Real-time diagnosis system of professional stage lighting control system

Abstract

The invention discloses a real-time diagnosis system for a professional stage lighting control system, and belongs to the technical field of stage lighting, and the system comprises a health monitoring module which is used for carrying out the health state evaluation of equipment; the behavior verification module is used for verifying the execution behavior of the equipment; the output verification module is used for verifying a result actually output by the equipment; the fault tracing module is used for judging a fault type and judging upstream abnormity; and the feedback repairing module is used for generating feedback according to the fault type and sending a repairing action instruction to the equipment meeting the repairable condition. According to the invention, stable operation and quick response of the light control system in the stage performance environment are realized through full-process variable tracking, dimension normalization and explanatory factor introduction.

Description

Technical Field

[0001] The invention belongs to the technical field of stage lighting, and in particular relates to a real-time diagnosis system for a professional stage lighting control system. Background Art

[0002] Current professional stage lighting systems generally rely on digital communication protocols (such as DMX512, Art-Net, and sACN) to achieve unified scheduling and control of various lamps, lifting devices, and optical components. As the scale of lighting systems in large-scale performances continues to expand, the complexity of equipment distribution and the network topology level have increased significantly, and the system has placed higher requirements on the integrity of command transmission, the consistency of equipment execution, and the accuracy of light output. In actual applications, common problems include: signals failing to be successfully delivered due to link aging or abnormal connections, although the equipment receives commands, the physical movement deviation is significant, and the optical output deviates from the preset effect. Such problems are often causal and manifest in different forms, making it difficult for traditional systems to determine the root cause of the fault through a single link or single variable.

[0003] Existing diagnostic methods often focus on determining whether a device is "online" or whether its echo signal is "responsive." They lack dynamic verification of the device's execution process and perception of the resulting light output. This makes it difficult for the system to accurately determine whether the device has truly completed its intended action, or to determine whether light output anomalies are caused by problems in the upstream link or by hardware damage to the light source itself. Furthermore, most current systems fail to establish an effective data closed loop, lacking a mechanism to support the entire process from anomaly detection to policy execution and feedback on results. This makes it impossible to provide a viable operational response or automated repair methods immediately after a problem occurs.

[0004] To this end, we propose a real-time diagnostic system for professional stage lighting control systems to solve the above problems. Summary of the Invention

[0005] The purpose of the present invention is to solve the problem in the prior art that the cause of an abnormality cannot be determined, and to propose a real-time diagnosis system for a professional stage lighting control system.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A real-time diagnostic system for a professional stage lighting control system, comprising:

[0008] A health monitoring module is used to evaluate the health status of the device. The health status is evaluated through the device's stability index and effective response rate. The stability index is obtained by calculating the average time interval between sending a probe signal to the device and receiving an echo signal. The effective response rate is obtained by calculating the ratio of the echo signal to the probe signal.

[0009] A behavior verification module is used to verify the execution behavior of the device. The verification is completed by calculating the device's behavior execution error and drift error. The behavior execution error is obtained by comparing a preset execution trajectory with an actual execution trajectory. The actual execution trajectory is obtained by performing attitude calculation using a Kalman filter on the actual execution data collected by the sensor. The drift error is obtained by comparing the device's attitude angle within a preset time window.

[0010] An output verification module is used to verify the actual output of the device. This verification is accomplished by calculating the device's light efficiency deviation score, which is obtained by weighted calculation of the deviation between the actual data collected from the device and the preset data. A determination factor is also introduced to determine the cause of the error. A maximum value for the determination factor indicates the highest probability that the deviation is caused by abnormal operation rather than the light source itself.

[0011] A fault tracing module is used to determine the fault type and upstream anomaly. The upstream anomaly is determined by calculating an upstream anomaly score, which is calculated by weighting the behavior execution error, drift error, device stability index, effective response rate, and a determination factor. The fault type is determined based on the upstream anomaly score and light efficiency deviation score, and a fault type label is output.

[0012] The feedback repair module is used to generate feedback according to the fault type and send repair action instructions to the equipment that meets the repairable conditions. After the repair action is completed, other modules are used to complete the detection again and output the repair result status.

[0013] Preferably, when the stability index and effective response rate of the output device in the health monitoring module are both higher than the preset threshold, the module goes to the behavior verification module to perform the next action; otherwise, the module ends directly and is marked as not receiving the instruction.

