Compressor casing noise prediction method and system based on acoustic boundary element model

Abstract

This invention discloses a method and system for predicting compressor casing noise based on an acoustic boundary element model, belonging to the field of noise prediction technology. The method specifically includes: establishing a three-dimensional geometric model of the compressor casing; constructing an acoustic boundary element model of the compressor casing based on the three-dimensional geometric model; discretizing the geometric model into boundary element units; identifying the main noise sources inside and outside the compressor; loading the identified noise sources as boundary conditions into the acoustic boundary element model; setting acoustic boundary conditions according to the actual working environment and material properties of the compressor casing; solving the acoustic boundary element model; calculating the acoustic response of the compressor casing surface; and predicting the noise of the compressor casing based on the calculated acoustic response of the compressor casing surface. This invention takes into account the complex geometry and material properties of the compressor casing, enabling more accurate localization and quantification of noise sources.

Description

Technical Field

[0001] This invention belongs to the field of noise prediction technology, specifically a method and system for predicting compressor casing noise based on the acoustic boundary element model. Background Technology

[0002] Compressors are widely used in various industrial and civil fields such as refrigeration, air conditioning, and gas compression. As a core device for energy conversion, they generate mechanical vibration and aerodynamic noise during operation. These noises mainly originate from gas pulsation inside the compressor, unbalanced forces in rotating parts, and vibration of the casing. Noise problems are particularly severe under high loads and high speeds, not only affecting the working environment of operators but also potentially causing noise pollution to the surrounding environment, and impacting the reliability and service life of the equipment.

[0003] In terms of compressor noise prediction, existing technologies mainly rely on noise testing using noise testing instruments. While noise testing technology has played an important role in compressor noise prediction research, it still has certain shortcomings. This technology is limited by its high cost, long processing time, difficulty in testing large units, and significant impact from background noise. Furthermore, it can only be applied to already manufactured physical models and is not convenient for use in the production optimization design stage within manufacturers' factories.

[0004] For example, Chinese patent CN113761679B discloses a method and apparatus for predicting compressor noise. The method includes: determining relevant information of a multi-stage compressor unit, which includes multiple single-stage compressor units; inputting the relevant information of each single-stage compressor unit into a prediction model to obtain predicted sound pressure values ​​for each single-stage compressor unit; and inputting the predicted sound pressure values ​​of each single-stage compressor unit into a superposition model to obtain predicted sound pressure values ​​for the multi-stage compressor unit. This application allows for rapid analysis of noise amplitude, composition, and sources, meeting the noise prediction requirements for compressors at the factory and facilitating quick on-site problem-solving, while also providing technical guidance for parameter optimization during the design phase.

[0005] The defects of the above patent are: 1) limited noise prediction capability under dynamic conditions; 2) difficulty in accurately distinguishing the contribution of different noise sources when facing complex noise environments, thus affecting the effectiveness of noise control and problem localization. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention proposes a method and system for predicting compressor casing noise based on an acoustic boundary element model. This method can accurately predict the noise level of the compressor casing under complex boundary conditions, thus overcoming the deficiencies of existing technologies.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] A method for predicting compressor casing noise based on the acoustic boundary element model includes:

[0009] Establish a three-dimensional geometric model of the compressor casing;

[0010] Based on the three-dimensional geometric model of the compressor casing, an acoustic boundary element model of the compressor casing is constructed, and the three-dimensional geometric model is discretized into boundary element units.

[0011] Identify the main noise sources inside and outside the compressor, and load the identified noise sources as boundary conditions into the acoustic boundary element model;

[0012] Acoustic boundary conditions are set based on the actual working environment and material properties of the compressor casing;

[0013] Solve the acoustic boundary element model and calculate the acoustic response of the compressor casing surface;

[0014] Based on the calculated acoustic response of the compressor casing surface, the noise of the compressor casing is predicted.

