Rotor aircraft coaxial contra-rotating sound source positioning method and system

Abstract

The invention discloses a coaxial contra-rotating sound source positioning method and system for a rotor aircraft, and belongs to the technical field of sound source recognition methods. Comprising the following steps: processing a sound pressure signal of a moving sound source by using a continuous wavelet transform method to obtain a time-frequency domain change result; doppler effect correction is carried out according to test working conditions; estimating the spatial position and the relative intensity of a noise source by adopting a cross-spectrum matrix and a weight vector; and performing phase-locked analysis on the intensity of the rotor noise source by using a phase-locked averaging method. The method is different from a traditional delay superposition algorithm working in a time domain and a cross-correlation spectrum method working in a frequency domain, an unsteady sound source can be imaged by using time-frequency domain features, the acoustic imaging problem of contra-rotating propeller noise is solved, and the method has potential application in the rotorcraft industry.

Description

Technical Field

[0001] The present invention relates to the technical field of sound source identification, and in particular to a method and system for locating the coaxial counter-rotating sound source of a rotorcraft. Background Art

[0002] Coaxial counter-rotating propellers are an old propulsion concept, dating back to Lanchester's patent in 1907. However, this concept has problems such as mechanical complexity, manufacturing cost, increased weight, vibration, propeller oscillation and noise. Among them, the noise problem of counter-rotating propellers remains an unresolved problem. For stationary sound sources, beamforming is a measurement technique used to estimate the location of noise sources. It has been widely used in aeroacoustic research to identify major aircraft noise sources. Most classical beamforming methods, including delay-sum and traditional beamforming methods, are effective in both the time domain and the frequency domain and can successfully handle fixed sound sources and moving aircraft flyover noise sources. To address specific aerospace applications, several advanced acoustic imaging methods have been proposed based on these classical beamforming methods. However, existing acoustic imaging methods cannot accurately locate rotating target sound sources.

[0003] To address the issue of rotating noise sources, Sijtsma first developed the so-called Rotating Source Identifier (ROSI), extending the delay-sum method to localize noise sources in a constantly rotating reference frame. In the ROSI method, Sijtsma employed a "de-Dopplerization" technique in the time domain to account for rotational effects (the Doppler effect). Later, Doughery and Walker, as well as Feng et al., proposed using a virtual rotating array to account for rotating sources. They employed a circular phased array coaxial with the propeller and processed the signals recorded by the microphone array to virtually set the rotation. Classical beamforming methods were then applied to the processed signals. Furthermore, Pannert and Maier also utilized a circular phased array and proposed a method based on modal decomposition. Guérin and Weckmüller proposed a beamforming method based on the short-time Fourier transform, which uses a Fourier transform based on time delay and the Doppler effect to achieve "de-Dopplerization." These methods can be applied to steady-state rotating problems, but encounter difficulties with transient phenomena, such as the case described by Fleury and Chélius in their work using these methods for counter-rotating devices. They found that the noise sources were located at locations in front of and behind the plane of rotation, locations that do not generate propeller noise.

[0004] The continuous wavelet transform method can analyze the sound pressure signal from the time-frequency domain, and can be used in combination with the acoustic imaging method to track the sound source generated by the counter-rotating propeller and analyze the noise generation mechanism. This beamforming method operating in the time-frequency domain can be applied to analyze problems such as stator-rotor interaction, shear layer-propeller interaction, and blade vortex interaction. However, unlike the interaction problems discussed in previous studies, the noise sources of counter-rotating propellers have different rotation directions. The coherence between the noise sources on different propeller blades leads to low spatial resolution of acoustic imaging and poses a challenge to wavelet-based beamforming methods. Summary of the Invention

[0005] In order to solve the problem of ambiguity in sound source localization caused by the coherence and Doppler shift of counter-rotating propellers, the present invention provides a method for localizing the coaxial counter-rotating sound source of a rotorcraft, comprising:

[0006] S1: Perform continuous wavelet transform on the sound pressure signal collected by the microphone array to obtain the time-frequency domain sound pressure signal;

[0007] S2: Calculate the displacement vector based on the scanning point and sensor coordinates, calculate the velocity vector of the point on the blade based on time and blade speed, and correct the sound pressure signal based on the Doppler effect to obtain the corrected time-frequency domain signal;

[0008] S3: Use the corrected time-frequency domain signal to construct the cross-spectral matrix, combine the steering vector and weight coefficient, and calculate the sound source imaging result;

[0009] S4: Through phase-locked averaging, the counter-rotating noise sources in the coaxial counter-rotating propeller are separated to generate the spatial and temporal distribution of the noise within the rotation period.

