A method for evaluating sound insulation characteristics of a sound barrier suitable for a complex sound field of an actual ship

Abstract

The application discloses a sound barrier sound insulation characteristic evaluation method suitable for a complex sound field of a real ship and belongs to the technical field of sound barriers of real ships, and the method comprises the following steps: arranging a hydrophone array at the acoustically mirror-symmetrical positions on the two sides of a sound barrier of a ship dome to form an in-situ measurement pair; controlling the ship to sail at multiple speeds; synchronously collecting time-domain signals of sound pressure on the two sides; pre-processing the signals, performing time-frequency analysis, calculating the sound pressure levels of the sound-incident surface and the back sound surface, and obtaining the in-situ sound pressure level difference; based on the sound pressure level differences under different speeds, analyzing the change rule of the sound insulation performance with frequency and speed, and comprehensively evaluating the sound insulation performance; and through the arrangement of vibration sensors and turbulent flow measuring devices, the path separation of structure-borne sound and flow-induced noise is realized, and the spatial coherence weighted average is introduced to improve the accuracy and representativeness of the evaluation under the complex sound field. The method overcomes the limitations of the distorted laboratory test environment and the single working condition, and can truly and comprehensively reflect the actual sound insulation efficiency of the sound barrier in the dynamic sailing of the real ship.

Description

Technical Field

[0001] This invention belongs to the field of sound baffle technology for actual ships, and specifically relates to a method for evaluating the sound insulation characteristics of sound baffles applicable to complex sound fields on actual ships. Background Technology

[0002] As a front-end component of sonar and other underwater acoustic systems, the core function of a ship's fairing is to provide hydrodynamic protection for the underwater acoustic transducer elements while minimizing interference from hydrodynamic noise. However, under actual ship navigation conditions, broadband self-noise generated by mechanical vibration, propeller operation, and turbulent boundary layers can enter the fairing through both structural transmission and fluid-acoustic coupling, severely limiting the detection range and resolution of the sonar system. To improve the acoustic environment of the sonar compartment, acoustic baffles are typically installed inside the fairing to isolate and attenuate noise from the direction of the ship's hull; their performance directly determines the final signal-to-noise ratio of the underwater acoustic system.

[0003] Currently, the evaluation of sound baffle performance generally relies on laboratory measurements, such as measuring insertion loss using standard sound sources in anechoic tanks. However, these methods struggle to reproduce the complex structural vibrations, non-uniform flow fields, and cabin acoustic cavity coupling effects encountered during real-world navigation. Of particular note is the presence of localized features such as reinforced structures at the stern of actual ship fairings, which can cause sound field distortion. These effects are easily overlooked in simplified laboratory models but are crucial in practical applications. Therefore, developing in-situ measurement techniques for actual ships to directly obtain the actual noise reduction effect of sound baffles under real-world conditions is of irreplaceable value for the acoustic design and combat effectiveness assessment of equipment.

[0004] Existing technologies have the following obvious shortcomings in practical engineering applications:

[0005] Environmental distortion: The underwater acoustic field of a real ship is highly complex and non-uniform, with a wide distribution of sound sources and diverse paths (including mechanical noise, propeller noise, flow-induced noise, and external environmental noise), and is strongly coupled with the vibration of the ship's structure and the turbulent fluctuations of the fluid boundary layer. Traditional laboratory or static testing cannot reproduce this complex acoustic environment with multi-physics coupling, leading to a significant deviation between the evaluation results and the actual sound insulation performance of the real ship.

[0006] Lack of dynamic operating conditions: At different speeds, the noise source intensity, frequency distribution, and structural vibration characteristics of ships all change dynamically, especially the transmission paths of flow-induced noise and structural sound, which vary significantly with speed. Most existing assessment methods are conducted under single, static operating conditions, failing to systematically examine the impact of speed changes on the sound insulation performance of sound baffles, and therefore cannot provide effective data support for acoustic design under all operating conditions.

[0007] Insufficient separation of interference factors: In the complex acoustic field of a real ship, the acoustic energy received by the back surface of the sound baffle comes not only from transmitted sound, but also from the re-radiated acoustic energy of structural vibration transmitted through the mounting base, as well as the flow-induced noise directly excited by the pressure pulsation of the turbulent boundary layer outside the fairing. Existing methods often fail to effectively identify and separate the above-mentioned multi-path contributions, resulting in the calculated "sound insulation" being a mixture of multiple transmission mechanisms, which cannot truly reflect the sound insulation capability of the sound baffle itself.

[0008] Spatial representativeness limitations: The sound field of a real ship is often non-uniformly distributed in space, and the local sound pressure level may fluctuate significantly. Traditional single-point measurement or sparse point distribution methods are easily affected by local distortions in the sound field, resulting in assessment results that lack spatial representativeness, have low confidence, and are difficult to fully reflect the sound insulation performance of the entire sound baffle area.

[0009] The evaluation indicators are too simplistic: existing evaluations focus on the sound insulation at specific frequency points or the average sound insulation under a certain working condition. They lack a multi-dimensional quantitative evaluation system that comprehensively considers spectral characteristics, dynamic change patterns and spatial uniformity, and cannot conduct a scientific and comprehensive graded evaluation of the overall sound insulation performance of sound barriers in the complex environment of actual ships.

