A moving head lamp dynamic correction system based on three-dimensional light column axis analysis

Abstract

The application discloses a moving head lamp dynamic correction system based on three-dimensional light column axis analysis and belongs to the technical field of stage light control. The application comprises the following: a visual perception unit for acquiring three-dimensional space information of a moving head lamp projected light column, at least including an actual center axis; a deviation solving module for calculating a posture deviation based on actual light column parameters combined with ideal light column parameters or through multi-lamp rule analysis; a correction instruction generation module for generating a motion correction instruction; and a correction execution module for sending the instruction to a lamp or a control system of the lamp. The application also supports functions such as verification and iteration, various correction working modes, individual characteristic compensation, group effect evaluation and computing power self-adaptive scheduling. The application realizes high-precision, automatic and real-time dynamic correction of the posture of the moving head lamp, and significantly improves the consistency of stage light effects.

Description

Technical Field

[0001] This invention relates to the field of stage lighting control technology, specifically to a moving head light dynamic correction system based on three-dimensional light column axis analysis, used to detect and correct the posture deviation of the moving head light projecting light column in space in real time. Background Technology

[0002] Moving head lights are widely used in modern stage performances, and their core aesthetic value lies in the light column shape they present in the space. However, due to factors such as installation errors, mechanical wear, temperature changes, and long-term operation, the actual projection direction of moving head lights often deviates from the design intent, resulting in distorted light column shapes and chaotic group effects.

[0003] Currently, the correction of such deviations mainly relies on visual inspection and manual fine-tuning, which has the following problems:

[0004] 1. Inefficiency: Large-scale performances often involve hundreds of lights, and manual correction of each light fixture takes several hours;

[0005] 2. Insufficient precision: The human eye has difficulty accurately judging angular deviations within 0.5 degrees;

[0006] 3. Inability to provide real-time dynamic correction: During the performance, the posture of the lighting fixtures may drift due to factors such as mechanical vibration and thermal expansion and contraction, and cannot be manually intervened in real time;

[0007] 4. Lack of individual difference compensation: Each lamp has individual deviations due to different manufacturing tolerances and usage time, which cannot be solved by traditional batch correction.

[0008] Therefore, there is an urgent need for a system that can automatically detect and correct the posture deviation of moving head lights.

[0009] Purpose of the invention

[0010] The present invention aims to provide a dynamic correction system for moving head lights based on three-dimensional light column axis analysis. The system obtains the actual axis of the light column through visual perception, compares it with the ideal axis or analyzes the pattern of multiple lights, automatically calculates the deviation and generates correction commands to achieve automatic correction of the moving head light posture. Summary of the Invention

[0011] A moving head light dynamic correction system based on three-dimensional light column axis analysis includes:

[0012] A visual perception unit is used to acquire three-dimensional spatial information of the light column projected by the moving head light in space, wherein the three-dimensional spatial information includes at least the actual central axis of the light column in three-dimensional space.

[0013] The deviation calculation module is connected to the visual perception unit and is used to calculate the attitude deviation of the light column based on the actual light column parameters obtained by the visual perception unit, combined with the ideal light column parameters in the pre-programmed model or through multi-lamp pattern analysis.

[0014] The correction instruction generation module is connected to the deviation calculation module and is used to generate correction instructions for the moving head light based on the deviation calculation results.

[0015] The correction execution module, connected to the correction instruction generation module, is used to send the correction control instruction to the corresponding lamp or the lamp's control system.

[0016] Preferably, the system also includes a verification and iteration module, which is used to acquire the corrected light column information again after sending the correction command, compare it with the preset ideal state for verification, and trigger a new round of correction when the accuracy requirements are not met, thus forming a closed-loop control.

[0017] Preferably, the deviation calculation module supports comparison methods based on pre-programmed data and autonomous detection methods based on pattern analysis.

[0018] Preferably, the system also includes a working mode selection module, which supports multiple working modes such as continuous correction, timed correction, triggered correction, manual correction, and mixed correction.

