Rocket fairing noise reduction method and device and storage medium

Abstract

The invention belongs to the technical field of rocket launching, and particularly relates to a rocket fairing noise reduction method and device and a storage medium. The method comprises the following steps: acquiring a noise signal; performing spectral analysis on the acquired noise signal by adopting fast Fourier transform to obtain a frequency domain signal, the frequency domain signal comprising amplitude and phase information under different frequency components; setting a boundary 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; the noise reduction strategy of each frequency band is optimized through an artificial bee colony algorithm, and the optimal frequency and amplitude of the anti-phase sound waves of each frequency band are obtained; and according to the output of the artificial bee colony algorithm, anti-phase sound waves are generated, and active noise reduction is carried out on the fairing. According to the method, the overall noise reduction performance of the fairing can be improved, the response speed is high, the requirement for computing resources is low, and the method is suitable for scenes with strict requirements for time and resources in rocket launching scenes.

Description

Technical Field

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

[0002] During the launch of a rocket, the main function of the fairing is to protect the rocket's payload 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 a rocket, the friction, separation and turbulence of the high-speed airflow on the surface of the fairing and the air form 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 the combustion are transmitted to the fairing through the rocket structure, causing it to generate vibration noise. (3) Aerodynamic instability: Due to the design of the connection between the fairing and the rocket body and the shape of the fairing, aerodynamic instability may occur, resulting in uneven fluid flow, which in turn causes additional noise.

[0003] During rocket launches, the main impact of noise is the interference with precision electronic equipment and payloads. Especially for high-precision equipment such as communication satellites and observation instruments, strong noise and vibration may cause component failure, data transmission errors and other potentially destructive consequences. In addition, high-frequency noise can also cause fatigue damage to materials and shorten the service life of equipment. How to safely, reliably and efficiently implement fairing noise reduction is a problem that needs to be solved in the aerospace field.

[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 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 the frequency, and the effect is limited for low-frequency and broadband noise. 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 the 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 rocket launch to a certain extent, there are still technical bottlenecks. With the high precision of the payload and the increasing 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, which aims to perform efficient noise reduction processing on the complex and multi-band noise in the rocket launch process by combining the advantages of fast Fourier transform (FFT) and artificial bee colony algorithm (ABC), 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 components of each frequency band according to the characteristic information of each frequency band;

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

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

[0011] The step 1 also includes the following steps: preprocessing the collected signal to remove interference signals and background noise.

[0012] 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 taking the frequency band below the noise threshold as the noise component.

[0013] In step 2, the frequency band boundaries are set including a low frequency band upper limit, a mid frequency band upper limit and a high frequency band lower limit, and the frequency is divided into three frequency bands: low frequency, mid frequency and high frequency.

[0014] 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.

[0015] The step 4 also includes the following steps: optimizing the sound absorbing material of the fairing and its arrangement position to perform passive noise reduction.

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

[0017] Step 5: Use the remote sensing data of 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.

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

[0019] The memory stores computer-executable instructions;

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

[0021] In addition, the present invention also 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 the rocket fairing noise reduction method.

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

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

[0024] The present invention decomposes complex noise signals into different frequency components through Fast Fourier Transform (FFT), and accurately identifies the low-frequency, medium-frequency, and high-frequency noise distribution during rocket launch. Combined with the global optimization and local adjustment capabilities of the Artificial Bee Colony (ABC) algorithm, the optimal noise reduction strategy can be adopted for each frequency band to ensure the effective suppression of multi-band noise.

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

[0026] The ABC algorithm has adaptive characteristics. The present invention uses the ABC algorithm to solve the noise reduction parameters, which can dynamically adjust the noise reduction parameters according to real-time environmental changes (such as changes in noise intensity and frequency). Real-time adjustment in different flight phases of the rocket (such as takeoff, acceleration, supersonic flight, etc.), the method can be optimized in real time to ensure that the noise reduction effect is always in the best state. This adaptive optimization capability enables the invention to still effectively reduce noise in complex and dynamic noise environments, improving the intelligence level of the system.

[0027] 3. Efficient computing and lightweight system

[0028] As an efficient spectrum analysis tool, FFT can quickly calculate the spectrum characteristics of noise signals and provide a data basis for noise reduction. At the same time, the ABC algorithm avoids overly complex calculation models through intelligent optimization, reduces the demand for hardware resources, and realizes a lightweight design of the system. This efficient computing architecture is suitable for rocket launch scenarios that have strict time and resource requirements.