[0010] Therefore, there is an urgent need to develop a new method for evaluating the sound insulation characteristics of sound barriers that can adapt to the complex sound field of actual ships, integrate dynamic testing under multiple working conditions, achieve separation of multiple interference paths, and have spatial representativeness and comprehensive quantitative evaluation capabilities, so as to make up for the above-mentioned shortcomings of existing technologies and provide accurate and reliable technical means for the design optimization, condition monitoring and performance evaluation of sound barriers on actual ships. Summary of the Invention

[0011] In view of this, to overcome the shortcomings of existing technologies in effectively evaluating the actual sound insulation performance of sound baffles under complex acoustic field environments on actual ships, this invention provides a method for evaluating the sound insulation characteristics of sound baffles applicable to complex acoustic fields on actual ships. This method directly quantifies the actual noise reduction effect of sound baffles under real navigation conditions through in-situ measurements, without relying on ideal acoustic environments or removing sound baffles to construct benchmarks. It has the advantages of being highly operable and providing intuitive and reliable results.

[0012] To achieve the above objectives, the present invention provides the following technical solution:

[0013] A method for evaluating the sound insulation properties of sound baffles applicable to complex sound fields on actual ships includes the following steps:

[0014] S1. Measurement system layout: On both sides of the acoustic baffle of the actual ship fairing, select acoustic mirror symmetrical positions to install the first hydrophone structure and the second hydrophone structure respectively, forming an in-situ measurement pair;

[0015] S2. Dynamic operating condition data acquisition: Control the ship to sail at multiple different speeds. Under each speed condition, synchronously acquire the sound pressure time domain signal measured by the first hydrophone structure and the second hydrophone structure. The first hydrophone structure is located on the front side of the sound baffle, and the second hydrophone structure is located on the back side of the sound baffle.

[0016] S3. Signal processing and index calculation: Perform time-frequency analysis on the collected sound pressure time-domain signal, calculate the sound pressure level on the front and back surfaces for a predetermined frequency range, and calculate the in-situ sound pressure level difference of the sound baffle at a preset frequency.

[0017] S4. Sound insulation performance evaluation: Based on the in-situ sound pressure level difference calculated at different speeds, analyze the variation law of the sound insulation performance of the actual ship's sound baffle with frequency and speed, and evaluate the sound insulation performance of the actual ship's sound baffle.

[0018] As a further preferred embodiment of the present invention, in S1, both the first hydrophone structure and the second hydrophone structure are hydrophone arrays. The hydrophone arrays of both the first and second hydrophone structures include four hydrophones, three of which are distributed in an isosceles triangle, and the other hydrophone is placed at the centroid of the isosceles triangle. The hydrophones in the first and second hydrophone structures are of the same model and have been paired and calibrated. In S3, the spatial average of the sound pressure level measured by all hydrophones in the first hydrophone structure at the same time is calculated as the frontal sound pressure level, and the spatial average of the sound pressure level measured by all hydrophones in the second hydrophone structure at the same time is calculated as the back sound pressure level.

[0019] As a further preferred embodiment of the present invention, S3 includes the following steps:

[0020] S31. Data preprocessing and segmentation: The sound pressure time-domain signals of the first and second hydrophone structures acquired synchronously are preprocessed by DC removal and bandpass filtering, and the filtered signals are divided into multiple data segments of equal length.

[0021] S32. Sound Pressure Level Spectrum Calculation: Perform a Fourier transform on each data segment to calculate the sound pressure autopower spectral density of the front and back surfaces, and then calculate the sound pressure level at each frequency point; average the sound pressure level results of all data segments at the corresponding frequency points to obtain the average sound pressure level spectrum of the front surface. and the average sound pressure level spectrum of the back surface ;

[0022] S33. In-situ sound pressure level difference calculation: Calculate the sound pressure level difference of the baffle at the following formula. In-situ sound pressure level difference :

[0023]

[0024] As a further preferred embodiment of the present invention, S4 includes the following steps:

[0025] S41. Spectral Characteristics Analysis: For each flight speed condition, plot the in-situ sound pressure level difference under that condition. With frequency The varying sound insulation spectrum curve was calculated, and the results were obtained within the predetermined sonar core operating frequency band. Average sound insulation within ;

[0026] S42. Dynamic Characteristics Analysis: This analysis gathers data corresponding to the core operating frequency band under all flight speed conditions. average sound insulation Plot the dynamic performance curve of the average sound insulation amount as a function of speed V, and analyze the changing trend of the dynamic performance curve.

[0027] S43. Comprehensive Evaluation: Based on the sound insulation trough frequency band identified by the sound insulation spectrum curve and the average sound insulation of the core working frequency band. The dynamic performance curves and their changing trends are used to quantitatively evaluate the overall sound insulation performance of the sound baffle in the complex sound field of a real ship.

[0028] As a further preferred embodiment of the present invention, in S2, a vibration acceleration sensor is also installed on the path of the hull vibration transmitted to the mounting base of the fairing, and the vibration acceleration time domain signal a(t) is collected synchronously.

[0029] S32 also includes a transmission path contribution separation process, which includes the following steps:

[0030] Coherence analysis: Time-domain analysis of synchronously acquired frontal sound pressure signals Back surface sound pressure signal and vibration acceleration signal Perform spectral analysis to calculate the coherence function between the sound pressure levels on the front and back surfaces. And the coherence function between vibration acceleration and back acoustic pressure. ;

[0031] Dominant path frequency band determination: Greater than The frequency band was determined to be the dominant contributing frequency band for transmitted sound;

[0032] In S33, frequency f is within the dominant contribution frequency band of the transmitted sound, and the average sound pressure level on the frontal surface is calculated. Average sound pressure level of the back surface The difference is used as the in-situ sound pressure level difference. .

