A method, device, medium and program for quickly predicting underwater vehicle propeller noise based on excitation source reconstruction

Abstract

The application discloses a kind of underwater vehicle propeller noise fast prediction method, device, medium and program based on excitation source reconstruction, belongs to noise prediction technical field.The method of the present application is based on the invariance of vibration transfer function relationship and the basic theory such as sound energy superposition principle, vibration source reconstruction technology is introduced into propeller noise prediction, to the vibration response measured and obtained by a plurality of vibration sensors on the stern structure of propeller as input, based on vibration transfer function reconstruction excitation source matches structure surface vibration, by the excitation source reconstructed, the radiation noise caused by the structure vibration of propeller shaft boat structure vibration generated by structure vibration can be solved;Establish the propeller direct sound fast prediction method under different coherence, based on energy superposition principle realizes including propeller shaft boat coupling noise and propeller direct sound propeller noise fast prediction evaluation.The present application is suitable for ship real-time monitoring propeller shaft vibration and radiation noise.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of noise prediction, and particularly relates to a method, device, medium and program for quickly predicting underwater vehicle propeller noise based on excitation source reconstruction. BACKGROUND

[0002] The vibration and acoustic radiation noise of an underwater vehicle is an important indicator for evaluating its performance. The increase of vibration noise not only increases the risk of being detected by the other party, but also interferes with the accuracy of the equipment such as the navigation and guidance system of the underwater vehicle, thereby reducing its working ability and survivability. Therefore, we must pay attention to the vibration noise problem of the underwater vehicle. A large number of studies have shown that the noise generated by the propeller device is one of the main sources of the vibration noise of the underwater vehicle, in which the propeller noise mainly includes the noise generated by the pulsating pressure of the propeller exciting or directly exciting the hull through the shafting, the rotating noise of the propeller and the cavitation noise. The rotating noise of the propeller is the noise generated due to its operation in a non-uniform flow field, and the frequency is mainly determined by the rotating frequency of the blade. Once the shafting reaches the cavitation critical speed, the propeller noise becomes the main source of noise of the underwater vehicle, which seriously affects its concealment. Therefore, the vibration and noise reduction design of the underwater vehicle is very important for its development.

[0003] Understanding the vibration and acoustic characteristics of the underwater vehicle is the premise of the vibration and noise reduction design, and currently the research on the propeller noise of the underwater vehicle is mainly based on computer simulation calculation, which needs to waste a lot of time for modeling and calculation, and the prediction result can only reflect the vibration and acoustic characteristics of the propeller-shaft-hull to a certain extent, lacks the verification of test data, and is difficult to obtain strong support. Therefore, it is very important to invent a propeller-shaft-hull vibration test and propeller noise prediction method for understanding the propeller noise of the underwater vehicle, thereby providing support for the vibration and noise reduction design development of the underwater vehicle. SUMMARY

[0004] The application aims to provide a method and application device for quickly predicting the propeller noise of a ship, solve the problem of real-time monitoring of the propeller shaft vibration and rapid evaluation of the radiation noise of the ship.

[0005] The application achieves the above-mentioned purpose by the following technical solutions.

[0006] A method for quickly predicting the propeller noise of an underwater vehicle based on excitation source reconstruction, comprising the following steps:

[0007] Step 1: For the noise caused by the propeller exciting the aft structure, the positions of the vibration sensing points, the positions of the reconstructed sources and the positions of the sound field evaluation points are determined.

[0008] Step 2: According to the vibration sensing point position and the position of the reconstructed source obtained in step 1, the vibration-to-vibration transfer function of the reconstructed source to the stern structure monitoring point is obtained through simulation calculation;

[0009] Step 3: According to the position of the sound field evaluation point obtained in step 1, the sound-to-vibration transfer function of the reconstructed source to the sound field evaluation point is obtained based on the acoustic finite element method;

[0010] Step 4: Based on the transfer function invariance, the sound field reconstruction model based on the reconstructed source is established according to the transfer functions obtained in steps 2 and 3;

[0011] Step 5: By measuring the response at the actual shell vibration sensing point, the excitation size of the reconstructed source is calculated based on the vibration-to-vibration transfer function of the reconstructed source to the main body surface, the vibration response of the propeller exciting the stern structure is obtained, and the noise of the propeller exciting the stern structure is calculated;

[0012] Step 6: A direct sound calculation model of the propeller is established, and the direct sound noise of the propeller is obtained according to the speed and rotational speed;

[0013] Step 7: The noise of the propeller exciting the stern structure obtained in step 5 and the direct sound noise obtained in step 6 are energy superimposed to complete the calculation of the propeller noise.

