Professional and educational integrated decorative lighting professional skill evaluation system and method

Abstract

The invention discloses a production and teaching integrated lamp professional skill assessment system and method, and relates to the technical field of professional skill assessment, and the method comprises the steps: calculating the local conductance change amplitude of each time point in a uniform conductance sequence, taking the maximum value of the difference value of front and back points, defining the maximum value as a micro-crack transition value, calculating composite indexes in a window, and carrying out the screening. Obtaining a transition point set; calculating ghosting intensity, constructing a time-intensity trajectory curve according to a time sequence, screening the time-intensity trajectory curve, generating a ghosting point group, calculating a single-point stability index based on instantaneous frequency and phase synchronization intensity, and calculating a mean value to obtain a comprehensive score; and skill grade judgment is carried out on the comprehensive score. According to the method, the maximum stress peak and the rollback index are combined, the accuracy and robustness of stress point recognition are enhanced, the comprehensiveness and accuracy of evaluation are improved through deep coupling of neurophysiology and phase synchronization, and errors of static analysis are avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of vocational skill assessment, and in particular to a lighting professional skill assessment system and method integrating industry and education. Background Art

[0002] The integration of industry and education, as well as school-enterprise cooperation, have become important means of improving the quality of talent training. Against this backdrop, vocational skills assessment, as a crucial bridge between teaching and employment, is increasingly receiving high attention from education authorities and employers. Technical fields with strong practicality and meticulous craftsmanship, such as lighting, require an intelligent assessment method that can both quantify the operator's actual abilities and meticulously reflect operational details. Currently, mainstream assessment methods mostly rely on manual observation, rating scales, or video review. These methods suffer from strong subjectivity, delayed feedback, and insufficient data value, making it difficult to comprehensively and objectively reflect the operator's true skill level. The development of technologies such as wearable devices, physiological signal processing, motion recognition, and computer vision has provided a new, multi-dimensional, automated approach to skills assessment.

[0003] The existing lighting professional skills evaluation system still has many limitations in practical applications. The evaluation indicators lack the ability to model deep structures and fail to effectively reveal the complex coupling relationship between microcrack transitions, stress responses and motion afterimages during operation. Summary of the Invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a lighting professional skills assessment system and method that integrates industry and education to solve the problem that the evaluation indicators lack deep structure modeling capabilities and fail to effectively reveal the complex coupling relationship between microcrack transitions, stress responses and motion afterimages during the operation process.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a lighting professional skills assessment system integrating industry and education, which includes the following steps:

[0008] The collection module is used to collect and preprocess the conductance and operation video data to generate conductance and operation video sequences, calculate the local conductance change amplitude at each time point in the uniform conductance sequence, take the maximum difference between the previous and next points, define it as the microcrack transition value, calculate the composite index within the window and filter it to obtain the transition point set;

[0009] The screening and scoring module is used to identify the hand bounding box in the operation video sequence, use the coda persistence index combined with pseudo-vorticity to calculate the afterimage intensity, construct and screen the time-intensity trajectory curve according to the chronological order, generate afterimage point groups, divide the dynamic stress intervals, calculate phase synchronization, and calculate the single-point stability index based on the instantaneous frequency and phase synchronization strength and calculate the average value to obtain a comprehensive score;

[0010] The level visualization module is used to judge the skill level based on the comprehensive score, associate the comprehensive score with the corresponding skill level label, generate a structured evaluation report, and build a visual interface to display the evaluation report.

[0011] As a preferred solution of the lighting professional skills assessment system for industry-education integration of the present invention, the composite indicators in the calculation window are screened to obtain a set of transition points, including:

[0012] The conductance sequence is converted into a uniform conductance sequence using linear interpolation. The local conductance change amplitude at each time point in the uniform conductance sequence is calculated. The maximum difference between the previous and next points is taken and defined as the microcrack transition value. The one-sided difference is calculated using the one-sided difference method. The transition threshold is set using the standard deviation. The one-sided difference values ​​with a sequence greater than the transition threshold are screened to generate a transition value sequence.