[0033] As a further preferred embodiment of the present invention, in S2, the boundary layer velocity U(t) and turbulent pressure pulsation signals outside the flow guide are simultaneously acquired. ;

[0034] In S32, a flow-induced noise separation process is added, including the following steps:

[0035] Flow noise identification: Time-domain signal of sound pressure level on the frontal surface With turbulent pressure pulsation signal Cross-spectral analysis was performed, and the acoustic transfer function of the boundary layer pressure fluctuation to the frontal surface was calculated based on the cross-spectral analysis results and the flow velocity U(t) of the boundary layer outside the shroud, so as to identify the dominant frequency band of turbulent fluctuation below 800Hz.

[0036] Signal-to-noise enhancement: In the frequency band dominated by turbulent fluctuations, an adaptive filter is used to... Elimination of reference signal The flow-induced noise component was used to obtain the purified frontal sound pressure signal. This is used for subsequent sound pressure level calculations;

[0037] Corrected calculation: The original signal is used directly in the non-turbulent dominant frequency band, and in the turbulent dominant frequency band, the original signal is used. Calculate the sound pressure level and record the flow-induced noise correction as an uncertainty component of the S4 evaluation.

[0038] As a further preferred embodiment of the present invention, S4 further includes a sound field spatial uniformity criterion and a measurement point confidence weighting, comprising the following steps:

[0039] Spatial coherence determination: Calculate the cross-correlation function between each hydrophone in the first and second hydrophone structures to obtain the spatial correlation coefficient of the sound field. ,in For hydrophone spacing; when At that time, it was determined that the sound field at that frequency was non-uniformly distributed;

[0040] Weighted average calculation: In the non-uniform sound field frequency band, a confidence weighting factor is introduced. Weighted spatial averaging is performed on each hydrophone measurement point to suppress evaluation distortion caused by local sound field distortion; the weighting factors are dynamically updated and recorded in the evaluation report.

[0041] As a further preferred embodiment of the present invention, S43 specifically includes the following steps:

[0042] S431. Extract multi-dimensional evaluation parameters: Extract spectral defect characteristic parameters from the sound insulation spectrum curve, including the center frequency, depth, and effective bandwidth of the sound insulation trough; extract the average sound insulation at rated cruising speed and the minimum average sound insulation across the entire speed range from the average sound insulation of the core operating frequency band; extract stability parameters from the changing trend of the dynamic performance curve, including the linear fitting slope and range.

[0043] S432. Construct a quantitative scoring model: Design standardized scoring functions for the spectral defect characteristic parameters, the average sound insulation parameters, and the stability parameters, map each parameter to a preset scoring interval, and assign weight coefficients to each scoring function;

[0044] S433. Calculate the comprehensive score and performance rating: Based on the scoring function and the weighting coefficient, calculate the comprehensive sound insulation performance score of the sound baffle, and compare the comprehensive score with the preset performance level threshold to determine its final quantitative performance level.

[0045] The beneficial effects of this invention are as follows:

[0046] 1. Solving the problem of environmental distortion and achieving in-situ evaluation under real operating conditions: This invention involves in-situ deployment of hydrophone structures on both sides of the acoustic baffle of a real ship's fairing, and synchronous acquisition of sound pressure signals under dynamic conditions at multiple speeds, directly measuring in a real and complex multi-physics coupled acoustic environment. This method avoids environmental distortion caused by simplified laboratory models and static tests, and can truly reflect the sound insulation performance of the acoustic baffle under actual navigation conditions, making the evaluation results highly reliable and practical.

[0047] 2. Filling the gap in dynamic operating conditions and revealing the variation of sound insulation performance with speed: By controlling the ship to sail at multiple different speeds and simultaneously collecting data, the dynamic changes in the sound insulation performance of the sound baffle with speed were systematically examined. Based on the in-situ sound pressure level difference at different speeds, the dynamic performance curve of sound insulation as a function of speed was analyzed and plotted, thereby comprehensively understanding the performance of the sound baffle across the entire operating range and providing key data support for acoustic design and operating condition optimization.

[0048] 3. Effective separation of multipath interference, improving the accuracy of sound insulation assessment: By adding vibration acceleration sensors and boundary layer flow velocity and turbulent pressure pulsation sensors, and introducing signal processing techniques such as coherence analysis, cross-spectral analysis, and adaptive filtering, the contribution of structural vibration transmission paths and flow-induced noise interference can be effectively identified and separated. In particular, calculating the in-situ sound pressure level difference within the dominant frequency band of transmitted sound ensures that the assessment results truly reflect the sound insulation capacity of the sound barrier itself, rather than the mixed effect of multiple transmission mechanisms.

[0049] 4. Enhanced spatial representativeness and improved reliability and robustness of assessment results: The use of array-type hydrophones combined with spatial averaging calculations enhances the spatial representativeness of single-point measurements. Furthermore, by determining the spatial coherence of the sound field and using confidence-weighted averaging, the weights of each measurement point are dynamically adjusted in the non-uniform frequency band of the sound field, effectively suppressing the assessment distortion caused by local sound field distortion and improving the reliability and robustness of the assessment results.