[0015] Specifically, establishing the three-dimensional geometric model of the compressor casing includes:

[0016] The compressor casing is modeled using CAD software, and the specific formula is as follows:

[0017] ,

[0018] in, This represents the three-dimensional geometric model of the compressor casing, where u and v represent the parameters of the three-dimensional geometric model of the compressor casing. and Let P represent the B-spline basis functions defined in the directions of parameters u and v, respectively. i,j Indicates the control points on the curved surface of the compressor casing. and These are the orders of the basis functions in the u and v directions, respectively, and w i,j Represents control point P i,j The associated weights, where i and j represent control point indices, and m and n represent the number of control points;

[0019] The initial geometric model is refined, and then corrected and optimized based on actual measurement data or simulation results.

[0020] Specifically, the acoustic boundary element model for constructing the compressor housing includes:

[0021] Based on the three-dimensional geometric model of the compressor casing, the three-dimensional geometric model is discretized to construct the acoustic boundary element model of the compressor casing. The specific formula of the acoustic boundary element model of the compressor casing is as follows:

[0022] ,

[0023] Where G represents the acoustic boundary element model of the compressor casing, G o Let N represent the 0th boundary element, and N represent the total number of boundary element elements.

[0024] Specifically, identifying the main noise sources inside and outside the compressor, and then loading the identified noise sources as boundary conditions into the acoustic boundary element model, includes:

[0025] By using sensors to collect vibration signals inside the compressor, and analyzing the spectrum of the vibration signals inside the compressor through Fourier transform, the main mechanical vibration frequencies are identified, and the internal noise sources are determined.

[0026] By measuring the airflow velocity and pressure at the compressor inlet and outlet, and combining this with fluid dynamics simulation, the main noise source frequencies are identified, and the external noise source is determined.

[0027] The identified main noise sources inside and outside the compressor are used as boundary conditions and loaded into the acoustic boundary element model. The acoustic boundary element model is then updated using the following formula:

[0028] ,

[0029] Where p(x) represents the acoustic boundary element model after one update, Let c0 represent the density of the sound propagation medium, c0 represent the speed of sound, and Gl(x,y) represent the acoustic Green's function from the boundary point y to the observation point x. Let represent the normal derivative of the sound pressure at boundary point y, and p(y) represent the sound pressure at point y on the compressor casing boundary. Let represent the derivative of the Green's function with respect to the normal vector, O represent the normal vector on the surface of the acoustic boundary element model G, and dG(y) represent the integral of the area element on the boundary surface of the acoustic boundary element model G with respect to the boundary point y.

[0030] Specifically, setting the acoustic boundary conditions includes:

[0031] Based on the actual working environment and material properties of the compressor housing, the acoustic boundary type of the compressor housing surface is determined, including: hard acoustic boundary and soft acoustic boundary;

[0032] The acoustic boundary conditions are set using the following formula:

[0033] ,

[0034] in, and This represents the weighting coefficient, which is adjusted based on the sound reflection and absorption characteristics of the compressor casing material;

[0035] Based on the acoustic boundary conditions, the acoustic boundary element model is updated a second time, and the specific formula is as follows:

[0036] ,

[0037] in, This represents the acoustic boundary element model after the second update, i.e., the updated sound pressure at the observation point x.

[0038] Specifically, solving the acoustic boundary element model and calculating the acoustic response of the compressor housing surface includes:

[0039] Solving the updated acoustic boundary element model yields the acoustic response of the compressor casing surface, as shown in the following formula:

[0040] ,

[0041] Where q(x) represents the acoustic response at observation point x on the compressor casing, and L(y a ) indicates at the boundary point y a The flow rate of sound waves. Let A represent the area of ​​the a-th boundary cell, and let A represent the number of boundary cells.

