A method for testing interactive performance of a three-dimensional breakwater simulation model

Abstract

The present invention discloses a method for testing the interactive performance of a three-dimensional simulation model of a breakwater, and specifically relates to the technical field of data management and analysis. By acquiring interactive performance characteristic data of a three-dimensional model of a breakwater project in real time and setting a three-dimensional simulation test scene of the breakwater project, a comprehensive evaluation and optimization of the interactive performance of the three-dimensional model of the breakwater project is achieved. By real-time monitoring and comprehensive analysis of the execution time deviation ratio, the operation fluency drift index and the feedback speed abnormality index during the test, the system can timely discover and evaluate abnormal situations of the interactive performance, and make fine adjustments to the model according to the evaluation results, which not only improves the accuracy and comprehensiveness of the interactive performance of the three-dimensional simulation model of the breakwater, but also saves time and cost, and helps to improve the efficiency and reliability of the design and evaluation of the breakwater project.

Description

Technical Field

[0001] The invention relates to the technical field of data management and analysis, and in particular to an interactive performance testing method for a three-dimensional breakwater simulation model. Background Art

[0002] Interactive testing of the breakwater 3D simulation model refers to testing the established breakwater 3D simulation model to evaluate its performance in an interactive environment. This test usually includes aspects such as the model's response speed, stability, visualization effects, and the smoothness of user operations. By simulating the user's interaction process with the simulation model, testers can evaluate the model's performance in real-time interaction and identify any potential performance issues or room for improvement.

[0003] In the specific testing process, the tester may simulate the user's behavior when interacting with the breakwater 3D simulation model, such as adjusting parameters, changing perspectives, performing operations, etc. By recording indicators such as the model's response time, stability, and user experience in different interaction scenarios, the interactive performance of the model can be comprehensively evaluated. Such testing helps ensure that the breakwater simulation model has good user interaction performance in actual applications and improves its usability and practicality.

[0004] The prior art has the following deficiencies:

[0005] In the design and evaluation of breakwater projects, traditional methods usually rely on physical models and experiments, which are not only time-consuming and labor-intensive, but also costly. 3D simulation technology provides an efficient alternative. By building a 3D simulation model, a variety of tests and evaluations can be performed in a virtual environment. However, existing technologies are still insufficient in interactive testing, making it difficult to accurately evaluate the real-time response of the model and user experience. Summary of the invention

[0006] The purpose of the present invention is to provide an interactive performance testing method for a three-dimensional breakwater simulation model to overcome the shortcomings of the background technology.

[0007] In order to achieve the above object, the present invention provides the following technical solutions: a method for testing the interactive performance of a three-dimensional simulation model of a breakwater, comprising the following steps;

[0008] S1: acquiring interactive performance characteristic data of the three-dimensional model of the breakwater project in real time, wherein the interactive performance characteristic data includes model loading speed, smoothness of perspective switching, and response speed of object selection and operation, and defining interactive requirements according to the interactive performance characteristic data;

[0009] S2: Set up a 3D simulation test scenario for the breakwater project according to the defined interaction requirements. Use different devices and network environments to test the interactive performance of the 3D model for the designed test scenario, and extract the execution time deviation ratio, operation fluency drift index, and feedback speed abnormality index during the test process.

[0010] S3: Comprehensively analyze the execution time deviation ratio, operation fluency drift index, and feedback speed abnormality index extracted during the test to evaluate whether the interactive performance of the breakwater project 3D model is abnormal;

[0011] S4: According to the evaluation results, the interactive performance of the three-dimensional model of the breakwater project in the test scenario is divided into two cases: abnormal interactive performance and normal interactive performance;

[0012] S5: When the interactive performance of the three-dimensional model of the breakwater project is abnormal, the interference degree of the abnormal interactive performance on the test is evaluated, and according to the evaluation result, it is divided into different interference degree levels, and the three-dimensional model is adjusted accordingly according to the different interference degree levels.

[0013] In a preferred embodiment, in S2, the method for obtaining the execution time deviation ratio is:

[0014] Real-time acquisition of actual execution time data in interactive requirements under different devices and network environments. The actual execution time data includes model loading time, perspective switching time, and object selection operation time. The model loading time is marked as T jz , the perspective switching time is marked as T qh and the object selection operation time is marked as T xz , and obtain the model loading standard time, perspective switching standard time and object selection operation standard time under the standard state preset by the interaction requirements in the test scene, and mark the model loading standard time as TB jz , the standard time mark for perspective switching is TB qh The standard time for object selection operation is TB xz , construct the collected execution time data into a time series, and perform time series analysis on the series. The model loading time T jz =[T jz1 , T jz2 , T jz3 , ..., T jzn ], view switching time T qh =[T qh1 , T qh2 , T qh3 , ..., T qhn ], object selection operation time T xz =[T xz1 , Txz2 、T xz3 , ..., T xzn ], n is the number of execution time data collected, and the execution time deviation ratio is calculated. The specific calculation expression is: In the formula, we sd is the execution time deviation ratio.