[0013] The dynamic sliding window length is set using the adaptive rate of change method, and the maximum stress peak and setback index within the window are calculated;

[0014] Based on the maximum stress peak and the setback index, the composite index within the window is calculated, and the time threshold is set using the mean method. The transition points corresponding to the composite index greater than the time threshold are screened to obtain the transition point set.

[0015] As a preferred solution of the lighting professional skill assessment system for industry-education integration of the present invention, the method of constructing a time-intensity trajectory curve and screening it to generate an afterimage point group includes:

[0016] Use the pre-trained YOLO model to identify the manipulation video sequence, output the hand bounding box, perform non-maximum suppression on the hand bounding box to obtain the hand region image, use the key point detection model MediaPipe to identify the key point coordinates of the hand region image, use affine transformation to map the key point coordinates from the cropped area back to the coordinates of the manipulation video frame, and calculate the mean of the coordinates of the manipulation video frame as the center coordinates;

[0017] The velocity vector and the velocity components in the x and y directions are calculated using the difference method. The decay length is calculated using the exponential decay model. The decay length is converted to the number of frames using time scale conversion and normalized. The coda persistence index is calculated using linear decay.

[0018] Based on the central coordinates, the pseudo-vorticity is calculated, and the afterimage intensity is calculated using the wake persistence index combined with the pseudo-vorticity. Then, a time-intensity trajectory curve is constructed in chronological order.

[0019] The fixed threshold method is used to set the detection threshold, and the afterimage intensities greater than the detection threshold are screened to generate afterimage point groups.

[0020] As a preferred solution of the lighting professional skills assessment system for industry-education integration of the present invention, the calculation of the single-point stability index and the average value to obtain a comprehensive score includes:

[0021] Extract the transition points from the transition point set, calculate the instantaneous frequency of the mean conductance sequence at the transition point, divide the dynamic stress interval, extract the afterimage intensity from the afterimage point group within the dynamic stress interval, and calculate the phase synchronization;

[0022] Based on the instantaneous frequency and phase synchronization strength, the single-point stability index is calculated, and the average stability index of all transition points is calculated to obtain a comprehensive score.

[0023] As a preferred solution of the lighting professional skills assessment system for industry-education integration of the present invention, the skill level judgment of the comprehensive score and the generation of a structured assessment report include:

[0024] Collect historical comprehensive scores and use the percentile method to set threshold values. Use physical feature threshold mapping to determine skill levels based on the comprehensive scores and generate skill level labels corresponding to the comprehensive scores.

[0025] Associate the comprehensive score with the corresponding skill level label to generate a structured assessment report.

[0026] As a preferred solution of the lighting professional skills assessment system for industry-education integration of the present invention, the construction of a visual interface to display the assessment report includes:

[0027] Use the front-end framework React.js to build a visual interface to visualize the evaluation report;

[0028] Users who have passed real-name verification are allowed to access the information.

[0029] As a preferred solution of the lighting professional skill assessment system for industry-education integration of the present invention, the collecting of conductance and operation video data and the generation of conductance and operation video sequences include:

[0030] Wearable bioelectrodes and cameras are used to collect the operator's conductance and operation video data. The conductance and operation video data are synchronized using the network time protocol. The conductance is denoised using low-pass filtering. The operation video is corrected for illumination using histogram equalization. The conductance and operation video data are normalized separately and sorted in chronological order to generate conductance and operation video sequences.

[0031] In a second aspect, the present invention provides a lighting professional skills assessment method integrating industry and education, comprising:

[0032] Conductivity and operation video data are collected and preprocessed to generate conductance and operation video sequences. The local conductance change amplitude at each time point in the uniform conductance sequence is calculated. The maximum difference between the previous and next points is taken, which is defined as the microcrack transition value. The composite index within the window is calculated and screened to obtain a transition point set.

