Performance effect digital control method and system

Abstract

The invention discloses a performance effect digital control method and a performance effect digital control system, which realize autonomous adaptation of states of multi-source stage sound effects, multi-point stage lighting, stage machinery and the like through digital information acquisition, processing and state matching technologies, not only improve the automation degree and the accuracy of performance, but also enrich the performance effect and improve the performance experience. The immersive experience and the interactive experience of the audience are improved, and meanwhile, the safe performance is ensured.

Description

Technical Field

[0001] The present invention relates to a digital control method and system for performance effects, and more specifically to a digital control method and system for achieving autonomous adaptation of multi-source stage sound effects, multi-point stage lighting, stage machinery and other states through digital information acquisition, processing and state matching technology, thereby satisfying diversified performance effects. Background Art

[0002] With the rapid development of the cultural performance industry, the audience's requirements for performance effects are increasing day by day. The traditional manual control method can no longer meet the complex and changing performance needs. Therefore, a system that can control the stage sound effects, lighting and mechanical status in real time and accurately is needed to create a more shocking and immersive performance experience. Summary of the invention

[0003] In view of the above-mentioned defects of the prior art, the object of the present invention is to provide a performance effect digital control method and system.

[0004] The technical solution of the present invention is: a performance effect digital control method, comprising the following steps:

[0005] (a) Data collection: deploy a variety of high-precision sensors, including sound sensors, light sensors, position sensors, pressure sensors, and motion capture devices. High-precision sensors are distributed throughout the stage space. i =f i (t) represents the sampling data of the i-th sensor at time t, where S i is the sampling data, f i is the corresponding sampling function;

[0006] (b) Data preprocessing: the collected raw data S i Perform preliminary processing, including data cleaning, data calibration and data compression, and use the formula S′ i =g i (S i ) represents the processed data, where S′ i is the processed data, g i is the corresponding processing function;

[0007] (c) Data transmission, using high-speed Ethernet, 5G wireless network or dedicated low-latency communication protocol to ensure data S′ i Real-time and stable transmission, according to the formula T(S′ i ) = h(S′ i ,Δt) represents the data transmission efficiency within Δt time, where T(S′ i ) is the transmission efficiency, h is the transmission function;

[0008] (d) Central control, running data analysis and processing software, including digital signal processing algorithms, machine learning models, optimization algorithms and simulation software, to monitor S′ i Conduct in-depth analysis and extract features where F j is the jth feature, is the corresponding feature extraction function;

[0009] (e) State matching and decision making, specifically including the following steps:

[0010] (e1) Building a large-scale performance effect status database;

[0011] (e2) Real-time data F j It is precisely matched with the preset state in the database, using the formula M(F j )=θ(F j , D) represents the degree of matching, where M(F j ) is the matching degree, θ is the matching function, and D is the preset state in the database;

[0012] (e3) Introducing artificial intelligence decision-making, based on deep learning and reinforcement learning algorithms, generates the optimal control decision according to the current performance situation and historical experience, using the formula C = α (M (F j ),H) represents the control decision, where C is the control decision, α is the decision function, and H is the historical experience data;

[0013] (f) Control execution: The controller receives the control decision C and executes the control operation with microsecond accuracy to achieve precise adjustment of the stage sound equipment, lighting equipment and stage mechanical devices, according to the formula E = β (C, D e ) represents the execution effect, where E is the execution effect, β is the execution function, and D e The device status data.

[0014] Furthermore, the following steps are included: (g) special effects generation, generating virtual scenes, special effects animations, and projection mapping visual effects according to performance requirements.

[0015] Furthermore, the following steps are included: (h) human-computer interaction, providing an intuitive graphical user interface and virtual reality and augmented reality interaction interfaces, and supporting multiple interaction methods such as voice commands and gesture control.