[0014] Further, the vibration transfer function of the main vibration source to the stern structure obtained in step 1 through simulation calculation is based on a Bi-LSTM neural network to establish an inverse sensing network model;

[0015] The vibration transfer relationship between the shaft system vibration sensing point and the stern shell surface is established through a Bi-LSTM neural network to realize the reconstruction of the stern structure vibration and determine the number, position and size of the reconstructed excitation source;

[0016] The size of the reconstructed excitation source is specifically:

[0017] The propeller structure is regarded as a linear system, and the relationship between the excitation vector a P (p j ,ω) of the reconstructed excitation source p j and the vibration acceleration response A P (r i ,ω) of the monitoring point r i on the stern structure is established;

[0018] A P (r i ,ω)=H vP (r i p j ,ω)*a P (p j ,ω)

[0019] wherein H vP (r i p j ,ω) is the vibration mapping relationship matrix between the reconstruction excitation source p j and the stern structure measurement point r i with the dimension of M*K;

[0020] The generalized inverse matrix is introduced to obtain the excitation source vector:

[0021] a P (p j ,ω) = [[H vP (r i p j ,ω)] H [H vP (r i p j ,ω)]] -1 [H vP (r i p j ,ω)] H *A P (r i ,ω).

[0022] Further, the step 2 establishes the underwater vehicle geometric model, including the propeller, the propeller shaft and the stern structure of the ship body; the underwater vehicle geometric model is placed in the fluid domain, and the fluid domain grid model and the structure finite element model are respectively established according to the underwater vehicle geometric model;

[0023] According to the reconstruction source and the vibration sensing point position established in the step 1, the monitoring point positions are uniformly arranged on the stern structure of the ship body, the vibration response of each vibration sensing point position is obtained by applying a unit force at the reconstruction source position, and the vibration response is the vibration vibration transfer function from the reconstruction source to each monitoring point of the stern structure.

[0024] Further, the step 3 sets the sound field examination point in the model flow field according to the sound field examination point established in the step 1, obtains the sound pressure at the sound field examination point by applying a unit force at the reconstruction source position based on the acoustic finite element method, and the sound pressure of the examination point at this time is the sound vibration transfer function from the reconstruction source to the sound field examination point.

[0025] Further, the step 4 converts the radiation sound power calculation formula into the sound pressure calculation formula, establishes the relationship between the sound pressure and the transfer function, and obtains the radiation sound pressure calculation formula under the propeller excitation stern structure:

[0026] P(Q) = H1 pa |a1| + H2 pa |a2| +... H jpa |a P j ,ω)|

[0027] where P(Q) is the noise pressure generated by the propeller exciting the hull structure, H j pa is the sound vibration transfer function of the coded reconstruction source to the sound field evaluation point, thereby establishing a sound field reconstruction model based on the reconstruction source; a P j is the excitation source vector.

[0028] Further, the step 6 is:

[0029] determining the rotation speed of the propeller of the underwater vehicle;

[0030]

[0031] where n max is the maximum rotation speed of the propeller, v is the linear speed of the propeller, v max is the maximum linear speed of the propeller; the f q value of the propeller blade frequency q and its second and third tuning frequency values are calculated as follows:

[0032] f q = qnZ, Hz, q = 1, 2, 3

[0033] where f q is the propeller frequency, q is the propeller blade frequency, n is the rotation speed of the propeller, and Z is the number of revolutions;

[0034] The radiation level of the propeller direct sound P Bq and its second and third tuning frequencies is calculated as follows:

[0035]

[0036] where F xq is the propeller blade frequency in the X direction, F xq is the propeller blade frequency in the Y direction, F xq is the propeller blade frequency in the Z direction, R1 is the maximum radius of the propeller, and P Bq is the propeller direct sound.

