Sound and vibration seat cooperative simulation system and method in helicopter simulator

Abstract

The application discloses a kind of helicopter simulator in sound and vibration seat collaborative simulation system and method, belong to flight simulation technical field.Its system includes sound data acquisition module, vibration data acquisition module, sound database, sound vibration data set construction module, sound vibration pre-training model, vibration seat driving component and collaborative simulation module component.Its method includes sound database construction, vibration data acquisition, sound vibration matching experiment, data set construction, model training, real-time simulation.The application effectively solves the problem of sound vibration asynchronization in traditional simulator, significantly improves the sense of reality and immersion of flight simulation, and provides a more realistic simulation environment for aviation training.The system has the characteristics of strong real-time, high precision, good adaptability, etc., and has good popularization and application value.

Description

Technical Field

[0001] This invention relates to the field of flight simulation technology, and in particular to a sound and vibration seat co-simulation system and method in a helicopter simulator. Background Technology

[0002] Existing helicopter flight simulators suffer from significant asynchrony issues in sound and vibration simulation, resulting in a poor user experience. Traditional methods often employ simple linear models to establish the sound-vibration relationship, which fails to accurately reflect the complex nonlinear relationship between sound and vibration in a real flight environment. Furthermore, due to low algorithm efficiency and significant system response delays, real-time synchronization of sound and vibration cannot be achieved, severely impacting the effectiveness of simulation training.

[0003] Most vibration seats on the market currently use preset vibration modes and cannot dynamically adjust vibration parameters according to real-time sound signals, lacking adaptive capabilities. In addition, sound acquisition and vibration parameter matching rely heavily on manual experience and lack scientific data-driven methods, resulting in unsatisfactory simulation effects. In particular, existing sound-vibration synchronization technology has the following defects: (1) the sound-vibration mapping relationship is too simple and cannot reflect the complex relationships in the real physical environment; (2) the system response delay is large and cannot meet the requirements of real-time simulation; (3) there is a lack of systematic data acquisition and processing methods, resulting in unsatisfactory simulation effects. Summary of the Invention

[0004] The purpose of this invention is to provide a sound and vibration seat co-simulation system and method in a helicopter simulator, which solves the problems of asynchronous sound and vibration, inaccurate model and poor real-time performance in the prior art, and significantly improves the realism and immersion of the helicopter simulator.

[0005] To achieve the above objectives, the present invention provides a sound and vibration seat co-simulation system for a helicopter simulator, comprising the following components connected in sequence: The sound data acquisition module is used to collect sound source files generated during helicopter flight and build a sound database containing sound intensity and frequency characteristics; The vibration data acquisition module is used to collect vibration data of the vibration seat during helicopter simulator operation, including vibration amplitude and frequency; The acoustic vibration dataset construction module determines the vibration parameters of the vibrating seats that match the sound features in the sound database through experiments, and identifies the sound features and corresponding vibration parameters to construct the acoustic vibration dataset. The acoustic and vibration pre-training model of the helicopter simulator is used to establish the mapping relationship between sound characteristics and vibration parameters; The co-simulation module is used to predict vibration parameters based on real-time sound data and control the vibration of the vibration seat during helicopter simulator operation. The output of the sound data acquisition module is connected to the input of the acoustic vibration dataset construction module, the output of the vibration data acquisition module is connected to another input of the acoustic vibration dataset construction module, the output of the acoustic vibration dataset construction module is connected to the training data input of the acoustic vibration pre-training model of the helicopter simulator, and the output of the acoustic vibration pre-training model of the helicopter simulator is connected to the control input of the co-simulation module.

[0006] Preferably, the sound data acquisition module includes an array system of multiple high-precision microphones, installed at different locations on the helicopter, for acquiring sound data of different directions and intensities.

[0007] Preferably, the vibration data acquisition module includes a sensor array composed of multiple high-precision accelerometers, which are installed at multiple locations on the vibration seat to collect vibration data from the vibration seat.

[0008] Preferably, the acoustic-vibration dataset construction module determines the acoustic-vibration matching relationship through ergonomic experiments, including playing sounds of different intensities and frequencies, adjusting the amplitude and frequency of the vibrating seat, and determining the optimal matching parameters through evaluation by testers.

[0009] Preferably, the acoustic vibration pre-training model adopts a MobileNetV3-Small lightweight neural network structure, with the input being the intensity and frequency characteristics of the sound, and the output being the amplitude and frequency of the vibrating seat.

