A rocket fairing noise reduction method and device and a storage medium

Abstract

The present application belongs to the technical field of rocket launching, and particularly relates to a method and device for reducing noise of a rocket fairing and a storage medium. The method comprises the following steps: collecting noise signals; performing frequency spectrum analysis on the collected noise signals by using fast Fourier transform to obtain frequency domain signals, wherein the frequency domain signals comprise amplitude and phase information under each different frequency component; setting boundaries of each frequency band, extracting feature information of each frequency band, and extracting noise components of each frequency band according to the feature information of each frequency band; optimizing noise reduction strategies of each frequency band by using an artificial bee colony algorithm to obtain the best frequency and amplitude of the anti-phase sound wave of each frequency band; and generating the anti-phase sound wave according to the output of the artificial bee colony algorithm to actively reduce noise of the fairing. The present application can improve the overall noise reduction performance of the fairing, has high response speed, has low requirements on computing resources, and is suitable for scenes with strict requirements on time and resources in the rocket launching scene.

Description

Technical Field

[0001] The present invention belongs to the field of rocket launching technology, and in particular relates to a method, equipment and storage medium for reducing noise of a rocket fairing. Background Art

[0002] During the launch of a rocket, the main function of the fairing is to protect the payload of the rocket and ensure that it is protected from external environmental factors such as aerodynamic pressure, heat flow and vibration during the launch and flight phases. However, the fairing will generate a lot of noise during the high-speed flight of the rocket. These noises mainly come from the following aspects: (1) Aerodynamic noise: During the launch of the rocket, the high-speed airflow on the surface of the fairing rubs against the air, separates and turbulently, forming strong aerodynamic noise. Especially during transonic and supersonic flight, the aerodynamic noise is particularly strong. (2) Structural vibration noise: During the operation of the rocket propulsion system, the vibration and shock waves generated by combustion are transmitted to the fairing through the rocket structure, causing it to generate vibration noise. (3) Aerodynamic instability: Due to the connection between the fairing and the rocket body and the design of the fairing shape, aerodynamic instability may occur, resulting in uneven fluid flow, which in turn causes additional noise.

[0003] During rocket launches, noise primarily interferes with precision electronics and payloads. Especially for high-precision equipment like communications satellites and observation instruments, intense noise and vibration can cause component failure, data transmission errors, and other potentially devastating consequences. Furthermore, high-frequency noise can cause material fatigue damage, shortening the lifespan of equipment. Safely, reliably, and efficiently implementing fairing noise reduction is a challenge currently facing the aerospace industry.

[0004] At present, the noise reduction methods of rocket fairings mainly include the following categories: (1) Structural design optimization: reducing aerodynamic noise by optimizing the shape of the fairing. This method is effective to a certain extent, but due to the complexity of the rocket aerodynamic design, the noise reduction effect is limited, and it is difficult to completely avoid the turbulent noise generated during high-speed flight. (2) Acoustic isolation materials: using sound-absorbing materials on the inner wall of the fairing to reduce noise propagation. However, the sound absorption effect of the material varies with frequency, and the effect on low-frequency and broadband noise is limited. At the same time, adding sound-absorbing materials may increase the weight of the rocket, thereby affecting the launch performance. (3) Active noise control: using sensors and speakers to generate anti-phase sound waves in real time to offset noise, but this technology has high requirements for the real-time performance of the noise frequency, and it is difficult to accurately match the noise waveform in a complex aerodynamic environment, which reduces the noise reduction effect. Therefore, although the existing technology can alleviate the noise problem during the rocket launch process to a certain extent, there are still technical bottlenecks. With the high precision of the payload and the improvement of the requirements for the launch environment, new and more efficient rocket fairing noise reduction technologies are particularly important. Therefore, researching and developing new rocket fairing noise reduction methods has great practical significance. Summary of the Invention

[0005] In order to solve the above technical problems, the present invention proposes a rocket fairing noise reduction method. By combining the advantages of fast Fourier transform (FFT) and artificial bee colony algorithm (ABC), the method aims to efficiently reduce the complex and multi-band noise during the rocket launch process, so as to significantly reduce the interference of noise on the equipment and improve the reliability of the launch mission and the life of the payload.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is: a rocket fairing noise reduction method, comprising the following steps:

