A method and system for free-field sound field measurement

Abstract

The application belongs to the technical field of acoustic measurement, and discloses a free space sound field measurement method and system, which constructs a free light path sound field measurement system based on the principle of Michelson interferometer; collects a reference image, introduces a sound field to be measured, performs translation and rotation scanning through a computer to control a loudspeaker or a laser beam, and completes interference pattern data collection; pre-processes the collected interference pattern, identifies the edge of the interference fringe by using edge detection technology, and calculates the light phase change amount; sound field reconstruction is performed by using a Radon inverse transform algorithm, sound field integral information carried by the laser beam is converted into the sound pressure value of each point in the real space, and a free field sound pressure distribution map is reconstructed. The application has the advantages of non-destructive and low cost, and significantly improves the sound field measurement accuracy and the integrity and reliability of reconstruction, can effectively capture the nanometer level optical path change caused by the sound field, and ensures the high accuracy of sound field measurement and the accuracy of sound source identification.

Description

Technical Field

[0001] This invention belongs to the field of acoustic measurement technology, and particularly relates to a method and system for measuring free-space sound fields, especially a new technology method and system for achieving non-destructive, high-precision, and non-invasive free-space sound field measurement using the acousto-optic effect. Background Technology

[0002] Existing acousto-optic measurement methods have limitations in sound field measurement: most methods derive the sound field through indirect parameters or vibration information, while the need to directly obtain the spatial distribution of sound pressure remains unmet. Furthermore, sound field measurement methods based on the laser beam deflection effect acquire sound field information by sensing the deflection displacement of the laser beam as it passes through the sound field using a position-sensitive detector (PSD). However, this method typically requires a strong sound field intensity, especially in the ultrasonic band, to generate a sufficiently significant and measurable laser beam deflection. Studies show that it can only obtain a stable deflection signal when measuring ultrasonic sound pressure levels on the order of 20 kPa. This means that for weak sound fields or low-frequency sound fields audible to the human ear, the sensitivity of the laser beam deflection effect may be insufficient for accurate measurement. Mach-Zehnder interferometers (MZIs) have also been used for optical measurement of sound field information. While MZIs have advantages in quantitatively measuring phase values ​​and achieve two-dimensional data acquisition through a CCD camera, their optical systems are typically complex, containing more beam splitters and reflectors, which increases the difficulty and cost of system setup and subsequent calibration. Furthermore, when the sound field frequency is high, MZI combined with a CCD camera may only function as a light intensity averaging detector, making it difficult to directly acquire instantaneous phase information. Although the existence of the sound field can be confirmed through differential image processing, a universal method for accurately inverting the instantaneous phase deviation from the average light intensity remains unclear, and its calibration and verification for actual sound pressure distribution require further research. These factors collectively limit the widespread application of existing acousto-optic effect measurement techniques.

[0003] Based on the above analysis, the problems and shortcomings of the existing technology are as follows:

[0004] (1) Traditional sound field measurement usually uses multiple sound sensors, but traditional sensor array measurement methods have inherent invasiveness problems, limited measurement accuracy, high cost and complicated operation.

[0005] (2) Existing sound field measurement methods based on acousto-optic effects are expensive, and the optical systems are usually quite complex, which will increase the difficulty and cost of system construction and subsequent calibration, and have limitations in sound field measurement. Summary of the Invention

[0006] To overcome the problems existing in related technologies, the present invention discloses a method and system for measuring free-space sound fields, the technical solution of which is as follows:

[0007] This invention is implemented as follows: a method for measuring a free-space sound field, comprising the following steps:

[0008] S1, Optical path construction: Constructing a free-path acoustic field measurement system based on the principle of Michelson interferometer;

[0009] S2, Sound Field Data Acquisition: Acquire a reference image, introduce the sound field to be measured, and use a computer-controlled loudspeaker or laser beam to perform translational and rotational scanning to complete the acquisition of interferometric pattern data;

[0010] S3, Interference fringe image processing and optical phase information extraction: The acquired interference pattern is preprocessed, the edges of the interference fringes are identified using edge detection technology, and the amount of optical phase change is calculated;

[0011] S4, Sound Field Sound Pressure Reconstruction: The Radon inverse transform algorithm is used to reconstruct the sound field, converting the sound field integral information carried by the laser beam into the sound pressure value of each point in the real space, and reconstructing the free field sound pressure distribution map.

[0012] In step S1, the optical path setup includes:

[0013] The free-path acoustic field measurement system uses a continuous laser as the light source. The emitted laser beam is expanded by a beam expander. The expanded laser beam is then incident on a beam splitter and split into a measurement beam and a reference beam.

[0014] The measuring light passes through the area where the sound field to be measured is placed, strikes the reflecting mirror M1, and is reflected back to the beam splitter; the reference light strikes the reflecting mirror M2 and is reflected back to the beam splitter.

[0015] The two reflected beams re-converge at the beam splitter, resulting in equal-thickness interference and forming alternating bright and dark interference fringes. The interference fringes are magnified by the objective lens and recorded by a CCD camera.

[0016] Furthermore, the sound field under test is generated by a loudspeaker, and all optical components are precisely fixed and adjusted using a high-stability series adjustment frame. All optical components (laser, beam splitter, beam expander, reflector, CCD, etc.) are mounted on the high-stability series adjustment frame and rigidly fixed to the optical vibration isolation platform.

[0017] The adjustment frame is equipped with a fine-tuning screw mechanism, which allows for precise adjustments in pitch, horizontal, and height to ensure that the beam propagates along the central axis of the platform.

[0018] After fixing, tighten the adjusting bracket locking screws to prevent the components from shifting at an angle due to minor vibrations.

[0019] After the laser is fixed, adjust the pitch angle and horizontal position to make the beam propagate along the center of the optical platform.

[0020] After the beam expander is installed, its height is precisely adjusted using the adjustment frame so that the expanded beam spot evenly covers the center of the beam splitter.

[0021] The beam splitter is fixed on the adjustment frame and positioned approximately 10–15 cm behind the beam expander. By fine-tuning the height and angle, the reflected and transmitted light are directed perpendicularly to the centers of reflectors M1 and M2, respectively.

[0022] Adjust the height and angle of M1 and M2 so that the reflected light coincides with the incident light when it returns, and forms clear interference fringes at the beam splitter.

[0023] In step S2, the sound field data acquisition includes:

[0024] Acquiring reference images: In the absence of sound field interference, the initial interference fringe pattern is captured and recorded by a CCD camera as the reference image for subsequent data processing;

[0025] Introducing a sound field: The sound field to be measured is introduced into the measurement optical path, causing the sound field to disturb the measurement light passing through the region;

[0026] Scanning measurement: Translation and rotation scanning are performed by computer-controlled speakers or laser beams;

[0027] Repeat the translation-scan and rotation-scan processes to complete the acquisition of interferometric pattern data at multiple positions and angles.

[0028] Furthermore, the scanning measurement includes: fixing the position of the laser beam, and performing step-by-step translation and rotation of the speaker in a two-dimensional plane; fixing the speaker on a stepper motor, and having the motor drive the speaker to move; after each translation a certain distance or rotation a certain angle, capturing and recording the interference fringe pattern after the sound field disturbance in real time using a CCD camera.

[0029] In step S3, the interference fringe image processing and optical phase information extraction include:

[0030] (1) Image preprocessing: preprocessing the acquired interference pattern by filtering and denoising;

[0031] (2) Fringe edge detection: An edge detection algorithm is used to identify the edges of the interference fringes;

[0032] (2) Calculation of optical phase change: Based on the linear relationship between the movement of interference fringes and optical path difference, and the relationship between the change of optical path difference and optical phase change, the movement of fringes is converted into the optical phase change caused by the light beam passing through the sound field.

[0033] Furthermore, the edge detection algorithm locates edge information in the image by detecting abrupt changes in pixel grayscale values. These abrupt changes include object contours and texture variations. A sub-pixel edge detection algorithm is used to analyze the fringe displacement to obtain the actual movement distance of the interference fringes. A four-stage edge detection algorithm, employing Gaussian filtering, Sobel operator gradient calculation, non-maximum suppression, and double threshold segmentation, is used to adapt to the sub-pixel level displacement measurement requirements of interference fringes. The specific process is as follows:

[0034] To address the random noise, including light intensity fluctuations and electronic noise, present in the interference fringe images acquired by CCD, a two-dimensional Gaussian function is used to smooth the image. The expression is as follows:

[0035] ;

[0036] ;

[0037] In the formula, This is a two-dimensional Gaussian function, a kernel function used for smoothing images. For the natural constant e The exponential function with base α, here is a core component of the two-dimensional Gaussian function, used to describe how the function value changes with... x , y The changing decay characteristics Let be the coordinate variable of the image in the horizontal direction, used to determine the positional values ​​of the two-dimensional Gaussian function in the horizontal direction. These are the coordinate variables of the image in the vertical direction, used to determine the positional values ​​of the two-dimensional Gaussian function in the vertical direction. The standard deviation of the Gaussian kernel. This is used to balance noise suppression and edge blurring; The grayscale values ​​of the filtered image. The grayscale values ​​of the original interference fringe image. This is a convolution operation;

[0038] The filtered image is calculated using the Sobel operator. The gradient of direction determines the magnitude and direction of the edge, and its expression is:

[0039] ;

[0040] ;

[0041] ;

[0042] ;

[0043] In the formula, They are respectively Orientation gradient, This represents the gradient magnitude, used to reflect edge strength. The gradient direction is used to reflect the edge orientation and matches the vertical direction of the interference fringes;

[0044] Local extrema are determined along the gradient direction, retaining edge center pixels and discarding non-edge pixels. The expression is:

[0045] ;

[0046] In the formula, For the image after non-maximum suppression, the edge width is thinned from 3 to 5 pixels to 1 pixel by setting high and low thresholds to connect broken edges. For adjacent pixels along the gradient direction;

[0047] To improve accuracy, subpixel edge localization is employed. Subpixel-level edge coordinate calculation is achieved based on interpolation. A quadratic polynomial is used to fit the grayscale values ​​of a 3×3 neighborhood near the edge, assuming that the grayscale values ​​near the edge satisfy… ,right Taking the derivative and setting it to 0, we obtain the subpixel coordinates:

[0048] ;

[0049] In the formula, These are the polynomial fitting coefficients. These are sub-pixel level edge coordinates, with a positioning accuracy of 0.1 pixels. These are pixel coordinates.