[0019] Preferably, the system also includes an individual feature compensation module for storing individual feature data of each luminaire and pre-compensating for correction commands. Individual feature acquisition employs a multi-pose testing method: the luminaire is controlled to sequentially point to multiple calibration points in different directions (no fewer than nine, covering the full range of the PAN axis from -170° to +170° and the Tilt axis from 0° to 90°), and the deviation between the actual pointing and the commanded pointing is collected. The luminaire's full-range error curves on the PAN and Tilt axes are then fitted using the least squares method. These error curves accurately describe the nonlinear response characteristics of the luminaire at different angles, achieving accurate full-range compensation, rather than simple single-point hysteresis compensation.

[0020] Preferably, the system also includes a group effect evaluation module and a computing power adaptive scheduling module to improve the multi-light coordination effect and system operating efficiency.

[0021] Beneficial effects

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] 1. High degree of automation: Deviation detection and correction are completed automatically without human intervention;

[0024] 2. High precision: Visual perception precision can reach 0.05 degrees, far exceeding that of manual visual inspection;

[0025] 3. Real-time dynamic correction: Supports continuous correction mode, tracking and correcting attitude drift in real time;

[0026] 4. High adaptability: Supports both pre-programmed and non-pre-programmed data modes to meet different application scenarios;

[0027] 5. Individualized compensation: Accurate pre-compensation for each lamp is achieved through the full-range error curve;

[0028] 6. Closed-loop optimization: The verification and iteration modules can form a closed loop to continuously improve correction accuracy;

[0029] 7. Flexible working modes: Supports multiple correction modes and adaptive scheduling to balance accuracy and computing power. Attached Figure Description

[0030] Figure 1 : Schematic diagram of the overall architecture of the automatic correction system of this invention.

[0031] Explanation of markings in the diagram:

[0032] 101—Visual perception unit, used to acquire three-dimensional spatial information of the beam of light projected by the moving head light;

[0033] 102—Pre-programmed data interface (optional), used to access the ideal light column parameters in the 3D pre-programmed model; 103—Deviation calculation module, used to calculate the deviation between the actual light column and the ideal light column, or to calculate the deviation independently through multi-lamp pattern analysis when there is no pre-programmed data;

[0034] 104 — Correction instruction generation module, used to generate correction instructions for the moving head light;

[0035] 105—Correction execution module, used to output correction commands to the corresponding lamp or the lamp's control system;

[0036] 106—Verification and Iteration Module (optional) is used to monitor the state of the corrected light column and feed it back to the deviation calculation module to form a closed-loop iterative optimization (as shown by the dashed arrow in the figure).

[0037] In the diagram, solid arrows indicate the main data flow, while dashed arrows indicate the feedback iteration path.

[0038] Figure 2 : Schematic diagram of the deviation calculation principle based on pre-programmed data.

[0039] Explanation of markings in the diagram:

[0040] 201—Actual light column, representing the three-dimensional spatial axis of the actual projected light column of the moving head light as obtained by the visual perception unit;

[0041] 202—Ideal light column, representing the three-dimensional spatial axis of the theoretical light column preset in the pre-programmed model;

[0042] 203— Deviation Calculation, indicating the process by which the deviation calculation module compares and calculates the actual light column with the ideal light column;

[0043] 204—PAN axis deviation, representing the angular deviation between the actual optical column and the ideal optical column in the horizontal rotation direction;

[0044] 205—Tilt axis deviation, representing the angular deviation between the actual beam and the ideal beam in the vertical rotation direction;

[0045] 206—Angle deviation, representing the deviation between the actual beam and the ideal beam in the beam divergence angle.

[0046] In the figure, the actual light column (201) is spatially compared with the ideal light column (202), and the deviation parameters (204-206) in three dimensions are output through deviation calculation (203).

[0047] Figure 3 Schematic diagram of the autonomous deviation detection principle based on pattern analysis.

[0048] This figure illustrates how the deviation calculation module (103) autonomously identifies abnormal lamps and calculates deviations by analyzing the spatial distribution and motion patterns among multiple lamps without pre-programmed data.