[0014] Preferably, a dynamic delay function is set in the behavior execution error described in the behavior verification module, and the dynamic delay function is defined as a time lag between the actual execution trajectory and the preset execution trajectory that is less than a threshold value, which is used to indicate that although the device has reached the target angle, it takes more than the preset time.

[0015] Preferably, when the behavior execution error in the behavior verification module is higher than a threshold and / or the drift error is higher than a threshold, it is determined that the execution has failed or is unstable, and the output verification module is entered for cross-validation.

[0016] Preferably, the actual data of the device includes light intensity, color vector, main wavelength and strobe frequency.

[0017] Preferably, a spatial matching weight item is also introduced into the light efficiency deviation score. The spatial matching weight item is calculated based on the field of view matching degree of the light beam in the corresponding viewing angle area, according to the lamp posture and the sensor projection area, and is used to suppress erroneous judgments caused by viewing angle deviation.

[0018] Preferably, the fault type label is determined according to the following rules:

[0019] When the stability index is less than a first threshold or the effective response rate is lower than the first threshold, it is determined to be a signal failure;

[0020] When the behavior execution error is greater than the second threshold or the drift error is greater than the second threshold, it is determined to be an action failure;

[0021] When the light efficiency deviation score is greater than the third threshold and the upstream abnormality score is less than the fourth threshold, it is determined to be an optical fault;

[0022] When the light efficiency deviation score is less than the third threshold and the upstream abnormality score is less than the fourth threshold, it is determined to be normal operation;

[0023] When a situation other than the above occurs, it is determined to be a mixed fault.

[0024] Preferably, the repairable condition in the feedback repair module is that the fault type label is a signal fault and / or an action fault and the upstream anomaly score is greater than a repair threshold.

[0025] In summary, the technical effects and advantages of the present invention are as follows: the present invention implements link health status assessment based on a compatible detection mechanism within the protocol to ensure signal delivery; then, the device response process is modeled and error calculated through the attitude sensor to quantify the quality of action completion; then, the output light beam is measured and compared in combination with the optical acquisition module to determine the light efficiency deviation; and then, the source of the anomaly is classified and interpreted by constructing a causal consistency scoring function to achieve accurate positioning of the fault type; the system automatically triggers repair instructions based on the fault type and credibility score, and judges the repair effectiveness through indicator recovery, completing a closed-loop execution process from diagnosis to control. The entire system constructs a highly reproducible, real-time, and engineering deployment-feasible diagnosis and recovery mechanism through technical means such as full-process variable tracking, dimensional normalization, and the introduction of explanatory factors, achieving stable operation and rapid response of the lighting control system in the stage performance environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 Schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION

[0027] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0028] like Figure 1 As shown, a real-time diagnostic system for a professional stage lighting control system includes:

[0029] A health monitoring module is used to evaluate the health status of the device. The health status is evaluated through the device's stability index and effective response rate. The stability index is obtained by calculating the average time interval between sending a probe signal to the device and receiving an echo signal. The effective response rate is obtained by calculating the ratio of the echo signal to the probe signal.

[0030] A behavior verification module is used to verify the execution behavior of the device. The verification is completed by calculating the device's behavior execution error and drift error. The behavior execution error is obtained by comparing a preset execution trajectory with an actual execution trajectory. The actual execution trajectory is obtained by performing attitude calculation using a Kalman filter on the actual execution data collected by the sensor. The drift error is obtained by comparing the device's attitude angle within a preset time window.

[0031] An output verification module is used to verify the actual output of the device. This verification is accomplished by calculating the device's light efficiency deviation score, which is obtained by weighted calculation of the deviation between the actual data collected from the device and the preset data. A determination factor is also introduced to determine the cause of the error. A maximum value for the determination factor indicates the highest probability that the deviation is caused by abnormal operation rather than the light source itself.

[0032] A fault tracing module is used to determine the fault type and upstream anomaly. The upstream anomaly is determined by calculating an upstream anomaly score, which is calculated by weighting the behavior execution error, drift error, device stability index, effective response rate, and a determination factor. The fault type is determined based on the upstream anomaly score and light efficiency deviation score, and a fault type label is output.