[0050] Furthermore, the calculation of the actual displacement distance of each interference fringe in the horizontal or vertical direction includes:

[0051] The fringe spacing of the Michelson interferometer under constant thickness interference is:

[0052] ;

[0053] In the formula, The spacing between the interference fringes. The wavelength of the laser. The angle between the mirror surfaces;

[0054] stripe movement for:

[0055] ;

[0056] In the formula, This is the change in optical path difference as the light path passes through the sound field;

[0057] The actual distance the stripes moved for:

[0058] ;

[0059] In the formula, This refers to the phase change.

[0060] Through phase change The linear relationship between the actual movement distance of the stripes is used to inversely calculate the sound field.

[0061] In step S4, sound field sound pressure reconstruction includes: inputting the acquired light phase change data under different projection angles and positions into the Radon inverse transform algorithm to reconstruct the sound field and generate a free field sound pressure distribution map;

[0062] The frame of reference for the sound field is The coordinate system, after rotating by 0 degrees, becomes coordinate system coordinate system and The transformation relationships between coordinate systems are as follows:

[0063] ;

[0064] The projection integration process is as follows:

[0065] ;

[0066] In the formula, The sound pressure to be measured in the sound field. For the path along the direction The sound pressure integral, This represents the path of light through the region of sound pressure disturbance.

[0067] Based on the dynamic offset, the relationship between the Radon transform of the sound pressure in the time domain and the sound pressure is obtained as follows:

[0068] ;

[0069] In the formula, Let be the wavenumber of light propagating in a vacuum. The photoluminescence coefficient of the medium, The phase measured by the interferometer. The isentropic pressure coefficient isotropic. For sound pressure level Along the path in the direction The points, The reconstructed sound field in coordinates place, time The sound pressure level;

[0070] ;

[0071] In the formula, For the relevant refractive index parameters of the medium, A coefficient related to the properties of the medium. For reference pressure;

[0072] The sound pressure of the measured sound field reconstructed by the inverse Radon transform is:

[0073] ;

[0074] In the formula, The reconstructed sound field in coordinates place, time sound pressure, This is the Radon inverse transform operator, which is used to infer the sound pressure distribution from the projection integral result.

[0075] Another object of the present invention is to provide a free-space sound field measurement system, which is used to control the free-space sound field measurement method, the system comprising:

[0076] A laser, used to emit a laser beam with good coherence, preferably a continuous laser;

[0077] Beam expander, used to expand a laser beam;

[0078] A beam splitter is used to split the expanded laser beam into a measurement beam and a reference beam.

[0079] A reflector is used to reflect the measurement light and the reference light, so that they re-interfere; wherein, the reflector M1 is placed at the end of the sound field region to be measured, so that the measurement light is reflected after passing through the sound field;

[0080] A loudspeaker / sound source is placed in the measurement optical path as the sound field to be measured, used to generate sound wave disturbances;

[0081] A scientific-grade CCD camera is placed in the area where interference fringes form to record interference patterns;

[0082] Objective lens, used to magnify interference fringes and improve the resolution of images recorded by CCD camera;

[0083] Computer and control system, used to control the scanning motion of loudspeakers / sound sources, data acquisition by CCD cameras, and to execute image processing and sound field reconstruction algorithms;

[0084] High-stability series adjustment brackets are used for precise fixing and adjustment of optical element positions.

[0085] Combining all the above technical solutions, the beneficial effects of this invention are as follows:

[0086] First, addressing the shortcomings of existing acousto-optic effect measurement methods in obtaining accurate instantaneous phase information and reconstructing complete sound pressure fields, this invention combines optical imaging magnification with sub-pixel edge detection algorithms to achieve nanometer-level high-precision measurement of interference fringe shift, thereby enabling direct and accurate acquisition of optical phase change information. This invention utilizes the Radon inverse transform algorithm to reconstruct the complete free-field sound pressure spatial distribution from high-precision optical phase data, and its feasibility has been verified through simulation. Compared to existing methods, this invention not only possesses the advantages of being non-destructive and low-cost, but also achieves significant improvements in sound field measurement accuracy and the completeness and reliability of the reconstruction.

[0087] The free-space sound field measurement system and method based on the acousto-optic effect proposed in this invention have the following significant advantages compared with the prior art:

[0088] 1. Non-destructive and non-invasive measurement: This invention utilizes a laser beam passing through a sound field to sense sound field information through the acousto-optic effect. The laser itself does not cause physical disturbance to the sound field, achieving truly non-contact and interference-free measurement. This solves the problem of the sensor body affecting the sound field in traditional microphone array measurements.

[0089] 2. High Measurement Accuracy: By utilizing the equal-thickness interference principle of the Michelson interferometer, combined with optical imaging magnification and sub-pixel edge detection algorithms, sub-nanometer displacement resolution can theoretically be achieved. This enables the invention to accurately sense nanometer-level optical path changes caused by the sound field, thereby achieving high-precision measurement of the sound field.

[0090] 3. High cost-effectiveness: Compared with the expensive laser Doppler vibration meter and other existing acousto-optic effect measurement equipment on the market, the present invention only requires a necessary continuous laser, high-precision optical lenses (such as reflectors and beam splitters) and CCD camera to build a measurement system, which greatly reduces the measurement cost.

[0091] 4. Direct acquisition of sound pressure distribution: This invention uses the Radon inverse transform algorithm to directly reconstruct the spatial distribution of sound pressure from the measured optical phase projection information, providing more intuitive and comprehensive data for sound field analysis.

[0092] 5. Wide applicability: This method is applicable to sound field measurement in free space and can be applied to various scenarios that require accurate acquisition of sound field information.

[0093] Secondly, the purpose of this invention is to address the limitations of traditional sound field measurement methods (such as sensor array methods) in terms of invasiveness and accuracy, as well as the high cost of existing acousto-optic effect measurement equipment. This invention proposes and implements a non-destructive, high-precision, and low-cost free-field sound field measurement system and method. By constructing a free-path measurement system based on a Michelson interferometer, this invention utilizes the acousto-optic effect principle, combined with advanced image and signal processing algorithms, to accurately acquire sound field information and reconstruct the sound field. Specifically, the measurement system designed in this invention can theoretically achieve sub-nanometer displacement resolution. For example, under conditions of equal thickness interference tilt angle of 0.1° and laser wavelength of 532nm, a displacement sensitivity of approximately 0.17nm / pixel can be achieved, theoretically realizing sub-nanometer displacement resolution. This high-precision detection capability can effectively capture nanometer-level optical path changes caused by the sound field, thereby ensuring high precision in sound field measurement and accurate sound source identification.

[0094] Third, traditional sound field measurement methods, such as the sensor array method, have inherent limitations. For example, they require placing the sensor directly in the sound field, which can interfere with the sound field, and they are also costly and complex to operate. While existing acousto-optic effect measurement equipment, such as laser Doppler vibrometers, can achieve non-destructive measurement, their high price greatly limits their widespread application. This invention, by building a system based on a Michelson interferometer, only requires relatively low-cost equipment such as a necessary continuous laser, high-precision optical lenses, and a CCD camera. This low-cost advantage makes it more attractive in scientific research and industrial fields, providing a cost-effective alternative for various enterprises and research institutions requiring precise sound field measurements.

[0095] Furthermore, this invention can directly reconstruct the spatial distribution of sound pressure in a sound field, providing more intuitive and comprehensive data. This has significant commercial application value in noise control, product acoustic quality testing (such as home appliances and automobiles), and acoustic stealth performance evaluation in the military field. Its non-invasiveness, high precision, and high reliability can meet the needs of scenarios with stringent requirements for sound field measurement, thereby expanding new market opportunities.

[0096] Fourth, this invention achieves non-destructive, high-precision sound field reconstruction: In existing technologies, measurement methods based on acousto-optic effects mostly derive the sound field through indirect parameters or vibration information, making it difficult to directly obtain the precise spatial distribution of sound pressure. This invention utilizes the Radon inverse transform algorithm, which can directly reconstruct a complete sound pressure distribution map from light phase change data (i.e., sound field integral information) obtained from different angles and positions.

[0097] This invention addresses the limitations of existing acousto-optic methods: While some Mach-Zehnder (MZI) based methods utilize acousto-optic effects, their complex optical systems and high calibration difficulty make it challenging to directly acquire instantaneous phase information when processing high-frequency sound fields. The Michelson interferometer employed in this invention combines optical magnification and sub-pixel edge detection algorithms, enabling nanometer-scale optical path change measurement. This overcomes the shortcomings of traditional methods in acquiring accurate instantaneous phase information and reconstructing complete sound pressure fields.