[0033] Identify the hand bounding box in the manipulation video sequence, use the coda persistence index combined with pseudo-vorticity to calculate the afterimage intensity, construct and filter the time-intensity trajectory curve according to the chronological order, generate afterimage point groups, divide the dynamic stress interval, calculate phase synchronization, and calculate the single-point stability index based on the instantaneous frequency and phase synchronization strength. Calculate the average value to obtain a comprehensive score;

[0034] Determine the skill level based on the comprehensive score, associate the comprehensive score with the corresponding skill level label, generate a structured evaluation report, and build a visual interface to display the evaluation report.

[0035] The beneficial effects of the present invention are as follows: the present invention enhances the accuracy and robustness of stress point identification by combining the maximum stress spike and the retraction index, improves the comprehensiveness and accuracy of the evaluation through the deep coupling of neurophysiology and phase synchronization, and avoids the errors of static analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0037] Figure 1 This is a flowchart of the lighting professional skills assessment system for industry-education integration in Example 1;

[0038] Figure 2 This is a schematic diagram of the lighting professional skills assessment method for industry-education integration in Example 1. DETAILED DESCRIPTION

[0039] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0040] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0041] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0042] Example 1, reference Figure 1 , which is the first embodiment of the present invention, provides a lighting professional skills assessment system integrating industry and education, including the following steps:

[0043] S1, a collection module, is used to collect and preprocess the conductance and operation video data, generate conductance and operation video sequences, calculate the local conductance change amplitude at each time point in the uniform conductance sequence, take the maximum difference between the previous and next points, define it as the microcrack transition value, calculate the composite index within the window and perform screening to obtain the transition point set;

[0044] Specifically, collecting conductance and operation video data and generating conductance and operation video sequences include:

[0045] Wearable bioelectrodes and cameras are used to collect the operator's conductance and operation video data. The conductance and operation video data are synchronized using the network time protocol. The conductance is denoised using low-pass filtering. The operation video is corrected for illumination using histogram equalization. The conductance and operation video data are normalized separately and sorted in chronological order to generate conductance and operation video sequences.

[0046] Through multimodal synchronous acquisition and preprocessing, high-precision timing alignment of motion and physiological signals and environmental interference suppression are achieved, significantly improving data quality and evaluation robustness, and ensuring data reliability through NTP and preprocessing technology.

[0047] Furthermore, the composite index within the window is calculated and filtered to obtain a set of transition points, including:

[0048] The conductance series is converted into a uniform conductance series using linear interpolation. The local conductance change amplitude at each time point in the uniform conductance series is calculated. The maximum value of the difference between the previous and next points is taken and defined as the microcrack transition value. The formula is:

[0049] F i =max(|g i+1 -g i |,|g i -g i-1 |),

[0050] Among them F i is the microcrack transition value at the i-th time point, g i is the conductance value at the i-th time point;

[0051] Use the one-sided difference method to calculate the one-sided difference, use the standard deviation to set the transition threshold, and screen the one-sided differences that are greater than the transition threshold to generate a transition value sequence. The formula is:

[0052] F1=|g2-F1|,

[0053] F T =|g T -g T-1 |,

[0054] Where 1 and T are boundary points, which are set using statistical analysis;

[0055] The dynamic sliding window length is set using the adaptive rate of change method, and the maximum stress peak and setback index within the window are calculated using the following formula:

[0056]

[0057] C j =max(F j ,F j+1 ,…,F j+ω-1 ),

[0058]

[0059] Among them C j is the maximum stress peak in the jth window, F j is the transition value in the jth window, ω is the length of the dynamic sliding window, α is the adjustment coefficient, which determines the sensitivity to fluctuations and is set using the empirical parameter adjustment method, std(G) is the standard deviation of the uniform conductance sequence, round(·) is rounded to the nearest integer, G is the mean of the uniform conductance sequence, and B j is the backoff index in the jth window, F j+k is the transition value within the j+kth window (if the window exceeds the boundary point (j+ω-1>T), it is only accumulated to T). The formula is:

[0060]

[0061] Based on the maximum stress peak and the setback index, the composite index within the window is calculated. The time threshold is set using the mean method. The transition points corresponding to the composite index greater than the time threshold are screened to obtain the transition point set. The formula is:

[0062]

[0063] Among them S j is the composite index in the j-th window, is the mean of the backoff index in the j-th window.