[0049] Explanation of markings in the diagram:

[0050] 301—Data input module, used to receive single-frame images, continuous sequence images, and multi-light image data acquired by the visual perception unit;

[0051] 302—Static Image Feature Analysis Module, used to extract features from a single frame of light pillar image and analyze static parameters such as the spatial position, shape, and angle of the light pillar;

[0052] 303—Motion trajectory feature analysis module, used to track and analyze continuous sequence images, and extract dynamic features such as the motion speed, acceleration, and trajectory smoothness of the light beam;

[0053] 304—Multi-lamp spatial distribution characteristic analysis module, used to analyze the group distribution of multiple moving head light columns, internally including:

[0054] 3041—Spatial distribution statistical algorithm, used to analyze the overall distribution density and uniformity of light beams in space;

[0055] 3042—Interval angle analysis algorithm, used to calculate the angle between adjacent light pillars;

[0056] 3043—Geometric shape fitting algorithm, used to identify the geometric shape formed by multiple light beams;

[0057] 3044—Multi-lamp motion coordination feature analysis algorithm, used to analyze the motion synchronization and coordination of multiple lamps in a time series;

[0058] 305—Abnormal Light Fixture Identification and Deviation Output Module, used to identify light fixtures with abnormal deviations based on the above analysis results, and output the deviation parameters of the light fixture relative to the group pattern.

[0059] Data flow in the diagram: The data input module (301) transmits the collected data to each analysis module (302, 303, 304), and the analysis results are summarized to the abnormal lamp identification and deviation output module (305), and the output deviation parameters are used by the correction instruction generation module (104).

[0060] Figure 4 : Schematic diagram of multiple correction working modes.

[0061] Explanation of markings in the diagram:

[0062] 401 — Schematic diagram of multiple correction working modes, used to integrate and demonstrate the multiple correction working modes included in this invention;

[0063] 402—Continuous correction mode, suitable for the commissioning stage or critical effect period, to perform high-frequency real-time acquisition and compensation of lamp posture;

[0064] 403 - Timed correction mode, suitable for regular performances, performs posture correction according to a preset cycle;

[0065] 404 — Temporary switch to continuous correction mode, used to quickly switch to continuous correction mode as needed during the operation of timed correction mode;

[0066] 405 - Manual Trigger Correction Mode, used by operators to manually trigger single or periodic corrections as needed on site.

[0067] The diagram uses a tree structure to illustrate the classification and applicable scenarios of various correction working modes. Each mode can be flexibly selected or combined according to actual performance needs.

[0068] Figure 5 Flowchart of pre-compensation correction based on individual characteristics.

[0069] Explanation of markings in the diagram:

[0070] 501 — Construction of an individual feature database for lighting fixtures, used to collect individual feature data such as posture deviation and optical characteristics of each lighting fixture to form a searchable feature database;

[0071] 502—Real-time attitude / optical data acquisition, used to obtain the actual attitude, optical output and other operating parameters of the luminaire under its current operating state;

[0072] 503 — Individual Feature Data Retrieval, used to match the corresponding individual feature data from the individual feature database based on the current lamp ID;

[0073] 504 — Pre-compensation calculation and command generation, used to perform pre-compensation calculations on real-time acquired attitude / optical data in combination with individual feature data, and generate corrected correction commands;

[0074] 505 — Post-compensation correction command issuance and execution, used to issue the compensated correction command to the corresponding lamp or the lamp's control system.

[0075] The diagram illustrates the five key steps (501-505) of pre-compensation correction based on individual characteristics in the form of a flowchart. The steps are connected in sequence, presenting a complete closed-loop process from the construction of the individual characteristic database to the execution of precise correction instructions. Detailed Implementation

[0076] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0077] Example 1: Continuous correction mode based on pre-programmed data (corresponding to) Figure 1 , Figure 2 , Figure 4 )

[0078] At a large concert, 200 moving head lights were suspended above the stage, and a complete 3D pre-programmed model had been constructed. The system adopted a continuous correction mode (402) based on the pre-programmed data.

[0079] 1. Data Acquisition and Perception: The visual perception unit (101) acquires the three-dimensional spatial information of 200 moving head light beams in real time, including the actual central axis, starting point coordinates, direction vector, and angular parameters (201) of each light beam. The acquisition frequency is 30 frames / second. At the same time, the pre-programmed data interface (102) retrieves the corresponding ideal light beam parameters (202) from the 3D pre-programmed model.