[0016] Furthermore, the following steps are included: (i) safety monitoring and emergency response, real-time monitoring of the system's operating status and equipment operating parameters, early warning of possible failures, overloads, overheating anomalies, and formulation of emergency response plans.

[0017] Furthermore, in step (e1), the performance effect status database covers various types and styles of performance preset states.

[0018] The present invention also provides a performance effect digital control system, including a controller, a data acquisition module, a data preprocessing module, a data transmission module, a central control module, a state matching and decision module, a control execution module, a special effect generation module, a human-computer interaction module, and a safety monitoring and emergency processing module.

[0019] Furthermore, the data acquisition module includes:

[0020] Sound sensor, used to collect sound data on the stage;

[0021] Light sensors to measure light intensity and color distribution on the stage;

[0022] Position sensors, used to determine the position of stage equipment, actors or audience members;

[0023] a pressure sensor to detect pressure changes on the stage;

[0024] Motion capture equipment is used to capture the movements and gestures of actors.

[0025] Furthermore, the data preprocessing module includes:

[0026] Data cleaning unit, responsible for dealing with missing values, outliers and duplicate values ​​in the original data;

[0027] A data calibration unit is used to adjust the data output by the sensor to eliminate the influence of sensor errors or environmental factors;

[0028] Data compression unit, used to reduce data storage space and transmission time while maintaining data integrity and accuracy.

[0029] Furthermore, the central control module includes:

[0030] The data processing and analysis unit is responsible for receiving data from the data acquisition module and performing preliminary processing and analysis;

[0031] A digital signal processing unit processes and analyzes the received signal using a digital signal processing algorithm;

[0032] The machine learning model unit uses machine learning algorithms to learn and predict the received data;

[0033] Optimization algorithm unit, which uses optimization algorithm to optimize the control parameters and strategies of the system;

[0034] The simulation software unit uses simulation software to simulate and predict the operation of the system.

[0035] Furthermore, the state matching and decision module includes:

[0036] The state matching unit builds a large-scale performance effect state database to accurately match real-time data with the preset states in the database;

[0037] Artificial intelligence decision-making unit uses artificial intelligence algorithms to generate optimal control decisions.

[0038] The beneficial effects of the present invention are as follows: the present invention realizes autonomous adaptation of multi-source stage sound effects, multi-point stage lighting, stage machinery and other states through digital information acquisition, processing and state matching technology, which not only improves the automation and accuracy of the performance, but also enriches the performance effect, enhances the audience's immersive experience and interactive experience, and ensures the safety of the performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a system block diagram of the present invention.

[0040] As shown in the figure: 1—controller, 2—data acquisition module, 3—data preprocessing module, 4—data transmission module, 5—central control module, 6—state matching and decision-making module, 7—control execution module, 8—special effects generation module, 9—human-computer interaction module, 10—safety monitoring and emergency handling module. DETAILED DESCRIPTION

[0041] In order to more intuitively and completely understand the technical solution of the present invention, a non-limiting feature description is now provided in conjunction with the accompanying drawings of the present invention as follows:

[0042] A performance effect digital control method comprises the following steps:

[0043] (a) Data collection: deploy a variety of high-precision sensors, including sound sensors, light sensors, position sensors, pressure sensors, and motion capture devices. High-precision sensors are distributed throughout the stage space. i =f i (t) represents the sampling data of the i-th sensor at time t, where S i is the sampling data, f i is the corresponding sampling function;

[0044] (b) Data preprocessing: collect the raw data S i Perform preliminary processing, including data cleaning, data calibration and data compression, and use the formula S′ i =g i (S i ) represents the processed data, where S′ i is the processed data, gi is the corresponding processing function;

[0045] (c) Data transmission, using high-speed Ethernet, 5G wireless network or dedicated low-latency communication protocol to ensure data S′ i Real-time and stable transmission, according to the formula T(S′ i ) = h(S′ i ,Δt) represents the data transmission efficiency within Δt time, where T(S′ i ) is the transmission efficiency, h is the transmission function;