[0015] In a preferred embodiment, in S2, the method for obtaining the operation fluency drift index is:

[0016] Collect operation fluency data on different devices and network environments ti , where i represents the i-th environment, t represents the time point, and the operation fluency data L in each environment ti Constructing time series;

[0017] Get the operation fluency corresponding to each time point t in real time as L ti , then the constructed time series is L i =(L 1i , L 2i , L 3i ,...,L Ti ), where T represents the number of data points, and the average value of the operation fluency in the i-th environment is calculated. The specific calculation expression is: Where, L qi is the average value of operation fluency in the i-th environment;

[0018] For each time series L in each environment i Perform time series analysis to identify the periodicity and trend of the sequence and calculate the operation fluency drift index at each time point t: Among them, rt fk is the operation fluency drift index, N represents the number of environments, L qi Represents the average value of operation fluency in the i-th environment.

[0019] In a preferred embodiment, in S2, the method for obtaining the feedback speed abnormality index is:

[0020] Collect system response speed data under different equipment and network test environments and mark them as YS mn , where m represents the mth environment and n represents the nth operation in that environment;

[0021] System response speed data for each test environment YS mn , calculate the mean value YS of all data in this test environment ip and standard deviation YS σp , for each data point YS mnCalculate its Z score. The specific calculation expression is: Get the test reference threshold of the Z score in the test environment, compare the Z score of each data point with the test reference threshold, and calculate the response speed data outlier. The specific calculation expression is: In the formula, ug df is the response speed data outlier, TZ mn To test the reference threshold;

[0022] Get the number of data points identified as outliers in the m test environments and mark them as H 异常 , and the total number of data points in the m test environments, which are marked as H 总 , calculate the feedback speed abnormality index, the specific calculation expression is: In the formula, yh cn It is the feedback speed abnormality index.

[0023] In a preferred embodiment, in S3, the execution time deviation ratio, operation fluency drift index and feedback speed abnormality index extracted during the test are comprehensively analyzed, specifically:

[0024] The execution time deviation ratio, operation fluency drift index and feedback speed anomaly index are normalized, and the anomaly evaluation coefficient of the interactive performance of the breakwater project three-dimensional model is calculated based on the normalized execution time deviation ratio, operation fluency drift index and feedback speed anomaly index.

[0025] In a preferred embodiment, in S4, according to the evaluation results, the interactive performance of the three-dimensional model of the breakwater project in the test scene is divided into two situations: abnormal interactive performance and normal interactive performance. Specifically,

[0026] The acquired abnormal evaluation coefficient is compared with the abnormal evaluation coefficient threshold; when the abnormal evaluation coefficient is greater than or equal to the abnormal evaluation coefficient threshold, an abnormal signal is generated and it is classified as an abnormal interactive performance state; when the abnormal evaluation coefficient is less than the abnormal evaluation coefficient threshold, a normal signal is generated and it is classified as a normal interactive performance state.

[0027] In a preferred embodiment, when the interactive performance of the three-dimensional model of the breakwater project is in an abnormal state, that is, when the abnormal assessment coefficient of the interactive performance of the three-dimensional model of the breakwater project in the test scenario is greater than or equal to the abnormal assessment coefficient threshold within a fixed time interval, the abnormal assessment coefficient when the abnormal assessment coefficient is greater than or equal to the abnormal assessment coefficient threshold in the subsequent fixed time interval is recorded and a data set is established. After comparing and analyzing the abnormal assessment coefficient with the abnormal assessment coefficient threshold, the interference degree index of the abnormal interactive performance on the accuracy of the test results is calculated.

[0028] In a preferred embodiment, a fixed interval for establishing a data set is set when the abnormal evaluation coefficient is greater than or equal to the abnormal evaluation coefficient threshold, and the number of abnormal evaluation coefficients when the abnormal evaluation coefficient is greater than or equal to the abnormal evaluation coefficient threshold is counted, and it is marked as K, where K=1, 2, 3, ..., A, where A is a positive integer greater than 0; the interference degree index of abnormal interaction performance on the accuracy of the test result is calculated, and the specific calculation expression is: In the formula, rg lx To calculate the interference index of abnormal interaction performance on the accuracy of test results, W rm is the abnormal assessment coefficient threshold.

[0029] In a preferred embodiment, the obtained interference degree index of the calculated abnormal interactive performance on the accuracy of the test results is compared with the reference threshold of the influence degree index; if the interference degree index of the calculated abnormal interactive performance on the accuracy of the test results is greater than or equal to the reference threshold of the interference degree index, a first-level warning signal is generated; if the interference degree index of the calculated abnormal interactive performance on the accuracy of the test results is less than the reference threshold of the interference degree index, a second-level warning signal is generated.