[0050] 5. Constructing a multi-dimensional comprehensive quantitative evaluation system to achieve scientific and comprehensive performance rating: This invention not only provides traditional spectrum analysis and average sound insulation calculation, but also further extracts multi-dimensional evaluation indicators such as spectrum defect characteristics and dynamic stability parameters, constructs a standardized scoring model, and ultimately provides a quantitative comprehensive performance rating. This system overcomes the limitations of existing single evaluation indicators, and can comprehensively, scientifically, and hierarchically evaluate the overall sound insulation performance of sound baffles in complex sound fields, providing a clear quantitative basis for design improvement, condition monitoring, and performance comparison.

[0051] In summary, this invention provides a complete methodology system from in-situ deployment, dynamic acquisition, signal processing to comprehensive evaluation. It effectively solves the evaluation bias problems caused by environmental distortion, static operating conditions, interference, spatial limitations, and single indicators in existing technologies. It achieves accurate, reliable, and comprehensive evaluation of the sound insulation characteristics of sound baffles in complex sound fields of actual ships, and has important engineering application value.

[0052] Other advantages, objectives, and features of the invention will be set forth in the following description and will be apparent to those skilled in the art in some respects, or may be learned by practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0053] To make the objectives, technical solutions, and beneficial effects of this invention clearer, the following figures are provided for illustration:

[0054] Figure 1 This is a schematic diagram of the overall process of the present invention;

[0055] Figure 2 This is a schematic diagram of the process of S3 in this invention;

[0056] Figure 3 This is a schematic diagram of the process of S4 in this invention. Detailed Implementation

[0057] Example 1:

[0058] like Figures 1-3 As shown, this invention discloses a method for evaluating the sound insulation characteristics of a sound barrier applicable to complex sound fields on a real ship, comprising the following steps:

[0059] S1. Measurement System Setup: Inside the actual ship's fairing, determine the installation positions of the hydrophone structures. Select two acoustically mirror-symmetrical locations on the frontal side (closer to the ship's noise source) and the back side (closer to the sonar transducer) of the sound baffle. Acoustic mirror symmetry means that, ignoring the presence of the sound baffle, the two locations are symmetrical with respect to the plane of the sound baffle, and their distances to the main noise sources and acoustic environmental characteristics are essentially the same. At each of these two locations, a hydrophone structure is fixedly installed, forming a pair of in-situ measurements. During installation, ensure a secure connection between the hydrophone and the structure, and take necessary vibration reduction measures to minimize the impact of installation-coupled vibrations on the measurements. The core of this step is to establish a measurement basis that directly reflects the sound pressure difference on both sides of the sound baffle. By selecting acoustically mirror-symmetrical points for setup, the consistency of the acoustic excitation environment on both sides of the measurement pair is maximized, ensuring that the final calculated sound pressure level difference mainly originates from the sound insulation effect of the sound baffle, rather than differences in measurement positions, laying the foundation for subsequent accurate evaluation.

[0060] S2. Dynamic Operating Condition Data Acquisition: During the actual shipboard test, the control system controls the ship to navigate at multiple different stable speeds (e.g., drifting, low speed, economic speed, rated speed, high speed, etc.) according to a predetermined test outline. Under each speed condition, after the ship's motion stabilizes, the system synchronously triggers and acquires the sound pressure time-domain signals measured by the first hydrophone structure (frontal side) and the second hydrophone structure (backal side) deployed in S1. and The sampling frequency should satisfy the Nyquist sampling theorem. Simultaneously, environmental parameters such as speed (V) and water depth are recorded for each operating condition. By collecting data at multiple typical speeds, the noise characteristics of the ship under different dynamic states and flow field conditions can be comprehensively captured, thereby evaluating the dynamic changes in the sound insulation performance of the sound baffle and overcoming the limitations of single static condition evaluation.

[0061] S3. Signal Processing and Index Calculation: Subsequent processing of the sound pressure time-domain signal acquired in S2.

[0062] S31. Data Preprocessing and Segmentation: First, process the raw signal... and DC component removal processing is performed to eliminate the DC bias of the measurement system. Then, based on a preset frequency range (e.g., 10 Hz ~ 10 kHz), a corresponding bandpass filter is designed and applied to remove out-of-band noise interference. The filtered long-time-history signal is divided into multiple equal-length, overlapping or non-overlapping data segments, each segment length ensuring that the frequency resolution meets the analysis requirements.

[0063] S32. Sound Pressure Level Spectrum Calculation: For each data segment, perform windowing (e.g., Hanning window) and Fourier transform (FFT) to calculate the sound pressure power spectral density of the front and back surfaces within that data segment. and Then, calculate the sound pressure level at each frequency point according to the sound pressure level formula. f Sound pressure level:

[0064]

[0065]

[0066] in This is a reference sound pressure (typically 1 μPa in water).

[0067] Put all data segments at the same frequency point f The above calculation and The arithmetic mean of the two values ​​is then used to obtain the average sound pressure level spectrum of the frontal surface under this flight speed condition. and the average sound pressure level spectrum of the back surface This piecewise averaging process helps improve the stability of spectral estimation and reduce the impact of random noise.