[0037] Further, the step 7 is:

[0038] Based on the energy superposition principle, the propeller noise considering the direct sound is obtained as follows:

[0039] P all = P(Q) + P Bq

[0040] ​​In the formula, P(Q) is the noise pressure generated by the propeller exciting the hull structure, P Bq is the direct radiation noise of the propeller.

[0041] A device for rapidly predicting underwater vehicle propeller noise based on excitation source reconstruction, comprising a data acquisition system and a prediction system;

[0042] The data acquisition system is used to send the collected data to the prediction system.

[0043] The prediction system is used to obtain the real-time propeller noise level and form a storage log.

[0044] A computer readable storage medium having stored thereon computer programs / instructions which, when executed by a processor, implement the steps of a method for rapidly predicting underwater vehicle propeller noise based on excitation source reconstruction.

[0045] A computer program product comprising computer programs / instructions which, when executed by a processor, implement the steps of a method for rapidly predicting underwater vehicle propeller noise based on excitation source reconstruction.

[0046] The beneficial effects of the present application are:

[0047] The method of the present application is based on the invariance of the vibration transfer function relationship and the basic theory of sound wave energy superposition principle, and introduces the vibration source reconstruction technology into the propeller noise prediction. The vibration response measured by a limited number of vibration sensors on the propeller stern structure is used as input, and the vibration transfer function is used to reconstruct the excitation source matching the structure surface vibration. The superposition of the reconstructed excitation source vibration exactly matches the measured structure vibration. By the reconstructed excitation source, the radiation noise caused by the structure vibration of the propeller shaft boat structure can be solved. A small number of monitoring sensors can be used to match the structure surface vibration in a wide frequency range, solving the problem of large number of sensors required. Considering the influence of coherence, a rapid prediction method for direct radiation noise of the propeller under different coherence is established. Based on the energy superposition principle, the rapid prediction and evaluation of the propeller noise including the propeller shaft coupling noise and the direct radiation noise of the propeller are realized.

[0048] Based on the above method, the present application also forms a set of rapid prediction device suitable for propeller stern structure vibration and propeller noise. The prediction device is composed of a prediction system and a data acquisition system. The data acquisition system is mainly composed of a signal acquisition system and a high-precision vibration acceleration sensor. The prediction system is composed of aluminum alloy material, and internally carries a signal acquisition channel, a signal source card, an industrial control mainboard and a storage hard disk.

[0049] The present application is suitable for real-time monitoring of propeller shaft vibration and radiation noise of a ship. Attached Figure Description

[0050] Figure 1 This is a schematic diagram of the calculation process of a thruster noise prediction method based on excitation source reconstruction in an embodiment of the present invention;

[0051] Figure 2 This is a schematic diagram illustrating the specific implementation of a thruster noise prediction method based on excitation source reconstruction in an embodiment of the present invention.

[0052] Figure 3 This is a schematic diagram of the noise assessment results of an underwater vehicle propulsion system implemented in an invention. Detailed Implementation

[0053] The present invention will now be further described with reference to the accompanying drawings.

[0054] Implementation method one, this implementation method is an example of a rapid prediction method for underwater vehicle thruster noise based on excitation source reconstruction, specifically including:

[0055] Figure 1 This is a flowchart of a thruster noise prediction method based on excitation source reconstruction, according to an embodiment of the present invention.

[0056] like Figure 1 As shown, the thruster noise prediction method based on excitation source reconstruction includes the following steps:

[0057] In step S1, for the noise caused by the thruster excitation of the stern structure, the location of the vibration sensing measurement point, the location of the reconstruction source, and the location of the sound field assessment point are first determined.

[0058] In step S101, for the propeller bearing force, the propeller shaft system and its supporting structure are the transmission path of the excitation force, and the hull is the sound radiator that ultimately generates radiated noise. Therefore, vibration sensing points are evenly distributed on the surface of the stern structure, and a limited-point vibration sensing arrangement scheme for the propeller is established based on gradually reducing the number of sensing points.

[0059] In step S102, acceleration sensors are deployed on the surface of the underwater vehicle's stern structure to measure the vehicle's vibration response at different speeds and rotational speeds. The vibration measurement points are numbered sequentially, i = 1: M, and the measured vibration acceleration is denoted as a. P (p j ,ω) are used as the data input for the forecasting system.