[0033] The feedback repair module is used to generate feedback according to the fault type and send repair action instructions to the equipment that meets the repairable conditions. After the repair action is completed, other modules are used to complete the detection again and output the repair result status.

[0034] The specific implementation steps of this system are as follows:

[0035] Step 1: Signal Link Health Monitoring and Echo Detection

[0036] In professional stage lighting control systems, most lamps are connected to the master control platform via wired DMX512, Art-Net, or sACN protocols, forming a complex star or serial cascade topology. Because performance venues are often temporary, with varying wiring lengths and numerous relay nodes, problems such as poor connector contact, signal delays, and timing drift are very common in the link. This step aims to perform a real-time health assessment of each signal link segment using a technical approach based on an echo response mechanism, outputting a "link stability indicator" that can be used to determine subsequent device behavior. This mechanism can operate continuously without interrupting the performance process.

[0037] The core logic of this step is composed of the echo interactive communication mechanism between the master control platform and the lamps. The master control platform regularly broadcasts to each registered lamp device through the DMX channel or UDP broadcast (taking Art-Net as an example). i A diagnostic probe frame is broadcast. This frame structure conforms to the existing communication protocol standard and includes a unique diagnostic identifier and timestamp in the data field. All devices receiving this diagnostic frame must package the original frame content along with the reception time within a fixed response latency window (set during system initialization, for example, 5ms) and return it to the master via the original path. The system uses the master's clock as a global reference and uses a high-precision timer (e.g., a hardware-level 100μs time slice) to record the round-trip transmission and reception time difference of the frame, which is recorded as the single echo delay.

[0038] To enhance robustness against device response jitter, the master controller continuously sends N detection frames to each device (usually 5 to 10 times), records the round-trip time for each, and calculates the following stability index:

[0039]

[0040] in:

[0041] R i Indicates device d i The echo stability index;

[0042] is the time when the kth signal is sent (recorded by the main control system);

[0043] is the corresponding echo signal receiving time (recorded by the main control system);

[0044] N is the number of detection signals sent in a detection period, usually 5 to 10.

[0045] At the same time, the system also counts the response frequency of each device within the period, which is defined as the effective reception rate P i :

[0046]

[0047] in:

[0048] P i Indicates device d i The effective response ratio;

[0049] M i Indicates the number of response frames successfully returned by the device in the current cycle;

[0050] Q represents the total number of detection frames set by the system, which is usually equal to N.

[0051] For example, during one detection cycle, the master controller sends 10 frames of diagnostic signals to lamp d3 and only successfully receives 7 echoes. Then its P3=0.7, which is lower than the set threshold of 0.85, and will be marked as "unstable signal reception".

[0052] The above data was collected through:

[0053] The signal scheduling module of the main control platform automatically broadcasts the detection frame (based on the protocol stack);

[0054] The network control chip embedded in each device (such as WIZnet module, ESP32, STM32 built-in MAC);

[0055] All timing data is uniformly calibrated by the high-precision clock module in the main control system (usually using a crystal oscillator to stabilize within ±50ppm);

[0056] The data is cached into the main controller's ring buffer through a dedicated communication thread for subsequent analysis module calls.

[0057] All data is acquired through non-intrusive communication, which does not affect the device's regular command channels and does not require additional hardware burden. It is suitable for batch deployment in large-scale stage engineering scenarios.

[0058] This step outputs two variables for use in the next step:

[0059] R i :device d i Signal echo stability index in the current period;

[0060] P i :device d i The effective signal response ratio.

[0061] Step 2: Device behavior verification

[0062] This step is used to verify the execution behavior of professional stage lighting equipment in real time. In a complex performance environment, lighting equipment usually performs physical actions such as rotation, zoom, lifting, etc. in response to the instructions issued by the control system. However, even if the device has received the signal (via R in step 1), i and P i There are still problems such as equipment execution anomalies, movement delays, and partial movements that are not in place. These anomalies may not appear immediately at the visual effect level, but will cause serious interference to stage performance and timing coordination. Traditional systems lack a feedback mechanism for the equipment execution process and cannot provide accurate warnings when the action is not completed or fails. This step proposes a motion execution deviation evaluation mechanism that combines motion trajectory modeling, dynamic filtering, and residual constraints to solve the above problems and form an objective and computable criterion for "whether the instruction is completed."

[0063] enter:

[0064] R i :device d i Signal link stability index;

[0065] P i :device d i effective response rate.