[0046] (d) Central control, running data analysis and processing software, including digital signal processing algorithms, machine learning models, optimization algorithms and simulation software, to monitor S′ i Conduct in-depth analysis and extract features Among them, F j is the jth feature, is the corresponding feature extraction function;

[0047] (e) State matching and decision making, specifically including the following steps:

[0048] (e1) Building a large-scale performance effect status database;

[0049] (e2) Real-time data F j It is precisely matched with the preset state in the database, using the formula M(F j )=θ(F j , D) represents the degree of matching, where M(F j ) is the matching degree, θ is the matching function, and D is the preset state in the database;

[0050] (e3) Introducing artificial intelligence decision-making, based on deep learning and reinforcement learning algorithms, generates the optimal control decision according to the current performance situation and historical experience, using the formula C = α (M (F j ), H) represents the control decision, where C is the control decision, α is the decision function, and H is the historical experience data;

[0051] (f) Control execution: The controller receives the control decision C and executes the control operation with microsecond accuracy to achieve precise adjustment of the stage sound equipment, lighting equipment and stage mechanical devices, according to the formula E = β (C, D e ) represents the execution effect, where E is the execution effect, β is the execution function, and D e is the device status data;

[0052] (g) Special effects generation: generating virtual scenes, special effects animations, and projection mapping visual effects according to performance requirements;

[0053] (h) Human-computer interaction: providing intuitive graphical user interfaces and virtual reality and augmented reality interaction interfaces, and supporting multiple interaction modes such as voice commands and gesture control;

[0054] (i) Safety monitoring and emergency response: real-time monitoring of the system's operating status and equipment's operating parameters, early warning of possible failures, overloads, overheating, and formulation of emergency response plans.

[0055] In step (e1), the performance effect status database covers various types and styles of performance preset states.

[0056] like Figure 1 As shown, a performance effect digital control system includes a controller 1, a data acquisition module 2, a data preprocessing module 3, a data transmission module 4, a central control module 5, a state matching and decision module 6, a control execution module 7, a special effect generation module 8, a human-computer interaction module 9, and a safety monitoring and emergency handling module 10.

[0057] The data acquisition module 2 includes:

[0058] Sound sensors are used to collect sound data on the stage, such as music, applause, and audience cheers. These data can be used to analyze the performance atmosphere and audience reactions.

[0059] Light sensors, which measure the intensity and color distribution of light on the stage, help adjust lighting effects and create the right atmosphere for the performance;

[0060] Position sensors are used to determine the location of stage equipment, actors or audience members, which is essential for stage scheduling and interactive effects;

[0061] Pressure sensors are used to detect pressure changes on the stage, such as the footsteps of actors and the vibration of stage equipment, which helps analyze stage dynamics and actor performances;

[0062] Motion capture equipment is used to capture the movements and gestures of actors. These data can be used to generate special effects animations, projection mapping and other visual effects to enhance the immersion and interactivity of the performance.

[0063] The data preprocessing module 3 includes:

[0064] The data cleaning unit is responsible for dealing with missing values, outliers, and duplicate values ​​in the original data. These problems may affect subsequent data analysis and control decisions, so data cleaning is needed to ensure the accuracy and consistency of the data.

[0065] Data calibration unit, used to adjust the data output by the sensor to eliminate the influence of sensor errors or environmental factors, which can ensure the consistency and comparability of data at different times and under different conditions;

[0066] Data compression unit, used to reduce the storage space and transmission time of data while maintaining the integrity and accuracy of the data, which is crucial to improving the real-time performance and efficiency of the system.