[0010] Preferably, the co-simulation module can achieve a system response delay of less than 50ms and predict and control vibration parameters in real time based on sound data.

[0011] This invention also provides a method for co-simulating sound and vibration seats in a helicopter simulator, comprising the following steps: S1. Sound Database Construction: Collect sound source files generated during helicopter flight and construct a sound database, which includes sound audio files and sound intensity and frequency characteristics; S2. Vibration data acquisition: During the operation of the helicopter simulator, vibration data of the vibration seat is acquired, including the amplitude and frequency of the vibration. S3. Sound-Vibration Matching Experiment: The vibration parameters of the vibrating seat that match the sound features in the sound database are determined through experiments. S4. Dataset Construction: Integrate sound features and corresponding vibration parameters into a sound-vibration dataset; S5. Model Training: Use deep neural networks to establish the mapping relationship between sound features and vibration parameters; S6. Real-time simulation: When the helicopter simulator is running, vibration parameters are predicted based on real-time sound data, and the vibration of the vibrating seat is controlled to create a realistic cockpit environment and achieve collaborative simulation of sound and vibration.

[0012] Preferably, in step S3, the acoustic-vibration matching experiment adopts a multi-person ergonomic evaluation method, and the optimal acoustic-vibration matching relationship is determined through evaluation by professional pilots.

[0013] Preferably, in step S5, the model training step adopts the MobileNetV3-Small lightweight neural network structure and optimizes the model parameters by training the acoustic vibration dataset.

[0014] Preferably, in step S6, real-time simulation can achieve millisecond-level synchronization of sound and vibration.

[0015] Therefore, the sound and vibration seat co-simulation system and method in a helicopter simulator using the above-described structure of the present invention has the following beneficial effects: (1) This invention significantly enhances the realism and immersion of helicopter simulation training. The system employs a multi-position high-precision microphone array and accelerometer array to comprehensively collect sound and vibration data from the real flight environment, ensuring the accuracy and integrity of the source data. A complex nonlinear mapping relationship between sound features and vibration parameters is established through a MobileNetV3-Small lightweight neural network, effectively overcoming the limitations of traditional linear models. The co-simulation module can complete real-time prediction and control of sound to vibration within 50ms, achieving millisecond-level sound and vibration synchronization, accurately restoring the physical characteristics of the real flight environment, and providing users with a highly realistic training experience.

[0016] (2) The system provided by this invention has strong adaptive capabilities and can dynamically adjust vibration parameters according to different flight states and operation commands to adapt to the simulation requirements of various flight scenarios. The distributed processing architecture and optimized data flow design further improve the system's resource utilization efficiency and effectively reduce hardware costs while ensuring performance.

[0017] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of a sound and vibration seat co-simulation system in a helicopter simulator according to the present invention; Figure 2 This is a schematic diagram of the co-simulation method for sound and vibration seats in a helicopter simulator according to the present invention; Figure 3This is a MobileNetV3-Small network structure diagram of a sound and vibration seat co-simulation system and method in a helicopter simulator according to the present invention. Detailed Implementation

[0019] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0020] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0021] Example like Figure 1 As shown, the present invention provides a sound and vibration seat co-simulation system for a helicopter simulator, which adopts a modular design and includes the following components: a sound data acquisition module, a vibration data acquisition module, a sound database, a sound and vibration dataset construction module, a sound and vibration pre-training model for the helicopter simulator, a vibration seat drive component, and a co-simulation module.

[0022] Specifically, the sound data acquisition module includes multiple high-sensitivity microphones installed at different locations on the helicopter to collect sound data from different directions and intensities.

[0023] Vibration data acquisition module: including acceleration sensor and displacement sensor, installed on the base of the vibration seat, used to collect vibration data of the vibration seat.

[0024] Vibrating seat drive assembly: includes an electric vibrator and connecting rods. The electric vibrator generates vibration using electromagnetic principles, and the intensity and frequency of the vibration are controlled by changing the magnitude and frequency of the current. The connecting rods connect the vibrating actuator to the seat frame, transmit the vibration force, and support the seat while allowing it to move in different directions.

[0025] Sound database: A sound array that collects sound source files generated during helicopter flight to build a sound database containing sound data intensity and frequency characteristic attributes.