[0010] Furthermore, in S1, the time-frequency domain sound pressure signal is obtained by:

[0011]

[0012] Obtain, among which, is the time-frequency domain sound pressure signal, is the microphone sensor serial number, is the signal acquisition time, Compute frequencies for the continuous wavelet transform, is the Morse wavelet The scaling function of For sensors In time The original sound pressure signal;

[0013] Morse wavelet The scaling function is:

[0014]

[0015] Obtain, among which, Morse wavelet The center frequency is 1Hz, is the sampling frequency.

[0016] Furthermore, in S2, the corrected time-frequency domain signal is obtained by:

[0017]

[0018] Obtain, among which, is the corrected time-frequency domain signal, is the propagation time from the scanning surface to the sensor, is the actual noise frequency.

[0019] Furthermore, in S3, the cross-spectral matrix is ​​obtained by:

[0020]

[0021] Obtain, among which, represents the conjugate of the function;

[0022] Imaging results are obtained through:

[0023]

[0024] get, For the imaging results, is the frequency before Doppler effect correction, is the weight coefficient.

[0025] Furthermore, in S4, the spatial and temporal distribution of noise within the rotation period is obtained by:

[0026]

[0027] Obtain, among which, is the spatial and temporal distribution of noise within the rotation period, To calculate the time, is the average number of cycles, is the cycle count index, The time it takes to complete one rotation.

[0028] Also provided is a method and system for locating the coaxial counter-rotating sound source of a rotorcraft, including:

[0029] A transformation module is used to perform continuous wavelet transform on the sound pressure signal collected by the microphone array to obtain a time-frequency domain sound pressure signal;

[0030] A correction module is used to calculate the displacement vector based on the scanning point and the sensor coordinates, calculate the velocity vector of the point on the blade based on the time and the blade speed, and correct the sound pressure signal based on the Doppler effect to obtain a corrected time-frequency domain signal;

[0031] The imaging module is used to construct a cross-spectral matrix using the corrected time-frequency domain signals, and calculate the sound source imaging results by combining the steering vector and weight coefficients;

[0032] The separation module is used to separate the counter-rotating noise sources in the coaxial counter-rotating propeller through phase-locked averaging processing and generate the temporal and spatial distribution results of the noise within the rotation period.

[0033] Beneficial effects of the present invention:

[0034] The present invention proposes a counter-rotating sound source identification method applied to rotor tests. The method uses a continuous wavelet transform to process the sound pressure signal of a moving sound source, obtains the time-frequency domain change results, and solves the problem that traditional sound source identification methods cannot identify moving sound sources. The Doppler effect is corrected according to the test conditions to reduce the influence of the Doppler frequency shift generated by the rotation of the blades on the positioning results. The instantaneous change process of the counter-rotating propeller noise is calculated using a sound source imaging method based on wavelet transform. The phase-locked averaging method is used to average the noise source in different rotation directions, reduce background noise interference, highlight the main noise from the front and rear blades, and improve the accuracy of the acoustic imaging results. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 Flow chart of the method of the present invention;

[0036] Figure 2 Schematic diagram of the experimental setup;

[0037] Figure 3 This is the spatial distribution diagram of the 7kHz noise source of the counter-rotating propeller;

[0038] Figure 4 This is the average acoustic imaging result of the noise of the counter-rotating propeller at 4800rpm. DETAILED DESCRIPTION

[0039] The technical solution of the present invention is further described below with reference to the embodiments, but is not limited thereto. Any modification or equivalent replacement of the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention shall be included in the scope of protection of the present invention. The process equipment or devices not specifically noted in the following examples are all conventional equipment or devices in the art. Unless otherwise specified, the raw materials used in the examples of the present invention can be obtained commercially; unless otherwise specified, the technical means used in the examples of the present invention are all conventional means well known to those skilled in the art.

[0040] Example 1, combined Figure 1 In this embodiment, a method for locating a coaxial counter-rotating sound source of a rotorcraft includes:

[0041] S1: Perform continuous wavelet transform on the sound pressure signal collected by the microphone array to obtain the time-frequency domain sound pressure signal;

[0042] S2: Calculate the displacement vector based on the scanning point and sensor coordinates, calculate the velocity vector of the point on the blade based on time and blade speed, and correct the sound pressure signal based on the Doppler effect to obtain the corrected time-frequency domain signal;

[0043] S3: Use the corrected time-frequency domain signal to construct the cross-spectral matrix, combine the steering vector and weight coefficient, and calculate the sound source imaging result;

[0044] S4: Through phase-locked averaging, the counter-rotating noise sources in the coaxial counter-rotating propeller are separated to generate the spatial and temporal distribution of the noise within the rotation period.