[0098] Fifth, in traditional sensor array methods, the sensors themselves cause sound scattering during measurement, disturbing the original sound field and affecting measurement accuracy and spatial resolution. This invention utilizes a laser beam for non-contact measurement, fundamentally solving this inherent invasiveness problem and achieving truly non-destructive measurement.

[0099] The challenge of balancing cost and accuracy: While existing equipment such as laser Doppler vibrometers can achieve high-precision measurements, their high cost limits their application. This invention significantly reduces equipment costs while maintaining high measurement accuracy, providing the industry with a feasible solution that balances performance and economy.

[0100] This invention demonstrates that by optimizing a relatively simple optical system (a Michelson interferometer) and combining it with innovative data processing algorithms (subpixel edge detection and Radon inverse transform), performance comparable to or even superior to that of expensive equipment can be achieved. This approach opens new avenues for acoustic measurements and drives technological advancements in the field. Attached Figure Description

[0101] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure;

[0102] Figure 1 This is a flowchart of the free space sound field measurement method provided in the embodiments of the present invention;

[0103] Figure 2 This is a schematic diagram of the free space sound field measurement method provided in an embodiment of the present invention;

[0104] Figure 3 This is an experimental optical path diagram provided in an embodiment of the present invention;

[0105] Figure 4 This is a diagram of the sound field data acquisition experiment provided in the embodiment of the present invention; wherein, (a) is a translation scan and (b) is a rotation scan;

[0106] Figure 5 This is the actual stripe pattern obtained by CCD imaging as provided in the embodiments of the present invention;

[0107] Figure 6 This is a simulation diagram of the change of interference fringes of a Michelson interferometer when subjected to sound field disturbance, provided by an embodiment of the present invention; wherein, (a) is the sound pressure distribution of the simulated point sound source, (b) is the refractive index change after being affected by the sound field, (c) is the phase change diagram of the beam after being incident laterally and passing through the sound field disturbance at different incident positions, and (d) is a comparison diagram of the fringe movement after the beam passes through the center position of the sound field and interferes.

[0108] Figure 7 This is a schematic diagram of the Radon transform principle provided in an embodiment of the present invention;

[0109] In the diagram: Laser is a laser, BS is a beam splitter, LBE is a beam expander, L is a lens, M1 and M2 are mirrors, and CCD is an industrial camera. Detailed Implementation

[0110] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of the present invention. However, the present invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0111] The innovation of this invention lies in:

[0112] 1. This invention proposes and implements a non-destructive measurement method for sound field in a free-path optical path based on a Michelson interferometer: It innovatively utilizes the principle of acousto-optic effect to build a Michelson interferometer to achieve laser tomography, thereby performing non-contact and interference-free measurement of the sound field in a free-path optical path, solving the problem of sound field disturbance caused by traditional contact sensors.

[0113] 2. This invention achieves high-precision measurement of sound field by improving the Michelson interferometer and combining it with advanced data processing algorithms: This invention combines optical imaging magnification technology and sub-pixel edge detection algorithm to finely process the measurement results of the Michelson interferometer, making it highly sensitive to the tiny optical phase changes caused by the sound field. Theoretically, it can achieve sub-nanometer displacement resolution, thereby ensuring high precision of sound field measurement.

[0114] The principle of the free-space sound field measurement method and system provided in this embodiment of the invention is as follows:

[0115] Sound propagation essentially involves changes in pressure within the propagation medium. When a sound field exists within a medium (such as air), changes in sound pressure cause alterations in the medium's optical properties, specifically a change in its refractive index. According to the Gladstone-Dale relation and Taylor expansion, under weak acousto-optic interactions, the change in the medium's refractive index is directly proportional to the sound pressure. The phase of light depends on its propagation distance within the medium and the medium's refractive index. Therefore, changes in the medium's refractive index caused by a sound field result in a change in the phase of the light beam passing through the sound field. By measuring this change in light phase, the sound pressure of the sound field can theoretically be calculated indirectly.

[0116] Sound propagation essentially involves changes in pressure within the propagation medium; therefore, sound information can be extracted from sound pressure fluctuations caused by a sound field. Since the refractive index of air changes under the influence of a sound field, and the phase of light also changes accordingly, theoretically, the sound pressure can be indirectly calculated by measuring the change in light phase. Based on this, lasers are used to capture the changes in the refractive index of air caused by sound vibrations, thereby extracting the sound pressure information.

[0117] The propagation of sound changes the density and pressure of the medium, thus affecting the refractive index of air. Assuming this process is adiabatic, the air pressure... With density The relationship between them is given by the following formula:

[0118] (1)

[0119] In the formula, and These are pressure and density under static conditions. It is the specific heat ratio.

[0120] When sound travels Corresponding to the superposition of static pressure and acoustic pressure, that is The effect of density variation on light propagation can be determined by combining the mechanical and optical properties of the medium. In 1863, Gladstone and Dale established the refractive index of various liquids. and density Empirical relationship between them:

[0121] (2)

[0122] In the formula, This is the Gladstone-Dale constant.

[0123] Combined with the static refractive index of air and static density It can be deduced that:

[0124] (3)

[0125] Combining the above formula, we can derive the relationship between air pressure and refractive index:

[0126] (4)

[0127] In the formula, The refractive index is under standard atmospheric conditions.

[0128] When the sound pressure is much smaller than the static pressure When this expression is used, it can be approximated by a first-order Taylor expansion:

[0129] (5)

[0130] Therefore, under weak acousto-optic interaction, the change in refractive index is proportional to the sound pressure. This demonstrates a linear relationship between sound pressure and the refractive index of air. Light can be used to sense this change in refractive index caused by the sound field in air, thus making it possible to measure sound pressure.

[0131] In a homogeneous, static medium (that is, whose electromagnetic properties are independent of spatial position and time), the wave equation for the electromagnetic field is:

[0132] (6)

[0133] When a sound field exists in the medium, it no longer possesses uniform and homogeneous properties. However, according to research by PM. Morse et al., the wave equation above remains valid when the following constraint relationship is satisfied.

[0134] (7)

[0135] Within the range of human hearing, the constraints in the above equation are completely satisfied. Therefore, the solution to the propagation equation can be:

[0136] (8)

[0137] In the formula, It is a complex number, containing the initial amplitude and phase information of the light; and These are the angular frequency and phase of light, respectively.

[0138] The relationship between phase and refractive index is:

[0139] (9)

[0140] In the formula, Let be the wavenumber of light propagating in a vacuum. This is the distance light travels in the air, i.e., the length of the light path.

[0141] In air, combining the above equation, we can obtain the relationship between the light phase and the air sound pressure:

[0142] (10)

[0143] In the formula, This is the shift in the phase of light in the absence of a sound field, and it depends on the path length of light in the medium. This term can be considered as a static shift. ;

[0144] The change in the refractive index of air due to the influence of the sound field, and the resulting change in the phase of light, is called the dynamic offset. :

[0145] (11)

[0146] The above equation shows the relationship between the path integral of the sound pressure field and the light phase. Therefore, as long as the change in the light phase is measured, the sound pressure field can be indirectly calculated in theory.

[0147] This invention utilizes the principle of equal-thickness interference in a Michelson interferometer to sense minute changes in the phase of light. The Michelson interferometer uses a beam splitter to separate light emitted from a light source into a measurement beam and a reference beam. The measurement beam passes through the region of the sound field to be measured, and its optical path changes due to variations in the refractive index of the medium caused by the sound field. After the measurement beam and the reference beam re-merge, they interfere, forming alternating bright and dark interference fringes. When the optical path of the measurement beam changes, the interference fringes shift. By comparing the amount of shift in the interference fringes before and after the presence of the sound field, the change in the phase of light can be obtained.

[0148] There is a linear relationship between the path integral of sound pressure and the phase of light in a sound field. The path integral of sound pressure obtained through interferometry can be viewed as a projection of the sound field onto the direction of light propagation; this projection method is the mathematical Radon transform. Therefore, by performing an inverse Radon transform on the projection information from multiple angles or locations, the spatial distribution of sound pressure in the sound field can be reconstructed.

[0149] Example 1, as Figure 1 As shown, the free-space sound field measurement method provided in this embodiment of the invention includes the following steps:

[0150] S1, Optical path construction: Constructing a free-path acoustic field measurement system based on the principle of Michelson interferometer;

[0151] The free-path acoustic field measurement system uses a continuous laser as its light source. The emitted laser beam is first expanded by a beam expander. The expanded laser beam is then incident on a beam splitter and split into a measurement beam and a reference beam. The measurement beam passes through the area where the acoustic field to be measured (e.g., generated by a loudspeaker) is placed, strikes mirror M1, and is reflected back to the beam splitter. The reference beam strikes mirror M2 and is also reflected back to the beam splitter. The two reflected beams re-merge at the beam splitter, resulting in equal-thickness interference and forming alternating bright and dark interference fringes. These interference fringes are magnified by an objective lens and recorded by a scientific-grade CCD camera. All optical components are precisely fixed and adjusted using a high-stability series of adjustment frames.

[0152] Traditional Mach-Zehnder interferometers have complex optical systems, making calibration difficult and costly. The Michelson interferometer used in this invention has a relatively simple structure, and all optical components are precisely fixed and adjusted using a highly stable series of adjustment frames, effectively reducing the difficulty of system setup and calibration. This results in a low-cost, highly stable measurement system that effectively reduces the cumulative impact of environmental disturbances (such as vibration and temperature) on optical path difference.

