Intelligent laboratory three-dimensional visualization system based on virtual reality
By recording the frequency and duration of errors in user operations, personalized simplified scripts are generated, which solves the problem of ambiguous user operation cognition in virtual reality laboratory systems and improves experimental efficiency and the transfer effect of real operation capabilities.
Patent Information
- Application Number
- CN202511544428.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-28
- Publication Date
- 2026-02-24
AI Technical Summary
Existing virtual reality laboratory 3D visualization systems cannot adapt to the personalized interaction needs of different users, resulting in users having a vague understanding of the core operating principles and device interaction logic of experimental steps. This reduces the practicality of virtual reality technology in experimental interaction scenarios and the transfer effect of real-world operational capabilities.
The information acquisition module records the frequency of errors and execution time during user operations. The simplified evaluation unit uses this data to determine whether the experimental steps need to be simplified and generates a simplified script. The simplified control unit controls the execution of the simplified script based on the user's familiarity with it, ensuring that the user gains standardized operating experience in the virtual reality device.
It improves the efficiency of virtual experiments, enhances users' proficiency in operating experimental procedures, realizes the effective transfer from virtual operation to real operation, and improves the practicality of virtual reality technology in experimental interaction scenarios.
Smart Images
Figure CN121564288A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of virtual interaction technology, specifically to a three-dimensional visualization system for a smart laboratory based on virtual reality. Background Technology
[0002] With the in-depth application of virtual reality technology in experimental teaching scenarios, the smart laboratory 3D visualization system based on virtual reality has become the core carrier for experimental operation simulation. This system accurately reproduces the device structure, operation process and interaction logic in real experimental scenarios by constructing an immersive 3D experimental environment, supporting users to complete experimental operations in virtual space, and effectively solving the technical pain points in traditional experimental scenarios such as high equipment procurement and maintenance costs, high risk of high-risk experimental operations, and strict time and space scene restrictions.
[0003] In existing technical solutions, in order to improve the operational efficiency of virtual experiments and reduce the user's operational threshold, designers often adopt a unified interaction simplification strategy to simplify the interaction process with the experimental device in the experimental steps. By pre-setting automated operation processes, reducing manual interaction steps, or simplifying the device operation logic, the goal of shortening the experimental time and reducing operational errors can be achieved, helping users to quickly complete the virtual experiment process.
[0004] However, different users have varying levels of proficiency in experimental procedures and understanding of device interaction logic. A standardized, simplified interaction strategy cannot meet users' personalized interaction needs. Furthermore, indiscriminate simplification can damage the integrity and logic of experimental device interaction, leading to users having a blurred understanding of the core operating principles, device coordination logic, and causal relationships of operational details in experimental procedures. For example, after simplifying the manual interaction steps of "microscope focus adjustment," users only need to click a button to complete the focusing, but they cannot perceive the adjustment mechanism of different knobs through interaction, nor the correspondence between image changes and knob operations during adjustment. After simplifying the interaction process of connecting chemical reaction devices, users are likely to overlook the matching rules of pipe interfaces and the operational logic of airtightness checks, losing the technical details of key interaction links.
[0005] Although users can quickly complete the experimental process in the virtual environment, they fail to grasp the essential principles of the experimental steps and the operating specifications of the device through interaction. This reduces the practicality of virtual reality technology in experimental interaction scenarios and also prevents the effective transfer of real operating capabilities through virtual interaction, thus restricting the interactive value of the system and the expansion of application scenarios.
[0006] To address the above problems, this invention proposes a solution. Summary of the Invention
[0007] The purpose of this invention is to provide a three-dimensional visualization system for a smart laboratory based on virtual reality, in order to solve the problems mentioned in the background art.
[0008] This invention provides a virtual reality-based smart laboratory 3D visualization system, comprising:
[0009] An experimental rendering terminal is used to obtain the rendering data and content data of an experiment after receiving the experiment name of an experiment pre-operated by a target user, render the rendering data to generate an experimental virtual scene for the target user, and transmit the rendering data to the virtual reality device worn by the target user so that the virtual reality device can visualize the experimental virtual scene. The content data includes the step numbers of all experimental steps required to operate the experiment, as well as all experimental devices and their parameter information that need to be interacted with to perform all experimental steps.
[0010] The information collection module is used to record the frequency of errors and execution time of the target user in each experimental step after the target user completes each experimental step when the target user starts to operate the experiment.
[0011] The simplified evaluation module includes a simplified evaluation unit and a simplified control unit. The simplified evaluation unit is used to retrieve whether the error frequency and execution time of the target user in the experimental step are stored after receiving the error frequency and execution time of the target user in the experimental step, and to determine whether to store the received error frequency and execution time based on the retrieval result.