[0045] Specifically, the placement of the test instruments is as follows: Figure 2 As shown, the test was conducted in an anechoic chamber. The present invention employed two counter-rotating propellers with a diameter of 0.22 meters and an axial separation of 0.02 meters. The front and rear propellers rotated clockwise and counterclockwise at the same speed and periodically overlapped on the x- and y-axes. The origin of the rotation angle was defined as the position where the front and rear propellers overlapped on the x-axis, and the encoder generated a pulse signal at this position. A 56-channel microphone array was used to measure the noise signal generated by the propellers. The array was parallel to the rotation plane and 0.8 meters from the center of the propellers. A National Instruments acquisition system was used to simultaneously acquire the propeller rotation angle and the corresponding acoustic signal at a sampling frequency of 50 kHz. The sound pressure level (SPL) was calculated for 50 blocks (based on the acquired pulse signals), each block length being 1 × 10,000 samples, to obtain reliable statistical results.

[0046] The present invention uses a continuous wavelet transform method to process the sound pressure signal of a moving sound source to obtain the time-frequency domain variation results; performs Doppler effect correction according to the test conditions; uses a cross-spectral matrix and a weight vector to estimate the spatial position and relative intensity of the noise source; and uses a phase-locked averaging method to perform phase-locked analysis on the rotor noise source intensity, ultimately obtaining the exact location of the noise generated by the counter-rotating blades.

[0047] In S1, the time-frequency domain sound pressure signal is obtained by:

[0048]

[0049] Obtain, among which, is the time-frequency domain sound pressure signal, is the microphone sensor serial number, is the signal acquisition time, Compute frequencies for the continuous wavelet transform, is the Morse wavelet The scaling function of For sensors In time The original sound pressure signal;

[0050] Morse wavelet The scaling function is:

[0051]

[0052] Obtain, among which, Morse wavelet The center frequency is 1Hz, is the sampling frequency.

[0053] Specifically, this step uses a continuous wavelet transform method to process the sound pressure signal of the moving sound source to obtain the time-frequency domain change results, thereby solving the problem that traditional sound source recognition methods cannot identify moving sound sources.

[0054] In S2, the corrected time-frequency domain signal is passed through:

[0055]

[0056] Obtain, among which, is the corrected time-frequency domain signal, is the propagation time from the scanning surface to the sensor, is the actual noise frequency.

[0057] Specifically, this step corrects the Doppler effect according to the test conditions to reduce the influence of the Doppler frequency shift caused by the rotation of the blades on the positioning result.

[0058] The actual noise frequency is generated by:

[0059]

[0060] Obtain, among which, is the frequency before Doppler effect correction, is the Doppler frequency shift coefficient, is the Doppler frequency shift.

[0061] The Doppler shift coefficient is obtained by:

[0062]

[0063] Obtain, among which, is the rotor rotation speed vector, is the propagation speed of the medium wave, is the angle between the rotor speed direction and the sound wave propagation direction.

[0064] The Doppler frequency shift satisfies:

[0065]

[0066] The angle between the rotor speed direction and the sound wave propagation direction and the rotor rotation speed vector satisfies:

[0067]

[0068] in, is the displacement vector with the point on the scanning surface as the starting point and the sensor as the end point.

[0069] The propagation time from the scanning surface to the sensor is:

[0070]

[0071] get.

[0072] In S3, the cross-spectral matrix is ​​obtained by:

[0073]

[0074] Obtain, among which, represents the conjugate of the function;

[0075] Imaging results are obtained through:

[0076]

[0077] get, For the imaging results, is the frequency before Doppler effect correction, is the weight coefficient.

[0078] Specifically, this step utilizes a sound source imaging method based on wavelet transform to calculate and obtain the instantaneous change process of the counter-rotating propeller noise.

[0079] The weight coefficients are obtained by:

[0080]

[0081] Obtain, among which, represents the norm calculation, is the steering vector after Doppler correction.

[0082] The Doppler corrected steering vector is obtained by:

[0083]

[0084] get.

[0085] Figure 3 The acoustic imaging results of the contra-rotating propeller at different rotation speeds at 7 kHz are shown.

[0086] In S4, the spatial and temporal distribution of noise within the rotation period is obtained by:

[0087]

[0088] Obtain, among which, is the spatial and temporal distribution of noise within the rotation period, To calculate the time, is the average number of cycles, is the cycle count index, The time it takes to complete one rotation.