[0042] Specifically, the prediction of noise from the compressor casing includes:

[0043] Based on the calculated acoustic response of the compressor casing surface, the noise of the compressor casing at observation point x is predicted using the following formula:

[0044] ,

[0045] Among them, L p Let denot be the predicted noise of the compressor casing at observation point x, lg() represent the logarithmic function with base 10, and p0 represent the reference sound pressure.

[0046] The compressor casing noise prediction system based on the acoustic boundary element model is used to implement the compressor casing noise prediction method based on the acoustic boundary element model. It includes: a geometric modeling module, a boundary discretization module, a sound source loading module, a condition setting module, a model solving module, and a noise prediction module.

[0047] The geometric modeling module is used to establish a three-dimensional geometric model of the compressor casing;

[0048] The boundary discretization module is used to construct an acoustic boundary element model of the compressor housing based on the three-dimensional geometric model of the compressor housing, and to discretize the three-dimensional geometric model into boundary element units.

[0049] The sound source loading module is used to identify the main noise sources inside and outside the compressor, and load the identified noise sources as boundary conditions into the acoustic boundary element model;

[0050] The condition setting module is used to set acoustic boundary conditions according to the actual working environment and material properties of the compressor housing;

[0051] The model solving module is used to solve the acoustic boundary element model and calculate the acoustic response of the compressor casing surface;

[0052] The noise prediction module is used to predict the noise of the compressor casing based on the calculated acoustic response of the compressor casing surface.

[0053] Compared with the prior art, the beneficial effects of the present invention are:

[0054] 1. This invention proposes a method for predicting compressor casing noise based on the acoustic boundary element model. The method based on the acoustic boundary element model can accurately simulate the sound field distribution and noise radiation characteristics of the compressor casing, and has higher prediction accuracy than traditional methods. Considering the complex geometry and material properties of the casing, the noise source can be more accurately located and quantified.

[0055] 2. This invention proposes a compressor casing noise prediction method based on the acoustic boundary element model. Compared with other numerical methods, the boundary element method can significantly reduce the consumption of computing resources and improve computing efficiency when dealing with external sound field problems by reducing the dimension of the solution region.

[0056] 3. This invention proposes a compressor casing noise prediction method based on an acoustic boundary element model, which is applicable to compressors of different types and sizes. By adjusting the model parameters, the noise level of the compressor can be optimized during the design phase, thereby achieving a customized noise control scheme. Attached Figure Description

[0057] Figure 1 A flowchart of the compressor casing noise prediction method based on the acoustic boundary element model provided by this invention;

[0058] Figure 2 The diagram shows the architecture of the compressor casing noise prediction system based on the acoustic boundary element model provided by this invention. Detailed Implementation

[0059] To facilitate understanding of the technical means, creative features, and achieved objectives and effects of this invention, it should be noted in the description of this invention that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "number one," "number two," and "number three" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. The invention will be further described below in conjunction with specific embodiments.

[0060] Example 1

[0061] Please see Figure 1 The present invention provides an embodiment of a compressor casing noise prediction method based on an acoustic boundary element model, comprising the following specific steps:

[0062] Step S1: Establish a three-dimensional geometric model of the compressor casing;

[0063] The specific steps of step S1 are as follows:

[0064] Step S101: Use CAD software to accurately model the compressor casing. The specific formula is as follows:

[0065] ,

[0066] in, This represents the three-dimensional geometric model of the compressor casing. u and v represent the parameters of this model. By adjusting the values ​​of parameters u and v, different points on the surface can be obtained. and Let P represent the B-spline basis functions defined in the directions of parameters u and v, respectively, which determine the smoothness and shape of the surface. i,j Indicates the control points on the curved surface of the compressor casing. and These are the orders of the basis functions in the u and v directions, respectively, representing the degree of the surface function. Higher orders can generate smoother and more complex surfaces. i,j Represents control point P i,j The associated weights, i and j represent control point indices, i is the control point index corresponding to the direction of parameter u, j is the control point index corresponding to the direction of parameter v, m and n represent the number of control points, n represents the number of control points in the direction of parameter u minus 1, that is, the total number of control points in the direction of u is n+1, m represents the number of control points in the direction of parameter v minus 1, that is, the total number of control points in the direction of v is m+1.