[0012] The simplified evaluation unit is also used to determine whether all experimental steps in any experiment need to be simplified when the number of error frequencies and execution times of the experimental step corresponding to the step number with the largest value in the experiment stored in the unit reaches a fixed amount. Based on the determination result, the simplified information of the experiment is generated, which includes all experimental steps in the experiment that are determined to need to be simplified.
[0013] The administrator writes a corresponding simplified script based on all the experimental steps contained in the simplified information and stores it in the rendering data of the experiment;
[0014] The simplified control unit is used to make an initial judgment after receiving the error frequency and execution time of the target user in the experimental steps. If the ratio of the number of simplified scripts for all remaining experimental steps executed by the target user to the number of simplified scripts for all experimental steps completed by the target user is greater than or equal to P2, then the simplified scripts for all remaining experimental steps operated by the target user are judged whether to continue to execute. Based on the judgment result, it is determined whether to not execute simplified scripts for each subsequent experimental step of the target user starting from the next experimental step executed by the target user. P2 is the preset initial judgment threshold of the experiment.
[0015] Furthermore, the information acquisition module is used to obtain the name of the experiment to be performed by the target user after the target user enters the target laboratory and completes the virtual reality device wearing, and transmit the experiment name to the experiment rendering terminal.
[0016] Furthermore, in the process of the simplified evaluation unit determining whether to store the received error frequency and execution time based on the retrieval results, if the error frequency and execution time of the target user in the experimental step are already stored, then the received error frequency and execution time of the target user in the experimental step are not stored simultaneously; otherwise, they are stored.
[0017] Furthermore, for any given experiment, once the number of error frequencies and execution times corresponding to the experimental step with the largest numerical value stored in the simplified evaluation unit reaches a fixed amount, the steps for determining whether simplification is necessary for all steps included in the experiment are as follows:
[0018] S11: Label all experimental steps required to perform the experiment in ascending order of step number as A1, A2, ..., Aa, where a≥1;
[0019] S12: Obtain all error frequencies of the stored experimental step A1 and label them as B1, B2, ..., Bb, where b≥1, and the unit is the number of errors;
[0020] S13: The first evaluation metric D1 for experimental step A1 is obtained by performing deviation analysis on the error frequencies B1, B2, ..., Bb;
[0021] S14: Obtain the execution duration that is synchronized with the error frequencies B1, B2, ..., Bb, and labeled as E1, E2, ..., Eb respectively;
[0022] S15: Based on the preset time intervals Z1, Z2, ..., Zz, which are the execution times E1, E2, ..., Eb respectively, the corresponding time intervals are matched and the second evaluation quantity D2 of experimental step A1 is calculated according to the preset calculation rules. z is the total number of time intervals preset by the administrator for experimental step A1. The content is as follows:
[0023] S16: Using the formula Calculate and obtain the simplified evaluation value J1 of experimental step A1. In the formula, G1 is the preset optimal threshold for error frequency under experimental step A1, G2 is the preset optimal threshold for interval time deviation under experimental step A1, and β1 and β2 are preset first and second weight coefficients.
[0024] S17: Compare the size of J1 and J, where J is the preset comprehensive simplification threshold. If J1≥J, then experimental step A1 is determined to be unnecessary to simplify; otherwise, experimental step A1 is determined to be necessary to simplify.
[0025] S18: Determine whether experimental steps A2, A3, ..., Aa need to be simplified in sequence according to S11 to S17. After the determination is completed, obtain all experimental steps that need to be simplified and generate simplified information of the experiment based on them.
[0026] Furthermore, in S15, the content of the second evaluation quantity D2 obtained in experimental step A1 is calculated as follows:
[0027] S151: The total number of execution times belonging to the time interval Z1 obtained from the execution times E1, E2, ..., Eb is calibrated as the time measurement H1 of the time interval Z1 under experimental step A1. H1 reflects the sample size of the time interval Z1 and is used to measure the representativeness of the data.
[0028] The duration intervals Z1, Z2, ..., Zz are [F1, F1+P1), [F1+P1, F1+2*P1), [F1+2*P1, F1+3*P1), ..., [F1+(z-1)*P1, F1+z*P1], where F1 is the minimum execution time preset by the administrator for experimental step A1, and P1 is the preset duration interval value;
[0029] S152; Calculate and obtain the duration measurements H2, H3, ..., Hz of the duration intervals Z2, Z3, ..., Zz under experimental step A1 in sequence according to S151;
[0030] S153: Using the formula Calculate the second evaluation quantity D2 for experimental step A1, where Hi represents the duration measurement of the duration interval Zi under experimental step A1, iopt is the label subscript of the optimal duration interval under experimental step A1, |i-iopt| represents the distance between the current duration interval Zi and the optimal duration interval, and ai is the preset interval weight of the duration interval Zi.