[0089] Specifically, this step uses a phase-locked averaging method to average the noise source in different rotation directions, reduce background noise interference, highlight the main noise from the front and rear blades, and improve the accuracy of the acoustic imaging results.

[0090] When observing a specific propeller for a long time, the noise sources with different rotation directions and rotation speeds will become background noise through long-term averaging. The test processing results are as follows: Figure 4 The figure shows the average acoustic imaging results of clockwise and counterclockwise rotating propellers at 4800 rpm. The noise sources are averaged in different rotation directions to highlight the main noise from the front and rear propellers.

[0091] Also provided is a method and system for locating the coaxial counter-rotating sound source of a rotorcraft, including:

[0092] A transformation module is used to perform continuous wavelet transform on the sound pressure signal collected by the microphone array to obtain a time-frequency domain sound pressure signal;

[0093] A correction module is used to calculate the displacement vector based on the scanning point and the sensor coordinates, calculate the velocity vector of the point on the blade based on the time and the blade speed, and correct the sound pressure signal based on the Doppler effect to obtain a corrected time-frequency domain signal;

[0094] The imaging module is used to construct a cross-spectral matrix using the corrected time-frequency domain signals, and calculate the sound source imaging results by combining the steering vector and weight coefficients;

[0095] The separation module is used to separate the counter-rotating noise sources in the coaxial counter-rotating propeller through phase-locked averaging processing and generate the temporal and spatial distribution results of the noise within the rotation period.

Claims

1. A method for localizing the coaxial counter-rotating sound source of a rotorcraft, characterized in that: include: S1: Perform continuous wavelet transform on the sound pressure signal collected by the microphone array to obtain the time-frequency domain sound pressure signal; S2: Calculate the displacement vector based on the scanning point and sensor coordinates, calculate the velocity vector of the point on the blade based on time and blade speed, and correct the sound pressure signal based on the Doppler effect to obtain the corrected time-frequency domain signal; S3: Use the corrected time-frequency domain signal to construct the cross-spectral matrix, combine the steering vector and weight coefficient, and calculate the sound source imaging result; S4: Through phase-locked averaging, the counter-rotating noise sources in the coaxial counter-rotating propeller are separated to generate the spatial and temporal distribution of the noise within the rotation period.

2. The method for locating the coaxial counter-rotating sound source of a rotorcraft according to claim 1, characterized in that: In S1, The time-frequency domain sound pressure signal is obtained by: Obtain, among which, is the time-frequency domain sound pressure signal, is the microphone sensor serial number, is the signal acquisition time, Compute frequencies for the continuous wavelet transform, is the Morse wavelet The scaling function of For sensors In time The original sound pressure signal; Morse wavelet The scaling function is: Obtain, among which, Morse wavelet The center frequency is 1Hz, is the sampling frequency.

3. The method for locating the coaxial counter-rotating sound source of a rotorcraft according to claim 1, characterized in that: In S2, the corrected time-frequency domain signal is passed through: Obtain, among which, is the corrected time-frequency domain signal, is the propagation time from the scanning surface to the sensor, is the actual noise frequency.

4. The method for locating the coaxial counter-rotating sound source of a rotorcraft according to claim 1, characterized in that: In S3, the cross-spectral matrix is ​​obtained by: Obtain, among which, represents the conjugate of the function; Imaging results are obtained through: get, For the imaging results, is the frequency before Doppler effect correction, is the weight coefficient.

5. The method for locating the coaxial counter-rotating sound source of a rotorcraft according to claim 1, characterized in that: In S4, the spatial and temporal distribution of noise within the rotation period is obtained by: Obtain, among which, is the spatial and temporal distribution of noise within the rotation period, To calculate the time, is the average number of cycles, is the cycle count index, The time it takes to complete one rotation.

6. A method and system for localizing the coaxial counter-rotating sound source of a rotorcraft, characterized in that: include: A transformation module is used to perform continuous wavelet transform on the sound pressure signal collected by the microphone array to obtain a time-frequency domain sound pressure signal; A correction module is used to calculate the displacement vector based on the scanning point and the sensor coordinates, calculate the velocity vector of the point on the blade based on the time and the blade speed, and correct the sound pressure signal based on the Doppler effect to obtain a corrected time-frequency domain signal; The imaging module is used to construct a cross-spectral matrix using the corrected time-frequency domain signals, and calculate the sound source imaging results by combining the steering vector and weight coefficients; The separation module is used to separate the counter-rotating noise sources in the coaxial counter-rotating propeller through phase-locked averaging processing and generate the temporal and spatial distribution results of the noise within the rotation period.

Images