[0067] In this embodiment, the complex geometry of the compressor housing can be accurately described, including details such as rounded corners, recesses, and protrusions. This accuracy is far superior to traditional polygon mesh modeling methods, especially when dealing with complex geometry and surface transitions. To further improve the accuracy of the model, this method introduces an adaptive thinning technique. By introducing a local thinning strategy, it is possible to thin out important geometric feature areas (such as rapidly changing surfaces or near boundaries) while keeping the global computational load under control, thereby improving the modeling accuracy of these areas.

[0068] Step S102: Refine the geometric model of the initial design. Based on actual measurement data or simulation results, correct and optimize the geometric model, such as bolt holes and support ribs, to ensure that it can accurately reflect the actual shape and structural characteristics of the compressor casing.

[0069] Step S2: Based on the three-dimensional geometric model of the compressor housing, construct the acoustic boundary element model of the compressor housing, and discretize the three-dimensional geometric model into boundary element units;

[0070] Constructing the acoustic boundary element model of the compressor casing includes:

[0071] Based on the three-dimensional geometric model of the compressor casing, the three-dimensional geometric model is discretized to construct the acoustic boundary element model of the compressor casing. The specific formula of the acoustic boundary element model of the compressor casing is as follows:

[0072] ,

[0073] Where G represents the acoustic boundary element model of the compressor casing, which is a closed surface in three-dimensional space, representing the outer surface of the entire geometric model, used for sound field analysis. o The 'o'-th boundary element represents a portion of the boundary after discretization, and N represents the total number of boundary elements, i.e., the number of boundary elements after discretizing the entire geometric model.

[0074] By using discretization and unitization steps, complex geometries and boundary conditions can be described more accurately, significantly improving the computational accuracy of acoustic boundary element models. Compared with traditional methods, the discretization technique using polygons or surface patches enables the model to maintain high accuracy and effectively capture detailed features when dealing with complex geometries.

[0075] Step S3: Identify the main noise sources inside and outside the compressor, and load the identified noise sources as boundary conditions into the acoustic boundary element model;

[0076] The specific steps of step S3 are as follows:

[0077] Step S301: Use sensors to collect vibration signals inside the compressor, analyze the spectrum of the vibration signals inside the compressor through Fourier transform, identify the main mechanical vibration frequencies, and determine the internal noise source.

[0078] Step S302: Measure the airflow velocity and pressure at the compressor inlet and outlet, and combine with fluid dynamics simulation to identify the main noise source frequencies and determine the external noise source;

[0079] Step S303: The identified main noise sources inside and outside the compressor are used as boundary conditions and loaded into the acoustic boundary element model. The acoustic boundary element model is then updated using the following formula:

[0080] ,

[0081] Where p(x) represents the acoustic boundary element model after one update, i.e., the initial sound pressure at the observation point x, which is an important physical quantity in the sound field used to measure the intensity of the sound wave. Here, c represents the density of the sound propagation medium, c0 represents the speed of sound, and Gl(x,y) represents the acoustic Green's function from the boundary point y to the observation point x. The Green's function is a key function in sound field analysis, used to calculate the distribution of sound pressure. It contains information about the attenuation and phase change of sound waves along different paths. The normal derivative represents the sound pressure at boundary point y, reflecting the rate of change of sound pressure at the boundary. The normal derivative is an important part of boundary conditions, used to describe the influence of the boundary on the sound field, especially at boundaries where a sound source exists. dG(y) represents the derivative of the Green's function with respect to the normal vector, O represents the normal vector on the surface of the acoustic boundary element model G, the normal vector defines the direction of the calculation of the derivatives of the sound pressure p(y) and the Green's function Gl(x,y) at the boundary point y, p(y) represents the sound pressure at the boundary point y of the compressor casing, and dG(y) represents the integral of the small area element on the boundary surface of the acoustic boundary element model G with respect to the boundary point y.