[0064] Linear interpolation is used to resample the data into an equidistant sequence to ensure time consistency. After interpolation processing, the calculation error caused by the "jump" in the time domain can be eliminated, and the robustness of subsequent differential and sliding window analysis can be enhanced. Through dynamic stress point detection, high-precision and personalized stress point extraction is achieved, which significantly improves the adaptability and accuracy of the evaluation system. The combination of microcrack transition value and backoff index comprehensively characterizes the instantaneous and continuous characteristics, unexpectedly enhancing the system's adaptability to complex task scenarios. Fixed window analysis often faces the "misalignment" problem, that is, the window length does not match the signal fluctuation period, resulting in feature extraction distortion. The dynamic window mechanism can Matching local fluctuation frequencies improves the timeliness and accuracy of transition point identification. Traditional conductivity analysis models often focus solely on "peak" or "amplitude" and lack modeling of behavioral persistence and reversibility. This method incorporates regression trends into its assessment, effectively avoiding misjudging short-term disturbances as abnormal operations and improving recognition accuracy. It is particularly suitable for judging operational consistency and response stability. This screening mechanism comprehensively considers instantaneous intensity and subsequent trends to avoid missed or false detections caused by a single indicator. The comprehensive modeling of signal disturbance patterns using composite indicators makes the transition point set more representative, providing high-value temporal anchor points for subsequent skill movement analysis or mental workload assessment.

[0065] S2, a screening and scoring module, is used to identify the hand bounding box in the manipulation video sequence, calculate the afterimage intensity using the coda persistence index combined with the pseudo-vorticity, construct and screen the time-intensity trajectory curve in chronological order, generate afterimage point groups, divide the dynamic stress intervals, calculate phase synchronization, and calculate the single-point stability index based on the instantaneous frequency and phase synchronization strength and calculate the average value to obtain a comprehensive score;

[0066] Specifically, a time-intensity trajectory curve is constructed and screened to generate a residual image point group, including:

[0067] Use the pre-trained YOLO model to identify the operation video sequence and output the hand bounding box (indicating the coordinates of the upper left and lower right corners of the hand area). Perform non-maximum suppression on the hand bounding box (removing redundant bounding boxes and retaining the box with the highest confidence) to obtain the hand area image.

[0068] Use the key point detection model MediaPipe to identify the key point coordinates of the hand area image, and use affine transformation to map the key point coordinates from the cropped area back to the coordinates of the operation video frame. The formula is:

[0069] x full =x min +x roi ·o′,

[0070] y full =y min +y roi o,

[0071] where x full and y full To map back to the key point coordinates of the operation video frame, x min and y min is the coordinate of the upper left corner of the hand area image in the operation video frame, x roi and y roi is the key point coordinate, o ′ and o are the width and height of the hand region image respectively;

[0072] Calculate the mean of the coordinates of the operation video frame as the center coordinate;

[0073] The velocity vector and the velocity components in the x and y directions are calculated using the difference method. The formula is:

[0074]

[0075]

[0076]

[0077] where v x (t) and v y (t) are the velocity components in the x and y directions at time t, respectively. c (t) and y c (t) is the center coordinate at time t, which represents the center coordinate in the x and y directions respectively. Δt is the motion analysis frame interval, which is set using the frame rate downsampling method. is the velocity vector;

[0078] The decay length is calculated using the exponential decay model, as follows:

[0079]

[0080] where λ t is the decay length at time t, k′ is the proportionality constant, which is set by experimental adjustment method and is used to adjust the relationship between decay length and speed;

[0081] The decay length is converted to the number of frames using time scale conversion and normalized using the formula:

[0082]

[0083] where N t is the number of decay frames at time t, is the global average velocity, f s is the frame rate, which indicates the number of frames collected per second;

