characterized in that: The teaching evaluation data is obtained as follows: Acquire operation sequence assessment data, and select Si knowledge points to be trained from the acquired multiple knowledge points to be trained; Obtain the correctness of the step sequence corresponding to the Si knowledge point to be trained, obtain the total score of the step assessment corresponding to the Si knowledge point to be trained, calculate the product of the correctness of the step sequence and the total score of the step assessment, and obtain the operation sequence score corresponding to the Si knowledge point to be trained; Obtain installation accuracy evaluation data, and score the installation accuracy of the Si knowledge points to be trained according to the installation accuracy evaluation data; The operation sequence score and the installation accuracy score are summed to obtain the teaching evaluation score corresponding to the Si knowledge points to be trained; The teaching evaluation score corresponding to each knowledge point to be trained is obtained to obtain the teaching evaluation data.

10. The teaching assessment simulation training system based on simulation deduction according to claim 9 is characterized in that: The installation accuracy score of the Si knowledge points to be trained is as follows: Obtain installation accuracy evaluation data, and obtain component installation deviation corresponding to Si knowledge point to be trained according to the installation accuracy evaluation data; If the component installation deviation is greater than 1, the installation accuracy score corresponding to the Si knowledge point to be trained is 0; If the component installation deviation is less than 1, the total score of the operation evaluation corresponding to the Si knowledge point to be trained is obtained, and the component installation deviation and the total score of the operation evaluation are calculated to obtain the installation accuracy score corresponding to the Si knowledge point to be trained; Calculate the installation accuracy score corresponding to the Si knowledge point to be trained. The specific formula is as follows: ； Among them, Ckz is the installation accuracy score corresponding to the Si knowledge point to be trained, Czf is the total score of the operation evaluation corresponding to the Si knowledge point to be trained, and Zpc is the component installation deviation corresponding to the Si knowledge point to be trained.

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