[0060] In step S103, in the coupling vibration and acoustic radiation problem of the propeller, the propeller shafting and the hull, the propeller bearing force is the excitation source of the radiation noise, the propeller shafting and its supporting structure are the transmission path of the excitation force, and the hull is the acoustic radiator that finally produces the radiation noise. Therefore, the stern bearing, the thrust bearing, the molded head and other positions are the main vibration sources, the vibration transfer function of the main vibration sources to the stern structure obtained through simulation calculation, and the inverse sensing network model is established based on the Bi-LSTM neural network. The vibration transmission relationship between the shafting vibration sensing point and the stern structure surface is established through the Bi-LSTM neural network, the computer is trained to realize the reconstruction of the stern structure vibration, so as to establish the number and position of the reconstruction source through machine learning, and the number of reconstruction sources is set as j, and numbered, j = 1:K.

[0061] In step S104, the size of the reconstructed excitation source is determined according to the following steps. The propeller structure is regarded as a linear system, and the acceleration a P (p j ,ω) of the excitation source p i j on the vibration transfer function structure of the reconstructed source to the surface of the ship structure is established. P i

[0062] A P (r i ,ω)=H vP (r i p j ,ω)*a P (p j ,ω)

[0063] H vP (r i p j ,ω) is the vibration mapping relationship matrix with a dimension of M*K between the excitation point p j and the measuring point r i of the stern structure.

[0064] Further, in actual engineering application, in order to meet the condition of unique solution, the generalized inverse matrix is introduced, and the excitation source vector is obtained:

[0065] a P (p j ,ω)=[[H vP (r i p j ,ω)] H [H vP (r i p j ,ω)]] -1 [H vP (r​​i p j ,ω)] H *A P (r i ,ω)

[0066] Based on the established vibration mapping relationship, the generalized inverse matrix is introduced to obtain the excitation source vector a P (p j ,ω), in order to obtain a P (p j ,ω) as accurately as possible, the number of shaft system measuring points i is kept greater than or equal to the number of main excitation sources, so as to avoid the occurrence of ill-conditioned equations, and the least square theory is introduced to obtain the optimal approximation solution of the system excitation source.

[0067] In step S105, according to actual needs, the positions of the sound pressure evaluation points are generally selected at the transverse and circumferential positions of the vehicle, the circumferential radius is set to 10 meters away from the outside of the hull, and the sound pressure evaluation points are arranged on the right side of the vehicle in the fore-and-aft direction.

[0068] In summary, for the coupling vibration and sound radiation problem of the propeller-propeller shaft-hull in step S1, the bearing force of the propeller is the excitation source of the radiation noise, the propeller shaft and its supporting structure are the transmission path of the excitation force, and the hull is the sound radiator that finally produces the radiation noise. Therefore, vibration sensors are uniformly arranged on the surface of the stern structure, vibration-vibration transfer functions from the main vibration source to the hull structure are obtained based on numerical simulation, an inverse sensing network model is established based on a Bi-LSTM neural network, the number and distribution of the excitation sources are reconstructed through machine learning, and the reconstruction source model is established.

[0069] In step S2, vibration-vibration transfer functions from the reconstruction source to the monitoring points of the stern structure are obtained through simulation calculation.

[0070] In step S201, an underwater vehicle propeller-shaft-stern (i.e., including a propeller, a propeller shaft and a hull stern) structure geometric model is established according to preset drawing data, the underwater vehicle propeller-shaft-stern structure geometric model is placed in a fluid domain, and a fluid domain grid model and a structure finite element model are respectively established according to the underwater vehicle propeller-shaft-stern structure geometric model. It should be noted that the distance between the inlet of the fluid domain and the bow of the underwater vehicle propeller-shaft-stern structure geometric model is greater than 6L, the distance between the outlet of the fluid domain and the stern of the underwater vehicle propeller-shaft-stern structure geometric model is greater than 10L, and the distance between the remaining boundaries of the fluid domain and the underwater vehicle geometric model is greater than 3L, wherein L is the total length of the underwater vehicle propeller-shaft-stern structure.