[0082] In this embodiment, sound pressure is directly related to the intensity and propagation characteristics of noise and is the main target of noise analysis and prediction. In the acoustic boundary element method, the formula calculates the sound pressure p(x) at the observation point x, combines the sound pressure p(y) on the boundary with the normal derivative of the Green's function Gl(x,y), and integrates it on the entire surface of the acoustic boundary element model G. The final sound pressure value is determined by summing the contribution of each point on the boundary. The normal vector O and the boundary integral G(y) are key factors, which determine how the sound wave propagates, reflects, and affects the sound pressure at the observation point on the boundary.

[0083] Step S4: Set acoustic boundary conditions based on the actual working environment and material properties of the compressor casing;

[0084] The specific steps of step S4 are as follows:

[0085] Step S401: Determine the acoustic boundary type of the compressor housing surface, including hard acoustic boundary and soft acoustic boundary, based on the actual working environment and material properties of the compressor housing.

[0086] Step S402: Set acoustic boundary conditions, the specific formula is as follows:

[0087] ,

[0088] in, and This represents the weighting coefficient, which is adjusted based on the sound reflection and absorption characteristics of the compressor casing material;

[0089] Step S403: Based on the acoustic boundary conditions, perform a second update on the acoustic boundary element model after the first update. The specific formula is as follows:

[0090] ,

[0091] in, This represents the acoustic boundary element model after the second update, i.e., the updated sound pressure at the observation point x.

[0092] Step S5: Solve the acoustic boundary element model and calculate the acoustic response of the compressor housing surface;

[0093] Solving the acoustic boundary element model and calculating the acoustic response of the compressor casing surface includes:

[0094] Solving the updated acoustic boundary element model yields the acoustic response of the compressor casing surface, as shown in the following formula:

[0095] ,

[0096] Where q(x) represents the acoustic response at observation point x on the compressor casing, i.e., the final calculated sound pressure at observation point x, and L(y a ) indicates at the boundary point y a The flow rate of sound waves at a given point reflects the energy transport of sound waves at that point, and it is related to the sound pressure and the material properties of the boundary point. Let A represent the area of ​​the a-th boundary element, which is the sum of these small areas on the entire boundary surface. This summation is used to calculate the total sound pressure contribution from all sound source points y to the observation point x on the boundary surface of the acoustic boundary element model G. Let A represent the number of boundary elements.

[0097] The sound pressure contributions of all boundary elements are summed through an integral equation to obtain the sound pressure distribution at various observation points on the compressor casing surface. The fast multipole method can effectively reduce the computational load and adapt to high-precision acoustic analysis of complex geometries. Finally, the model is verified by experimental data or actual measurement results to ensure the reliability of the prediction results.

[0098] Step S6: Based on the calculated acoustic response of the compressor casing surface, predict the noise of the compressor casing.

[0099] Predicting the noise of the compressor casing, including:

[0100] Based on the calculated acoustic response of the compressor casing surface, the noise of the compressor casing at observation point x is predicted using the following formula:

[0101] ,

[0102] Among them, L p Let lg() represent the predicted noise of the compressor casing at observation point x, lg() represent the logarithmic function with base 10, and p0 represent the reference sound pressure, typically taken as 20. This value corresponds to the minimum sound pressure level that the human ear can hear, and is therefore often used as a reference benchmark in sound pressure level calculations.

[0103] By calculating the sound pressure level and sound power level, a noise field distribution map can be drawn around the compressor. These distribution maps can visually show the propagation path and intensity distribution of noise in space, helping to identify the main location of the noise source and the noise transmission path.