[0080] 2. Deviation Calculation The deviation calculation module (103) spatially compares the actual light column (201) with the ideal light column (202), calculates the PAN axis deviation (204), Tilt axis deviation (205), and angular deviation (206), and outputs the three-dimensional deviation parameters. The calculation uses the least squares method to fit the light column axis, and the deviation calculation accuracy reaches 0.01 degrees.

[0081] 3. Correction Command Generation and Execution The correction command generation module (104) generates correction commands for each lamp based on the deviation parameters. The system operates in continuous correction mode (402), performing high-frequency real-time acquisition and compensation of the lamp attitude at a frequency of 30 times per second. The correction execution module (105) outputs the commands to the lamp control system via the DMX512 protocol, driving the lamp to correct the attitude deviation.

[0082] 4. Verification and Iteration (Optional) If the system includes a verification and iteration module (106), the light column state after the correction is executed is monitored, and the verification results are fed back to the deviation calculation module (103) to form a closed-loop iterative optimization. After 3 rounds of iteration, the average deviation of 200 lamps was reduced from the initial 0.8 degrees to less than 0.05 degrees.

[0083] This embodiment is applicable to the debugging phase or critical effect period, and achieves high-precision real-time correction.

[0084] Example 2: Self-correction mode based on pattern analysis (corresponding to) Figure 1 , Figure 3 , Figure 4 )

[0085] At a temporary outdoor music festival, where no pre-programmed model was available, the system adopted a self-correction mode based on pattern analysis.

[0086] 1. Data Acquisition and Input: The visual perception unit (101) acquires image data from 150 moving head light columns across the entire venue, including single-frame images, continuous sequence images, and multi-light images. The data input module (301) receives the above data at a sampling frequency of 30 frames / second.

[0087] 2. Multidimensional Feature Analysis

[0088] The static image feature analysis module (302) extracts static parameters such as the spatial position, shape, and subtended angle of the light column;

[0089] The motion trajectory feature analysis module (303) tracks the dynamic features of the light beam, such as its motion speed, acceleration, and trajectory smoothness.

[0090] The multi-lamp spatial distribution feature analysis module (304) analyzes the overall distribution density and uniformity of the light pillars through the spatial distribution statistical algorithm (3041); calculates the angle between adjacent light pillars through the interval angle analysis algorithm (3042); identifies the geometric shape formed by the multi-lamp light pillars through the geometric shape fitting algorithm (3043); and analyzes the motion synchronization and coordination of the multi-lamp through the multi-lamp motion coordination feature analysis algorithm (3044).

[0091] 3. Anomaly Identification and Deviation Output The anomaly lamp identification and deviation output module (305) identifies abnormal lamps that deviate from the group pattern based on the above analysis. The anomaly judgment threshold is set based on historical data statistics: when the PAN axis angle of a lamp deviates from the overall distribution mean by more than 2.5 degrees, or the interval angle deviates from the average interval by more than 30%, or the movement phase deviates from the group average phase by more than 0.2 seconds, it is identified as an anomaly. The module outputs parameters such as the relative angle deviation, relative position deviation, and movement phase deviation of the lamp.

[0092] 4. Correction Instruction Generation and Execution

[0093] The correction instruction generation module (104) generates correction instructions based on the deviation parameters. The system operates in timed correction mode (403), performing attitude correction once every 30 seconds, with each correction iteration consisting of 3 rounds. The correction execution module (105) outputs the instructions to the lighting control system.

[0094] This embodiment achieves autonomous deviation detection and correction of all lighting fixtures without a pre-programmed model, making it suitable for rapid deployment scenarios.

[0095] Example 3: Pre-compensation correction based on individual characteristics (corresponding to) Figure 1 , Figure 5 )

[0096] During a certain tour, some lighting fixtures exhibited individual deviations due to long-term use (e.g., the PAN axis response of one fixture lagged by 0.2 degrees). The system adopted a pre-compensation correction scheme based on individual characteristics.

[0097] 1. Construction of Individual Feature Database (501)

[0098] Before the performance, the system collects individual characteristic data such as posture deviation and optical properties of each lighting fixture, establishing a database of individual fixture characteristics. The data collection method employs a multi-posture testing approach.