[0084] The coda persistence index is calculated using linear decay, as follows:

[0085]

[0086] where θ t is the coda duration index at time t, N′ t is the normalized attenuation frame number, a is the time step (frame difference), which represents the time interval between the current frame t and the future frame t+a;

[0087] Based on the central coordinates, the pseudo-vorticity is calculated using the formula:

[0088]

[0089] where w t is the pseudo-vorticity at time t;

[0090] The afterimage intensity is calculated using the coda persistence index combined with the pseudo-vorticity, and a time-intensity trajectory curve is constructed in chronological order. The formula is:

[0091]

[0092] where R t is the afterimage intensity at time t, is the global average coda persistence index;

[0093] The fixed threshold method is used to set the detection threshold, and the afterimage intensities greater than the detection threshold are screened to generate afterimage point groups.

[0094] The introduction of YOLO and MediaPipe models solves the information disconnection problem between local detection and global evaluation, providing high-quality input for subsequent speed and afterimage calculations. Afterimage analysis is often used in motion image processing (such as trajectory tracking), but combining it with hand motion recognition is still innovative, especially the addition of pseudo-vorticity indicators, which enables the intensity to not only reflect the continuity of motion but also characterize the complexity of rotation. Compared with traditional screening methods based on key frames or speed thresholds, afterimage intensity is more expressive in modeling operating habits (such as whether there is repeated dragging or rotation hesitation).

[0095] Furthermore, the single-point stability index is calculated and the mean is calculated to obtain a comprehensive score, including:

[0096] Extract the transition points from the transition point set, calculate the instantaneous frequency of the mean conductance sequence at the transition point, and divide the dynamic stress interval The formula is:

[0097]

[0098] Among them F z is the instantaneous frequency of the zth transition point, t z is the timestamp of the z-th transition point, Δt ′ is the sampling time interval, which is set using the sampling synchronization method, G(t) is the mean conductance sequence at time t, and J z is the length of the stress interval of the z-th transition point;

[0099] In the dynamic stress range, the afterimage intensity is extracted from the afterimage point group and the phase synchronization is calculated using the formula:

[0100]

[0101] Among them, P z is the phase synchronization of the zth transition point, N z is the number of sampling points in the interval;

[0102] Based on the instantaneous frequency and phase synchronization strength, the single-point stability index is calculated as follows:

[0103]

[0104] Among them S z is the single point stability index of the z-th transition point;

[0105] Calculate the average stability index of all transition points to get the comprehensive score Q i .

[0106] By constructing synchronization intervals and introducing the concept of "phase synchronization", signal linkage modeling is realized from the perspective of time structure, and the conductance and motion trajectory coupling index is introduced as the quantitative basis to avoid subjective bias. It not only retains the behavioral dimension, but also integrates the physiological response intensity. It is suitable for various complex scenarios such as high-pressure operations, stress training, and control ability assessment.

[0107] S3, the level visualization module, is used to determine the skill level based on the comprehensive score, associate the comprehensive score with the corresponding skill level label, generate a structured evaluation report, and build a visual interface to display the evaluation report;

[0108] Specifically, the comprehensive score is used to determine the skill level and generate a structured assessment report, including:

[0109] Collect historical comprehensive scores and use the percentile method to set threshold values ​​(0.95, 0.80, 0.60), use physical feature threshold mapping to judge the skill level of the comprehensive scores, and generate skill level labels corresponding to the comprehensive scores, including Q i >0.95, the level is advanced skill, if 0.8 i ≤0.95, the level is good skill, if 0.6 i ≤0.8, the level is qualified skill, if Q i If ≤0.6, the skill level is unqualified;

[0110] Associate the comprehensive score with the corresponding skill level label to generate a structured assessment report.

[0111] The threshold is dynamically adjusted as historical samples are updated to avoid grade misjudgment caused by the use of static dividing values. The comprehensive score is a fusion of multiple complex factors such as motion afterimages and phase synchronization, and cannot be quantified by a simple threshold. The percentile method can reflect the relative position, effectively adapt to high-dimensional input distributions, avoid grade compression or expansion problems, and improve the user-friendliness of the evaluation system. Structured information supports multi-platform analysis and display on the Web, mobile, and even VR devices.