[0007] Step 1: Collect a noise signal; perform spectrum analysis on the collected noise signal using fast Fourier transform to obtain a frequency domain signal, wherein the frequency domain signal includes amplitude and phase information at each different frequency component;

[0008] Step 2: Set the boundaries of each frequency band, divide the frequency into multiple frequency bands, extract the characteristic information of each frequency band, and extract the noise component of each frequency band based on the characteristic information of each frequency band;

[0009] Step 3: After removing the noise components from the frequency domain signals of each frequency band extracted in step 2, the noise reduction strategy of each frequency band is optimized using the artificial bee colony algorithm to obtain the optimal frequency and amplitude of the anti-phase sound wave in each frequency band;

[0010] Step 4: Generate anti-phase sound waves based on the output of the artificial bee colony algorithm to perform active noise reduction on the fairing.

[0011] The step 1 further comprises the following steps: pre-processing the collected signal, removing interference signal and background noise.

[0012] In the step 2, the specific method for extracting the noise component of each frequency band is: setting a noise threshold based on energy or amplitude, comparing the feature information of each frequency band with the noise threshold, and regarding the frequency band lower than the noise threshold as the noise component.

[0013] In the step 2, the set frequency band boundary includes the upper limit of the low frequency band, the upper limit of the medium frequency band and the lower limit of the high frequency band, and the frequency is divided into three frequency bands of low frequency, medium frequency and high frequency.

[0014] In the step 3, the artificial bee colony algorithm evaluates the noise reduction effect through the fitness function, and updates the frequency and amplitude of the inverse sound wave.

[0015] The step 4 further comprises the following steps: optimizing the sound absorption material of the fairing and its arrangement position, and performing passive noise reduction.

[0016] The rocket fairing noise reduction method further comprises the following steps:

[0017] Step 5: Real-time monitoring of the noise level in the fairing through the telemetry data of the noise sensor in the fairing, recording the signal change before and after active noise reduction, and analyzing the noise reduction effect.

[0018] In addition, the present application also provides a rocket fairing noise reduction device, comprising: a processor and a memory in communication connection with the processor;

[0019] The memory stores computer execution instructions;

[0020] The processor executes the computer execution instructions stored in the memory to realize the rocket fairing noise reduction method.

[0021] In addition, the present application also provides a computer readable storage medium, the computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by the processor to realize the rocket fairing noise reduction method.

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

[0023] (1) Strong broad-spectrum noise reduction ability.

[0024] This method uses a fast Fourier transform (FFT) to decompose complex noise signals into their frequency components, accurately identifying the distribution of low-, medium-, and high-frequency noise during rocket launches. Combined with the global optimization and local adjustment capabilities of the Artificial Bee Colony (ABC) algorithm, it can employ the optimal noise reduction strategy for each frequency band, ensuring effective suppression of multi-band noise.

[0025] (2) Adaptive optimization and real-time response.

[0026] The ABC algorithm possesses adaptive properties. The present invention uses this algorithm to solve for noise reduction parameters, dynamically adjusting them based on real-time environmental changes (such as changes in noise intensity and frequency). This method allows for real-time optimization during different rocket flight phases (such as takeoff, acceleration, and supersonic flight), ensuring optimal noise reduction at all times. This adaptive optimization capability enables the invention to achieve efficient noise reduction in complex and dynamic noise environments, enhancing the system's intelligence.

[0027] 3. Efficient computing and lightweight system

[0028] As an efficient spectrum analysis tool, FFT can quickly calculate the spectral characteristics of noise signals, providing a data foundation for noise reduction. Furthermore, the ABC algorithm uses intelligent optimization to avoid overly complex computational models, reducing hardware resource requirements and achieving a lightweight system design. This efficient computing architecture is well-suited for rocket launch scenarios, which place stringent time and resource requirements.