[0026] Acoustic-Vibration Dataset Construction Module: By playing sounds of different intensities and frequencies and adjusting the amplitude and frequency of the vibrating seat, test subjects evaluate the degree of matching between the sound and vibration, recording the vibration parameters corresponding to each sound. The sound data and corresponding vibration parameters are then integrated into an acoustic-vibration dataset.

[0027] Acoustic vibration pre-trained model: The mapping relationship between sound features and vibration parameters is established using the MobileNetV3-Small convolutional network, and the weights and biases of the model are optimized by training the acoustic vibration dataset.

[0028] Co-simulation module: When the helicopter simulator is running, it predicts vibration parameters based on real-time sound data and controls the vibration of the vibrating seat to create a realistic cockpit environment and achieve co-simulation of sound and vibration.

[0029] The system's workflow is as follows: The sound data acquisition module collects sound signals from various parts of the helicopter using a high-precision microphone array, extracts intensity and frequency features, and then transmits them to the sound and vibration dataset construction module. Simultaneously, the vibration data acquisition module collects seat vibration data through an accelerometer sensor network, and synchronously transmits the processed amplitude and frequency parameters to the dataset construction module. The sound and vibration dataset construction module matches and identifies the two types of data, then outputs a training dataset to the pre-trained model. The trained neural network model ultimately provides predictive support for the co-simulation module, enabling real-time mapping and output control of sound to vibration parameters.

[0030] like Figure 2 As shown, the present invention also provides a method for co-simulating sound and vibration seats in a helicopter simulator, the specific steps of which are as follows: S1. Sound Data Acquisition and Database Construction: During helicopter flight, multiple high-precision microphones are used to collect various sounds in the real flight environment, including rotor sounds, engine sounds, airflow sounds, instrument prompts, landing sounds, etc. The collected sound data is analyzed to extract the intensity (decibels) and frequency (hertz) features of the sound and construct a sound database.

[0031] S2. Vibration Data Acquisition: During helicopter simulator operation, multiple high-precision accelerometers are used to collect vibration data of the vibration seat, including vibration amplitude (displacement) and frequency (Hertz).

[0032] S3. Simulator Experiment to Build an Acoustic and Vibration Dataset: Select a typical flight environment for simulator flight simulation. During the simulation, rely on the simulator's sound system to simulate various sounds in the real flight environment, and adjust the amplitude and frequency of the vibration seat to allow testers to evaluate the degree of matching between sound and vibration, confirm the best match, record the vibration parameters corresponding to each sound, and establish an acoustic and vibration dataset.

[0033] S4. Pre-trained acoustic and vibration model for helicopter simulator: To accurately establish the mapping relationship between sound and seat vibration and improve the real-time synchronization of sound and vibration in helicopter simulator, a MobileNetV3-Small convolutional network is trained on the acoustic and vibration dataset. The pre-trained acoustic and vibration model is obtained by optimizing the model's weights and biases, thereby improving the model's prediction accuracy.

[0034] S5. Co-simulation Implementation: During helicopter simulator operation, the system plays sound characteristics in real time based on the simulator's sound system. The corresponding vibration parameters are predicted through the helicopter simulator's acoustic and vibration pre-training model. The amplitude and frequency of the vibration seat are adjusted in real time based on the predicted vibration parameters to achieve co-simulation of sound and vibration, creating a realistic cockpit environment.

[0035] like Figure 3 As shown, the MobileNetV3-SmallBottleneck network structure used in this invention is optimized for the real-time requirements of acoustic-vibration mapping, significantly improving computational efficiency while ensuring accuracy.

[0036] The network structure employs a bottleneck design principle, significantly reducing the number of parameters and computational cost through depthwise separable convolutions. The structure diagram shows three main parts: a dilated layer, a deep convolutional layer, and a compression layer. The dilated layer uses 1×1 convolutions to increase feature dimensionality; the deep convolutional layer uses 3×3 convolutions for spatial feature extraction; and the compression layer again uses 1×1 convolutions to reduce dimensionality and fuse features. This design allows the model to run efficiently on mobile devices, making it particularly suitable for real-time simulation scenarios. The diagram also shows a skip connection structure, effectively mitigating the vanishing gradient problem in deep networks and ensuring training stability. The network ultimately outputs the amplitude and frequency control parameters of the vibrating seat, achieving a high-precision nonlinear mapping from sound features to vibration parameters.