[0112] Furthermore, a visual interface is constructed to display the evaluation report, including:

[0113] Use the front-end framework React.js to build a visual interface to visualize the evaluation report;

[0114] Users who have passed real-name verification are allowed to access the information.

[0115] Users can intuitively view the scoring curve, grade labels and scoring analysis charts to enhance the interactive experience. Real-name binding can prevent anonymous viewing of other people's reports, which is especially suitable for sensitive scenarios such as medical care, security, and education.

[0116] ​​Example 2, reference Figure 2 The second embodiment of the present invention is a lighting professional skills assessment method integrating industry and education, comprising:

[0117] Conductivity and operation video data are collected and preprocessed to generate conductance and operation video sequences. The local conductance change amplitude at each time point in the uniform conductance sequence is calculated. The maximum difference between the previous and next points is taken, which is defined as the microcrack transition value. The composite index within the window is calculated and screened to obtain a transition point set.

[0118] Identify the hand bounding box in the manipulation video sequence, use the coda persistence index combined with pseudo-vorticity to calculate the afterimage intensity, construct and filter the time-intensity trajectory curve according to the chronological order, generate afterimage point groups, divide the dynamic stress interval, calculate phase synchronization, and calculate the single-point stability index based on the instantaneous frequency and phase synchronization strength. Calculate the average value to obtain a comprehensive score;

[0119] Determine the skill level based on the comprehensive score, associate the comprehensive score with the corresponding skill level label, generate a structured evaluation report, and build a visual interface to display the evaluation report.

[0120] This embodiment also provides a computer device, which is suitable for the lighting professional skills assessment method of industry-education integration, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the lighting professional skills assessment method of industry-education integration proposed in the above embodiment.

[0121] The computer device may be a terminal, comprising a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a button, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0122] This embodiment also provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the lighting professional skills assessment method for realizing the integration of industry and education as proposed in the above embodiment; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, disk or optical disk.

[0123] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A lighting professional skills assessment system integrating industry and education, characterized by: The steps include: The collection module is used to collect and preprocess the conductance and operation video data to generate conductance and operation video sequences, calculate the local conductance change amplitude at each time point in the uniform conductance sequence, take the maximum difference between the previous and next points, define it as the microcrack transition value, calculate the composite index within the window and filter it to obtain the transition point set; The screening and scoring module is used to identify the hand bounding box in the operation video sequence, use the coda persistence index combined with pseudo-vorticity to calculate the afterimage intensity, construct and screen the time-intensity trajectory curve according to the chronological order, generate afterimage point groups, divide the dynamic stress intervals, calculate phase synchronization, and calculate the single-point stability index based on the instantaneous frequency and phase synchronization strength and calculate the average value to obtain a comprehensive score; The level visualization module is used to judge the skill level based on the comprehensive score, associate the comprehensive score with the corresponding skill level label, generate a structured evaluation report, and build a visual interface to display the evaluation report.

2. The lighting professional skills assessment system integrating industry and education as claimed in claim 1, characterized in that: The composite index within the calculation window is screened to obtain a set of transition points, including: The conductance sequence is converted into a uniform conductance sequence using linear interpolation. The local conductance change amplitude at each time point in the uniform conductance sequence is calculated. The maximum difference between the previous and next points is taken and defined as the microcrack transition value. The one-sided difference is calculated using the one-sided difference method. The transition threshold is set using the standard deviation. The one-sided difference values ​​with a sequence greater than the transition threshold are screened to generate a transition value sequence. The dynamic sliding window length is set using the adaptive rate of change method, and the maximum stress peak and setback index within the window are calculated; Based on the maximum stress peak and the setback index, the composite index within the window is calculated, and the time threshold is set using the mean method. The transition points corresponding to the composite index greater than the time threshold are screened to obtain the transition point set.