[0029] In summary, the present invention proposes a method, device and storage medium for reducing the noise of a rocket fairing, which quickly calculates the spectral characteristics of the noise signal based on the FFT algorithm, providing a data basis for noise reduction. At the same time, the ABC algorithm is used to intelligently optimize the noise reduction strategies for different frequency bands, avoiding overly complex calculation models, reducing the demand for hardware resources, and realizing a lightweight design of the system. Moreover, according to the noise reduction parameters optimized by the ABC algorithm, specific noise reduction measures are implemented, including generating and adjusting anti-phase sound waves to achieve active noise reduction, and optimizing the arrangement and selection of sound-absorbing materials to enhance the passive noise reduction effect. By selecting a combination of these measures, the noise level inside and outside the fairing is effectively reduced, and the overall noise reduction performance of the fairing is improved. Moreover, the noise reduction method of the present invention has a high response speed and low requirements for computing resources, and is suitable for scenarios with strict time and resource requirements in rocket launch scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 A schematic flow chart of a method for reducing noise of a rocket fairing provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are part of the embodiments of the present invention, not all the embodiments; based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0032] Example 1

[0033] like Figure 1 As shown, the first embodiment of the present invention provides a method for reducing noise of a rocket fairing, comprising the following steps:

[0034] Step 1: Collect the noise signal inside the fairing; use fast Fourier transform (FFT) to perform spectrum analysis on the collected noise signal to obtain a frequency domain signal, which includes amplitude and phase information at different frequency components.

[0035] The step 1 also includes the following steps: pre-processing the collected signal to remove interference signals and background noise.

[0036] In this step, the FFT algorithm is used to convert the preprocessed noise signal into the frequency domain, and the amplitude and phase information of different frequency components are identified to provide basic data for the subsequent noise reduction strategy formulation.

[0037] Step 2: Set the boundaries of each frequency band, divide the frequency into multiple frequency bands, extract the characteristic information of each frequency band, and extract and remove the noise components of each frequency band based on the characteristic information of each frequency band.

[0038] In this step, the FFT analysis results are thoroughly analyzed to extract characteristic information for each frequency band. Key parameters such as total energy, frequency center, and bandwidth are then calculated for each band. The primary noise components are identified, and the characteristics of the low-, mid-, and high-frequency bands are marked. This step aims to provide detailed spectral characteristic data for optimizing the ABC algorithm, ensuring the targeted nature of subsequent noise reduction strategies.

[0039] In step 2, the specific method for extracting the noise components of each frequency band is: setting a noise threshold based on energy or amplitude, comparing the characteristic information of each frequency band with the noise threshold, and treating the frequency band below the noise threshold as the noise component.

[0040] In step 2, the frequency band boundaries are set to include the upper limit of the low frequency band, the upper limit of the mid-frequency band, and the lower limit of the high frequency band, and the frequency band is divided into three frequency bands: low frequency, mid-frequency, and high frequency. Specifically, the upper limit of the low frequency band, the upper limit of the mid-frequency band, and the lower limit of the high frequency band are set to 100, 1000, and 10000 Hz, respectively. Then, the frequency ranges corresponding to the low frequency band, the mid-frequency band, and the high frequency band are obtained as follows: 0-100 Hz, 100-1000 Hz, and 1000-10000 Hz, respectively.

[0041] The following is a detailed technical description of step 2.

[0042] Input parameters include:

[0043] Number of signal samples N: The total number of signal samples when performing FFT analysis.

[0044] Sampling frequency fs: The sampling frequency of the signal, used to calculate the frequency corresponding to the frequency band.

[0045] FFT result: The frequency domain signal obtained after FFT transformation, which represents the amplitude and phase of each frequency component.

[0046] Frequency range F: The frequency range used for analysis, which is (0, fs / 2).

[0047] Frequency band division B = [b1, b2, b3]: used to distinguish the frequency band boundaries of low frequency, medium frequency and high frequency:

[0048] b1: upper limit of low frequency band;

[0049] b2: upper limit of the mid-frequency band;

[0050] b3: Lower limit of high frequency band.

[0051] Total energy E i : The total energy of the i-th (i=1, 2, 3) frequency band is calculated as the sum of the energies of each frequency component.

[0052] Frequency center f c,i : The frequency center of the i-th frequency band, which represents the weighted average frequency of the energy in this frequency band.

[0053] Bandwidth BWi: The bandwidth of the i-th frequency band, indicating the frequency range of the band.

[0054] Noise threshold Tn: The threshold used to distinguish signal from noise, calculated based on energy or amplitude.

[0055] Noise component marker C: records the markers of the identified main noise components and stores the frequency and amplitude of each component in array form.