[0068] S33. In-situ sound pressure level difference calculation: For frequencies within a preset range or the entire analysis frequency band. f Calculate the in-situ sound pressure level difference of the sound baffle at this frequency. :

[0069]

[0070] This difference is the estimated sound insulation provided by the sound baffle at that frequency point. Through systematic time-frequency analysis and spectral averaging, stable frequency-domain sound pressure level information is extracted from the complex time-domain signal, and the core indicator reflecting the performance of the sound baffle—the in-situ sound pressure level difference—is directly calculated, providing a reliable data basis for quantitative evaluation.

[0071] S4. Sound insulation performance evaluation: Based on the calculations obtained in S3, at different speeds... The dataset was used for comprehensive evaluation.

[0072] S41. Spectrum Characteristics Analysis: For each speed condition, based on frequency... The x-axis is... Plot the sound insulation spectrum curve under this operating condition, using the vertical axis as the ordinate. Analyze the overall trend of the curve, the peak and trough of sound insulation. Simultaneously, analyze the specific frequency bands where the sonar system operates core-wise. Calculate the average sound insulation within this frequency band. :

[0073]

[0074] Where N is the number of frequency points within the frequency band.

[0075] S42. Dynamic Characteristics Analysis: The average sound insulation of the core operating frequency band calculated under various flight speed conditions. Extracted, with speed V as the x-axis, Plot the dynamic performance curve of average sound insulation as a function of ship speed, with the vertical axis as the ordinate. Analyze the trend of this curve, such as whether the sound insulation decreases monotonically with increasing speed, remains stable, or shows an inflection point.

[0076] S43. Comprehensive Assessment: Based on the analysis results of S41 and S42, and combining the frequency bands where the sound insulation troughs (weak points) are identified by the sound insulation spectrum curve, the average sound insulation level of the core operating frequency band, and the stability of sound insulation performance with speed, a qualitative or preliminary quantitative assessment conclusion is made on the comprehensive sound insulation performance of the sound barrier in the complex sound field environment of a real ship.

[0077] By analyzing the sound insulation performance from both spectral and dynamic dimensions, this study not only reveals the performance details of the sound baffle at different frequencies but also understands its variation patterns under different navigation conditions. This represents a leap from single-point data to a comprehensive performance profile, making the evaluation conclusions more scientific and closer to engineering practice.

[0078] Example 2

[0079] This embodiment optimizes the hydrophone arrangement and data processing in S1 and S3 based on Embodiment 1. In S1, both the first and second hydrophone structures employ specific hydrophone array configurations. Each array contains four identical hydrophones that have undergone precise pairing and calibration. Three hydrophones (H1, H2, H3) are positioned at the three vertices of an isosceles triangle, while the fourth hydrophone (H4) is positioned at the centroid of the isosceles triangle. The array plane should be as parallel as possible to the surface of the sound baffle. The geometric configurations of the frontal and rearal arrays are completely identical.

[0080] In the sound pressure level calculation of S3, for the frontal surface, the instantaneous sound pressure measured by the four hydrophones in the first hydrophone array at the same time t is first calculated. The sound pressure level corresponding to (i=1,2,3,4) Then, its spatial average value is calculated as the frontal sound pressure level at that moment. :

[0081]

[0082] Similarly, calculate the sound pressure level on the back surface. :

[0083]

[0084] The subsequent spectrum calculation (S32) is based on and The time-domain sequence was processed to obtain the spatially averaged sound pressure level spectrum. and Then calculate according to the original formula. .

[0085] By employing a four-point array and spatial averaging, the random errors and local distortions caused by the uneven spatial distribution of sound pressure in the complex sound field of a real ship are effectively overcome in single-point measurements. The arrangement of isosceles triangles with centroids can better reflect the spatial characteristics of the sound field within a small area with a limited number of measurement points. Paired calibration ensures the comparability of measurement results between the two arrays, further improving the accuracy of in-situ sound pressure level difference calculation.

[0086] Example 3

[0087] This embodiment refines the evaluation steps of S4 based on Embodiment 1. S4 specifically includes the following steps:

[0088] The specific steps for S4 are as follows:

[0089] S41. Spectrum Characteristic Analysis: For each speed V, plot... - Curve. Within the core operating frequency band of the sonar. Calculate the average sound insulation. The formula is the same as in Example 1.

[0090] S42. Dynamic Characteristics Analysis: This analysis gathers data from all M speed conditions. ,draw -V curve. The trend of its change is analyzed using methods such as linear regression. For example, the slope k of the curve is calculated. If k is significantly negative, it indicates that the sound insulation performance decreases with increasing speed.

[0091] S43. Comprehensive Assessment: The assessment should consider three aspects: 1) Significant sound insulation troughs identified from the frequency spectrum curve (e.g., 1) The frequency band, valley depth, and bandwidth where the value is below a certain threshold or a local minimum occurs; 2) The average sound insulation of the core operating frequency band at various flight speeds. 3) The trend of the dynamic performance curve, to judge the sensitivity of sound insulation performance to speed. It can give a comprehensive evaluation description such as "there is a weak point in sound insulation in a certain frequency band, the average sound insulation value of the core frequency band at rated speed, and the performance decreases slightly with the increase of speed".

[0092] The evaluation process was standardized and streamlined, clarifying the analytical requirements for three key aspects: spectral characteristics, core band performance, and dynamic changes. This made the evaluation conclusions more systematic and complete, avoiding arbitrariness and one-sidedness in the evaluation.