[0037] Therefore, this invention collects various sound data during helicopter flight, including sound intensity and frequency, to construct a sound database. It then determines the amplitude and frequency of a matching vibration seat through simulator flight experiments. Furthermore, it annotates the sound features and corresponding vibration parameters to create an acoustic-vibration dataset, and uses a neural network to establish a mapping relationship between sound and vibration. To achieve real-time synchronization of sound and vibration in the helicopter simulator, a lightweight convolutional neural network, MobileNetV3-Small, is trained on the acoustic-vibration dataset, effectively reducing computational load and parameter count, and improving algorithm efficiency.

[0038] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A sound and vibration seat co-simulation system for a helicopter simulator, characterized in that: It includes a sound data acquisition module, a vibration data acquisition module, a sound and vibration dataset construction module, a sound and vibration pre-training model for a helicopter simulator, and a co-simulation module, which are connected in sequence. The output of the sound data acquisition module is connected to the input of the sound and vibration dataset construction module, the output of the vibration data acquisition module is connected to another input of the sound and vibration dataset construction module, the output of the sound and vibration dataset construction module is connected to the training data input of the sound and vibration pre-training model of the helicopter simulator, and the output of the sound and vibration pre-training model of the helicopter simulator is connected to the control input of the co-simulation module. The sound data acquisition module is used to acquire sound data from different directions and intensities; The vibration data acquisition module is used to acquire vibration data from the vibration seat; The acoustic-vibration dataset construction module determines the acoustic-vibration matching relationship through ergonomic experiments, including playing sounds of different intensities and frequencies, adjusting the amplitude and frequency of the vibration seat, and determining the optimal matching parameters through evaluation by testers. The acoustic and vibration pre-training model of the helicopter simulator uses a deep neural network to establish the mapping relationship between sound features and vibration parameters; The co-simulation module predicts vibration parameters based on real-time sound data and controls the vibration of the vibrating seat during helicopter simulator operation to create a realistic cockpit environment and achieve co-simulation of sound and vibration.

2. The sound and vibration seat co-simulation system in a helicopter simulator according to claim 1, characterized in that: The sound data acquisition module includes an array system of multiple high-precision microphones, which are installed at different locations on the helicopter.

3. The sound and vibration seat co-simulation system in a helicopter simulator according to claim 1, characterized in that: The vibration data acquisition module includes a sensor array consisting of multiple high-precision accelerometers, which are installed at multiple locations on the vibration seat.

4. The sound and vibration seat co-simulation system in a helicopter simulator according to claim 1, characterized in that: The acoustic vibration pre-training model adopts a MobileNetV3-Small lightweight neural network structure. The input is the intensity and frequency characteristics of the sound, and the output is the amplitude and frequency of the vibrating seat.

5. The sound and vibration seat co-simulation system in a helicopter simulator according to claim 1, characterized in that: The co-simulation module can achieve a system response delay of less than 50ms and predict and control vibration parameters in real time based on sound data.

6. A method for co-simulating sound and vibration seats in a helicopter simulator, characterized in that, Includes the following steps: S1. Sound Database Construction: Collect sound source files generated during helicopter flight and construct a sound database, which includes sound audio files and sound intensity and frequency characteristics; S2. Vibration data acquisition: During the operation of the helicopter simulator, vibration data of the vibration seat is acquired, including the amplitude and frequency of the vibration. S3. Sound-Vibration Matching Experiment: The vibration parameters of the vibrating seat that match the sound features in the sound database are determined through experiments. S4. Dataset Construction: Integrate sound features and corresponding vibration parameters into a sound-vibration dataset; S5. Model Training: Use deep neural networks to establish the mapping relationship between sound features and vibration parameters; S6. Real-time simulation: When the helicopter simulator is running, vibration parameters are predicted based on real-time sound data, and the vibration of the vibrating seat is controlled to create a realistic cockpit environment and achieve collaborative simulation of sound and vibration.

7. The method for co-simulating sound and vibration seats in a helicopter simulator according to claim 6, characterized in that: In step S6, real-time simulation can achieve millisecond-level synchronization of sound and vibration.

8. A helicopter simulator device, characterized in that: The system comprises any one of claims 1-5.

9. A storage medium having a computer program stored thereon, characterized in that: When executed by a processor, the program implements the steps of the method described in any of claims 6-7.

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