[0067] The central control module 5 includes:

[0068] The data processing and analysis unit is responsible for receiving data from the data acquisition module and performing preliminary processing and analysis;

[0069] Digital signal processing unit, which processes and analyzes the received signal using digital signal processing algorithms, such as filtering and denoising, signal transformation, signal detection and recognition;

[0070] The machine learning model unit uses the machine learning algorithm to learn and predict the received data. The machine learning model can be trained using historical data and training algorithms to improve the prediction accuracy of the model. The trained machine learning model can be used to predict and analyze new data to obtain future trends and rules. The machine learning model can be optimized and adjusted according to the prediction results and actual needs to improve the adaptability and accuracy of the model.

[0071] Optimization algorithm unit, which uses optimization algorithm to optimize the control parameters and strategies of the system;

[0072] The simulation software unit uses simulation software to simulate and predict the operation of the system.

[0073] The state matching and decision module 6 includes:

[0074] The state matching unit is capable of building a large-scale performance effect state database and accurately matching real-time data with the preset states in the database;

[0075] An AI decision-making unit, which uses AI algorithms (particularly deep learning and reinforcement learning) to generate optimal control decisions.

[0076] By deploying a variety of high-precision sensors and adopting advanced digital information acquisition and processing technologies, the present invention can monitor and control stage sound effects, lighting and mechanical status in real time and accurately, greatly improving the automation and accuracy of performance effects, thereby meeting complex and changeable performance needs.

[0077] The present invention utilizes high-speed Ethernet, 5G wireless network or dedicated low-latency communication protocol to ensure real-time and stable transmission of data, reduce transmission delay, enable the system to quickly respond to various changes in the performance process, and enhance the audience's immersive experience.

[0078] The present invention introduces artificial intelligence decision-making and is based on deep learning and reinforcement learning algorithms. It can generate optimal control decisions according to current performance conditions and historical experience, realize intelligent management and optimization of performance effects, and improve the overall quality and effect of the performance.

[0079] In addition to basic stage sound effects, lighting and mechanical control, the present invention also supports the generation of visual effects such as virtual scenes, special effects animations, projection mapping, and the provision of intuitive graphical user interfaces and virtual reality and augmented reality interactive interfaces, enriching the performance effects and enhancing the audience's interactive experience.

[0080] The present invention monitors the operating status of the system and the working parameters of the equipment in real time, issues early warnings for possible abnormal situations such as failures, overloads, overheating, etc., and formulates emergency response plans to ensure the smooth progress of the performance and the safety of the audience.

[0081] The system architecture and modular design of the present invention make it have good scalability and flexibility, and can be flexibly configured and expanded according to different performance requirements and scenarios, meeting the diverse needs of the cultural performance industry.

[0082] In summary, the present invention realizes autonomous adaptation of multi-source stage sound effects, multi-point stage lighting, stage machinery and other states through digital information acquisition, processing and state matching technology, which not only improves the automation and accuracy of the performance, but also enriches the performance effect, enhances the audience's immersive and interactive experience, and ensures the safety of the performance.

[0083] Of course, the above are only preferred embodiments of the present invention, and the patent scope of the present invention is not limited thereto. All simple modifications and equivalent structural changes made using the contents of the specification and drawings of the present invention should be included in the patent protection scope of the present invention.