[0071] In step S202, the monitoring points are uniformly arranged on the model stern structure, the vibration response of each vibration sensing point is obtained by applying a unit force at the reconstructed source position established in S1, and the vibration response is the vibration-to-vibration transfer function from the reconstructed source to each monitoring point of the stern structure since the unit force is applied, and the monitoring points are sequentially numbered.

[0072] In step S3, the sound-to-vibration transfer function from the reconstructed source to the sound field evaluation point is obtained based on the acoustic finite element method.

[0073] Specifically, the sound field evaluation points are established according to S1, the sound field evaluation points are arranged in the model flow field, the sound pressure at the sound field evaluation points is obtained based on the acoustic finite element method by applying a unit force at the reconstructed source position, and the sound pressure at the evaluation points is the sound-to-vibration transfer function from the reconstructed source to the sound field evaluation points since the unit force is applied.

[0074] In step S4, the sound field reconstruction model based on the reconstructed source is established based on the transfer function invariance.

[0075] In step S401, according to the acoustic principle of the underwater vehicle, the relationship between the vibration velocity of the propeller main body surface and the radiated sound power is as follows:

[0076]

[0077] In the formula, W rad is the sound power radiated by the propeller, pc is the acoustic impedance of the propeller structure, S is the underwater radiation surface area of the structure, i.e., the wet surface area of the propeller; σ ra d is the radiation efficiency of the underwater vehicle; is the root mean square vibration velocity of the wet surface area of the propeller, and the reconstructed vibration response A p (r i ,ω) is converted to realize the reconstruction of the root mean square vibration velocity of the main body structure of the propeller.

[0078] In S402, the relationship between the reconstructed excitation source F and the root mean square vibration velocity of the outer surface of the main body is as follows:

[0079]

[0080] Substituting formula (1) into formula (2) above, we have:

[0081]

[0082] In the formula, H is the vibration-to-vibration transfer function from the reconstructed source to the outer surface of the main body, and a is the excitation size of the reconstructed source.

[0083] In step S403, the radiated sound power calculation formula is converted into a sound pressure calculation formula, the relationship between the sound pressure and the transfer function is established, and a radiated sound pressure calculation formula of the propeller excited stern structure is obtained.

[0084] P(Q) = H1 pa |a1| + H2 pa |a2| +... H j pa |a P (p j ,ω)|

[0085] wherein P(Q) is the noise sound pressure generated by the propeller excited ship structure, H j pa is the sound vibration transfer function from the coded reconstruction source to the sound field evaluation point.

[0086] Thus, the sound field reconstruction model based on the reconstruction source is established.

[0087] In step S4, the propeller-shaft-stern structure sound vibration prediction model is established according to a series of drawings such as the type value table, general arrangement drawing, propeller model drawing and weight distribution of the specific ship, the unit vibration acceleration data is directly loaded at the reconstruction excitation source measurement point position, the propeller-shaft-ship underwater evaluation point sound pressure is calculated through numerical simulation, the ship sound vibration transfer function is directly obtained, and these sound vibration transfer functions are stored in the computer storage module in the form of a matrix; based on the invariability of the sound vibration transfer function, the numerical solution of the reconstruction excitation source is multiplied by the sound vibration transfer function, so that the sound field sound pressure to be analyzed can be quickly obtained. As long as the structure model is unchanged, the pre-stored sound vibration transfer function will not be invalid, which has important application value in engineering and to some extent solves the problem of online monitoring of the propeller-shaft-ship vibration acceleration data of the specific ship and online prediction of the propeller-shaft-ship underwater radiated sound field.

[0088] In step S5, the response at the actual shell vibration measurement point is taken as the input, the vibration vibration transfer function from the reconstruction source to the main body outer surface is used to determine the excitation size of the reconstruction source. The vibration response of the propeller excited stern structure is calculated, and the noise of the propeller excited stern structure is calculated.

[0089] In step S6, a propeller direct radiation sound calculation model is established, and the propeller direct radiation sound noise is obtained according to the speed and rotational speed.