[0153] The laboratory Michelson interferometer uses a continuous laser with a wavelength of 532nm. The beam splitter is a non-polarized flat beam splitter with a diameter of 25.4mm and a thickness of 5.0mm, with a splitting ratio of 50:50 (R:T). The anti-reflection coating is 400nm-700nm. The beam expander is a variable magnification laser beam expander with a working wavelength of 532nm and a magnification of 2-10 times. The reflector is a high-power laser reflector with a diameter of 12.7mm, a working wavelength of 532nm, and a surface flatness of λ / 10. The optical path calibration begins by fixing the laser and adjusting its pitch and horizontal position to ensure the laser beam propagates along the central axis of the optical platform. A beam expander is placed at the laser's output port, and its height is adjusted to ensure the expanded parallel beam spot evenly covers the center of the subsequent beam splitter. The beam splitter (BS) is then fixed on the adjustment frame, positioned 10-15 cm behind the beam expander. The height and angle of the beam splitter are then finely adjusted so that the reflected light (reference optical path) is perpendicular to the center of mirror M1, and the transmitted light (measurement optical path) is perpendicular to the center of mirror M2. The heights of the adjustment frames for M1 and M2 are adjusted so that the centers of the reflecting surfaces of the two mirrors are aligned with the height of the incident beam. Adjust the fine-tuning knob of M1 so that the reference light reflected by M1 returns along the original optical path and finally coincides with the incident light spot on the screen near the laser output port. Adjust the fine-tuning knob of M2 so that the measurement light returns along the original optical path after being reflected by M2 and merges with the reference light at the beam splitter. At this time, a CCD camera is placed behind the beam splitter, and blurry interference fringes can be observed. Then, by fine-tuning the angle between the mirrors of M2 and M1, bright and clear interference fringes can be obtained. The experiment ensures the stability of interference from four dimensions: hardware vibration isolation, environmental control, optical path optimization, and data assistance. First, the Michelson interferometer is built on an optical vibration isolation platform, and all optical components (laser, mirror, CCD) are rigidly fixed on the platform with special fixtures to prevent the components from shifting. After optical path calibration, tighten the locking screws of the MT-AM1T adjustment bracket to prevent the reflector from shifting due to minor vibrations. Then, construct a closed windproof cover with dimensions of 1200×1000×1000mm using a light-shielding cloth to enclose the entire interference optical path, preventing fluctuations in the air refractive index in the measurement optical path caused by laboratory airflow (such as air conditioning or personnel breathing). The experimental area is kept at a constant temperature by air conditioning to avoid thermal expansion and contraction of optical components due to temperature changes. The experiment reduces the cumulative error of optical path difference by shortening the optical path length. The total length of the reference optical path and the measurement optical path is controlled within 1-1.5m to reduce the cumulative impact of environmental disturbances (such as vibration and temperature) on the optical path difference. Finally, in terms of data acquisition, the speaker drive and CCD acquisition are synchronized using the Matlab control framework. After each speaker movement or rotation, the CCD acquires an image within 100ms, shortening the acquisition time and reducing fringe drift. At the same time, multiple acquisitions are averaged during the acquisition process. Interference fringes under the same sound field conditions are acquired 10 times consecutively, and the image averaging algorithm is used to eliminate fringe jitter caused by random vibrations.

[0154] S2, Sound Field Data Acquisition: Acquire a reference image, introduce the sound field to be measured, and use a computer-controlled loudspeaker or laser beam to perform translational and rotational scanning to complete the acquisition of interferometric pattern data;

[0155] (1) Acquiring reference image: In the absence of sound field interference, the initial interference fringe pattern is captured and recorded by a CCD camera as the reference image for subsequent data processing;

[0156] (2) Introducing a sound field: Introducing the sound field to be measured into the measurement optical path to disturb the measurement light passing through the region;

[0157] (3) Scanning measurement: Translation and rotation scanning are performed by computer-controlled speakers or laser beams;

[0158] For example, the laser beam is positioned fixedly, while the loudspeaker performs step-by-step translation and rotation within a two-dimensional plane. The loudspeaker can be firmly fixed to a stepper motor, which drives its movement. After each translation a certain distance or rotation a certain angle, an interference fringe pattern disturbed by the sound field is captured and recorded in real time by a CCD camera.

[0159] In scanning measurements, parallel line scanning of the sound field is achieved by placing the speaker on a motor turntable and moving the turntable perpendicular to the beam of the Michelson interferometer's measuring arm. The movement range is 30cm to the left and 30cm to the right of the measuring arm, with a scanning angle range of 0°-180°. Because the projection data for θ≥180° in parallel beam scanning mode is a copy of the θ-180° projection, data redundancy can be effectively avoided and the measurement process simplified. The quality of the two-dimensional reconstruction of the sound field depends on the spatial and angular resolution of the scan. Too low a resolution will result in a blurry reconstructed sound field with lost details; while too high a resolution will lead to an extremely slow reconstruction process and reduced efficiency. Therefore, sound field reconstruction requires a trade-off between reconstruction quality and reconstruction efficiency. Simultaneously, the reconstruction resolution is limited by the laser diameter. If the spatial resolution is higher than the laser diameter, the laser cannot be considered an ideal linear beam. Therefore, it is necessary to ensure that the translation distance is higher than the laser beam diameter. The experimental laser diameter was 1.5 mm, the spatial resolution (translation step size) was set to 2 cm, and the angular resolution (rotation angle interval) was 10°. The wavelength of a 2 kHz sound wave in air is about 17 cm. The spatial resolution of 2 cm is less than half of that (8.5 cm), which satisfies the Nyquist sampling theorem and avoids aliasing. The drive signal of the loudspeaker and the data acquisition system controlled by the Matlab program realize the synchronous triggering of signal transmission and acquisition, ensuring that the sound field excitation and the optical phase measurement of the interferometer are synchronized.

[0160] (4) Repeat the translation-scanning and rotation-scanning process to complete the acquisition of interference pattern data at multiple positions and angles.

[0161] Traditional sensor array methods require a large number of sensors, resulting in high costs and complex calibration. This invention, through scanning measurement, requires only a single laser beam and sound source to complete data acquisition, significantly reducing hardware costs and operational complexity. It achieves omnidirectional, multi-angle data acquisition of the sound field, providing ample projection information for subsequent accurate reconstruction. In scanning mode, spatial and angular resolutions can be flexibly set according to the sound wave frequency. For example, a 2kHz sound wave has a wavelength of approximately 17cm in air; a spatial resolution of 2cm is less than half of that (8.5cm), satisfying the Nyquist sampling theorem and avoiding aliasing effects.

[0162] S3, Interference fringe image processing and optical phase information extraction: The acquired interference pattern is preprocessed, the edges of the interference fringes are identified using edge detection technology, and the amount of optical phase change is calculated;

[0163] For each set of "interference fringe patterns with sound field" and "interference fringe patterns without sound field" collected in step S2, the following processing is performed:

[0164] 1. Image preprocessing: The acquired interference pattern is preprocessed by filtering, denoising and other operations to improve image quality.

[0165] 2. Fringe Edge Detection: Edge detection technology from image processing is used to identify the sharp edges of interference fringes. This algorithm locates edge information in the image by detecting abrupt changes in pixel grayscale values ​​(such as object contours, texture changes, etc.). To improve measurement accuracy, a sub-pixel edge detection algorithm can be used to analyze the fringe displacement and accurately obtain the actual movement distance of the interference fringes. The specific processing procedure is as follows:

[0166] (1) Image acquisition and region cropping: First, the interference fringe image is acquired from the CCD camera, and the image is selectively cropped through the region of interest (ROI) to focus on the core region of the interference fringe.

[0167] (2) Image Filtering and Gradient Calculation: Applying an edge detection filter to the cropped image is a crucial step after acquisition. This filter is used to obtain the edge gradient and direction of the image. Commonly used operators include the Canny operator used in this invention. In addition, the Sobel operator, edges_image, derivate_gauss, edges_color, etc., can also be used for this purpose. These filters identify potential edges by finding parts of the image where the pixel grayscale values ​​change significantly. After identifying potential edges, subsequent thresholding can be used to locate the edge information of the stripes.

[0168] (3) Edge extraction and thresholding: After applying the filter, the bright edges (i.e., pixels with high gradients) in the striped image are extracted by thresholding (such as the threshold operator or the hysteresis_threshold operator), reducing non-critical edges and forming thin edge lines.

[0169] (4) Non-maximum suppression and edge refinement: The extracted edges are further subjected to non-maximum suppression to ensure that the edge line width is one pixel, thereby improving the accuracy of the edges. Subsequently, the Skelcton operator or other methods can be used to draw or refine the edges. For discontinuous edges, merging and background separation are also required to obtain a complete outline.

[0170] (5) Subpixel edge localization: To improve measurement accuracy, a subpixel edge detection algorithm is adopted. This algorithm achieves subpixel-level precise localization of interference fringe edges by interpolating or curve fitting the grayscale information between pixels (e.g., using the Gauss-Seidel iterative method, Zernike moment method, or interpolation method).

[0171] (6) Calculation of fringe displacement: Obtain the subpixel-level edge position of the reference image without sound field, and the subpixel-level edge position of each scan position and angle image with sound field. By comparing these two sets of edge data, the actual displacement distance of each interference fringe in the horizontal or vertical direction is accurately calculated.