[0066] Only when R i >0.85 and P i Only devices with a value greater than 0.85 will be considered by the system to have received a valid signal and will then enter the action verification process. Otherwise, this step will be skipped and the device will be directly marked as "not receiving the command."

[0067] When the device d i Receive the action command from the control system (such as rotating the lamp head to a specified angle ), the system continuously collects actual motion data from the device within the action window T. The data comes from the IMU module installed inside each lamp or next to the bracket. Common sensors include MPU6050, ICM-42688, LSM6DS3, etc., which are equipped with a three-axis gyroscope and a three-axis accelerometer. This data is uploaded to the main control system at a fixed sampling frequency (usually 100Hz) and the attitude is calculated through Kalman filtering to form a complete attitude trajectory θ i (t).

[0068] To quantify whether the device's action is completed, the system calculates its trajectory deviation index E i At the same time, a dynamic delay penalty term is introduced to strengthen the distinction between "action delayed but eventually completed" and "action not completed". The definition is as follows:

[0069]

[0070] in:

[0071] E i :device d i Comprehensive behavioral execution deviation;

[0072] θ i (t): actual angular trajectory of the device at time t calculated from the IMU;

[0073] The target motion trajectory set in the system control logic;

[0074] D i (t): represents the dynamic delay function of the device in reaching the target angle, defined as i (t) with The time lag that differs less than the threshold δ;

[0075] λ: Delay penalty weight, reflecting the sensitivity of action timing (usually set to 2-5 in stage performances).

[0076] Specifically, D i A large (t) value indicates that the device reached the target angle but took too long. The system therefore increases the penalty, improving the accuracy of identifying time-sensitive actions. For example, in a fast-paced rhythm light action, a delay of 300ms would still be considered unsuccessful.

[0077] In addition, considering that stage equipment may have jitter errors caused by hardware aging, load interference, etc., the system introduces a "steady-state drift penalty term" to the sensor data, which is based on the drift residual S after the action is completed t>T i Express:

[0078]

[0079] in:

[0080] S i :device d i The steady-state attitude drift index reflects whether it remains unstable after the action is completed;

[0081] Δt: Drift observation window after the action is completed, typically set to 0.5 seconds;

[0082] dθ i (t) / dt: Approximated by the filtered attitude angle derivative to avoid noise amplification.

[0083] After the main control system collects the IMU data uniformly, it compares and analyzes it with the target trajectory and finally obtains E i With S iTwo quantitative indicators. They reflect whether the device completes the action according to the expected trajectory and whether it enters a stable state after completion. The system judges the execution quality by combining the two indicators:

[0084] If E i <0.1 and S i <0.05, the device is judged to have successfully completed the instruction;

[0085] If E i Larger or S i If the light intensity does not decrease for a long time, it will be recorded as execution failure or instability, and the subsequent steps will be used for cross-verification of light effect anomalies.

[0086] IMU data is transmitted via I 2 The C interface connects to the local microcontroller, which then uploads the data via the RS485 or CAN interface. All trajectory comparison and integration operations are completed on the main control platform, supporting GPU acceleration or edge computing acceleration chip deployment to improve concurrent device processing capabilities.

[0087] This step outputs two variables for use in the next step:

[0088] E i :device d i Execution error;

[0089] S i :device d i The steady-state drift error after the execution is completed.

[0090] Step 3: Light output verification

[0091] This step accurately verifies the actual light output of stage lighting fixtures and is the final step in the diagnostic system to determine whether the perceived results meet the intended instructions. Unlike the previous two diagnostic steps, "signal reception" and "action completion," light output directly correlates to the visual presentation of the stage. It is the final stage information received by the audience and the most difficult to determine whether it is normal using traditional methods. Many lighting anomalies, such as color deviation, insufficient brightness, color temperature drift, and stroboscopic interference, do not stem from problems with the execution of control commands or device gestures, but rather from aging light source components, abnormal power supply drivers, or environmental interference. Therefore, this step, centered around an optical sensor array, constructs a full-dimensional light effect diagnostic mechanism that combines spectral decomposition, timing drift, and gesture execution for coordinated judgment. This aims to systematically quantify hidden issues such as "light not coming on as planned" and establish a deep causal relationship with the previous two steps.