[0099] The control lamp is sequentially pointed to multiple calibration points covering the entire range. At each calibration point (no less than 9, covering the full range of PAN axis -170° to +170° and Tilt axis 0° to 90°), the deviation between the actual pointing and the command pointing is measured.

[0100] The full-range error curves of each lamp on the PAN and Tilt axes are fitted by the least squares method to accurately describe the nonlinear response characteristics of the lamp at different angles.

[0101] Instead of simply storing single-point deviation values, the error curve parameters (polynomial coefficients) are stored in an individual feature database.

[0102] During the tour, the system can dynamically update the individual feature library based on the actual correction effect. After each performance, the correction residual recorded by the verification and iteration module (106) is used as new feature data to refit the error curve and update the feature library of the corresponding lamps in order to cope with the slow changes in lamp performance (such as motor aging, belt loosening, etc.).

[0103] 2. Real-time data acquisition (502)

[0104] During the performance, the system collects the actual operating parameters of the current lighting fixtures in real time, including data such as PAN axis angle, Tilt axis angle, beam angle, and brightness.

[0105] 3. Individual Feature Recall (503)

[0106] Based on the current lamp ID, the system matches the corresponding individual feature data from the individual feature library. For example, if the current correction object is identified as L001, its full-range PAN axis error curve is retrieved.

[0107] 4. Pre-compensation calculation and command generation (504) The correction command generation module (104) combines individual feature data to perform pre-compensation calculation on the real-time acquired attitude data. For example, based on the current target angle, the corresponding compensation value is found on the error curve, and the correction command is additionally increased by this compensation amount in the PAN axis direction to generate the corrected correction command.

[0108] 5. Command Issuance and Execution (505) The compensation and correction command is issued to the lighting control system to drive the lighting fixture to complete the precise posture correction.

[0109] This embodiment improves the correction accuracy by 0.1-0.2 degrees by pre-compensating for the individual characteristics of the lamps, effectively solving the correction deviation problem caused by individual differences in lamps.

[0110] Example 4: Flexible switching between multiple correction modes (corresponding to) Figure 4 )

[0111] In a certain performance, different segments have different requirements for correction accuracy. The system supports flexible switching between multiple correction modes.

[0112] 1. Debugging Phase: During the pre-performance debugging phase, the system adopts a continuous correction mode (402) with high-frequency real-time acquisition and compensation at 30 times per second to ensure that the posture of all lights is accurately in place.

[0113] 2. During the regular performance phase, after the performance begins, the system switches to the timed correction mode (403), performing posture correction once every 60 seconds. Each correction iteration consists of 2 rounds, which reduces the system's computational load while ensuring the correction effect.

[0114] 3. Key Effects Segments: When the performance enters a key effects segment (such as the climax of a light show), the system triggers a temporary switch to continuous correction mode (404) via timecode (SMPTE). Detection logic: When the timecode enters the preset "key effects segment" interval, continuous correction mode is automatically activated; or when the verification and iteration module (106) detects a sudden increase in the deviation of the light beam group (such as an average deviation exceeding 0.5 degrees for 3 consecutive frames), a temporary switch is automatically triggered. The system operates in continuous correction mode for 30 seconds to ensure the accuracy of the lighting effects in the key segments. After the climax, the system automatically switches back to timed correction mode.

[0115] 4. Manual Intervention: If the lighting technician discovers a significant deviation in the lighting fixtures in a certain area through the monitoring screen, the correction mode (405) can be manually triggered through the operation interface. The system will immediately perform a single correction (3 iterations) to quickly correct the deviation.

[0116] This embodiment achieves a dynamic balance between correction accuracy and system load through a flexible combination of multiple correction modes, meeting the needs of different performance scenarios.

[0117] The above embodiments are merely illustrative examples. Those skilled in the art can adjust the functions and parameters of each module according to actual needs without departing from the protection scope defined by the claims of this invention.