[0030] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0031] 1. The present invention monitors and analyzes interactive performance characteristic data in real time, so that the system can promptly detect interactive performance anomalies and evaluate and analyze the anomalies. Targeted monitoring and evaluation can help teachers and engineers understand the state of the model's interactive performance in a timely manner, so as to take corresponding adjustment and optimization measures. By fine-tuning the interactive performance, the stability and reliability of the system can be improved, and the risk of failure and anomalies can be reduced.

[0032] 2. When the interactive performance of the three-dimensional model of the breakwater project is abnormal, the present invention evaluates the degree of interference of the abnormal interactive performance on the test, sets the abnormal evaluation coefficient and threshold, and calculates the interference degree index, so as to accurately identify the abnormal interactive performance, and take corresponding early warning and adjustment measures according to different interference degree levels, thereby ensuring the stability and reliability of the test process. This systematic evaluation and response mechanism helps to improve the efficiency and usability of the three-dimensional model of the breakwater project in practical applications, while reducing the adverse effects on the interactive test of the three-dimensional model of the breakwater project. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0034] Figure 1 The present invention is a flow chart of the method.

[0035] Figure 2 It is a system module diagram of the present invention. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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.

[0037] Example 1

[0038] See also Figure 1 and Figure 2 As shown, the interactive performance testing method of a breakwater three-dimensional simulation model described in this embodiment includes the following steps:

[0039] S1: acquiring interactive performance characteristic data of the three-dimensional model of the breakwater project in real time, wherein the interactive performance characteristic data includes model loading speed, smoothness of perspective switching, and response speed of object selection and operation, and defining interactive requirements according to the interactive performance characteristic data;

[0040] S2: Set up a 3D simulation test scenario for the breakwater project according to the defined interaction requirements. Use different devices and network environments to test the interactive performance of the 3D model for the designed test scenario, and extract the execution time deviation ratio, operation fluency drift index, and feedback speed abnormality index during the test process.

[0041] S3: Comprehensively analyze the execution time deviation ratio, operation fluency drift index, and feedback speed abnormality index extracted during the test to evaluate whether the interactive performance of the breakwater project 3D model is abnormal;

[0042] S4: According to the evaluation results, the interactive performance of the three-dimensional model of the breakwater project in the test scenario is divided into two cases: abnormal interactive performance and normal interactive performance;

[0043] S5: When the interactive performance of the three-dimensional model of the breakwater project is abnormal, the interference degree of the abnormal interactive performance on the accuracy of the test results is evaluated, and according to the evaluation results, it is divided into different interference degree levels, and the three-dimensional model is adjusted accordingly according to the different interference degree levels.

[0044] Among them, in S1, the interactive performance characteristic data of the three-dimensional model of the breakwater project is obtained in real time, and the interactive performance characteristic data includes the loading speed of the model, the smoothness of the perspective switching, the response speed of object selection and operation, and the interactive requirements are defined according to the interactive performance characteristic data.

[0045] The construction of the three-dimensional simulation model of the breakwater project specifically includes:

[0046] First, it is necessary to collect relevant data of the breakwater project, including engineering design drawings, topographic data, material parameters, etc. These data can be obtained from multiple sources such as engineering design documents, geographic information system (GIS) databases, and measurement data.

[0047] Using professional 3D modeling software (such as AutoCAD, Revit, SketchUp, 3ds Max, etc.), we gradually create a 3D model of the breakwater project based on the collected data. This process includes establishing the geometric shape of the structure, adding material textures, setting the scale and size of the model, etc.

[0048] The use of Building Information Modeling (BIM) technology can further improve the accuracy and usability of the model. BIM software (such as Revit) can help model building elements as intelligent objects with properties and parameters, able to interact with other objects, and support collaborative design and management of models.

[0049] In the process of model building, it is necessary to add details and features, such as the texture of the breakwater, edge details, equipment and facilities, etc. These details can increase the realism and simulation effect of the model.

[0050] Use rendering software (such as V-Ray, Lumion, etc.) to illuminate and render the model to give it a realistic appearance and light and shadow effects. Good lighting and rendering can improve the visual effect and attractiveness of the model.

[0051] Defining interactive requirements is to determine the specific requirements and expectations for interactive performance in teaching activities based on these characteristic data. For example, the loading speed of the model refers to the time required to load the three-dimensional model of the breakwater project from the teaching software or platform. If the loading speed is too slow, it may affect the learner's patience and learning efficiency. The smoothness of perspective switching involves the learner's experience when switching perspectives in the model. If there is a freeze or unsmooth phenomenon when switching perspectives, it may affect the learner's understanding and exploration of the model. The response speed of object selection and operation is related to the feedback speed when learners select and operate objects in the model. If the response speed is too slow, it may cause learners to feel confused or dissatisfied.