[0092] The input of this step is the output of step 2:

[0093] E i :device d i Posture motion error;

[0094] S i :device d i The steady-state attitude drift indicator.

[0095] These two variables determine whether the device action is complete and stable. i <0.2 and S i If any device exceeds the threshold, the system will mark the light effect as "abnormal action leading to undetermined" to avoid misjudgment due to uncertain source.

[0096] Device d i After completing the gesture execution, the light beam it emits will form a specific visual effect in the performance area. To measure this effect, the system deploys a directional optical acquisition device (including a micro-spectrometer, a colorimeter sensor, a fast photosensitive array, etc.) on the stage. Each device d i Each has a corresponding monitoring viewing area A i The main control system schedules the corresponding acquisition view in real time and performs synchronous sampling based on the device number and current posture trajectory.

[0097] The first physical quantities collected include:

[0098] Light intensity L i : Unit illumination sensor collection;

[0099] Color vector C i : Reconstruct XYZ or RGB expression based on three-channel color sensor;

[0100] Dominant wavelength λ i : The main luminous frequency is analyzed by a small spectrometer;

[0101] Strobe frequency F i : Obtained by fast ADC and photodiode sampling followed by Fourier transform.

[0102] In order to deal with the problems of device viewing angle offset, projection overlap, ambient light interference, etc. in the actual stage environment, the system introduces the spatial matching weight term w based on the target reference model. i (t), dynamically adjust the proportion of reference light effect in the comparison process. Finally, define the fusion light effect deviation index V i for:

[0103]

[0104] in:

[0105] V i : Light output deviation score, a larger value indicates a more serious deviation;

[0106] Li 、C i ,λ i 、F i :device d i The actual measured light intensity, color vector, dominant wavelength, and strobe frequency;

[0107] The system presets the lighting effect model based on the lamp model, current angle and scene;

[0108] w i (t): The reference beam is in the current viewing area A i The field of view matching degree is calculated based on the lamp posture and the sensor projection area, with a value range of [0.5, 1.0], which is used to suppress incorrect judgments caused by viewing angle deviation;

[0109] The coefficients α, β, γ, and δ represent the weighted coefficients of the deviation term, which are automatically configured by the system according to the type of lamp. For example, strobe lights are enhanced by δ, and color lights are enhanced by β.

[0110] In addition, in order to attribute the light effect deviation based on the device action status, the system introduces the action-light effect coupling factor

[0111]

[0112] The innovation of this factor design is: when E i With S i Approaching 0, tends to 0, indicating that the light effect deviation should be attributed to the light source or the optical system itself; and when E i or S i When it is larger, It rises rapidly, and the system attributes the lighting problem to incomplete movement or unstable posture, which is a downstream reflection of the abnormalities in the first two steps.

[0113] All collected data is timestamped with millisecond-level timestamps. The control platform creates a three-dimensional data index of device, action, and lighting effect in a distributed database, supporting retrospective analysis and fault recurrence. The sampling module uploads data via protocols such as wired RS485 or wireless 2.4GHz Zigbee, and is precisely synchronized with the control platform's clock (within ±2ms).

[0114] After processing all the sampled data, the system outputs V i and The results are also stored in the diagnostic log. If the device's lighting efficiency is abnormal for more than three consecutive detection cycles, the subsequent fault attribution and maintenance recommendation module will be triggered.

[0115] This step outputs two variables:

[0116] Vi :device d i The light efficiency deviation score represents the comprehensive difference between its output beam and the expected value;

[0117] The coupling factor between device execution anomalies and lighting effect anomalies is used to determine whether the deviation is caused by the action or an independent lighting effect problem.

[0118] Step 4: Root cause analysis and tracing

[0119] The task of this step is to conduct a systematic modeling analysis of the light efficiency deviation results output by the previous link, and to achieve "root cause tracing" of the equipment failure. It occupies a central position in the diagnostic chain in the entire patented architecture, and is responsible for integrating and attributing all quantitative results between the signal link status (step 1), the equipment behavior execution status (step 2) and the light efficiency output (step 3), and ultimately outputs a fault type label with operational guidance significance. By constructing a causal consistency scoring mechanism for the dynamic characteristics of stage performances, the system can automatically determine whether the current abnormality of the equipment is caused by upstream factors or by the optical system itself, providing a reliable basis for the next step of response and repair.