Claims

1. A dynamic correction system for moving head lights based on three-dimensional light column axis analysis, characterized in that, include: A visual perception unit is used to acquire three-dimensional spatial information of the light column projected by the moving head light in space, wherein the three-dimensional spatial information includes at least the actual central axis of the light column in three-dimensional space. The deviation calculation module is connected to the visual perception unit and is used to calculate the attitude deviation of the light column based on the actual light column parameters obtained by the visual perception unit, combined with the ideal light column parameters in the pre-programmed model or through multi-lamp pattern analysis. The correction instruction generation module is connected to the deviation calculation module and is used to generate correction instructions for the moving head light based on the deviation calculation results. The correction execution module, connected to the correction instruction generation module, is used to send the correction control instruction to the corresponding lamp or the lamp's control system.

2. The system according to claim 1, characterized in that, It also includes a verification and iteration module, which is connected to the correction execution module and the visual perception unit. After sending the correction command, it obtains the three-dimensional spatial information of the corrected light column again through the visual perception unit and compares it with the preset ideal state. When the verification result does not meet the preset accuracy requirements, it triggers a new round of correction to form a closed-loop control.

3. The system according to claim 1, characterized in that, The deviation calculation module analyzes the actual center axis using at least one of the following methods: The comparison method based on pre-programmed data is as follows: the ideal light column model data preset in the 3D pre-programming software is obtained through the pre-programmed data interface, the actual center axis is compared with the ideal center axis in three-dimensional space, and the angular deviation is calculated. Autonomous detection method based on pattern analysis: In the absence of pre-programmed data, by statistically analyzing the actual central axes of multiple moving head lights, abnormal lights that do not conform to the overall distribution pattern can be identified; or by analyzing the continuous motion trajectory of a single moving head light in a time series, dynamic positioning that does not conform to the motion pattern can be identified, and correction instructions can be generated based on the detected abnormalities.

4. The system according to claim 3, characterized in that, The autonomous detection method based on pattern analysis includes: Multi-lamp spatial distribution pattern analysis: perform cluster analysis or statistical distribution analysis on the actual central axes of multiple lamps to identify abnormal lamps that deviate from the overall distribution characteristics; Single-lamp time series pattern analysis: Perform smoothness, periodicity, or consistency analysis on the motion trajectory of a single lamp in a continuous time series to identify abnormal fluctuation points.

5. The system according to claim 1, characterized in that, The visual perception unit includes the system described in another patent application filed by the applicant on the same day, entitled "A Physical-Virtual Fusion Multi-View Perception System for Stage Lighting Control".

6. The system according to claim 1, characterized in that, It also includes a working mode selection module, connected to the deviation calculation module and the correction execution module, for supporting the use of different correction execution strategies based on user selection or preset conditions, wherein the correction execution strategy includes at least one of the following modes: Continuous correction mode: continuously executes a closed-loop process of visual acquisition, deviation calculation, correction instruction generation and verification; Timed correction mode: The correction process is executed at preset time intervals; Triggered correction mode: The correction process is executed only when a user trigger command is received or a preset trigger condition is detected; Manual correction mode: Executed after the user confirms the correction command; Hybrid correction mode: Automatically switches between the above modes based on the performance stage, computing power margin, and accuracy requirements.

7. The system according to claim 6, characterized in that, The preset triggering conditions include at least one of the following: The deviation between the lamp's movement trajectory and the pre-programmed trajectory was detected to exceed a preset threshold; Received a stage switching signal from the performance control system; In the autonomous detection mode, anomalies that did not conform to the pattern were detected.

8. The system according to claim 1, characterized in that, It also includes an individual feature compensation module for storing individual feature data for each moving head light. The individual feature data includes at least one or more of motor hysteresis and response delay data. The correction command generation module generates a correction control command after pre-compensating based on the angle deviation and the individual feature data.

9. The system according to claim 1, characterized in that, It also includes a group effect evaluation module, which is connected to the deviation calculation module. When multiple moving head lights work together to present a preset geometric shape, it analyzes the overall outline clarity, spacing uniformity and angle consistency of the geometric shape, and generates a multi-light collaborative correction command based on the analysis results.

10. The system according to claim 1, characterized in that, It also includes a computing power adaptive scheduling module, used for: Real-time monitoring of system CPU / GPU utilization; The correction mode or sampling frequency is automatically adjusted based on the available computing power. When the computing power usage exceeds the preset threshold, it automatically switches from continuous correction mode to timed correction mode or reduces the sampling frequency.

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