[0052] Therefore, based on these interactive performance characteristic data, we can define interactive requirements, such as: the model loading speed should be completed within 3 seconds; the smoothness should be maintained at least 20 frames per second when switching perspectives; the response time of object selection and operation should be controlled within 100 milliseconds, etc. By defining clear interactive requirements, it can help developers or teaching designers determine the specific goals of the model's interactive performance and ensure that the interactive performance requirements of teaching activities are met when designing and optimizing the model.

[0053] When learners open the 3D model of the breakwater project, it should be loaded within 3 seconds to ensure that learners can quickly enter the teaching scene. When learners click to open the breakwater project model on the teaching platform, the model should be loaded from the server or local storage within 3 seconds, and learners can immediately start exploring the structure and characteristics of the breakwater.

[0054] The view switching should maintain a smoothness of at least 20 frames per second to ensure that learners do not experience lag or stuttering when exploring the model. When learners switch viewpoints using the mouse or gestures, the model should present the new viewpoint smoothly without any lag or flickering to ensure learners' observation experience.

[0055] The response time for object selection and operation should be controlled within 100 milliseconds to ensure that learners can operate the model quickly and accurately. When learners click to select or operate objects in the model, they should get response feedback within 100 milliseconds, for example, objects should be selected or operated immediately to make corresponding changes to keep learners focused and motivated.

[0056] Data updates should be completed within 10 seconds, and real-time interactions and simulations should respond within 1 second to ensure that learners can obtain the latest information and interactive feedback in a timely manner. When the teaching model needs to update data or reload, the data update should be completed within 10 seconds. For example, after adjusting the design parameters of the breakwater, the model should reflect the new design within 10 seconds. At the same time, if the learner adjusts the simulation parameters, such as adjusting the height of the wave, the simulation should respond within 1 second to ensure that the learner can observe the change effect in time.

[0057] The teaching model should be able to run stably and continuously for 24 hours to avoid the impact of software crashes or system failures on the normal progress of teaching activities. During the teaching process, the three-dimensional model of the breakwater project should maintain stable operation, and teaching activities should not be interrupted due to software crashes or system failures, ensuring that learners can continue to learn and explore.

[0058] S2: Set up a 3D simulation test scenario for the breakwater project according to the defined interaction requirements. Use different devices and network environments to test the interactive performance of the 3D model for the designed test scenario, and extract the execution time deviation ratio, operation fluency drift index, and feedback speed abnormality index during the test process.

[0059] Based on the defined interaction requirements, clarify the interaction performance standards that the test scenarios need to achieve. Create a 3D model that includes all parts of the breakwater project, including wave walls, embankments, water surfaces, etc. Design different perspective switching scenarios, covering different angles and heights, such as from the sea surface perspective, shore perspective, aerial perspective, etc. Design test scenarios for object selection and operation, including selecting a single object, multiple objects, moving, rotating, or editing. Set monitoring points in each test scenario to record model loading time, perspective switching smoothness, and object selection operation response time.

[0060] Use teaching software or platform to load the designed 3D model in the teaching environment. Execute the designed test scenarios one by one and record the interactive performance characteristic data in each scenario, including loading speed, perspective switching smoothness and object selection operation response speed. Record environmental factors during the test, such as network speed, device performance, etc.

[0061] Extract the execution time deviation ratio, operation fluency drift index and feedback speed abnormality index during the test process, specifically:

[0062] Obtaining the execution time deviation ratio plays an important role in evaluating the interactive performance of the three-dimensional model of the breakwater project, including:

[0063] The execution time deviation ratio can be used to detect whether there are abnormalities in the interactive performance under different devices and network environments. When the execution time deviation ratio exceeds the expected range, it may indicate that the execution time of some key tasks has significantly deviated from expectations, indicating that there may be performance anomalies or performance bottlenecks.

[0064] By analyzing the execution time deviation ratio, we can help locate the specific cause of abnormal interactive performance. For example, if the execution time deviation ratio of a key task is large, it may be caused by problems in software algorithms, hardware devices, or network communications. By locating the cause of the problem, we can optimize and improve performance in a targeted manner.

[0065] The method for obtaining the execution time deviation ratio is as follows: real-time acquisition of the actual execution time data in the interactive requirements of different devices and network environments. The actual execution time data includes model loading time, perspective switching time, and object selection operation time, and the model loading time is marked as T jz , the perspective switching time is marked as T qh and the object selection operation time is marked as T xz , and obtain the model loading standard time, perspective switching standard time and object selection operation standard time under the standard state preset by the interaction requirements in the test scene, and mark the model loading standard time as TB jz , the standard time mark for perspective switching is TB qh The standard time for object selection operation is TB xz , construct the collected execution time data into a time series, and perform time series analysis on the series. The model loading time T jz =[T jz1 , T jz2 , T jz3 , ..., T jzn ], view switching time T qh =[T qh1 , T qh2 , T qh3 , ..., T qhn ], object selection operation time T xz =[T xz1 , T xz2 , T xz3 , ..., T xzn ], n is the number of execution time data collected, and the execution time deviation ratio is calculated. The specific calculation expression is: In the formula, we sd is the execution time deviation ratio.