[0031] Furthermore, the following content determines whether the simplified script should not be executed for any subsequent experimental steps for the target user, starting from the next experimental step performed by the target user:
[0032] S21: When the target user starts operating the experiment, based on the error frequency and execution time of all experimental steps currently executed by the target user, mark all experimental steps currently executed by the target user in the order they were received according to their error frequency and execution time as K1, K2, ..., Kk, k≥1;
[0033] S22: After obtaining the target user's start of operating the experiment, obtain the error frequencies L1, L2, ..., Lk and execution durations M1, M2, ..., Mk of executing experimental steps K1, K2, ..., Kk received;
[0034] S23: Use the formula to calculate and obtain the familiarity N1 of the target user with the experiment. In the formula, Lm' represents each of the error frequencies L1, L2, ..., Lk after dimensionless processing, Mm' represents each of the execution durations M1, M2, ..., Mk after dimensionless processing, and λ1, λ2 are respectively preset first and second proportion weights;
[0035] Compare the magnitudes of N1 and N. If N1 < N, it is determined that the target user is familiar with the experiment well and no treatment is performed. Otherwise, it is determined that the target user is less familiar with the experiment, and it is determined that starting from the next experimental step executed by the target user, no simplified script is executed for each subsequent experimental step of the target user. N is a preset determination reference threshold.
[0036] Compared with the prior art, the following beneficial effects are achieved:
[0037] In this invention, an information collection module is set to collect the experiment name of the experiment pre-operated by the user, an experiment rendering terminal is set to render the rendering data of the experiment pre-operated by the user to generate an experimental virtual scene, and the virtual reality device worn by the user is synchronized to complete the visualization of the experimental virtual scene. By setting a simplified evaluation unit, it is determined whether each experimental step in a plurality of experiments needs to be simplified based on the error frequencies and execution durations recorded in each experimental step executed by several users. Based on the determination result, the management personnel write a simplified script for the experimental steps determined to need simplification, and write a simplified script for the experimental steps with relatively low operation difficulty and low error rate to shorten the operation time-consuming, avoiding the waste of the user's operation time cost and occupation of the user's learning energy for such experimental steps, improving the efficiency of the virtual experiment. The experimental steps with relatively high difficulty and large operation difficulty retain their complete interaction processes to enable the user to form a standardized operation muscle memory during the operation process and strengthen the experimental value of the virtual reality technology, thereby enhancing the practicality of the virtual reality technology in the experimental interaction scenario, and also effectively transferring the real operation ability through virtual interaction;
[0038] This invention, through a simplified control unit, determines whether to continue executing the simplified scripts for all remaining experimental steps of a user's experiment when the ratio of the number of simplified scripts for all remaining experimental steps to the number of simplified scripts for the completed experimental steps reaches a preset initial threshold. The user's ability level is assessed by calculating their familiarity with the experiment. For users with lower proficiency, the simplified scripts for all subsequent experimental steps are not executed, thus specifically enhancing their understanding of the subsequent experimental steps. For users with higher proficiency, the simplified scripts for all subsequent experimental steps continue to be executed, thereby ensuring the experimental efficiency of these users. Attached Figure Description
[0039] Figure 1 This is a system block diagram of the present invention. Detailed Implementation
[0040] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0041] Please see Figure 1 This application provides a smart laboratory 3D visualization system based on virtual reality, including an information acquisition module, an experimental rendering terminal, and a simplified evaluation module;
[0042] The information acquisition module is used to obtain the name of the experiment to be performed by the target user after the target user enters the target laboratory and completes the virtual reality device wearing, and transmit the experiment name to the experiment rendering terminal. The virtual reality device includes, but is not limited to, VR helmet and data gloves. The VR helmet can realize immersive presentation of the experimental scene and spatial position calibration.
[0043] The data gloves have built-in bending sensors, pressure sensors and inertial measurement units, which can capture the wearer's finger joint bending angle, force of movement and spatial movement trajectory in real time, providing data support for precise interaction in subsequent experimental operations;
[0044] The experimental rendering terminal is used to call the corresponding rendering data according to the experiment name and quickly generate an immersive experimental virtual scene. The experimental rendering terminal pre-stores the experiment name, rendering data and content data of several experiments. The rendering data includes, but is not limited to, the 3D model of the experimental device (including detailed textures and physical property parameters), experimental environment scene elements (such as laboratory layout, lighting effects, background sound effects), experimental operation interaction logic scripts (such as reagent addition trigger mechanism, experimental device startup process), and dynamic simulation data of experimental phenomena (such as chemical reaction color change, physical experiment movement trajectory).
[0045] Meanwhile, the experimental rendering terminal is equipped with a high-performance graphics processing unit and a real-time collision detection algorithm. It can dynamically respond to the user's interactive actions based on the operation data transmitted by the data glove, and realize real-time feedback of virtual experimental operations. For example, when the user performs the action of pouring reagents through the data glove, the terminal can simultaneously render the reagent flow trajectory and the liquid level change effect in the container.