[0056] The details are as follows:

[0057] (1) Prepare signal data and fast Fourier transform (FFT): Determine the number of signal samples N and the sampling frequency f s , generate or read the noise signal data to be analyzed, and perform a fast Fourier transform (FFT) on the signal to obtain its frequency domain representation:

[0058] N=2048,f s =1000Hz;

[0059] X(k)=FFT(signal);

[0060] Signal=sin(2Π×50t)+0.5×noise;

[0061] Among them, signal represents the original noise signal, X(k) represents the frequency domain signal after FFT transformation, k represents the frequency, and noise represents the noise component therein, where the noise component is random.

[0062] (2) Calculate frequency band characteristics and noise identification: set the frequency band boundary B and calculate the total energy E of each frequency band i , frequency center f c,i and bandwidth BW i , to identify the impact of noise components on the signal. The frequency band boundaries can be set as:

[0063] B=[b1,b2,b3]=[100,1000,10000]Hz;

[0064] The total energy E of each frequency band i The calculation is as follows:

[0065]

[0066] The frequency center is calculated as:

[0067]

[0068] Where X(k) represents the signal strength at the kth frequency, f(k) represents the frequency value corresponding to k, and Bi represents the i-th frequency band.

[0069] Bandwidth is defined as:

[0070] BW i =b j -b k , j=3,2,k=2,1; (3)

[0071] (3) Noise component labeling and output results: Setting the noise threshold T n , used to identify the signal noise component in the spectrum. The noise threshold can be set based on the mean value of the signal amplitude:

[0072] T n =mean(|X|); (4)

[0073] By comparing with the noise threshold, the noise component C is identified:

[0074] C=f where|X(k)| <T n ; (5)

[0075] Step 3: After removing the noise components from the frequency domain signals of each frequency band extracted in step 2, the remaining frequency domain signals are used as input. The noise reduction strategy of each frequency band is optimized through the artificial bee colony algorithm to obtain the optimal frequency and amplitude of the anti-phase sound wave in each frequency band.

[0076] Specifically, in step 3, the artificial bee colony algorithm evaluates the noise reduction effect through a fitness function and updates the frequency and amplitude of the anti-phase sound wave.

[0077] The following is a detailed technical description of step 3.

[0078] Input parameters include:

[0079] 1. M: colony size (number of bees participating in the search);

[0080] 2. T_max: number of iterations (maximum number of iterations the algorithm runs);

[0081] 3.S: Search space (the range of frequency and amplitude of the anti-phase sound wave)

[0082] 4.f_init: initial anti-phase sound wave frequency;

[0083] 5.A_init: initial inverse phase sound wave amplitude;

[0084] 6. L: learning factor (controls the balance between global search and local search);

[0085] 7.F_obj: fitness function (objective function for evaluating noise reduction effect);

[0086] 8. Δx: local search step size (the size of the steps the bee moves in the local search);

[0087] 9. ΔG: Global search range (the range of frequency and amplitude used for global search);

[0088] 10.BPF_params: Bandpass filter parameters (center frequency and bandwidth);

[0089] 11. D_a: Dynamic adaptability parameter (a parameter that is dynamically adjusted according to real-time noise changes);

[0090] 12. f_target: target frequency band for noise reduction (specific target frequency range);

[0091] 13. T_th: threshold for inhibition (set the minimum requirement for noise reduction effect).

[0092] Step 4: According to the output of the artificial bee colony algorithm, generate inverse sound waves to actively reduce the noise of the fairing.

[0093] The step 4 further comprises the following steps: optimizing the sound absorption material of the fairing and its arrangement position, and passively reducing the noise.

[0094] In this embodiment, the noise reduction parameters optimized by the ABC algorithm are used to implement specific noise reduction measures. These measures include generating and adjusting inverse sound waves to achieve active noise reduction, and optimizing the arrangement and selection of sound absorption materials to enhance passive noise reduction effect. By selecting these measures, the noise level inside and outside the fairing is effectively reduced, and the overall noise reduction performance of the fairing is improved.

[0095] Further, the rocket fairing noise reduction method of the embodiment further comprises the following steps:

[0096] Step 5: Real-time monitoring of noise level inside the fairing through telemetry data of noise sensors inside the fairing, recording signal changes before and after active noise reduction, and analyzing noise reduction effect.

[0097] The specific implementation of the embodiment is as follows:

[0098]

[0099]

[0100]

[0101]

[0102] The feasibility of the present application has been verified through a series of experiments, simulations and practical applications.