[0066] The larger the execution time deviation ratio, the greater the possibility of abnormal interactive performance of the breakwater project 3D model. Specifically, when the execution time deviation ratio is large, it means that the deviation between the actual execution time and the expected execution time under different devices and network environments is large. When users perform operations such as model loading, perspective switching or object selection, if the actual execution time is much longer than the expected time, it will cause operation delays. Users may need to wait for a long time to complete the operation, which reduces the real-time and smoothness of the interaction.

[0067] Large execution time deviations will affect the user experience, and users may feel that the operation is slow to respond, resulting in reduced user satisfaction. Especially in teaching environments where real-time interactivity is required, users are more likely to feel abnormal interactive performance.

[0068] If the interactive performance is abnormally serious, it may affect the teaching effect. The teacher cannot carry out the teaching operation smoothly, cannot demonstrate or explain the relevant concepts in time, and affects the communication of teaching content and the achievement of learning effect.

[0069] The operation fluency drift index refers to the index used to measure the change in operation fluency when evaluating the interactive performance of the breakwater project 3D model under different devices and network environments during the test. It reflects the degree of change in fluency felt by users when operating the model in different environments.

[0070] The operation fluency drift index can help identify the impact of different devices and network environments on interactive performance. By comparing the drift index in different environments, it is possible to determine which environmental factors have a greater impact on interactive performance, which helps optimize system design and network configuration.

[0071] A smaller operation fluency drift index means that the user's interactive experience in different environments is basically the same, and the operation fluency changes little. Maintaining a stable operation fluency can improve user satisfaction with the system and the quality of experience.

[0072] By analyzing the operation fluency drift index, we can find out the fluctuations of interactive performance in different environments, which helps to identify system performance problems and perform targeted optimization to improve system stability and performance.

[0073] The method for obtaining the operation fluency drift index is as follows:

[0074] Collect operation fluency data on different devices and network environments ti , where i represents the i-th environment, t represents the time point, and the operation fluency data L in each environment ti Construct a time series.

[0075] Get the operation fluency corresponding to each time point t in real time as L ti , then the constructed time series is L i =(L 1i , L 2i , L 3i ,...,L Ti ), where T represents the number of data points, and the average value of the operation fluency in the i-th environment is calculated. The specific calculation expression is: Where, L qi is the average value of operation fluency in the i-th environment;

[0076] For each time series L in each environment i Perform time series analysis to identify the periodicity and trend of the sequence and calculate the operation fluency drift index at each time point t: Among them, rt fk is the operation fluency drift index, N represents the number of environments, L qi Represents the average value of operation fluency in the i-th environment.

[0077] When the operation fluency drift index is large, it means that there are obvious differences in the operation fluency in different environments, and the user's interactive experience in different devices and network environments varies greatly. This may be due to the poor performance of the system in certain environments, resulting in unsmooth operation or delayed response. Therefore, a large operation fluency drift index indicates that there are abnormalities in interactive performance, which need to be further analyzed and resolved to improve user experience and system stability.

[0078] In the 3D simulation teaching test scenario, feedback speed usually refers to the user's feedback speed on the system operation, including the system's response speed to the user's operation and the system's processing speed on the user's input.

[0079] The method for obtaining the feedback speed abnormality index is:

[0080] Collect system response speed data under different equipment and network test environments and mark them as YS mn , where m represents the mth environment and n represents the nth operation in that environment;

[0081] System response speed data for each test environment YS mn , calculate the mean value YS of all data in this test environment ip and standard deviation YS σp , for each data point YS mn Calculate its Z score. The specific calculation expression is: Get the test reference threshold of the Z score in the test environment, compare the Z score of each data point with the test reference threshold, and calculate the response speed data outlier. The specific calculation expression is: In the formula, ug df is the response speed data outlier, TZ mn is the reference threshold for testing;

[0082] Get the number of data points identified as outliers in the m test environments and mark them as H 异常 , and the total number of data points in the m test environments, which are marked as H 总 , calculate the feedback speed abnormality index, the specific calculation expression is: In the formula, yh cn It is the feedback speed abnormality index.

[0083] When the feedback speed anomaly index is large, it means that the system's feedback speed has obvious changes or anomalies in different devices and network environments. This may indicate that the system responds slowly, delayed or unstable in some cases, affecting the user's interactive experience. A large anomaly index may be due to problems in the system processing user input, resulting in inconsistent system response speed or anomalies.

[0084] S3: Comprehensively analyze the execution time deviation ratio, operation fluency drift index, and feedback speed abnormality index extracted during the test to evaluate whether there are any abnormalities in the interactive performance of the breakwater project 3D model.