[0093] Example 4

[0094] This embodiment adds the identification and separation of structural vibration transmission paths based on embodiment 1.

[0095] In S2, in addition to acquiring underwater acoustic signals, one or more vibration acceleration sensors are deployed along the critical path of the ship's structural vibration transmission to the fairing mounting base (e.g., at the base flange) to synchronously acquire vibration acceleration time-domain signals. .

[0096] In S32 of S3, a sub-step for separating the contribution of the transmission path is added:

[0097] Coherence analysis: for synchronously acquired data , , Perform spectral analysis to calculate the constant coherence function between the sound pressure levels on the front and back surfaces. And the constant coherence function between vibration acceleration and back acoustic pressure. The calculation formula is:

[0098]

[0099] in, It is the cross-power spectral density of signals x and y. and It is the self-power spectral density.

[0100] Dominant path frequency band determination: comparison and The magnitude at the same frequency f. If > If the sound pressure at the back surface is considered to originate primarily from the transmission of sound pressure from the front surface (airborne or waterborne sound transmission), then at that frequency, the sound pressure at the back surface is considered to originate primarily from the transmission of sound pressure at the front surface; conversely, if the sound pressure at the back surface is considered to originate from the transmission of sound pressure from the front surface (airborne or waterborne sound transmission), then at that frequency, the sound pressure at the back surface is considered to originate primarily from the transmission of sound pressure from the front surface ( If the sound pressure is larger, it is assumed that the sound pressure on the back surface mainly originates from the re-radiation of structural vibrations (structural sound transmission). > The established frequency band is determined to be the "frequency band dominated by transmitted sound".

[0101] Calculate the in-situ sound pressure level difference in S33. At that time, calculations and subsequent analyses were performed only for frequencies *f* within the "dominantly contributing frequency band of transmitted sound." For frequency bands dominated by structure sound, its... It cannot accurately reflect the sound barrier's ability to isolate transmitted sound, therefore it can be excluded or specifically noted in this assessment.

[0102] It effectively distinguishes between "transmitted sound" transmitted through the sound baffle and "structural sound" transmitted through diffraction of the installation structure, thus improving the calculated sound insulation index. It more purely reflects the sound insulation performance of the sound baffle material itself, and the evaluation results are more targeted, which helps to accurately identify the design defects of the sound baffle itself, rather than the vibration isolation problems of the installation structure.

[0103] Example 5

[0104] This embodiment, based on embodiment 1, adds the identification and separation of flow-induced noise outside the flow deflector.

[0105] In S2, the time-domain velocity signal U(t) of the outer boundary layer of the fairing is simultaneously acquired (which can be estimated by combining the ship's speed with the boundary layer model or measured using a small current meter) and the turbulent pressure fluctuation signal. (This can be obtained by placing a turbulent pressure sensor on the outer wall of the fairing).

[0106] In S32 of S3, a sub-step for separating flow-induced noise is added:

[0107] Stream noise identification: and Cross-spectral analysis was performed, and combined with the flow velocity U(t), the acoustic transfer function of the boundary layer turbulent pressure fluctuations transmitted to the measurement points on the frontal surface inside the fairing was estimated. Based on theory and experience, the frequency band below 800 Hz is usually preliminarily identified as the potential dominant frequency band for flow-induced noise generated by turbulent pressure excitation.

[0108] Signal-to-noise reduction: Within the identified turbulence-dominant frequency band (e.g., f < 800 Hz), an adaptive filtering algorithm (such as the LMS algorithm) is employed. This is based on the turbulent pressure pulsation signal. As a reference input, the frontal sound pressure signal As the main input, it is adjusted by a filter, from To the maximum extent offset with The relevant components, thereby outputting a purified signal. The flow-induced noise component in the signal was significantly suppressed.

[0109] Corrected calculations: in subsequent calculations For non-turbulent dominant frequency bands (e.g., f ≥ 800 Hz), the original values ​​are used directly. The calculated sound pressure level. For the turbulence-dominant frequency band, a method based on... The calculated sound pressure level. At the same time, the sound pressure level difference between the original signal and the purified signal in the turbulence-dominant frequency band is recorded as an evaluation uncertainty component introduced by flow-induced noise interference, and explained in the final evaluation report of S4.

[0110] It significantly reduces the contamination of the sound pressure measurement on the frontal surface by the flow-induced noise directly excited by the turbulent boundary layer pulsating pressure outside the fairing, making the sound pressure measured on the frontal surface more accurately represent the noise from inside the hull that needs to be isolated by the sound baffle, thereby improving the accuracy of sound insulation assessment, especially in the low frequency range.

[0111] Example 6

[0112] This embodiment adds the judgment of sound field spatial uniformity and data processing optimization to the basis of embodiment 1.

[0113] In S4, a sound field spatial uniformity criterion and measurement point confidence weighting step are added:

[0114] Spatial coherence determination: For each pair of hydrophones within the first hydrophone structure (or the second hydrophone structure), calculate their spatial cross-correlation coefficient at frequency f. .in This is the distance between hydrophone i and hydrophone j. Calculate the cross-power spectrum and self-power spectrum based on the measured signals from each hydrophone. Set a threshold, for example, 0.5. If, for a certain frequency f, most hydrophone pairs within the structure... If the value is less than 0.5, it is determined that the sound field is non-uniformly distributed within the spatial scale covered by the measurement array at that frequency (i.e., the diffusion field condition is not satisfied).