[0090] The propeller noise mainly includes propeller rotating noise and cavitation noise. The rotating noise is the noise caused by the propeller running in the non-uniform flow field (the frequency of which is mainly determined by the blade frequency). Once the shaft system reaches the cavitation critical speed, the propeller noise becomes the main noise source of the underwater vehicle. The characteristics of the cavitation noise are related to factors such as the shape, area and pitch distribution of the blade. At a certain speed, the vortex frequency generated by the propeller blade is close to the natural frequency of the blade, and the blade will produce a blade singing.

[0091] Specifically, the rotating speed of the propeller of the underwater vehicle is determined;

[0092]

[0093] In the formula, n max is the maximum rotating speed of the propeller, v is the linear speed of the propeller, v max is the maximum linear speed of the propeller

[0094] Z is the number of revolutions, f q of the propeller blade frequency (q = 1) and the second (q = 2) and third (q = 3) tuning frequency values thereof are calculated as follows:

[0095] f q = qnZ, Hz, q = 1, 2, 3

[0096] The sound radiation level P Bq of the blade frequency and the radiation levels of the second and third tuning frequencies are calculated as follows:

[0097]

[0098] In the formula, F iq is the propeller blade frequency in three directions, and R1 is the maximum radius of the propeller.

[0099] In step S7, the noise of the propeller exciting the stern structure and the direct sound are energy superimposed, and the propeller noise calculation is completed.

[0100] Based on the energy superposition principle, the propeller noise considering the direct sound is obtained as follows.

[0101] P all = P(Q) + P Bq .

[0102] In step S7, based on the superposition principle of sound waves, the phase relationship between the two columns of waves is ignored and only the sound wave amplitude is superimposed, a non-coherent sound wave superposition result, i.e. the energy superposition result of the sound wave, is given, and the propeller noise considering the direct sound is obtained, as shown in Figure 2 .

[0103] Embodiment two, the embodiment is based on the above-mentioned method of a kind of underwater vehicle propeller noise quick prediction method based on excitation source reconstruction, the embodiment based on above-mentioned method has formed a set of propeller stern structure vibration and propeller noise quick prediction device suitable for, specifically includes:

[0104] The quick prediction device is composed of data acquisition system and prediction system.

[0105] The data acquisition system is mainly composed of signal acquisition system and high-precision vibration acceleration sensor. The signal acquisition system will transmit the collected vibration signal into the prediction system through optical fiber. Specifically, the measurement signal acquisition of data acquisition system and prediction system adopts the following way: acceleration sensor is first connected to adaptive amplifier, and the measurement signal is transmitted to the acquisition control end of prediction system through multi-channel signal acquisition system.

[0106] The prediction system is composed of aluminum alloy material, and is internally equipped with signal acquisition channel, signal source card, industrial control mainboard and storage hard disk. Specifically, the industrial control mainboard internally stores the data of reconstruction source size, distribution and sound vibration transfer function between sound pressure test points, the vibration data obtained by signal acquisition system is input into prediction system through signal acquisition channel, and the real-time propeller noise level can be obtained by one key through the propeller noise quick prediction module of prediction system, and storage log is formed.

[0107] As shown in Figure 3 The propeller noise calculated by the present application and the simulation calculation result keep good consistency in trend and peak value, which verifies the feasibility of the present application.

[0108] The above only describes the preferred embodiments of the present application and is not used to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for fast prediction of underwater vehicle propeller noise based on reconstruction of excitation sources, characterized by: The method comprises the following steps: Step 1: determining the positions of vibration sensing points, the positions of reconstructed sources and the positions of sound field evaluation points for noise caused by propeller excitation of the stern structure; A vibration transmission relationship between the vibration sensing point positions of the shafting and the surface of the stern shell is established through a Bi-LSTM neural network to realize vibration reconstruction of the stern structure, and the number, position and size of the reconstructed excitation sources are determined; The size of the reconstructed excitation source is specifically: Treating the thruster structure as a linear system, a reconfiguration excitation source is established. The activation vector is Measuring points on the stern structure Vibration acceleration response The interrelationship between them; ； wherein, to reconstruct the excitation source and stern structure measurement points between the dimensions of vibration mapping relationship matrix; The excitation source vector is obtained by introducing a generalized inverse matrix: ； Step 2: obtaining the vibration transmission function from the reconstructed source to the monitoring point positions of the stern structure through simulation calculation according to the positions of the vibration sensing points and the positions of the reconstructed sources obtained in Step 1; Step 3: obtaining the vibro-acoustic transmission function from the reconstructed source to the sound field evaluation points based on the acoustic finite element method according to the positions of the sound field evaluation points obtained in Step 1; Step 4: establishing a sound field reconstruction model based on the reconstructed source based on the transmission functions obtained in Steps 2 and 3 and the invariance of the transmission function; Step 5: calculating the excitation size of the reconstructed source based on the vibration transmission function from the reconstructed source to the surface of the main body and obtaining the vibration response of the propeller excitation of the stern structure and the noise of the propeller excitation of the stern structure through the measured response of the actual shell vibration sensing points; Step 6: establishing a propeller direct radiation sound calculation model to obtain the propeller direct radiation sound noise according to the speed and rotational speed; Step 7: superimposing the noise of the propeller excitation of the stern structure obtained in Step 5 and the direct radiation sound noise obtained in Step 6 to complete the calculation of the propeller noise.