[0085] The execution time deviation ratio, operation fluency drift index and feedback speed anomaly index are normalized, and the anomaly evaluation coefficient of the interactive performance of the breakwater project three-dimensional model is calculated based on the normalized execution time deviation ratio, operation fluency drift index and feedback speed anomaly index.

[0086] For example, the present invention can use the following formula to calculate the abnormal evaluation coefficient of the interactive performance of the three-dimensional model of the breakwater project, and the calculation expression is: Where, wh rm is the abnormal assessment coefficient, we sd is the execution time deviation ratio, rt fk is the drift index of operation fluency, yh cn is the feedback speed anomaly index, a1, a2, and a3 are the proportional coefficients of the data trend correlation index and the data value composite index, and a2>a1>a3>0;

[0087] It can be seen from the calculation expression that the execution time deviation ratio, the operation fluency drift index and the feedback speed abnormality index are all positively proportional to the abnormality assessment coefficient. That is, as the execution time deviation ratio, the operation fluency drift index and the feedback speed abnormality index increase, the abnormality assessment coefficient also increases, and the possibility of abnormality in the interactive performance of the breakwater project three-dimensional model is higher.

[0088] S4: According to the evaluation results, the interactive performance of the three-dimensional model of the breakwater project in the test scenario is divided into two situations: abnormal interactive performance and normal interactive performance. Specifically:

[0089] Compare the obtained abnormal assessment coefficient with the abnormal assessment coefficient threshold;

[0090] When the abnormal evaluation coefficient is greater than or equal to the abnormal evaluation coefficient threshold, an abnormal signal is generated and classified as an abnormal interactive performance state, indicating that there are obvious abnormalities in the interactive performance of the three-dimensional model of the breakwater project in the test scenario, and the user's interactive experience with the system is significantly affected. It is necessary to further analyze the specific causes of the abnormality and take corresponding optimization and improvement measures to improve the quality and stability of the interactive performance.

[0091] When the abnormal evaluation coefficient is less than the abnormal evaluation coefficient threshold, a normal signal is generated and classified as a normal interactive performance state, indicating that the interactive performance in the test scenario meets expectations and no obvious abnormalities occur. The user's interactive experience with the system is at a normal level, and the user can operate smoothly and get good feedback. Although the interactive performance is normal, the system can still be further optimized and improved to further improve the user experience and system performance.

[0092] In this embodiment, the interactive performance characteristic data of the three-dimensional model of the breakwater project is obtained in real time, including loading speed, smoothness of perspective switching, and response speed of object selection and operation, and the interactive requirements are defined. On the basis of setting the interactive requirements, the interactive performance of the three-dimensional model is comprehensively tested using different devices and network environments, and key indicators such as execution time deviation ratio, operation smoothness drift index, and feedback speed abnormality index are extracted. By comprehensively analyzing these indicators, it is evaluated whether the interactive performance of the three-dimensional model of the breakwater project is abnormal. According to the evaluation results, the interactive performance in the test scene is divided into two situations: abnormal interactive performance and normal interactive performance, and the abnormal evaluation coefficient is compared with the abnormal evaluation coefficient threshold set in advance. When the abnormal evaluation coefficient is greater than or equal to the threshold, an abnormal signal is generated, indicating that the interactive performance in the test scene is obviously abnormal and needs further optimization and improvement. When the abnormal evaluation coefficient is less than the threshold, a normal signal is generated, indicating that the interactive performance in the test scene meets expectations, but further optimization can still be performed to improve user experience and system performance.

[0093] Example 2

[0094] S5: When the interactive performance of the three-dimensional model of the breakwater project is abnormal, the interference degree of the abnormal interactive performance on the accuracy of the test results is evaluated, and according to the evaluation results, it is divided into different interference degree levels, and the three-dimensional model is adjusted accordingly according to the different interference degree levels.

[0095] When the interactive performance of the three-dimensional model of the breakwater project is in an abnormal state, that is, when the abnormal assessment coefficient of the interactive performance of the three-dimensional model of the breakwater project in the test scenario is greater than or equal to the abnormal assessment coefficient threshold within a fixed time interval, the abnormal assessment coefficient when the abnormal assessment coefficient is greater than or equal to the abnormal assessment coefficient threshold in the subsequent fixed time interval is recorded and a data set is established. After comparing and analyzing the abnormal assessment coefficient with the abnormal assessment coefficient threshold, the interference degree index of the abnormal interactive performance on the accuracy of the test results is calculated.

[0096] A fixed interval for establishing a data set when the abnormal evaluation coefficient is greater than or equal to the abnormal evaluation coefficient threshold is set, and the number of abnormal evaluation coefficients when the abnormal evaluation coefficient is greater than or equal to the abnormal evaluation coefficient threshold is counted, and it is marked as K, where K = 1, 2, 3, ..., A, where A is a positive integer greater than 0; the interference degree index of abnormal interaction performance on the accuracy of the test result is calculated, and the specific calculation expression is: In the formula, rg lx To calculate the interference index of abnormal interaction performance on the accuracy of test results, W rm is the abnormal assessment coefficient threshold.