[0046] The content data contains the step numbers of all experimental steps required to perform the corresponding experiment, as well as the experimental apparatus and parameter information required to perform the corresponding experimental steps. The step number serves as a unique identifier for the execution order of the experimental steps, starting from the number 1 and proceeding sequentially. The smaller the value of the step number, the earlier the corresponding experimental step is executed.
[0047] The core function of the parameter information of any experimental device is to clearly define the parameters, operation configuration requirements and technical control standards of the experimental device in the corresponding experimental steps. This provides a clear and executable technical basis for the standardized operation and precise operation of the experimental device in the corresponding steps, ensuring that the operating status of the experimental device is highly compatible with the technical requirements of the corresponding experimental steps, thereby ensuring that the experimental steps are carried out in an orderly manner according to the preset plan and that the experimental results are stable and repeatable.
[0048] Taking the "ethanol distillation and purification experiment" in chemistry and the "voltmeter-ammeter method for measuring resistance" in physics as examples, this experiment requires the execution of the experimental step "heating and distillation of the mixed solution and collection of fractions." This step requires the simultaneous interaction of four experimental devices: distillation flask, condenser, alcohol lamp, and thermometer. The parameter information and function of each device are as follows:
[0049] The parameters of the distillation flask are: volume 500mL, 200mL of ethanol-water mixture is added, and the height of the side arm of the distillation head is level with the mercury bulb of the thermometer. These parameters clarify the specifications of the device, the amount of material loaded, and the installation positioning standards, so as to avoid the mixture from boiling over and overflowing due to excessive loading, or the distillation efficiency from the installation deviation, and provide basic equipment conditions for the stable operation of the distillation process.
[0050] The parameters of the condenser are as follows: a straight condenser is used, the cooling water inlet is located at the lower end of the condenser, the outlet is located at the upper end, the water flow rate is controlled at 8 mL / s, and the cooling water temperature is maintained at 10-15℃. These parameters define the device type, water flow direction, and operating parameters. By setting standardized cooling conditions, the distilled ethanol vapor is ensured to liquefy rapidly, while avoiding fraction loss due to improper water flow rate or temperature, thus ensuring purification efficiency.
[0051] The parameters of the alcohol lamp are as follows: it uses an outer flame for heating, and the heating power is adjusted to the medium level by adjusting the height of the wick to ensure that the bottom of the distillation flask is heated evenly and avoid local overheating. These parameters clearly define the heating method and power control standard, which not only meets the heat requirement for the mixture to reach the boiling point of ethanol (78°C), but also avoids problems such as the decomposition of the mixture caused by local overheating, thus ensuring the precise control of the distillation temperature.
[0052] The thermometer's parameters are: range 0-100℃, accuracy 0.1℃, mercury bulb placed at the branch end of the distillation head to monitor the temperature of the distilled vapor in real time, and fraction collection begins when the temperature stabilizes at 78±0.5℃. These parameters define the device's measurement range, accuracy, and installation location, and also clarify the operational triggering conditions based on temperature parameters. Through precise temperature monitoring and judgment, accurate collection of ethanol fractions is achieved, ensuring fraction purity.
[0053] After receiving the transmitted experiment name, the experimental rendering terminal obtains the pre-stored rendering data and content data corresponding to the experiment, and renders the rendering data to generate an experimental virtual scene for the target user. At the same time, the experimental rendering terminal synchronously transmits the rendering data to the virtual reality device worn by the target user through the communication link, and the virtual reality device realizes the visualization of the experimental virtual scene. Specifically, when the VR headset receives the rendering data, the graphics processing chip built into the VR headset decodes and adapts the received rendering data to match the VR headset's display resolution (such as a 4K dual-lens screen) and refresh rate (usually above 90Hz to avoid screen ghosting).
[0054] By using binocular display technology to generate images that are slightly different for the left and right eyes, and by using the parallax effect of the human eye to construct three-dimensional stereoscopic vision, the target user can perceive the spatial hierarchy of the experimental device (such as the height of the reagent bottle and the depth of the experimental platform).
[0055] By combining the environmental positioning components of the VR headset, such as the gyroscope and accelerometer, the screen angle is adjusted in real time. When the user turns their head, the VR headset will synchronously send position data back to the rendering terminal. The terminal quickly generates the rendering content of the corresponding angle and transmits it back to the VR headset, realizing an immersive experience of "head movement, screen movement".
[0056] The acquired data corresponding to the experiment is transmitted to the experiment monitoring module.
[0057] When the target user begins to operate the experiment, after the target user completes each experimental step, the information acquisition module synchronously records the error frequency and execution time of the target user in the experimental step and transmits it to the simplified evaluation module. The determination of the error frequency is based on the evaluation of all experimental devices and their parameter information required to perform the experimental step. The execution process of the target user performing the experimental step is fully verified. The defined error types include, but are not limited to, omission of experimental steps, operation sequence errors, and incorrect parameter settings of experimental devices.