[0120] To unify the dimensions, the system first normalizes the following two indicators with physical dimensions:

[0121] in The preset maximum execution error threshold for the device category;

[0122] in The preset maximum allowable steady-state drift.

[0123] Normalized and All are dimensionless values in the interval [0,1] to ensure the dimensional consistency of subsequent model calculations.

[0124] The inputs for this step include:

[0125] V i :device d i Light efficiency deviation score;

[0126] The coupling factor between the light effect deviation and the device execution state (output from step 3);

[0127] Read-only reference variables include:

[0128] The device's motion execution error and posture stability (output from step 2, normalized);

[0129] The signal link stability of the device (output from step 1);

[0130] P i : The effective response rate of the device (output from step 1).

[0131] The core innovation of this step is to define a multi-source causal consistency scoring function Φ i , used to measure the light efficiency deviation V i Can it be "reasonably explained" by the above upstream variables:

[0132]

[0133] in:

[0134] Φ i : The upstream explainability score of the light efficiency anomaly. A higher value indicates that the light efficiency deviation may be caused by an upstream fault.

[0135] θ1~θ5: Configurable weight parameters. The system default value is [0.25, 0.15, 0.25, 0.15, 0.20]. It can be dynamically adjusted according to the device type or performance task.

[0136] From step 3, it measures the degree of statistical coupling between the light effect deviation and the device operation state. The larger the value, the more likely the deviation is caused by abnormal operation rather than the light source itself.

[0137] In obtaining Φ i After that, the system further combines the light effect deviation itself V i , output fault type label G i , used for subsequent response strategy generation:

[0138]

[0139] illustrate:

[0140] If Φ i A higher value indicates that the light efficiency deviation is “explainable” by the preceding fault chain, without the need to trace back to the optical components;

[0141] If Φ i Lower and V i If it is large, it is judged to be a problem with the optical system itself, such as LED aging, filter damage, etc.

[0142] All cutoff values (such as 0.85, 0.2, and 0.3) can be optimized and adjusted based on historical data during system deployment.

[0143] The system will V i , Φ i and G iThe information is stored in the diagnostic database for the next step of the policy scheduling module to call, and a structured log is generated at the same time, including the device number, fault type, and recommended actions (such as resending instructions, scheduling maintenance, skipping execution, etc.).

[0144] System implementation:

[0145] All variables are pulled from the cached results of steps 1 to 3, without the need for repeated collection;

[0146] Scoring and classification rules can be managed through configuration files and support hot loading;

[0147] The operation logic is implemented in a rule tree manner to ensure response speed and stability.

[0148] This step outputs two variables:

[0149] Φ i : A score indicating whether the light effect deviation is “explainable” by upstream anomalies;

[0150] G i : Fault classification label, used by subsequent repair execution modules.

[0151] Step 5: Real-time visual feedback and automated remediation execution

[0152] This step completes the visualization and executable automated repair operations based on the fault diagnosis results.

[0153] Step details:

[0154] System based on G i Classification, generating visual interface feedback (color marking, abnormal trajectory, recommended strategy, etc.);

[0155] If G i Belongs to the "repairable" category and Φ i >0.5, then the automatic repair operation is triggered;

[0156] The repair action is to resend commands through the control protocol (such as reset, reconfigure parameters, resend action instructions, etc.);

[0157] Recollect relevant indicators after repair (E i ,S i ,V i ), determine whether the repair is successful;

[0158] Automatic repair is attempted only twice, and if it fails, it will be transferred to manual processing.

[0159] The trigger conditions are as follows:

[0160]

[0161] Repair result status:

[0162]

[0163] Output:

[0164] A i : Whether to trigger automatic repair;

[0165] F i : Repair result status, for system display and recording.

[0166] The technical solutions in the above-mentioned embodiments of the present application have at least the following technical effects or advantages: the present invention implements link health status assessment based on a compatible detection mechanism within the protocol to ensure signal delivery; then the device response process is modeled and error calculated through the attitude sensor to quantify the quality of action completion; then the output light beam is measured and compared with the optical acquisition module to determine the light efficiency deviation; and then the source of the anomaly is classified and interpreted by constructing a causal consistency scoring function to achieve accurate positioning of the fault type; the system automatically triggers repair instructions based on the fault type and credibility score, and judges the repair effectiveness through indicator recovery, completing a closed-loop execution process from diagnosis to control. The entire system uses technical means such as full-process variable tracking, dimensional normalization, and the introduction of explanatory factors to construct a highly reproducible, real-time, and engineering deployment-feasible diagnosis and recovery mechanism, achieving stable operation and rapid response of the lighting control system in a stage performance environment.