[0104] Furthermore, the noise level of the compressor in various working environments can be assessed based on the noise field distribution under different operating conditions, and corresponding noise reduction measures can be formulated. By comparing the noise field distribution of different design schemes, the compressor design can be optimized, thereby reducing noise pollution and improving the acoustic performance of the equipment.

[0105] In this embodiment, 10log 10 It reflects the conversion relationship between sound pressure and sound pressure level. By performing a 20-fold logarithmic transformation on the sound pressure, the physical quantity of sound pressure can be converted into an easily interpretable scalar value, usually in decibels (dB). The calculation of decibel values ​​allows for direct comparison of the sound pressure levels of different sound sources.

[0106] Example 2

[0107] Please see Figure 2Another embodiment of the present invention provides a compressor casing noise prediction system based on an acoustic boundary element model, comprising: a geometric modeling module, a boundary discretization module, a sound source loading module, a condition setting module, a model solving module, and a noise prediction module;

[0108] The geometric modeling module is used to establish a three-dimensional geometric model of the compressor casing;

[0109] The boundary discretization module is used to construct an acoustic boundary element model of the compressor housing based on the three-dimensional geometric model of the compressor housing, and to discretize the three-dimensional geometric model into boundary element units.

[0110] The sound source loading module is used to identify the main noise sources inside and outside the compressor, and load the identified noise sources as boundary conditions into the acoustic boundary element model;

[0111] The condition setting module is used to set acoustic boundary conditions according to the actual working environment and material properties of the compressor housing;

[0112] The model solving module is used to solve the acoustic boundary element model and calculate the acoustic response of the compressor casing surface;

[0113] The noise prediction module is used to predict the noise of the compressor casing based on the calculated acoustic response of the compressor casing surface.

[0114] In addition, the parts of the technical solutions provided in the embodiments of this application that are consistent with the implementation principles of the corresponding technical solutions in the prior art have not been described in detail, so as to avoid excessive elaboration.

[0115] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the invention. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for predicting compressor casing noise based on an acoustic boundary element model, characterized in that, include: Establish a three-dimensional geometric model of the compressor casing; Based on the three-dimensional geometric model of the compressor casing, an acoustic boundary element model of the compressor casing is constructed, and the three-dimensional geometric model is discretized into boundary element units. Identify the main noise sources inside and outside the compressor, and load the identified noise sources as boundary conditions into the acoustic boundary element model; Acoustic boundary conditions are set based on the actual working environment and material properties of the compressor casing; Solve the acoustic boundary element model and calculate the acoustic response of the compressor casing surface; Based on the calculated acoustic response of the compressor casing surface, the noise of the compressor casing is predicted; The process of identifying the main noise sources inside and outside the compressor, and then applying these identified noise sources as boundary conditions to the acoustic boundary element model, includes: By using sensors to collect vibration signals inside the compressor, and analyzing the spectrum of the vibration signals inside the compressor through Fourier transform, the main mechanical vibration frequencies are identified, and the internal noise sources are determined. By measuring the airflow velocity and pressure at the compressor inlet and outlet, and combining this with fluid dynamics simulation, the main noise source frequencies are identified, and the external noise source is determined. The identified main noise sources inside and outside the compressor are used as boundary conditions and loaded into the acoustic boundary element model. The acoustic boundary element model is then updated using the following formula: ， Where p(x) represents the acoustic boundary element model after one update, Let c0 represent the density of the sound propagation medium, c0 represent the speed of sound, and Gl(x,y) represent the acoustic Green's function from the boundary point y to the observation point x. Let represent the normal derivative of the sound pressure at boundary point y, and p(y) represent the sound pressure at point y on the compressor casing boundary. Let represent the derivative of the Green's function with respect to the normal vector, O represent the normal vector on the surface of the acoustic boundary element model G, and dG(y) represent the integral of the area element on the boundary surface of the acoustic boundary element model G with respect to the boundary point y. The setting of acoustic boundary conditions includes: Based on the actual working environment and material properties of the compressor housing, the acoustic boundary type of the compressor housing surface is determined, including: hard acoustic boundary and soft acoustic boundary; The acoustic boundary conditions are set using the following formula: ， in, and This represents the weighting coefficient, which is adjusted based on the sound reflection and absorption characteristics of the compressor casing material; Based on the acoustic boundary conditions, the acoustic boundary element model is updated a second time, and the specific formula is as follows: ， in, This represents the acoustic boundary element model after the second update, i.e., the updated sound pressure at the observation point x.