[0058] It should be noted that the minimum error frequency of the target user is 0, which means that the target user did not make any errors during the execution of the experimental steps;
[0059] The execution time is the time taken for the target user to complete the experimental steps.
[0060] The simplified evaluation module is used to evaluate whether all experimental steps contained in all preset experiments need to be simplified, and also to determine whether a simplified script should be executed for several subsequent experimental steps of a user who is performing an operation step. The simplified evaluation module includes a simplified evaluation unit and a simplified control unit.
[0061] After receiving the error frequency and execution time of the target user in the experimental step, the simplified evaluation module transmits them to the simplified evaluation unit and the simplified control unit, respectively.
[0062] After receiving the error frequency and execution time of the target user in the experimental steps, the simplified evaluation unit searches whether the error frequency and execution time of the target user in the experimental steps are already stored. If the error frequency and execution time of the target user in the experimental steps are already stored, the received error frequency and execution time of the target user in the experimental steps are not stored simultaneously; otherwise, they are stored. It should be noted that this operation ensures that for any given experiment, each user operating the experiment only stores the error frequency and execution time of all experimental steps performed during their first operation. In this application, the unit of execution time is seconds (s).
[0063] For any given experiment, once the number of error frequencies and execution times corresponding to the step number with the largest numerical value in the experiment stored in the simplified evaluation unit reaches a fixed amount, it determines whether simplification is needed for all steps included in the experiment, as follows:
[0064] S11: Label all experimental steps required to perform the experiment in ascending order of step number as A1, A2, ..., Aa, where a≥1;
[0065] S12: Obtain all error frequencies of the stored experimental step A1 and label them as B1, B2, ..., Bb, where b ≥ 1, and the unit is the number of times. Here, b is a fixed amount stored by the administrator based on the preset error frequencies of experimental step A1, which also represents the total number of error frequencies of the stored experimental step A1. The value of b is set based on the premise of ensuring data representativeness and analysis reliability, so as to ensure that the amount of data is sufficient to support the analysis, avoid the analysis results being one-sided due to insufficient data, and avoid data redundancy, so as to provide an effective basis for subsequent simplified evaluation.
[0066] S13: By performing deviation analysis on the error frequencies B1, B2, ..., Bb, the first evaluation metric D1 for experimental step A1 is obtained. The specific details are as follows: using the formula... 1≤c≤b Calculate the deviation C1 of the error frequencies B1, B2, ..., Bb in experimental step A1. Compare the magnitudes of C1 and C. In the formula, Bc represents each of the error frequencies B1, B2, ..., Bb, B is the average value of Bc at this time, and C is the preset standard deviation threshold of the error frequency in experimental step A1.
[0067] If C1 > C, then delete the corresponding Bc values in descending order of |Bc-B| and calculate the deviation C1 of the remaining Bc values. Compare C1 with C again until C1 ≤ C. Obtain the average value of all remaining Bc values and label the average value as the first evaluation metric D1 of experimental step A1.
[0068] It should be noted here that the first evaluation metric obtained by screening the effective error frequencies through deviation analysis can be used to evaluate the reasonableness of the error rate in experimental step A1.
[0069] S14: Obtain the execution duration that is synchronized with the error frequencies B1, B2, ..., Bb, and labeled as E1, E2, ..., Eb respectively;
[0070] S15: Based on the preset time intervals Z1, Z2, ..., Zz, which are the execution times E1, E2, ..., Eb respectively, the corresponding time intervals are matched and the second evaluation quantity D2 of experimental step A1 is calculated according to the preset calculation rules. z is the total number of time intervals preset by the administrator for experimental step A1. The content is as follows:
[0071] S151: The total number of execution times belonging to the time interval Z1 obtained from the execution times E1, E2, ..., Eb is calibrated as the time measurement H1 of the time interval Z1 under experimental step A1. H1 reflects the sample size of the time interval Z1 and is used to measure the representativeness of the data.
[0072] For example, if the execution duration E1 is 35s, the duration interval Z1 is [30,40), and Z2 is [40,50). Since 35s satisfies 30<35<40, the execution duration E1 belongs to the duration interval Z1.
[0073] In this application, the time intervals Z1, Z2, ..., Zz are respectively [F1, F1+P1), [F1+P1, F1+2*P1), [F1+2*P1, F1+3*P1), ..., [F1+(z-1)*P1, F1+z*P1], where F1 is the minimum execution time preset by the administrator for experimental step A1, that is, the reasonable minimum time threshold required to complete experimental step A1;
[0074] P1 is the preset time interval value determined by the administrator based on two dimensions: first, the operational complexity of experimental step A1 (e.g., whether it involves the collaborative interaction of multiple experimental devices, whether it requires precise adjustment of parameters, etc.); second, the individual differences of users (including the proficiency gradient of different operational levels, and the difference in the impact of different levels of learning ability on the operation time).