[0172] Traditional image processing methods suffer from blurred edges and low positioning accuracy in interferometric fringe measurement. This invention solves this problem by employing an optimized four-stage edge detection algorithm (Gaussian filtering, Sobel operator, non-maximum suppression, and double threshold segmentation) and sub-pixel positioning technology. The edge positioning error is reduced from approximately 1.2 pixels in traditional methods to approximately 0.1 pixels, improving accuracy by 10 times while doubling processing efficiency. This high-precision detection capability effectively captures nanometer-level optical path changes caused by the acoustic field.

[0173] 3. Calculation of optical phase change: Based on the linear relationship between the movement of interference fringes and the optical path difference, and the relationship between the change in optical path difference and the optical phase change, the fringe movement is converted into the optical phase change caused by the light beam passing through the sound field.

[0174] This invention utilizes equal-thickness interference with a Michelson interferometer to measure the sound field. When the measuring light interferes with the reference light, alternating bright and dark vertical fringes are formed. As the optical path of the measuring light changes, the interference fringes shift. Theoretically, by comparing the amount of fringe shift before and after the presence of the sound field, the change in optical path can be determined, thus revealing the change in optical phase. Therefore, due to the presence of the sound field, the optical path of the measuring light changes, and the fringes shift when it interferes with the reference light at the same thickness. By comparing the amount of fringe shift before and after the presence of the sound field, the change in optical phase can be determined, thereby achieving the measurement of the sound field.

[0175] The fringe spacing of the Michelson interferometer under the condition of equal thickness interference is:

[0176] (12)

[0177] In the formula, The spacing between the interference fringes. The wavelength of the laser. The angle between the mirror surfaces;

[0178] stripe movement for:

[0179] (13)

[0180] In the formula, This is the change in optical path difference as the light path passes through the sound field;

[0181] From this, we can obtain the actual distance the stripes moved. for:

[0182] (14)

[0183] In the formula, This refers to the phase change.

[0184] Therefore, the phase change can be obtained. The linear relationship between the actual movement distance of the stripes and the actual movement distance of the stripes allows us to know the phase change caused by the presence of the sound field, thus enabling us to inversely deduce the sound field.

[0185] S4, Sound Field Sound Pressure Reconstruction: The Radon inverse transform algorithm is used to reconstruct the sound field, converting the sound field integral information carried by the laser beam into the sound pressure value of each point in the real space, and reconstructing the free field sound pressure distribution map.

[0186] The acquired data on the phase change of light at different positions and angles (i.e., the path integral information of the sound field) are input into the sound field reconstruction algorithm. This invention uses the Radon inverse transform algorithm for sound field reconstruction. The Radon inverse transform can reverse the spatial distribution of the original two-dimensional sound field from the line integral projection data at multiple angles. Through this algorithm, the sound field integral information carried by the laser beam can be converted into the sound pressure value of each point in real space, thereby reconstructing a complete free-field sound pressure distribution map.

[0187] By using lasers to capture changes in the air's refractive index caused by sound vibrations, sound pressure information can be extracted. This data can then be used to reconstruct the sound pressure distribution of the sound field. The line integral of sound pressure can be viewed as a projection of the sound field onto the direction of light propagation; this projection method is known mathematically as the Radon transform.

[0188] The frame of reference for the sound field is The coordinate system, after rotating by 0 degrees, becomes Coordinate systems. There is a transformation relationship between these two coordinate systems:

[0189] (15)

[0190] This projection integration process can be described as:

[0191] (16)

[0192] In the formula, The sound pressure to be measured in the sound field. For along Directional path is The sound pressure integral, This represents the path of light through the region of sound pressure disturbance.

[0193] Based on the relationship between phase and sound pressure in equation (11), the relationship between the Radon transform of sound pressure and sound pressure in the time domain can be obtained:

[0194] (17)

[0195] In the formula, Let be the wavenumber of light propagating in a vacuum. The photoluminescence coefficient of the medium, The phase measured by the interferometer. The isentropic pressure coefficient isotropic. The reconstructed sound field in coordinates place, time t The sound pressure level;

[0196] Therefore, the sound pressure of the measured sound field can be reconstructed using the inverse Radon transform:

[0197] (18)

[0198] In the formula, The reconstructed sound field in coordinates place, time t sound pressure, This is the Radon inverse transform operator, which is used to infer the sound pressure distribution from the projection integral result.

[0199] The process of sound field reconstruction using the Radon inverse transform algorithm is as follows:

[0200] First, a series of optical phase changes at different projection angles and positions are obtained from step S3. These optical phase changes represent the line integral of the sound field (i.e., the refractive index change) along the laser beam propagation path, and can be regarded as the projection data of the sound field in the corresponding direction. The Radon transform of the sound pressure p of the sound field can be expressed as the line integral along a specific direction. Then, the collected projection data from multiple angles and positions are used as input, and the inverse Radon transform algorithm is applied. The inverse Radon transform is the inverse operation of the Radon transform, and its core idea is to reconstruct the original two-dimensional (or three-dimensional) function distribution based on the projection data obtained from multiple angles. In acoustic measurement, this means that the sound pressure value at each point on the path is deduced from the sound pressure projection information, thereby realizing the reconstruction of the sound field distribution. The output of the inverse Radon transform is the spatial distribution function of the original two-dimensional sound field. This means that the sound field information carried by the laser beam and integrated along a specific path is successfully converted into the information of each discrete point in the sound field space. The sound pressure level is then calculated. Finally, the reconstructed two-dimensional sound pressure distribution data is visualized to generate a sound pressure distribution map.

[0201] Through the above process, the present invention can transform the indirect projection information obtained by optical measurement into a complete free-field sound pressure spatial distribution map with physical meaning, providing accurate data support for acoustic analysis and noise control.

[0202] Example 2: The free-space sound field measurement system provided in this embodiment of the invention mainly includes:

[0203] like Figure 3As shown, the system uses a 532nm continuous laser as the light source. The laser beam emitted by the laser serves as the main optical path, first passing through a beam expander (LBE) for beam amplification, and then incident on a beam splitter. The beam splitter, located at the center of the optical path, splits the incident beam in two. One beam serves as a reference beam, incident on mirror M1, and reflected back to the beam splitter. The other beam serves as the measurement beam, passing through the area of ​​the sound field to be measured and finally striking mirror M2, which reflects it back to the beam splitter. A loudspeaker is placed in the measurement optical path as the sound source to be measured and is fixed on a guide rail. The guide rail is used to enable translation and rotation scanning of the loudspeaker in a two-dimensional plane. The two beams reflected from M1 and M2 re-merge at the beam splitter, resulting in equal-thickness interference and forming alternating bright and dark interference fringes. After being magnified by an objective lens, the interference fringes are recorded by a CCD (scientific-grade CCD camera) located below the objective lens. A computer is connected to the loudspeaker and CCD via wires to control the loudspeaker's scanning motion, such as translation and rotation. Control the CCD camera to acquire data, i.e., capture interferometric patterns. Receive and process the image data acquired by the CCD, and execute image processing and sound field reconstruction algorithms.

[0204] Laser: Used to emit laser beams with good coherence, such as continuous lasers.

[0205] Beam expander (LBE): Expands the laser beam to allow for the observation of interference fringes.

[0206] Beam splitter (BS): splits the expanded laser beam into two beams: a measurement beam and a reference beam.

[0207] Reflectors (M1, M2): Used to reflect the measurement light and the reference light, causing them to re-converge and interfere. Mirror M1 is placed at the end of the acoustic field region to be measured, so that the measurement light is reflected after passing through the acoustic field.

[0208] Loudspeaker / sound source: Placed in the measurement optical path as the sound field to be measured, used to generate sound wave disturbances.

[0209] Scientific-grade CCD camera: Placed in the area where interference fringes form, used to record interference patterns.

[0210] Objective lens: Used to magnify interference fringes and improve the resolution of images recorded by the CCD camera.

[0211] Computer and control system: used to control the scanning motion of the loudspeaker / sound source, the data acquisition of the CCD camera, and to execute image processing and sound field reconstruction algorithms.

[0212] High-stability series adjustment brackets: used for precise fixing and adjustment of the position of optical components.

[0213] Example 3, Alternative Sound Source Movement Methods: The movement of the loudspeaker can be achieved through various high-precision positioning devices such as robotic arms and automated guide rail systems, rather than being limited to stepper motor drives. Laser beam scanning can also be achieved through optical scanning equipment such as high-speed scanning galvanometers, thereby keeping the sound source stationary.

[0214] Example 4, Replacement of CCD camera and objective lens: A CMOS camera or other photodetector with high resolution and high frame rate, combined with a microscope objective lens with high magnification, can also replace the scientific-grade CCD camera and objective lens combination, as long as the acquisition accuracy and resolution requirements of the interference fringe image can be met.

[0215] Example 5, Alternatives to edge detection algorithms: In addition to the Halcon correlation operator and subpixel edge detection algorithm, other advanced image processing algorithms, such as deep learning-based image segmentation and displacement estimation methods, can also be used for interference fringe recognition and displacement extraction to further improve processing speed and accuracy.

[0216] Example 6, Interferometer type alternative: Although the present invention uses the Michelson interferometer as an example, other types of interferometers (such as Mach-Zehnder interferometers) can also be used as alternatives if the principle allows, and if they can achieve accurate measurement of the optical phase change caused by the sound field.

[0217] Example 7, Laser type substitution: Other types of lasers, such as pulsed lasers (if they can be matched with the response speed of the interferometer and accurately measure the transient sound field), can also be used as substitutes for continuous lasers, provided that a laser beam with good coherence and suitable wavelength can be provided.

[0218] To further demonstrate the positive effects of the above embodiments, the present invention conducts the following experiments based on the above technical solutions.