[0167] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A real-time diagnostic system for a professional stage lighting control system, characterized in that: include: A health monitoring module is used to evaluate the health status of the device. The health status is evaluated through the device's stability index and effective response rate. The stability index is obtained by calculating the average time interval between sending a probe signal to the device and receiving an echo signal. The effective response rate is obtained by calculating the ratio of the echo signal to the probe signal. A behavior verification module is used to verify the execution behavior of the device by calculating the device's behavior execution error and drift error. The behavior execution error is obtained by comparing the preset execution trajectory with the actual execution trajectory. The actual execution trajectory is obtained by performing posture calculation using a Kalman filter on the actual execution data collected by the sensor. The drift error is obtained by comparing the attitude angle of the device within a preset time window; An output verification module is used to verify the actual output of the device. This verification is accomplished by calculating the device's light efficiency deviation score, which is obtained by weighted calculation of the deviation between the actual data collected from the device and the preset data. A determination factor is also introduced to determine the cause of the error. A maximum value for the determination factor indicates the highest probability that the deviation is caused by abnormal operation rather than the light source itself. A fault tracing module is used to determine the fault type and upstream anomaly. The upstream anomaly is determined by calculating an upstream anomaly score, which is calculated by weighting the behavior execution error, drift error, device stability index, effective response rate, and determination factor. Determine the fault type based on the upstream anomaly score and light efficiency deviation score and output the fault type label; The feedback repair module is used to generate feedback according to the fault type and send repair action instructions to the equipment that meets the repairable conditions. After the repair action is completed, other modules are used to complete the detection again and output the repair result status.

2. The real-time diagnostic system for a professional stage lighting control system according to claim 1, characterized in that: When the stability index and effective response rate of the output device described in the health monitoring module are both higher than the preset threshold, it goes to the behavior verification module to perform the next action; otherwise it ends directly and is marked as not receiving the instruction.

3. The real-time diagnostic system for a professional stage lighting control system according to claim 1, characterized in that: A dynamic delay function is set in the behavior execution error described in the behavior verification module. The dynamic delay function is defined as the time lag between the actual execution trajectory and the preset execution trajectory that is less than a threshold value. It is used to indicate that although the device has reached the target angle, it takes more than the preset time.

4. The real-time diagnostic system for a professional stage lighting control system according to claim 1, characterized in that: When the behavior execution error described in the behavior verification module is higher than the threshold and / or the drift error is higher than the threshold, it is determined that the execution has failed or is unstable, and the output verification module is entered for cross-validation.

5. The real-time diagnostic system for a professional stage lighting control system according to claim 1, characterized in that: The actual data of the device include light intensity, color vector, dominant wavelength and strobe frequency.

6. The real-time diagnostic system for a professional stage lighting control system according to claim 1, characterized in that: A spatial matching weight term is also introduced into the light efficiency deviation score. The spatial matching weight term is calculated based on the field of view matching degree of the light beam in the corresponding viewing angle area, according to the lamp posture and the sensor projection area, and is used to suppress erroneous judgments caused by viewing angle deviation.

7. The real-time diagnostic system for a professional stage lighting control system according to claim 1, characterized in that: The fault type label is determined according to the following rules: When the stability index is less than a first threshold or the effective response rate is lower than the first threshold, it is determined to be a signal failure; When the behavior execution error is greater than the second threshold or the drift error is greater than the second threshold, it is determined to be an action failure; When the light efficiency deviation score is greater than the third threshold and the upstream abnormality score is less than the fourth threshold, it is determined to be an optical fault; When the light efficiency deviation score is less than the third threshold and the upstream abnormality score is less than the fourth threshold, it is determined to be normal operation; When a situation other than the above occurs, it is determined to be a mixed fault.

8. The real-time diagnostic system for a professional stage lighting control system according to claim 1, characterized in that: The repairable condition described in the feedback repair module is that the fault type label is a signal fault and / or an action fault and the upstream anomaly score is greater than a repair threshold.

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