[0075] The core function of P1 is to divide the overall execution time of experimental step A1 into multiple continuous and progressive intervals, thereby accurately adapting to the time consumption characteristics of user groups with different operational levels and different learning abilities, and ultimately providing a standardized interval reference for subsequent evaluation of whether experimental step A1 needs to be simplified.
[0076] S152; Calculate and obtain the duration measurements H2, H3, ..., Hz of the duration intervals Z2, Z3, ..., Zz under experimental step A1 in sequence according to S151;
[0077] S153: Using the formula The second evaluation quantity D2 of experimental step A1 is calculated and obtained. In the formula, Hi represents the duration measurement of the duration interval Zi under experimental step A1, iopt is the subscript of the optimal duration interval under experimental step A1. The optimal duration interval is pre-selected by the management personnel according to the operational characteristics and reasonable execution standards of experimental step A1, corresponding to the optimal execution duration range. |i-iopt| represents the distance between the current duration interval Zi and the optimal duration interval. The larger the distance, the more significant the deviation of the duration interval from the optimal standard, and the lower the rationality. ai is the preset interval weight of duration interval Zi. In this application, a higher weight is given to the duration interval with excessive time consumption, i.e., the duration interval with the sequence number greater than iopt, in order to highlight the negative impact of such intervals on the overall rationality of time consumption. Zi represents each of the duration intervals Z1, Z2, ..., Zz.
[0078] It should be noted that the second evaluation metric is artificially defined and is used to reflect the overall degree to which the time consumption of all time intervals of experimental step A1 deviates from the optimal time interval. The higher the value, the more unreasonable the overall time consumption is.
[0079] S16: Using the formula The simplified evaluation value J1 of experimental step A1 is calculated. In the formula, G1 is the preset optimal threshold for error frequency under experimental step A1, in units of number of errors. It is set by the administrator based on the maximum acceptable number of errors under experimental step A1 preset by the subject teacher of the experiment. G2 is the preset optimal threshold for interval time deviation under experimental step A1. It is set by the administrator based on the maximum acceptable time deviation value under experimental step A1 preset by the subject teacher of the experiment. β1 and β2 are preset first and second weighting coefficients used to balance the importance of error frequency and time deviation. In this application, β1 + β2 = 1, and both are positive values. They can be adjusted according to the emphasis on error frequency and interval time.
[0080] It should be noted that D1 and G1 have the same unit, which is the number of times. The result of D1 / G1 is a dimensionless relative proportion (e.g., 7 times / 5 times = 1.4, no unit). D2 and G2 have the same attribute, being dimensionless. The ratio of D2 / G2 is also a dimensionless relative proportion (e.g., 10 / 8 = 1.25, no unit). Through the above calculation, D1 and D2 are transformed into relative values of the same dimension, eliminating the difference in dimensions and ensuring that the result of the subsequent weighted sum has a unified logical meaning, which can comprehensively reflect the degree exceeding the critical value.
[0081] S17: Compare J1 and J, where J is the preset comprehensive simplification threshold. If J1≥J, it means that the user is not proficient enough in performing experimental step A1 and the user needs to become familiar with the operation of experimental step A1. It is determined that experimental step A1 does not need to be simplified. Otherwise, it is determined that experimental step A1 needs to be simplified.
[0082] S18: Determine whether experimental steps A2, A3, ..., Aa need to be simplified in sequence according to S11 to S17. After the determination is completed, obtain all experimental steps that need to be simplified and generate simplified information of the experiment based on them.
[0083] The simplified information of the experiment is displayed to the administrator. Based on the simplified information, which contains all the experimental steps that need to be simplified, the administrator writes a corresponding simplified script. The simplified script is used to reduce the interaction between the user and the experimental device that needs to be interacted with when performing the corresponding experimental steps, and to reduce the complexity of the interaction, thereby simplifying the user's interaction process with the specified experimental device in the experimental step.
[0084] After the administrator writes the corresponding simplified script based on the experimental steps in the simplified information, he or she inputs it into the experimental rendering terminal, which stores it in the rendering data of the corresponding experiment. When the next user pre-operates the experiment, if there is a simplified script for each experimental step executed by the user, the simplified script of the experimental step will be executed.