3. The lighting professional skills assessment system integrating industry and education as claimed in claim 2, characterized in that: The method of constructing a time-intensity trajectory curve and screening it to generate an afterimage point group includes: Use the pre-trained YOLO model to identify the manipulation video sequence, output the hand bounding box, perform non-maximum suppression on the hand bounding box to obtain the hand region image, use the key point detection model MediaPipe to identify the key point coordinates of the hand region image, use affine transformation to map the key point coordinates from the cropped area back to the coordinates of the manipulation video frame, and calculate the mean of the coordinates of the manipulation video frame as the center coordinates; The velocity vector and the velocity components in the x and y directions are calculated using the difference method. The decay length is calculated using the exponential decay model. The decay length is converted to the number of frames using time scale conversion and normalized. The coda persistence index is calculated using linear decay. Based on the central coordinates, the pseudo-vorticity is calculated, and the afterimage intensity is calculated using the wake persistence index combined with the pseudo-vorticity. Then, a time-intensity trajectory curve is constructed in chronological order. The fixed threshold method is used to set the detection threshold, and the afterimage intensities greater than the detection threshold are screened to generate afterimage point groups.

4. The lighting professional skills assessment system integrating industry and education as claimed in claim 3 is characterized by: The calculation of the single-point stability index and the average value to obtain a comprehensive score includes: Extract the transition points from the transition point set, calculate the instantaneous frequency of the mean conductance sequence at the transition point, divide the dynamic stress interval, extract the afterimage intensity from the afterimage point group within the dynamic stress interval, and calculate the phase synchronization; Based on the instantaneous frequency and phase synchronization strength, the single-point stability index is calculated, and the average stability index of all transition points is calculated to obtain a comprehensive score.

5. The lighting professional skills assessment system integrating industry and education as claimed in claim 4 is characterized by: The comprehensive score is used to determine the skill level and generate a structured assessment report, including: Collect historical comprehensive scores and use the percentile method to set threshold values. Use physical feature threshold mapping to determine skill levels based on the comprehensive scores and generate skill level labels corresponding to the comprehensive scores. Associate the comprehensive score with the corresponding skill level label to generate a structured assessment report.

6. The lighting professional skills assessment system integrating industry and education as claimed in claim 5, characterized in that: The construction of a visual interface to display the assessment report includes: Use the front-end framework React.js to build a visual interface to visualize the evaluation report; Users who have passed real-name verification are allowed to access the information.

7. The lighting professional skills assessment system integrating industry and education as claimed in claim 6, characterized in that: The collecting of conductance and operation video data and generating conductance and operation video sequences comprises: Wearable bioelectrodes and cameras are used to collect the operator's conductance and operation video data. The conductance and operation video data are synchronized using the network time protocol. The conductance is denoised using low-pass filtering. The operation video is corrected for illumination using histogram equalization. The conductance and operation video data are normalized separately and sorted in chronological order to generate conductance and operation video sequences.

8. A lighting professional skills assessment method for integrating industry and education, used to implement the lighting professional skills assessment system for integrating industry and education as described in any one of claims 1 to 7, characterized in that: include: Conductivity and operation video data are collected and preprocessed to generate conductance and operation video sequences. The local conductance change amplitude at each time point in the uniform conductance sequence is calculated. The maximum difference between the previous and next points is taken, which is defined as the microcrack transition value. The composite index within the window is calculated and screened to obtain a transition point set. Identify the hand bounding box in the manipulation video sequence, use the coda persistence index combined with pseudo-vorticity to calculate the afterimage intensity, construct and filter the time-intensity trajectory curve according to the chronological order, generate afterimage point groups, divide the dynamic stress interval, calculate phase synchronization, and calculate the single-point stability index based on the instantaneous frequency and phase synchronization strength. Calculate the average value to obtain a comprehensive score; Determine the skill level based on the comprehensive score, associate the comprehensive score with the corresponding skill level label, generate a structured evaluation report, and build a visual interface to display the evaluation report.

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