[0097] Compare the interference degree index of the obtained calculation abnormal interaction performance on the accuracy of the test result with the reference threshold of the influence degree index;

[0098] If the interference index of the calculated abnormal interaction performance on the accuracy of the test results is greater than or equal to the reference threshold of the interference index, a first-level warning signal is generated, indicating that the impact of the abnormal interaction performance of the breakwater project 3D model on the test has reached a serious level and needs to be taken seriously. Relevant responsible personnel need to be notified for further processing and response measures.

[0099] If the interference index of the calculated abnormal interaction performance on the accuracy of the test results is less than the reference threshold of the interference index, a secondary warning signal is generated, indicating that the impact of the abnormal interaction performance of the breakwater project 3D model on the test has not yet reached a serious level, but it still needs to be vigilant. Relevant responsible personnel need to be reminded to pay attention to abnormal situations and conduct necessary monitoring and tracking.

[0100] In this embodiment, when the interactive performance of the three-dimensional model of the breakwater project is abnormal, the degree of interference of the abnormal interactive performance on the test is evaluated. By recording the abnormal evaluation coefficient when the abnormal evaluation coefficient is greater than or equal to the abnormal evaluation coefficient threshold and establishing a data set, the interference degree index of the abnormal interactive performance on the test is calculated according to the comparative analysis of the abnormal evaluation coefficient and the abnormal evaluation coefficient threshold. Within the set fixed interval, the number of abnormal evaluation coefficients greater than or equal to the abnormal evaluation coefficient threshold is counted, and the interference degree index is obtained by the calculation formula. Then, the calculated interference degree index is compared with the interference degree index reference threshold. If the calculated interference degree index is greater than or equal to the interference degree index reference threshold, a first-level warning signal is generated, indicating that the abnormal interactive performance has seriously affected the test effect, and it is necessary to immediately attract the attention of the relevant responsible personnel, and further processing and response measures are taken. If the calculated interference degree index is less than the interference degree index reference threshold, a second-level warning signal is generated, indicating that an abnormal situation exists, and the relevant responsible personnel need to pay attention, and necessary monitoring and tracking are carried out to prevent the problem from further deteriorating.

[0101] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0102] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0103] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0104] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0105] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0106] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for testing the interactive performance of a three-dimensional breakwater simulation model, characterized in that: The steps include: S1: acquiring interactive performance characteristic data of the three-dimensional model of the breakwater project in real time, wherein the interactive performance characteristic data includes model loading speed, smoothness of perspective switching, and response speed of object selection and operation, and defining interactive requirements according to the interactive performance characteristic data; S2: Set up a 3D simulation test scenario for the breakwater project according to the defined interaction requirements. Use different devices and network environments to test the interactive performance of the 3D model for the designed test scenario, and extract the execution time deviation ratio, operation fluency drift index, and feedback speed abnormality index during the test process. The step S2 specifically includes: the method for obtaining the execution time deviation ratio is: obtaining the actual execution time data in the interaction requirements under different devices and network environments in real time, the actual execution time data includes the model loading time, the perspective switching time and the object selection operation time, and marking the model loading time as T jz , the perspective switching time is marked as T qh and the object selection operation time is marked as T xz , and obtain the model loading standard time, perspective switching standard time and object selection operation standard time under the standard state preset by the interaction requirements in the test scene, and mark the model loading standard time as TB jz , the standard time for perspective switching is marked as TB qh The standard time for object selection operation is TB xz , construct the collected execution time data into a time series, and perform time series analysis on the series. The model loading time T jz =[T jz1 , T jz2 , T jz3 , ..., T jzn ], view switching time T qh =[T qh1 , T qh2 , T qh3 , ..., T qhn ], object selection operation time T xz =[T xz1 , T xz2 , T xz3 , ..., T xzn |, n is the number of execution time data collected, and the execution time deviation ratio is calculated. The specific calculation expression is: In the formula, we sd is the execution time deviation ratio; The method for obtaining the operation fluency drift index is to collect the operation fluency data L under different devices and network environments. ti , where i represents the i-th environment, t represents the time point, and the operation fluency data L in each environment ti Build a time series; obtain the operation fluency corresponding to each time point t in real time as L ti , then the constructed time series is L i =(L 1i , L 2i , L 3i ,...,L Ti ), where T represents the number of data points, and the average value of the operation fluency in the i-th environment is calculated. The specific calculation expression is: Where, L qi is the average value of the operation fluency in the i-th environment; for the time series L in each environment i Perform time series analysis to identify the periodicity and trend of the sequence and calculate the operation fluency drift index at each time point t: Among them, rt fk is the operation fluency drift index, N represents the number of environments, L qi represents the average value of operation fluency in the i-th environment; The method for obtaining the feedback speed abnormality index is to collect system response speed data under different equipment and network test environments and mark it as YS mn , where m represents the mth environment and n represents the nth operation in the environment; for each test environment, the system response speed data YS mn , calculate the mean value YS of all data in this test environment ip and standard deviation YS σp , for each data point YS mn Calculate its Z score. The specific calculation expression is: Get the test reference threshold of the Z score in the test environment, compare the Z score of each data point with the test reference threshold, and calculate the response speed data outlier. The specific calculation expression is: In the formula, ug df is the response speed data outlier, TZ mn is the test reference threshold; obtain the number of data points identified as outliers in the m test environments and mark them as H 异常 , and the total number of data points in the m test environments, which are marked as H 总 , calculate the feedback speed abnormality index, the specific calculation expression is: In the formula, yh cn Feedback speed abnormality index: S3: Comprehensively analyze the execution time deviation ratio, operation fluency drift index, and feedback speed abnormality index extracted during the test to evaluate whether the interactive performance of the breakwater project 3D model is abnormal; The step S3 specifically includes: normalizing the execution time deviation ratio, the operation fluency drift index and the feedback speed abnormality index, and calculating the abnormality evaluation coefficient of the interactive performance of the breakwater project three-dimensional model through the normalized execution time deviation ratio, the operation fluency drift index and the feedback speed abnormality index; The calculation expression of the abnormal evaluation coefficient of the interactive performance of the three-dimensional model of the breakwater project is: Where, wh rm is the abnormal assessment coefficient, we sd is the execution time deviation ratio, rt fk is the drift index of operation fluency, yh cn is the feedback speed anomaly index, a1, a2, and a3 are the proportional coefficients of the data trend correlation index and the data value composite index, and a2>a1>a3>0; S4: According to the evaluation results, the interactive performance of the three-dimensional model of the breakwater project in the test scenario is divided into two cases: abnormal interactive performance and normal interactive performance; S5: When the interactive performance of the three-dimensional model of the breakwater project is abnormal, the interference degree of the abnormal interactive performance on the accuracy of the test results is evaluated, and according to the evaluation results, it is divided into different interference degree levels, and the three-dimensional model is adjusted accordingly according to the different interference degree levels.