[0085] After receiving the error frequency and execution time of the target user in the experimental steps, the simplified control unit performs an initial judgment. If the ratio of the number of simplified scripts for all remaining experimental steps executed by the target user to the number of simplified scripts for all completed experimental steps is less than or equal to P2, no processing is performed. P2 is a preset initial judgment threshold for the experiment, which is preset by the administrator based on the experiment numbers of all experimental steps with simplified scripts included in the experiment. Only the received error frequency and execution time of the experimental steps are temporarily stored. If the ratio is greater than or equal to P2, a judgment is made on whether the target user should continue to execute the simplified scripts for all remaining experimental steps. The judgment steps are as follows:
[0086] S21: When the target user starts operating the experiment, based on the error frequency and execution time of all experimental steps currently executed by the target user, mark all experimental steps currently executed by the target user in the order they were received according to their error frequency and execution time as K1, K2, ..., Kk, k≥1;
[0087] S22: After obtaining that the target user starts to operate the experiment, obtain the error frequencies L1, L2, ..., Lk and execution durations M1, M2, ..., Mk of executing experimental steps K1, K2, ..., Kk received;
[0088] S23: Use the formula to calculate and obtain the familiarity N1 of the target user with the experiment. In the formula, Lm' represents each of the error frequencies L1, L2, ..., Lk after dimensionless processing, Mm' represents each of the execution durations M1, M2, ..., Mk after dimensionless processing, and λ1, λ2 are respectively preset first and second proportion weights;
[0089] Compare the sizes of N1 and N. If N1 < N, it is determined that the target user is familiar with the experiment and no processing is done. Otherwise, it is determined that the target user is less familiar with the experiment. It is determined that starting from the next experimental step executed by the target user, the simplified script for each subsequent experimental step of the target user will not be executed, and a stop simplification instruction is generated. N is a preset determination reference threshold;
[0090] The simplification control unit transmits the generated stop simplification instruction to the experimental rendering terminal and the virtual reality device worn by the target user. Starting from when the target user executes the next experimental step, the corresponding simplified script for each subsequent experimental step of the target user will not be executed until the target user completes the operation of the experiment. Here, the virtual reality device refers to a VR headset;
[0091] In this application, for any experiment, the simplification control unit makes an initial determination each time it receives the error frequency and execution duration of a user in an experimental step of the experiment. In the initial determination, if it is determined whether to continue executing the simplified scripts for all the remaining experimental steps of the user operating the experiment, then no initial determination will be made for the error frequency and execution duration of each subsequent experimental step of the user received in the experiment until the user completes the operation of the experiment.
[0092] Some of the data in the above formula are numerically calculated after removing their dimensions, and the content not described in detail in this specification belongs to the prior art well-known to those skilled in the art.
[0093] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.
Claims
1. A three-dimensional visualization system for a smart laboratory based on virtual reality, characterized in that, include: An experimental rendering terminal is used to obtain the rendering data and content data of an experiment after receiving the experiment name of an experiment pre-operated by a target user, render the rendering data to generate an experimental virtual scene for the target user, and transmit the rendering data to the virtual reality device worn by the target user so that the virtual reality device can visualize the experimental virtual scene. The content data includes the step numbers of all experimental steps required to operate the experiment, as well as all experimental devices and their parameter information that need to be interacted with to perform all experimental steps. The information collection module is used to record the frequency of errors and execution time of the target user in each experimental step after the target user completes each experimental step when the target user starts to operate the experiment. The simplified evaluation module includes a simplified evaluation unit and a simplified control unit. The simplified evaluation unit is used to retrieve whether the error frequency and execution time of the target user in the experimental step are stored after receiving the error frequency and execution time of the target user in the experimental step, and to determine whether to store the received error frequency and execution time based on the retrieval result. The simplified evaluation unit is also used to determine whether all experimental steps in any experiment need to be simplified when the number of error frequencies and execution times of the experimental step corresponding to the step number with the largest value in the experiment stored in the unit reaches a fixed amount. Based on the determination result, the simplified information of the experiment is generated, which includes all experimental steps in the experiment that are determined to need to be simplified. The administrator writes a corresponding simplified script based on all the experimental steps contained in the simplified information and stores it in the rendering data of the experiment; The simplified control unit is used to make an initial judgment after receiving the error frequency and execution time of the target user in the experimental steps. If the ratio of the number of simplified scripts for all remaining experimental steps executed by the target user to the number of simplified scripts for all experimental steps completed by the target user is greater than or equal to P2, then the simplified scripts for all remaining experimental steps operated by the target user are judged whether to continue to execute. Based on the judgment result, it is determined whether to not execute simplified scripts for each subsequent experimental step of the target user starting from the next experimental step executed by the target user. P2 is the preset initial judgment threshold of the experiment.
2. The three-dimensional visualization system for a smart laboratory based on virtual reality according to claim 1, characterized in that, The information acquisition module is used to obtain the name of the experiment to be performed by the target user after the target user enters the target laboratory and completes the virtual reality device wearing, and transmit the experiment name to the experiment rendering terminal.