[0115] Weighted average calculation: For frequencies f that are determined to be non-uniformly distributed in the sound field, when calculating the spatial average sound pressure level of the hydrophone structure, a simple arithmetic average is no longer used. Instead, a confidence weighting factor based on spatial coherence is introduced. A weighted average is performed. For the j-th hydrophone within the structure, its weighting factor is defined as the normalized value of the spatial correlation coefficient between that hydrophone and all other hydrophones within the structure:

[0116]

[0117] Where N is the number of hydrophones. Then, the weighted average sound pressure level (taking the energy average before the logarithmic domain as an example) is:

[0118]

[0119] This represents the sound pressure level (in dB) measured by the j-th hydrophone at frequency f. This weighting factor is dynamically updated and recorded in the evaluation report.

[0120] In the complex acoustic field of a real ship, non-uniformity of the acoustic field is a common phenomenon. This step automatically identifies non-uniform frequency bands through acoustic field coherence analysis and adopts a weighted averaging strategy to assign greater weight to measurement points with higher acoustic field correlation, thereby reducing the impact of measurement points with strong local acoustic field distortion or near-field effects on the overall evaluation, thus improving the robustness and reliability of the evaluation results under non-ideal acoustic field conditions.

[0121] Example 7

[0122] This embodiment expands upon the S43 comprehensive evaluation steps in greater depth and quantification, based on Embodiment 1.

[0123] The specific implementation steps for S43 are as follows:

[0124] S431. Extract multi-dimensional evaluation parameters: Extract spectral defect characteristic parameters from the sound insulation spectrum curve, including the center frequency, depth (difference from adjacent peaks or average values) and -3dB or -10dB effective bandwidth of the sound insulation trough; extract the average sound insulation at rated cruising speed and the minimum average sound insulation across the entire speed range from the average sound insulation of the core operating frequency band; perform linear fitting on the dynamic performance curve, and extract stability parameters from the trend of the dynamic performance curve, including the linear fitting slope and range.

[0125] S432. Construct a quantitative scoring model: Design standardized scoring functions for the spectral defect characteristic parameters, the average sound insulation parameters, and the stability parameters, map each parameter to a preset scoring interval, and assign weight coefficients to each scoring function;

[0126] S433. Calculate the comprehensive score and performance rating: Based on the scoring function and the weighting coefficient, calculate the comprehensive sound insulation performance score of the sound baffle, and compare the comprehensive score with the preset performance level threshold to determine its final quantitative performance level.

[0127] The comprehensive assessment based on experience and qualitative description is transformed into a quantitative and hierarchical assessment based on multi-dimensional feature parameter extraction and a standardized scoring model. This method yields objective and consistent assessment results, facilitates horizontal comparisons between different sound baffle designs, and also facilitates the establishment of product performance profiles and lifespan rating standards, greatly enhancing the engineering practicality and management scientific nature of the assessment.

[0128] Finally, it should be noted that the above preferred embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail through the above preferred embodiments, those skilled in the art should understand that various changes can be made to it in form and detail without departing from the scope defined by the claims of the present invention.

Claims

1. A method for evaluating the sound insulation characteristics of a sound baffle applicable to complex sound fields on a real ship, characterized in that, Includes the following steps: S1. Measurement system layout: On both sides of the acoustic baffle of the actual ship fairing, select acoustic mirror symmetrical positions to install the first hydrophone structure and the second hydrophone structure respectively, forming an in-situ measurement pair; S2. Dynamic operating condition data acquisition: Control the ship to sail at multiple different speeds. Under each speed condition, synchronously acquire the sound pressure time domain signal measured by the first hydrophone structure and the second hydrophone structure. The first hydrophone structure is located on the front side of the sound baffle, and the second hydrophone structure is located on the back side of the sound baffle. S3. Signal processing and index calculation: Perform time-frequency analysis on the collected sound pressure time-domain signal, calculate the sound pressure level on the front and back surfaces for a predetermined frequency range, and calculate the in-situ sound pressure level difference of the sound baffle at a preset frequency. S4. Sound insulation performance evaluation: Based on the in-situ sound pressure level difference calculated at different speeds, analyze the variation law of the sound insulation performance of the actual ship's sound baffle with frequency and speed, and evaluate the sound insulation performance of the actual ship's sound baffle. S3 includes the following steps: S31. Data Preprocessing and Segmentation: The time-domain sound pressure signals from the synchronously acquired first and second hydrophone structures are preprocessed with DC removal and bandpass filtering, and the filtered signals are divided into multiple data segments of equal length. S32. Sound Pressure Level Spectrum Calculation: Fourier transform is performed on each data segment to calculate the sound pressure autopower spectral density of the front and back surfaces, and then the sound pressure level at each frequency point is calculated. The sound pressure level results of all data segments are averaged at the corresponding frequency points to obtain the average sound pressure level spectrum of the front surface. and the average sound pressure level spectrum of the back surface S33. In-situ sound pressure level difference calculation: Calculate the sound baffle at the following frequency using the formula below. In-situ sound pressure level difference : In S2, vibration acceleration sensors are also installed on the path of the hull vibration transmitted to the mounting base of the fairing, and the vibration acceleration time domain signal a(t) is collected synchronously. S32 also includes a transmission path contribution separation process, which includes the following steps: Coherence analysis: Time-domain analysis of synchronously acquired frontal sound pressure signals Back surface sound pressure signal and vibration acceleration signal Perform spectral analysis to calculate the coherence function between the sound pressure levels on the front and back surfaces. And the coherence function between vibration acceleration and back acoustic pressure. ; Dominant path frequency band determination: Greater than The frequency band was determined to be the dominant contributing frequency band for transmitted sound; S33 frequency Calculate the average sound pressure level on the frontal surface within the dominant frequency band of transmitted sound. Average sound pressure level of the back surface The difference is used as the in-situ sound pressure level difference. ; In S2, the boundary layer velocity U(t) and turbulent pressure fluctuation signals outside the flow deflector are simultaneously acquired. ; In S32, a flow-induced noise separation process is added, including the following steps: Flow noise identification: Time-domain signal of sound pressure level on the frontal surface With turbulent pressure pulsation signal Cross-spectral analysis was performed, and the acoustic transfer function of the boundary layer pressure fluctuation to the frontal surface was calculated based on the cross-spectral analysis results and the flow velocity U(t) of the boundary layer outside the shroud, so as to identify the dominant frequency band of turbulent fluctuation below 800Hz. Signal-to-noise enhancement: In the frequency band dominated by turbulent fluctuations, an adaptive filter is used to... Elimination of reference signal The flow-induced noise component was used to obtain the purified frontal sound pressure signal. This is used for subsequent sound pressure level calculations; Corrected calculation: The original signal is used directly in the non-turbulent dominant frequency band, and the original signal is used in the turbulent dominant frequency band. Calculate the sound pressure level and record the flow-induced noise correction as an uncertainty component of the S4 evaluation.