[0219] 1. Achieved non-destructive and non-invasive measurement.

[0220] Traditional sound field measurement methods, such as sensor array methods, have inherent invasiveness issues. The sensor itself needs to be placed directly in the sound field to be measured, and its physical presence will cause sound scattering, thus disturbing the original sound field. This interference, within the limited sound field space, not only limits the number of microphones in the array but also affects the measurement accuracy and spatial resolution.

[0221] This invention utilizes the principle of acousto-optic effect, sensing sound field signals using only a laser beam passing through the sound field. The laser itself does not physically disturb the sound field, achieving truly contactless and interference-free measurement. This fundamentally solves the inherent problem of sensor interference with the sound field in traditional microphone array measurements.

[0222] 2. It has high measurement accuracy.

[0223] Sub-nanometer displacement resolution: This invention employs the equal-thickness interference principle of a Michelson interferometer, combined with optical imaging magnification and advanced sub-pixel edge detection algorithms. This combination enables the system to accurately sense nanometer-level optical path changes caused by the acoustic field. Under the conditions of an equal-thickness interference tilt angle of 0.1° and a laser wavelength of 532nm, the system can theoretically achieve a displacement sensitivity of approximately 0.17nm / pixel, realizing sub-nanometer displacement resolution.

[0224] Improved Edge Detection Algorithm: The improved sub-pixel edge detection algorithm used in this invention reduces the stripe localization error from approximately 1.2 pixels in traditional methods to approximately 0.1 pixels. Compared to traditional methods, its accuracy is improved by 10 times, while its processing efficiency is also improved by 2 times. This high-precision stripe displacement measurement ensures high accuracy in sound field measurement and accurate sound source identification.

[0225] Data acquisition stability: Through various measures such as hardware vibration isolation, environmental control (wind shield and constant temperature), optical path optimization and data assistance (synchronous acquisition, multiple acquisition and averaging), this invention effectively ensures the stability of the interference, reduces fringe drift and jitter, and ensures the reliability of the measurement.

[0226] 3. Lower cost advantage:

[0227] Compared to existing acousto-optic effect measurement equipment such as expensive laser Doppler vibrometers, this invention only requires relatively low-cost equipment such as necessary continuous lasers, high-precision optical lenses, and scientific-grade CCD cameras, which greatly reduces measurement costs.

[0228] 4. Feasibility verified by theory and simulation

[0229] The feasibility of this invention has been verified through simulation. Simulations of a 1000Hz point sound source show that it can cause nanometer-level changes in optical path and micrometer-level fringe shifts, requiring a high-resolution CCD camera and edge detection algorithms for measurement. Furthermore, Radon transform simulations of monopoles and simply supported aluminum plates also verify the feasibility of reconstructing the sound field from laser measurement data. These theoretical and simulation results collectively demonstrate the great potential of this method in achieving high-precision, non-destructive sound field measurement.

[0230] This invention addresses the effective measurement of sound field information in free-path light. By constructing a free-path light measurement system based on a Michelson interferometer, it utilizes the characteristic that the perturbation of the sound field causes a change in the phase of light. Combined with advanced image processing and signal reconstruction algorithms, it achieves non-destructive, high-precision, and low-cost measurement of the sound field.

[0231] The flowchart of the method used in this invention is as follows: Figure 2As shown, the laser emitted by the laser is expanded and then enters the Michelson interferometer, splitting into a measurement beam and a reference beam. The measurement beam passes through the region of the sound field to be measured and merges with the reference beam to produce interference fringes. A CCD camera captures images of the interference fringes with and without sound field disturbances. Through image processing, including edge detection and subpixel displacement analysis, the movement of the interference fringes is accurately obtained, thus yielding information on the optical phase change caused by the sound field. Finally, using the Radon inverse transform algorithm, the spatial distribution of sound pressure in the sound field is reconstructed from the optical phase change data at multiple locations and angles.

[0232] The free-space sound field measurement method provided in this embodiment of the invention specifically includes the following steps:

[0233] Step 1: Experimental optical path setup.

[0234] Reference Figure 3 As shown, a free-path acoustic field measurement system based on the Michelson interferometer principle is constructed. The system uses a 532nm continuous laser (MSI-FN-532-300mW) as the light source. The laser beam is first expanded by a VBE-532-2-10X variable-magnification laser beam expander to obtain a suitable beam diameter for observing interference fringes. The expanded laser beam is then incident on a BS2155-A unpolarized flat beam splitter (BS). The beam splitter divides the laser beam into two paths: one for measurement and one for reference. The measurement beam passes through the area containing the acoustic field to be measured, strikes a high-power laser line reflector M1 (LPM10-532-1064-HP), and is reflected back to the beam splitter. The reference beam strikes another reflector M2 (LPM10-532-1064-HP) and is reflected back to the beam splitter. The two reflected beams re-converge at the beam splitter, resulting in equal-thickness interference and forming alternating bright and dark interference fringes. These interference fringes are magnified by the objective lens and recorded by a scientific-grade CCD camera. All optical components are precisely fixed and adjusted using a highly stable series of adjustment mounts.

[0235] Step 2: Acquisition of sound field measurement data.

[0236] A Matlab control framework was built in the computer to control the scanning path. The speaker was firmly fixed to a stepper motor, which drove it to move and rotate.

[0237] 1. Acquire a reference image: In the absence of a sound field, acquire an interference fringe image using a CCD camera as a reference image.

[0238] 2. Introducing and scanning the sound field: A sound field is generated through a loudspeaker and placed in the measurement optical path of the Michelson interferometer, allowing the measurement light to pass through this sound field. For example... Figure 4 As shown, the scanning process includes:

[0239] Translation scan: such as Figure 4 As shown in Figure (a), while keeping the laser beam position constant, the speaker performs step-by-step translations within a two-dimensional plane. After each translation a certain distance, the CCD camera acquires the interference fringe pattern at the current position (see Figure 1). Figure 5 ).

[0240] Rotational scanning: such as Figure 4 As shown in Figure (b), based on translational scanning, or by performing rotational scanning alone, the speaker disturbs the laser beam at different angles. After each rotation by a certain angle, the CCD camera acquires the corresponding interference fringe pattern (see Figure 1). Figure 5 ).

[0241] 3. Repeat the above translation-scan and rotation-scan process to complete the data acquisition of "acoustic field interference fringe patterns" at multiple positions and angles.

[0242] Step 3: Interference fringe image analysis and extraction of optical phase changes.

[0243] For each pair of "silent field interference fringe patterns" and "sound field interference fringe patterns" acquired in step 2, the following processing is performed:

[0244] 1. Image preprocessing: The acquired interference pattern is preprocessed by filtering, denoising and other operations to improve image quality.

[0245] 2. Fringe Edge Detection: This algorithm utilizes edge detection techniques from image processing to identify the sharp edges of interference fringes. It locates edge information in the image by detecting abrupt changes in pixel grayscale values ​​(such as object contours or texture variations). To improve measurement accuracy, a sub-pixel edge detection algorithm can be used to analyze the fringe displacement, precisely obtaining the actual movement distance of the interference fringes. The figure shows the observed interference fringes.

[0246] 3. Calculation of optical phase change: Based on the linear relationship between the movement of interference fringes and the optical path difference, and the relationship between the change in optical path difference and the optical phase change, the fringe movement is converted into the optical phase change caused by the light beam passing through the sound field.

[0247] Edge detection algorithms locate edge information in images by detecting abrupt changes in pixel grayscale values. These abrupt changes include object contours and texture variations. Sub-pixel edge detection algorithms analyze fringe displacement to obtain the actual movement distance of the interference fringes. A four-stage edge detection algorithm, employing Gaussian filtering, Sobel gradient calculation, non-maximum suppression, and double threshold segmentation, is used to meet the requirements for measuring sub-pixel displacement of interference fringes. The mathematical principles of each stage are as follows:

[0248] To address the random noise (such as light intensity fluctuations and electronic noise) present in the interference fringe images acquired by CCD, a two-dimensional Gaussian function is used to smooth the image, as shown in the following formula:

[0249] ;

[0250] ;

[0251] In the formula, This is a two-dimensional Gaussian function, a kernel function used for smoothing images. For the natural constant e The exponential function with base α, here is a core component of the two-dimensional Gaussian function, used to describe how the function value changes with... x , y The changing decay characteristics. Let be the coordinate variable of the image in the horizontal direction, used to determine the positional values ​​of the two-dimensional Gaussian function in the horizontal direction. These are the coordinate variables of the image in the vertical direction, used to determine the positional values ​​of the two-dimensional Gaussian function in the vertical direction. The standard deviation of the Gaussian kernel. This is used to balance noise suppression and edge blurring; The grayscale values ​​of the filtered image. The grayscale values ​​of the original interference fringe image. This is a convolution operation;

[0252] The filtered image is calculated using the Sobel operator. The gradient of direction determines the magnitude and direction of the edge, as shown in the following formula:

[0253] ;

[0254] ;

[0255] ;

[0256] ;

[0257] In the formula, They are respectively Orientation gradient, This represents the gradient magnitude, used to reflect edge strength. The gradient direction is used to reflect the edge orientation and matches the vertical direction of the interference fringes;

[0258] Local extrema are determined along the gradient direction, retaining edge center pixels and discarding non-edge pixels, as shown in the following formula:

[0259] ;

[0260] In the formula, For the image after non-maximum suppression, the edge width is thinned from 3 to 5 pixels to 1 pixel by setting high and low thresholds to connect broken edges. Two-dimensional Gaussian function, For adjacent pixels along the gradient direction;

[0261] Finally, sub-pixel edge localization is used to improve accuracy. Sub-pixel level edge coordinate calculation is achieved based on interpolation. A quadratic polynomial is used to fit the gray values ​​of the 3×3 neighborhood near the edge, assuming that the gray values ​​near the edge satisfy... ,right Taking the derivative and setting it to 0, we obtain the subpixel coordinates:

[0262] ;

[0263] In the formula, These are the polynomial fitting coefficients. These are sub-pixel level edge coordinates, with a positioning accuracy of 0.1 pixels. These are pixel coordinates.