2. The interactive performance testing method of a breakwater three-dimensional simulation model according to claim 1, characterized in that: In S4, according to the evaluation results, the interactive performance of the three-dimensional model of the breakwater project in the test scenario is divided into two cases: abnormal interactive performance and normal interactive performance, specifically: The acquired abnormal evaluation coefficient is compared with the abnormal evaluation coefficient threshold; when the abnormal evaluation coefficient is greater than or equal to the abnormal evaluation coefficient threshold, an abnormal signal is generated and it is classified as an abnormal interactive performance state; when the abnormal evaluation coefficient is less than the abnormal evaluation coefficient threshold, a normal signal is generated and it is classified as a normal interactive performance state.

3. The interactive performance testing method of a breakwater three-dimensional simulation model according to claim 2, characterized in that: When the interactive performance of the three-dimensional model of the breakwater project is in an abnormal state, that is, when the abnormal assessment coefficient of the interactive performance of the three-dimensional model of the breakwater project in the test scenario is greater than or equal to the abnormal assessment coefficient threshold within a fixed time interval, the abnormal assessment coefficient when the abnormal assessment coefficient is greater than or equal to the abnormal assessment coefficient threshold in the subsequent fixed time interval is recorded and a data set is established. After comparing and analyzing the abnormal assessment coefficient with the abnormal assessment coefficient threshold, the interference degree index of the abnormal interactive performance on the accuracy of the test results is calculated.

4. The interactive performance testing method of a breakwater three-dimensional simulation model according to claim 3, characterized in that: When the abnormal evaluation coefficient is greater than or equal to the abnormal evaluation coefficient threshold, a fixed interval is set for establishing a data set. When the abnormal evaluation coefficient is greater than or equal to the abnormal evaluation coefficient threshold, the number of abnormal evaluation coefficients is counted and marked as K, where K = 1, 2, 3, ..., A, where A is a positive integer greater than 0; the interference degree index of abnormal interaction performance on the accuracy of the test result is calculated, and the specific calculation expression is: In the formula, rg lx To calculate the interference index of abnormal interaction performance on the accuracy of test results, W rm is the abnormal evaluation coefficient threshold, wh rm is the abnormal assessment coefficient.

5. The interactive performance testing method of a breakwater three-dimensional simulation model according to claim 4, characterized in that: Compare the interference degree index of the obtained calculation abnormal interaction performance on the accuracy of the test result with the reference threshold of the influence degree index; If the interference degree index of the calculated abnormal interactive performance on the accuracy of the test result is greater than or equal to the interference degree index reference threshold, a first-level warning signal is generated; If the interference degree index of the calculated abnormal interactive performance on the accuracy of the test result is less than the interference degree index reference threshold, a second-level warning signal is generated.

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