[0103] In summary, the embodiment provides a rocket fairing noise reduction method, which has the following technical features:

[0104] 1. The present application realizes the fusion of FFT spectrum analysis and ABC optimization.

[0105] In the present invention, FFT is used to analyze the spectral characteristics of noise, convert the noise from a time domain signal into a frequency domain signal, and decompose it into different frequency bands, such as low frequency, medium frequency, and high frequency. Based on the FFT decomposition, the ABC algorithm performs global search and local optimization for the noise characteristics of each frequency band, dynamically adjusts the noise reduction parameters, and realizes customized noise reduction processing for different frequency bands. FFT provides the spectral information of the noise, and ABC searches for the optimal noise reduction strategy in multiple frequency bands based on this information. FFT is responsible for "analysis and decomposition", while ABC is responsible for "optimization and execution", and the two work together to complete the noise reduction task.

[0106] 2. The present invention realizes the coordinated optimization of multi-band noise processing.

[0107] The present invention uses FFT to analyze the spectral characteristics and divides the fairing noise into multiple frequency bands. The ABC algorithm then adaptively finds the optimal noise reduction parameter combination based on the characteristics of each frequency band (e.g., passive sound absorption for low-frequency bands and active noise reduction for high-frequency bands). For example, the ABC algorithm optimizes the phase, amplitude, and frequency of the anti-phase sound waves of the active noise reduction system in each frequency band.

[0108] Example 2

[0109] Embodiment 2 of the present invention provides a rocket fairing noise reduction device, comprising: a processor and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement a rocket fairing noise reduction method as described in embodiment 1.

[0110] Example 3

[0111] Embodiment 3 of the present invention provides a computer-readable storage medium, in which computer execution instructions are stored. When the computer execution instructions are executed by a processor, they are used to implement a rocket fairing noise reduction method as described in embodiment 1.

[0112] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for reducing noise of a rocket fairing, characterized in that: The following steps are involved: Step 1: Collect a noise signal; perform spectrum analysis on the collected noise signal using fast Fourier transform to obtain a frequency domain signal, wherein the frequency domain signal includes amplitude and phase information at each different frequency component; Step 2: Set the boundaries of each frequency band, divide the frequency into multiple frequency bands, extract the characteristic information of each frequency band, and extract the noise component of each frequency band based on the characteristic information of each frequency band; Step 3: After removing the noise components from the frequency domain signals of each frequency band extracted in step 2, the noise reduction strategy of each frequency band is optimized using the artificial bee colony algorithm to obtain the optimal frequency and amplitude of the anti-phase sound wave in each frequency band; Step 4: Based on the output of the artificial bee colony algorithm, generate anti-phase sound waves to actively reduce the noise of the fairing.

2. A rocket fairing noise reduction method according to claim 1, characterized in that: The step 1 also includes the following steps: pre-processing the collected signal to remove interference signals and background noise.

3. The method for reducing noise of a rocket fairing according to claim 1, wherein: In step 2, the specific method for extracting the noise components of each frequency band is: setting a noise threshold based on energy or amplitude, comparing the characteristic information of each frequency band with the noise threshold, and treating the frequency band below the noise threshold as the noise component.

4. The method for reducing noise of a rocket fairing according to claim 1, wherein: In step 2, the frequency band boundaries set include a low frequency band upper limit, a mid frequency band upper limit and a high frequency band lower limit, and the frequency bands are divided into three frequency bands: low frequency, mid frequency and high frequency.

5. The method for reducing noise of a rocket fairing according to claim 1, wherein: In step 3, the artificial bee colony algorithm evaluates the noise reduction effect through a fitness function and updates the frequency and amplitude of the anti-phase sound wave.

6. A rocket fairing noise reduction method according to claim 1, characterized in that: The step 4 further includes the following steps: optimizing the sound absorbing material of the fairing and its arrangement position to perform passive noise reduction.

7. The method for reducing noise of a rocket fairing according to claim 1, wherein: The following steps are also included: Step 5: Use the telemetry data from the noise sensor inside the fairing to monitor the noise level inside the fairing in real time, record the signal changes before and after active noise reduction, and analyze the noise reduction effect.

8. A rocket fairing noise reduction device, characterized in that: include: a processor and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

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