[0029] In summary, the present invention proposes a method, device and storage medium for reducing noise of a rocket fairing, which quickly calculates the spectral characteristics of the noise signal based on the FFT algorithm to provide 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 the 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 can be effectively reduced, and the overall noise reduction performance of the fairing can be 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 rocket launch scenarios with strict requirements on time and resources. 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, rather than 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] Embodiment 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 in 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: preprocessing 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, identify the amplitude and phase information of different frequency components, and 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 analyzed in depth to extract the characteristic information of each frequency band. Then, key parameters such as the total energy, frequency center, and bandwidth of each frequency band are calculated to identify the main components of the noise and mark the characteristics of the low-frequency, medium-frequency, and high-frequency bands. The goal of this step is to provide detailed spectrum characteristic data for the optimization of the ABC algorithm to ensure the pertinence of the subsequent noise reduction strategy.

[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 taking 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 middle frequency band and the lower limit of the high frequency band, and the frequency is divided into three frequency bands of low frequency, middle frequency and high frequency. Specifically, the upper limit of the low frequency band, the upper limit of the middle frequency band and the lower limit of the high frequency band are set to 100, 1000 and 10000 Hz respectively, and the frequency ranges corresponding to the low frequency band, middle frequency band and 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] The 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, indicating the amplitude and phase of each frequency component.

[0046] Frequency range F: The frequency range used for analysis, (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-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 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] Among them, 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 in the frequency domain signals of each frequency band extracted in step 2, the remaining frequency domain signals are used as input, and the noise reduction strategy of each frequency band is optimized by the artificial bee colony algorithm to obtain the optimal frequency and amplitude of the anti-phase sound wave of 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] The input parameters include:

[0079] 1. M: colony size (the 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 (range of frequency and amplitude of anti-phase sound wave)

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

[0083] 5.A_init: initial anti-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 step 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 dynamically adjusted according to real-time noise changes);

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

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

[0092] Step 4: Generate anti-phase sound waves based on the output of the artificial bee colony algorithm to actively reduce the noise of the fairing.

[0093] The step 4 also includes the following steps: optimizing the sound absorbing material of the fairing and its arrangement position to perform passive noise reduction.

[0094] In this embodiment, specific noise reduction measures are implemented by optimizing the noise reduction parameters obtained by the ABC algorithm. This includes 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.

[0095] Furthermore, a rocket fairing noise reduction method of this embodiment further includes the following steps:

[0096] Step 5: Use the remote sensing data of 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.

[0097] The schematic code for the specific implementation of this embodiment is as follows:

[0098]

[0099]

[0100]

[0101]

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

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

[0104] 1. The present invention realizes the integration 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 time domain signals to frequency domain signals, and decompose it into different frequency bands, such as low frequency, medium frequency and high frequency. Based on 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 together complete the noise reduction task.

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

[0107] In the present invention, after performing spectrum characteristic analysis by FFT, the fairing noise is divided into multiple frequency bands, and then the ABC algorithm is used to adaptively find the optimal noise reduction parameter combination according to the characteristics of each frequency band (such as passive sound absorption in low frequency bands and active noise reduction in high frequency bands). For example, the ABC algorithm is used to optimize the phase, amplitude and frequency of the anti-phase sound wave of the active noise reduction system in each frequency band.

[0108] Embodiment 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 execution instructions; the processor executes the computer execution instructions stored in the memory to implement a rocket fairing noise reduction method as described in Embodiment 1.

[0110] Embodiment 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 aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned 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 components of each frequency band according to the characteristic information of each frequency band; Step 3: After removing the noise components in the frequency domain signals of each frequency band extracted in step 2, the noise reduction strategy of each frequency band is optimized by artificial bee colony algorithm to obtain the optimal frequency and amplitude of the anti-phase sound wave of each frequency band; Step 4: Generate anti-phase sound waves based on the output of the artificial bee colony algorithm 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: preprocessing the collected signal to remove interference signals and background noise.

3. A rocket fairing noise reduction method according to claim 1, characterized in that: 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 taking the frequency band below the noise threshold as the noise component.

4. A rocket fairing noise reduction method according to claim 1, characterized in that: In step 2, the frequency band boundaries are set including a low frequency band upper limit, a mid frequency band upper limit and a high frequency band lower limit, and the frequency is divided into three frequency bands: low frequency, mid frequency and high frequency.

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

7. A rocket fairing noise reduction method according to claim 1, characterized in that: The following steps are also included: Step 5: Use the remote sensing data of 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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