2. The method for evaluating the sound insulation characteristics of a sound baffle applicable to complex sound fields on a real ship, as described in claim 1, is characterized in that: In S1, both the first and second hydrophone structures are hydrophone arrays. Each hydrophone array in both structures includes four hydrophones, with three hydrophones arranged in an isosceles triangle and the fourth hydrophone placed at the centroid of the isosceles triangle. The hydrophones in both structures are of the same model and have been paired and calibrated. In S3, the spatial average of the sound pressure level measured by all hydrophones in the first structure at the same time is calculated as the frontal sound pressure level, and the spatial average of the sound pressure level measured by all hydrophones in the second structure at the same time is calculated as the back sound pressure level.

3. The method for evaluating the sound insulation characteristics of a sound barrier suitable for complex sound fields on a real ship, as described in claim 1, is characterized in that: S4 includes the following steps: S41. Spectral Characteristics Analysis: For each flight speed condition, plot the in-situ sound pressure level difference under that condition. With frequency The varying sound insulation spectrum curve was calculated, and the results were obtained within the predetermined sonar core operating frequency band. Average sound insulation within ; S42. Dynamic Characteristics Analysis: This analysis gathers data corresponding to the core operating frequency band under all flight speed conditions. average sound insulation Plot the dynamic performance curve of the average sound insulation amount as a function of speed V, and analyze the changing trend of the dynamic performance curve. S43. Comprehensive Evaluation: Based on the sound insulation trough frequency band identified by the sound insulation spectrum curve and the average sound insulation of the core working frequency band. The dynamic performance curves and their changing trends are used to quantitatively evaluate the overall sound insulation performance of the sound baffle in the complex sound field of a real ship.

4. The method for evaluating the sound insulation characteristics of a sound barrier suitable for complex sound fields on a real ship, as described in claim 1, is characterized in that: S4 also includes a sound field spatial uniformity criterion and measurement point confidence weighting, including the following steps: Spatial coherence determination: Calculate the cross-correlation function between each hydrophone in the first and second hydrophone structures to obtain the spatial correlation coefficient of the sound field. ,in For hydrophone spacing; when At that time, it was determined that the sound field at that frequency was non-uniformly distributed; Weighted average calculation: In the non-uniform sound field frequency band, a confidence weighting factor is introduced. Weighted spatial averaging is performed on each hydrophone measurement point to suppress evaluation distortion caused by local sound field distortion; the weighting factors are dynamically updated and recorded in the evaluation report.

5. The method for evaluating the sound insulation characteristics of a sound barrier suitable for complex sound fields on a real ship, as described in claim 3, is characterized in that: S43 specifically includes the following steps: S431, Extracting multi-dimensional evaluation parameters: Extracting spectral defect characteristic parameters from the sound insulation spectrum curve, including the center frequency, depth, and effective bandwidth of the sound insulation trough; extracting the average sound insulation at rated cruising speed and the minimum average sound insulation across the entire speed range from the average sound insulation of the core operating frequency band; extracting stability parameters from the changing trend of the dynamic performance curve, including the linear fitting slope and range; S432, Constructing a quantitative scoring model: Designing standardized scoring functions for the spectral defect characteristic parameters, the average sound insulation parameters, and the stability parameters respectively, mapping each parameter to a preset scoring interval, and assigning weight coefficients to each scoring function; S433, Calculating the comprehensive score and performance rating: Calculating the comprehensive sound insulation performance score of the sound barrier based on the scoring functions and the weight coefficients, and comparing the comprehensive score with a preset performance level threshold to determine its final quantitative performance level.

Images