Claims

1. A digital control method for performance effects, characterized in that The following steps are involved: (a) Data collection: deploy a variety of high-precision sensors, including sound sensors, light sensors, position sensors, pressure sensors, and motion capture devices. High-precision sensors are distributed throughout the stage space. i =f i (t) represents the sampling data of the i-th sensor at time t, where S i is the sampling data, f i is the corresponding sampling function; (b) Data preprocessing: the collected raw data S i Perform preliminary processing, including data cleaning, data calibration and data compression, and use the formula S′ i =g i (S i ) represents the processed data, where S′ i is the processed data, g i is the corresponding processing function; (c) Data transmission, using high-speed Ethernet, 5G wireless network or dedicated low-latency communication protocol to ensure data S′ i Real-time and stable transmission, according to the formula T(S′ i ) = h(S′ i ,Δt) represents the data transmission efficiency within Δt time, where T(S′ i ) is the transmission efficiency, h is the transmission function; (d) Central control, running data analysis and processing software, including digital signal processing algorithms, machine learning models, optimization algorithms and simulation software, to monitor S′ i Conduct in-depth analysis and extract features where F j is the jth feature, is the corresponding feature extraction function; (e) State matching and decision making, specifically including the following steps: (e1) Building a large-scale performance effect status database; (e2) Real-time data F j It is precisely matched with the preset state in the database, using the formula M(F j )=θ(F j , D) represents the degree of matching, where M(F j ) is the matching degree, θ is the matching function, and D is the preset state in the database; (e3) Introducing artificial intelligence decision-making, based on deep learning and reinforcement learning algorithms, generates the optimal control decision according to the current performance situation and historical experience, using the formula C = α (M (F j ), H) represents the control decision, where C is the control decision, α is the decision function, and H is the historical experience data; (f) Control execution: The controller receives the control decision C and executes the control operation with microsecond accuracy to achieve precise adjustment of the stage sound equipment, lighting equipment and stage mechanical devices, according to the formula E = β (C, D e ) represents the execution effect, where E is the execution effect, β is the execution function, and D e The device status data.

2. A method for digitally controlling performance effects according to claim 1, characterized in that The following steps are also included: (g) Special effects generation: generating virtual scenes, special effects animations, and projection mapping visual effects according to performance requirements.

3. A performance effect digital control method according to claim 2, characterized in that The following steps are also included: (h) Human-computer interaction: It provides an intuitive graphical user interface and virtual reality and augmented reality interaction interfaces, and supports multiple interaction methods such as voice commands and gesture control.

4. A method for digitally controlling performance effects according to claim 3, characterized in that The following steps are also included: (i) Safety monitoring and emergency response: real-time monitoring of the system's operating status and equipment's operating parameters, early warning of possible failures, overloads, overheating, and formulation of emergency response plans.

5. A performance effect digital control method according to claim 4, characterized in that: In step (e1), the performance effect status database covers various types and styles of performance preset states.

6. A digital control system for performance effects, used to implement a digital control method for performance effects as claimed in claim 5, characterized in that: It includes a controller, a data acquisition module, a data preprocessing module, a data transmission module, a central control module, a state matching and decision-making module, a control execution module, a special effect generation module, a human-computer interaction module, and a safety monitoring and emergency handling module.

7. A performance effect digital control system according to claim 6, characterized in that: The data acquisition module includes: Sound sensor, used to collect sound data on the stage; Light sensors to measure light intensity and color distribution on the stage; Position sensors, used to determine the position of stage equipment, actors or audience members; a pressure sensor to detect pressure changes on the stage; Motion capture equipment is used to capture the movements and gestures of actors.

8. A performance effect digital control system according to claim 6, characterized in that: The data preprocessing module includes: Data cleaning unit, responsible for dealing with missing values, outliers and duplicate values ​​in the original data; A data calibration unit is used to adjust the data output by the sensor to eliminate the influence of sensor errors or environmental factors; Data compression unit, used to reduce data storage space and transmission time while maintaining data integrity and accuracy.

9. A performance effect digital control system according to claim 6, characterized in that: The central control module includes: The data processing and analysis unit is responsible for receiving data from the data acquisition module and performing preliminary processing and analysis; A digital signal processing unit processes and analyzes the received signal using a digital signal processing algorithm; The machine learning model unit uses machine learning algorithms to learn and predict the received data; Optimization algorithm unit, which uses optimization algorithm to optimize the control parameters and strategies of the system; The simulation software unit uses simulation software to simulate and predict the operation of the system.

10. A performance effect digital control system according to claim 6, characterized in that: The state matching and decision-making modules include: The state matching unit builds a large-scale performance effect state database to accurately match real-time data with the preset states in the database; Artificial intelligence decision-making unit uses artificial intelligence algorithms to generate optimal control decisions.

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