3. The three-dimensional visualization system for a smart laboratory based on virtual reality according to claim 1, characterized in that, In the process of the simplified evaluation unit determining whether to store the received error frequency and execution time based on the retrieval results, if the error frequency and execution time of the target user in the experimental step are already stored, then the received error frequency and execution time of the target user in the experimental step are not stored simultaneously; otherwise, they are stored.
4. The three-dimensional visualization system for a smart laboratory based on virtual reality according to claim 1, characterized in that, For any given experiment, once the number of error frequencies and execution times corresponding to the experimental step with the largest numerical value stored in the simplified evaluation unit reaches a fixed amount, the steps for determining whether simplification is needed for all steps included in the experiment are as follows: S11: Label all experimental steps required to perform the experiment in ascending order of step number as A1, A2, ..., Aa, where a≥1; S12: Obtain all error frequencies of the stored experimental step A1 and label them as B1, B2, ..., Bb, where b≥1, and the unit is the number of errors; S13: The first evaluation metric D1 for experimental step A1 is obtained by performing deviation analysis on the error frequencies B1, B2, ..., Bb; S14: Obtain the execution duration that is synchronized with the error frequencies B1, B2, ..., Bb, and label them as E1, E2, ..., Eb respectively; S15: Based on the preset time intervals Z1, Z2, ..., Zz, which are the execution times E1, E2, ..., Eb respectively, the corresponding time intervals are matched and the second evaluation quantity D2 of experimental step A1 is calculated according to the preset calculation rules. z is the total number of time intervals preset by the administrator for experimental step A1. The content is as follows: S16: Using the formula Calculate and obtain the simplified evaluation value J1 of experimental step A1. In the formula, G1 is the preset optimal threshold for error frequency under experimental step A1, G2 is the preset optimal threshold for interval time deviation under experimental step A1, and β1 and β2 are preset first and second weight coefficients. S17: Compare the size of J1 and J, where J is the preset comprehensive simplification threshold. If J1≥J, then experimental step A1 is determined to be unnecessary to simplify; otherwise, experimental step A1 is determined to be necessary to simplify. S18: Determine whether experimental steps A2, A3, ..., Aa need to be simplified in sequence according to S11 to S17. After the determination is completed, obtain all experimental steps that need to be simplified and generate simplified information of the experiment based on them.
5. The three-dimensional visualization system for a smart laboratory based on virtual reality according to claim 4, characterized in that, S15, the content of the second evaluation quantity D2 obtained in experimental step A1 is as follows: S151: The total number of execution times belonging to the time interval Z1 obtained from the execution times E1, E2, ..., Eb is calibrated as the time measurement H1 of the time interval Z1 under experimental step A1. H1 reflects the sample size of the time interval Z1 and is used to measure the representativeness of the data. The duration intervals Z1, Z2, ..., Zz are [F1, F1+P1), [F1+P1, F1+2*P1), [F1+2*P1, F1+3*P1), ..., [F1+(z-1)*P1, F1+z*P1], where F1 is the minimum execution time preset by the administrator for experimental step A1, and P1 is the preset duration interval value; S152; Calculate and obtain the duration measurements H2, H3, ..., Hz of the duration intervals Z2, Z3, ..., Zz under experimental step A1 in sequence according to S151; S153: Using the formula Calculate the second evaluation quantity D2 for experimental step A1, where Hi represents the duration measurement of the duration interval Zi under experimental step A1, iopt is the label subscript of the optimal duration interval under experimental step A1, |i-iopt| represents the distance between the current duration interval Zi and the optimal duration interval, and ai is the preset interval weight of the duration interval Zi.
6. The three-dimensional visualization system for a smart laboratory based on virtual reality according to claim 1, characterized in that, The following content determines whether to exclude the simplified script from all subsequent experimental steps for the target user, starting from the next experimental step performed by the target user: S21: When the target user starts to operate the experiment, according to the error frequency and execution duration of all the experimental steps that the target user has currently completed in the experiment, mark all the experimental steps that the target user has currently completed in the experiment as K1, K2, ..., Kk in the order of receipt of their error frequency and execution duration from the front to the back, where k ≥ 1; S22: After the target user starts to operate the experiment, obtain the error frequencies L1, L2, ..., Lk and execution durations M1, M2, ..., Mk of executing the experimental steps K1, K2, ..., Kk received; S23: Utilize the formula Calculate the target user's familiarity with the experiment N1. In the formula, Lm' represents each of the error frequencies L1, L2, ..., Lk after dimensionless processing, Mm' represents each of the execution times M1, M2, ..., Mk after dimensionless processing, and λ1 and λ2 are the preset first and second proportion weights, respectively. Compare the magnitudes of N1 and N. If N1 < N, it is determined that the target user has a good familiarity with the experiment and no action is taken. Otherwise, it is determined that the target user has a poor familiarity with the experiment, and it is determined that starting from the next experimental step executed by the target user, the simplified script is not executed for each subsequent experimental step of the target user. N is a preset determination reference threshold.