[0264] This invention's edge detection algorithm, through Gaussian filtering optimization and sub-pixel localization improvement, solves the problems of blurred edges, low localization accuracy, and poor efficiency in interference fringe measurement using traditional methods. Traditional methods have an edge localization error of approximately 1.2 pixels, while this invention, through its improved algorithm, reduces this error to approximately 0.1 pixels, a 10-fold improvement compared to traditional detection methods, while also reducing the measurement error of fringe movement. Traditional edge detection algorithms are general-purpose (e.g., applicable to natural images), while this invention's algorithm, combining the periodicity and vertical orientation of interference fringes, limits gradient direction calculation to 0° or 90° (only vertical edges are needed), reducing computational load by 50%. By combining sub-pixel localization with fast fitting, it improves accuracy by 10 times while still increasing processing efficiency by 2 times. This invention's algorithm can directly process low-contrast fringe images acquired by CCDs, while traditional methods require additional image contrast enhancement, making it more suitable for practical sound field measurement scenarios.

[0265] 1) Image acquisition and region cropping: The interference fringe image is acquired from the CCD camera, and the image is selectively cropped through the region of interest to focus on the core area of ​​the interference fringes;

[0266] Supplement: The interference fringes directly acquired by the CCD camera are images captured from the complete CCD target surface, including unwanted black borders and even interference from imperfections. Furthermore, the blurring of the interference fringes at the edges of the image interferes with edge extraction. Therefore, it is only necessary to select areas with clear and high-quality interference fringes in the image for cropping. The code for the bounding box selection algorithm is written using Matlab software. After determining the image area to be cropped, the program crops and saves the areas with good interference quality in each image.

[0267] 2) Image filtering and gradient calculation: Apply an edge detection filter to the cropped image to obtain the edge gradient and direction of the image;

[0268] 3) Edge extraction and thresholding: After applying the filter, the bright edges in the striped image are extracted by thresholding using the threshold operator or the hysteresis_threshold operator, forming thin edge lines;

[0269] 4) Non-maximum suppression and edge refinement: Non-maximum suppression is applied to the extracted edges, and the Skelcton operator is used to draw or refine the edges; discontinuous edges are merged and the background is separated to obtain a complete outline;

[0270] 5) Subpixel edge localization: A subpixel edge detection algorithm is used to achieve subpixel-level precise localization of interference fringe edges by interpolating or curve fitting the grayscale information between pixels.

[0271] 6) Calculation of fringe displacement: Obtain the subpixel-level edge position of the reference image when there is no sound field, and the subpixel-level edge position of each scan position and angle image when there is a sound field; by comparing the two sets of edge data, calculate the actual displacement distance of each interference fringe in the horizontal or vertical direction.

[0272] Step 4: Sound field sound pressure reconstruction.

[0273] The light phase change data (i.e., path integral information of the sound field) obtained in step 3 at different positions and angles is input into the sound field reconstruction algorithm. This invention uses the Radon inverse transform algorithm for sound field reconstruction. The Radon inverse transform can reverse the spatial distribution of the original two-dimensional or three-dimensional sound field from the line integral projection data at multiple angles. Through this algorithm, the sound field integral information carried by the laser beam can be converted into the sound pressure value of each point in real space, thereby reconstructing a complete free-field sound pressure distribution map.

[0274] First, the reconstruction performance of the method of this invention was simulated at audible frequencies in a 2kHz scene. Due to the relatively low frequency and long wavelength of the sound wave, the sound pressure distribution exhibited a wide concentric circle ripple pattern. The reconstructed image clearly captured the concentric circle structure of the original sound field, with high image sharpness and high consistency with the original sound field. The final calculated root mean square error (RMSE) was 1.0124. This low error value indicates that the method of this invention has high accuracy and reliability in reconstructing audible sound fields.

[0275] A complex sound field generated by the superposition of two independent sound sources was simulated to verify the ability of this method to handle multi-source sound fields. Sound source 1 is 1000Hz, located at (-0.2m, -0.2m), and sound source 2 is 2000Hz, located at (0.2m, 0.2m). Both have a vibrational velocity amplitude of 20m / s, as shown in the figure. The original sound field exhibits two independent sound pressure centers, with two sets of concentric circular ripples superimposed to form a typical complex interference pattern. The reconstructed image clearly identifies and reconstructs the relative positions and intensities of the two sound sources, effectively capturing the complex sound field superposition pattern. The final calculated root mean square error (RMSE) is 2.0350. This low error value indicates that this method can successfully handle complex sound fields composed of multiple sound sources and accurately reconstruct them.

[0276] The reconstruction performance of the proposed method at very high frequencies was simulated in an ultrasonic field (200kHz). The sound frequency was 200kHz, the source velocity amplitude was 20m / s, and the source z-coordinate was -0.1m. As shown in the figure, due to the extremely high frequency and very short wavelength, the sound pressure distribution in space exhibits extremely dense and complex ring-shaped ripples. Although the reconstructed image captures the basic ring structure, the dense ripples result in significant loss of reconstruction details, leading to a relatively blurry image. The final calculated root mean square error (RMSE) was 101.2353. This high error value indicates that without increasing the scanning resolution (i.e., reducing the translation step size and angular interval), the reconstruction accuracy of this method for extremely high-frequency sound fields with extremely short wavelengths is limited.

[0277] This method can effectively and accurately reconstruct low-frequency and mid-frequency sound fields, including some complex ones. Although the reconstruction accuracy decreases at the current resolution for extremely high-frequency ultrasonic fields with very short wavelengths (200kHz), the reconstruction results can be significantly improved by increasing the sampling density (reducing the translation step size and rotation angle). For complex scenarios such as multi-point sound sources, this method demonstrates powerful processing capabilities and reconstruction accuracy.

[0278] Example inversion effect:

[0279] 1. Simulation of Acousto-optic Effect Measurement:

[0280] like Figure 6As shown, the changes in interference fringes of a Michelson interferometer when subjected to sound field disturbances were simulated. The simulation object was a planar sound field with a point source at a frequency of 1000 Hz and a diameter of 1 m, located 10 cm below the measurement plane, with an assumed light wavelength of 532 nm. The simulation results show that the sound pressure distribution causes a change in the air refractive index, which in turn causes a phase change when light passes laterally through the sound field. At the maximum sound pressure of 1.539 Pa, the maximum refractive index change is 2.96 × 10⁻⁶. -9 The maximum phase change is 0.027 rad.

[0281] Simultaneously, the interference fringes formed by the interference of the measurement light and the reference light after passing through the sound field were simulated. With an interference mirror angle of approximately 0.1 degrees and equal thickness, the optical path difference ranged from 1.03 to 2.74 nm, the fringe shift ranged from 0.0032 to 0.0087 fringes, the fringe spacing was 0.16 mm, and the fringe displacement ranged from 0.51 to 1.37 μm. This indicates that the fringe shift is at the micrometer level, imperceptible to the human eye, and requires measurement using a high-resolution CCD camera and edge detection algorithms.

[0282] Theoretical calculations show that the measurement system must achieve an accuracy of one-thousandth of a wavelength. Under the conditions of a 0.1° tilt angle for equal-thickness interference and a laser wavelength of 532 nm, the fringe spacing for equal-thickness interference is approximately 152 μm. The pixel size of an existing industrial camera in the laboratory is approximately 1.85 μm, which becomes 0.18 μm / pixel after 10x magnification with an objective lens. When the boom moves by half a wavelength, the fringes move by one spacing, yielding a displacement sensitivity of approximately 0.31 nm / pixel. Combining optical magnification with a sub-pixel edge detection algorithm, sub-nanometer displacement resolution can theoretically be achieved. Furthermore, the optical path change of light affected by a sound field with a sound pressure level of approximately 2 Pa is at the nanometer level, thus enabling high-precision measurement of the sound field.

[0283] 2. Radon transform simulation verification:

[0284] The principle of Radon transform is as follows: Figure 7 As shown, computer simulations analyzed the acousto-optic effect as an explanation of the Radon transform of the sound field. The simulation results show that the sound pressure distribution pattern of the point sound source resembles concentric circles, spreading outwards with gradually decreasing sound pressure. The projected distribution pattern after the Radon transform looks like a fence with a thicker center and thinner edges. This is a result of the spherical symmetry of the sound field under study, meaning the integral of the sound field is independent of angles, leading to the same result. This verifies that measuring the sound field with a laser is actually a Radon transform process. Simulations of the Radon transform of a simply supported aluminum plate further validated the feasibility of reconstructing the sound field using laser measurement data.

[0285] These results demonstrate that the free-field sound field measurement system and method based on acousto-optic effect proposed in this invention are feasible for achieving high-precision, non-destructive sound field measurement in both theory and simulation.