2. The method for predicting compressor casing noise based on the acoustic boundary element model as described in claim 1, characterized in that, The process of establishing a three-dimensional geometric model of the compressor casing includes: The compressor casing is modeled using CAD software, and the specific formula is as follows: ， in, This represents the three-dimensional geometric model of the compressor casing, where u and v represent the parameters of the three-dimensional geometric model of the compressor casing. and Let P represent the B-spline basis functions defined in the directions of parameters u and v, respectively. i,j Indicates the control points on the curved surface of the compressor casing. and These are the orders of the basis functions in the u and v directions, respectively, and w i,j Represents control point P i,j The associated weights, where i and j represent control point indices, and m and n represent the number of control points; The initial geometric model is refined, and then corrected and optimized based on actual measurement data or simulation results.

3. The method for predicting compressor casing noise based on the acoustic boundary element model as described in claim 2, characterized in that, The acoustic boundary element model for constructing the compressor casing includes: Based on the three-dimensional geometric model of the compressor casing, the three-dimensional geometric model is discretized to construct the acoustic boundary element model of the compressor casing. The specific formula of the acoustic boundary element model of the compressor casing is as follows: ， Where G represents the acoustic boundary element model of the compressor casing, G o Let N represent the 0th boundary element, and N represent the total number of boundary element elements.

4. The compressor casing noise prediction method based on the acoustic boundary element model as described in claim 3, characterized in that, The solution of the acoustic boundary element model, calculating the acoustic response of the compressor casing surface, includes: Solving the updated acoustic boundary element model yields the acoustic response of the compressor casing surface, as shown in the following formula: ， Where q(x) represents the acoustic response at observation point x on the compressor casing, and L(y a ) indicates at the boundary point y a The flow rate of sound waves. Let A represent the area of ​​the a-th boundary cell, and let A represent the number of boundary cells.

5. The compressor casing noise prediction method based on the acoustic boundary element model as described in claim 4, characterized in that, The prediction of noise from the compressor casing includes: Based on the calculated acoustic response of the compressor casing surface, the noise of the compressor casing at observation point x is predicted using the following formula: ， Among them, L p Let denot be the predicted noise of the compressor casing at observation point x, lg() represent the logarithmic function with base 10, and p0 represent the reference sound pressure.

6. A compressor casing noise prediction system based on an acoustic boundary element model, used to implement the compressor casing noise prediction method based on an acoustic boundary element model as described in any one of claims 1-5, characterized in that, include: The module includes a geometric modeling module, a boundary discretization module, a sound source loading module, a condition setting module, a model solving module, and a noise prediction module. The geometric modeling module is used to establish a three-dimensional geometric model of the compressor casing; The boundary discretization module is used to construct an acoustic boundary element model of the compressor housing based on the three-dimensional geometric model of the compressor housing, and to discretize the three-dimensional geometric model into boundary element units. The sound source loading module is used to identify the main noise sources inside and outside the compressor, and load the identified noise sources as boundary conditions into the acoustic boundary element model; The condition setting module is used to set acoustic boundary conditions according to the actual working environment and material properties of the compressor housing; The model solving module is used to solve the acoustic boundary element model and calculate the acoustic response of the compressor casing surface; The noise prediction module is used to predict the noise of the compressor casing based on the calculated acoustic response of the compressor casing surface.

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