2. The method of claim 1, wherein: In Step 2, an underwater vehicle geometric model is established, which includes a propeller, a propeller shaft and a ship stern structure; the underwater vehicle geometric model is placed in a fluid domain, and a fluid domain grid model and a structure finite element model are respectively established according to the underwater vehicle geometric model; According to the positions of the reconstructed sources and the vibration sensing points established in Step 1, monitoring points are uniformly arranged on the stern structure of the ship body, and the vibration response of each vibration sensing point is obtained by applying a unit force at the position of the reconstructed source, which is the vibration transmission function from the reconstructed source to each monitoring point of the stern structure.

3. The method of claim 1, wherein: In Step 3, the sound field evaluation points are set in the model flow field according to the sound field evaluation points established in Step 1, and the sound pressure at the sound field evaluation points is obtained based on the acoustic finite element method by applying a unit force at the position of the reconstructed source, which is the vibro-acoustic transmission function from the reconstructed source to the sound field evaluation points.

4. The method of claim 1, wherein: In Step 4, the radiation sound power calculation formula is converted into a sound pressure calculation formula to establish the relationship between the sound pressure and the transmission function, and the radiation sound pressure calculation formula under the propeller excitation of the stern structure is obtained: ； wherein, P is the sound pressure of the noise generated by the propulsion excited ship structure, is the sound vibration transfer function of the coded reconstruction source to the sound field evaluation point, thereby establishing a sound field reconstruction model based on the reconstruction source; is the excitation source vector.

5. The method of claim 1, wherein: In Step 6: The rotational speed of the propeller of the underwater vehicle is determined; ； wherein is the maximum rotational speed of the propeller, is the linear speed of the propeller, is the maximum linear speed of the propeller; The frequency q of the propeller blades The value and its second and third tuning frequencies are calculated using the following formula: ； wherein wherein f is the propeller frequency, q is the propeller blade frequency, n is the rotational speed of the propeller, and Z is the number of revolutions. Propeller directivity and the second and third tuning frequencies of the radiator are calculated as follows: ； wherein is the propeller blade frequency in the X direction, is the propeller blade frequency in the Y direction, is the propeller blade frequency in the Z direction, is the maximum radius of the propeller, is the propeller directivity.

6. The method of claim 1, wherein: In Step 7: Based on the energy superposition principle, the propeller noise considering direct radiation sound is obtained as follows: ； wherein P is the sound pressure of the noise generated by the propulsion excited hull structure, P is the sound pressure of the noise generated by the propulsion excited hull structure, 7. An apparatus for performing a quick prediction method of noise of a propeller of an underwater vehicle based on reconstruction of an excitation source according to any one of claims 1 to 6, characterized in that: The data acquisition system is used to send the collected data to the prediction system; The prediction system is used to obtain the real-time propeller noise level and form a storage log. The computer program / instructions are executed by the processor to realize the steps of the method in any one of claims 1 to 6.

8. A computer readable storage medium having stored thereon computer programs / instructions, characterized in that: ​ 9. A computer program product comprising computer programs / instructions, characterized in that: The computer program / instructions, when executed by the processor, implement the steps of the method of any one of claims 1 to 6.

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