[0286] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by those skilled in the art within the scope of the technology disclosed in the present invention and within the spirit and principles of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for measuring a free-space sound field, characterized in that, The method includes the following steps: S1, Optical path construction: Constructing a free-path acoustic field measurement system based on the principle of Michelson interferometer; S2, Sound Field Data Acquisition: Acquire a reference image, introduce the sound field to be measured, and use a computer-controlled loudspeaker or laser beam to perform translational and rotational scanning to complete the acquisition of interferometric pattern data; S3, Interference fringe image processing and optical phase information extraction: The acquired interference pattern is preprocessed, the edges of the interference fringes are identified using edge detection technology, and the amount of optical phase change is calculated; S4, Sound Field Sound Pressure Reconstruction: The Radon inverse transform algorithm is used to reconstruct the sound field, converting the sound field integral information carried by the laser beam into the sound pressure value of each point in the real space, and reconstructing the free field sound pressure distribution map.

2. The free-space sound field measurement method according to claim 1, characterized in that, In step S1, the optical path setup includes: The free-path acoustic field measurement system uses a continuous laser as the light source. The emitted laser beam is expanded by a beam expander. The expanded laser beam is then incident on a beam splitter and split into a measurement beam and a reference beam. The measuring light passes through the area where the sound field to be measured is placed, strikes the reflecting mirror M1, and is reflected back to the beam splitter; the reference light strikes the reflecting mirror M2 and is reflected back to the beam splitter. The two reflected beams re-converge at the beam splitter, resulting in equal-thickness interference and forming alternating bright and dark interference fringes. The interference fringes are magnified by the objective lens and recorded by a CCD camera.

3. The free-space sound field measurement method according to claim 2, characterized in that, The sound field under test is generated by a loudspeaker. All optical components are precisely fixed and adjusted using a high-stability series adjustment frame. The laser, beam splitter, beam expander, reflector, and CCD are all mounted on the high-stability series adjustment frame and rigidly fixed to the optical isolation platform. The adjustment frame has a fine-tuning screw mechanism for adjusting the pitch angle, horizontal angle, and height to ensure that the beam propagates along the central axis of the platform. After fixing, the locking screws of the adjustment frame are tightened to prevent the components from shifting due to minor vibrations. After the laser is fixed, the pitch angle and horizontal position are adjusted to make the beam propagate along the center of the optical platform. After the beam expander is installed, its height is precisely adjusted using the adjustment frame to ensure that the expanded beam spot uniformly covers the center of the beam splitter. The beam splitter is fixed on the adjustment frame and positioned 10-15cm behind the beam expander. By fine-tuning the height and angle, the reflected light and transmitted light are directed perpendicularly to the centers of reflectors M1 and M2, respectively. Adjust the height and angle of reflectors M1 and M2 so that the reflected light coincides with the incident light when it returns, and forms clear interference fringes at the beam splitter.

4. The free-space sound field measurement method according to claim 1, characterized in that, In step S2, the sound field data acquisition includes: Acquiring reference images: In the absence of sound field interference, the initial interference fringe pattern is captured and recorded by a CCD camera as the reference image for subsequent data processing; Introducing a sound field: The sound field to be measured is introduced into the measurement optical path, so that the sound field disturbance passes through the measurement light where the sound field to be measured is placed; Scanning measurement: Translation and rotation scanning are performed by computer-controlled speakers or laser beams; Repeat the translation-scan and rotation-scan processes to complete the acquisition of interferometric pattern data at multiple positions and angles.

5. The free-space sound field measurement method according to claim 4, characterized in that, The scanning measurement includes: fixing the position of the laser beam, and moving the speaker in a step-by-step translation and rotation in a two-dimensional plane; fixing the speaker on a stepper motor and moving the speaker by the motor; after each translation a certain distance or rotation a certain angle, the interference fringe pattern after the sound field disturbance is captured and recorded in real time by a CCD camera.

6. The free-space sound field measurement method according to claim 1, characterized in that, In step S3, the interference fringe image processing and optical phase information extraction include: (1) Image preprocessing: preprocessing the acquired interference pattern by filtering and denoising; (2) Fringe edge detection: An edge detection algorithm is used to identify the edges of the interference fringes; (2) Calculation of optical phase change: Based on the linear relationship between the movement of interference fringes and optical path difference, and the relationship between the change of optical path difference and optical phase change, the movement of fringes is converted into the optical phase change caused by the light beam passing through the sound field.

7. The free-space sound field measurement method according to claim 6, characterized in that, Edge detection algorithms locate edge information in images by detecting abrupt changes in pixel grayscale values. These abrupt changes include object contours and texture variations. A sub-pixel edge detection algorithm is used to analyze fringe displacement and obtain the actual movement distance of the interference fringes. A four-stage edge detection algorithm, employing Gaussian filtering, Sobel gradient calculation, non-maximum suppression, and double threshold segmentation, is used to meet the requirements for measuring sub-pixel displacement of interference fringes. The specific process is as follows: To address the random noise, including light intensity fluctuations and electronic noise, present in the interference fringe images acquired by CCD, a two-dimensional Gaussian function is used to smooth the image. The expression is as follows: In the formula, This is a two-dimensional Gaussian function, a kernel function used for smoothing images. For the natural constant The exponential function with base α, here is a core component of the two-dimensional Gaussian function, used to describe how the function value changes with... The changing decay characteristics; Let be the coordinate variable of the image in the horizontal direction, used to determine the positional values ​​of the two-dimensional Gaussian function in the horizontal direction. These are the coordinate variables of the image in the vertical direction, used to determine the positional values ​​of the two-dimensional Gaussian function in the vertical direction. The standard deviation of the Gaussian kernel. Used to balance noise suppression and edge blurring; The grayscale values ​​of the filtered image. The grayscale values ​​of the original interference fringe image. This involves convolution operations; the filtered image is then calculated using the Sobel operator. The gradient of direction determines the magnitude and direction of the edge, and its expression is: In the formula, They are respectively Orientation gradient, This represents the gradient magnitude, used to reflect edge strength. The gradient direction is used to reflect the edge orientation and matches the vertical direction of the interference fringes. Local extrema are determined along the gradient direction, retaining the center pixels of the edges and discarding non-edge pixels. The expression is: In the formula, For the image after non-maximum suppression, the edge width is thinned from 3 to 5 pixels to 1 pixel by setting high and low thresholds to connect broken edges. For adjacent pixels along the gradient direction; To improve accuracy, subpixel edge localization is employed. Subpixel-level edge coordinate calculation is achieved based on interpolation. A quadratic polynomial is used to fit the grayscale values ​​of a 3×3 neighborhood near the edge, assuming that the grayscale values ​​near the edge satisfy... right Taking the derivative and setting it to 0, we obtain the subpixel coordinates: In the formula, These are the polynomial fitting coefficients. The positioning accuracy is 0.1 pixels; These are pixel coordinates.

8. The free-space sound field measurement method according to claim 7, characterized in that, The actual displacement distance of each interference fringe in the horizontal or vertical direction is calculated as follows: The fringe spacing of the Michelson interferometer under constant thickness interference is: In the formula, The spacing between the interference fringes. The wavelength of the laser. The angle between the mirror surfaces; the amount of fringe movement. for: In the formula, The change in optical path difference as the light path passes through the sound field; the actual distance the fringes move. for: In the formula, The phase change; through the phase change The linear relationship between the actual movement distance of the stripes is used to inversely calculate the sound field.

9. The free-space sound field measurement method according to claim 1, characterized in that, In step S4, sound field sound pressure reconstruction includes: inputting the acquired light phase change data at different projection angles and positions into the Radon inverse transform algorithm to reconstruct the sound field and generate a free-field sound pressure distribution map; the reference frame of the sound field is... coordinate system, rotation The coordinate system after the angle becomes coordinate system coordinate system and The transformation relationships between coordinate systems are as follows: The projection integration process is as follows: In the formula, The sound pressure to be measured in the sound field. For the path along the direction The sound pressure integral, Let be the path of light through the sound pressure disturbance region; based on the dynamic offset, the relationship between the Radon transform of the sound pressure in the time domain and the sound pressure is obtained as follows: In the formula, Let be the wavenumber of light propagating in a vacuum. The photoluminescence coefficient of the medium, The phase measured by the interferometer. The isentropic pressure coefficient isotropic. For sound pressure level Along the path in the direction of the path The points, The reconstructed sound field in coordinates place, time The sound pressure level; In the formula, For the relevant refractive index parameters of the medium, A coefficient related to the properties of the medium. The reference pressure is used; the sound pressure of the measured sound field is reconstructed using the inverse Radon transform as follows: In the formula, The inverse transform operator is used to infer the sound pressure distribution from the projection integral result.

10. A free-space sound field measurement system, characterized in that, This system is used to control the free-space sound field measurement method according to any one of claims 1-9, and the system comprises: A laser is used to emit a laser beam with good coherence; this laser is a continuous laser. Beam expander, used to expand a laser beam; A beam splitter is used to split the expanded laser beam into a measurement beam and a reference beam. A reflector is used to reflect the measurement light and the reference light, so that they re-interfere; wherein, the reflector M1 is placed at the end of the sound field region to be measured, so that the measurement light is reflected after passing through the sound field; A loudspeaker / sound source is placed in the measurement optical path as the sound field to be measured, used to generate sound wave disturbances; A scientific-grade CCD camera is placed in the area where interference fringes form to record interference patterns; Objective lens, used to magnify interference fringes and improve the resolution of images recorded by CCD camera; Computer and control system, used to control the scanning motion of loudspeakers / sound sources, data acquisition by CCD cameras, and to execute image processing and sound field reconstruction algorithms; High-stability series adjustment brackets are used for precise fixing and adjustment of the position of optical components.

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