Method for constructing aerodynamic noise prediction model of rotor aircraft in unsteady transient maneuvering state

Abstract

The invention discloses an aerodynamic noise prediction model construction method of an unsteady transient maneuvering state rotor aircraft, and belongs to the technical field of aircraft noise prediction. The problem that in the prior art, a traditional aircraft noise prediction method is difficult to achieve instantaneous efficient aerodynamic noise prediction under the maneuvering state of a rotor type aircraft is solved. The method comprises the following steps: constructing a six-degree-of-freedom linearization equation of the Updating the manipulated variable and state variable of the rotor aircraft based on a trajectory tracking control law, and outputting a maneuvering flight simulation data file; the sound pressure contribution of each sound source infinitesimal to a far-field observation point is calculated based on a Farassat 1A formula, time dimension interpolation is carried out on the far-field observation point at the observation time, integral summation is carried out on the infinitesimal sound pressure contribution at the same observation time to obtain sound pressure time calendar data of the observation point, discrete Fourier transform is carried out on the sound pressure time calendar data, and the noise characteristics of the maneuvering-state rotorcraft are obtained through analysis. The method improves the calculation efficiency of calculating the infinitesimal sound pressure contribution at the observation point time, and can be used for predicting the instantaneous noise of the aircraft.

Description

Technical Field

[0001] The present invention relates to a method for constructing an aerodynamic noise prediction model, in particular to a method for constructing an aerodynamic noise prediction model for a rotorcraft in an unsteady transient maneuvering state, and belongs to the technical field of aircraft noise prediction. Background Art

[0002] Rotorcraft play a unique role in both civil and military fields with their advantages such as vertical take-off and landing, hovering, and good low-altitude and low-speed performance. However, noise pollution from eVTOL (electric Vertical Take-off and Landing) aircraft can affect the living comfort of ground personnel. Helicopters' noise problems can expose their targets prematurely, endangering their own safety and causing mission failure. Therefore, research on rotorcraft noise prediction technology is of great significance.

[0003] Maneuvering flight is crucial for rotorcraft to perform their missions. Under unsteady transient maneuvering flight, operations such as acceleration and deceleration, turning, climbing and descending of rotorcraft will cause the directionality and amplitude of noise to change significantly over time. In addition, due to the influence of kinematics and aerodynamics, the maneuvering state will cause a significant increase in noise.

[0004] In summary, there is a need for a method to construct an aerodynamic noise prediction model for rotorcraft in unsteady transient maneuvering states. Summary of the Invention

[0005] A brief overview of the present invention is provided below to provide a basic understanding of certain aspects of the present invention. It should be understood that this overview is not an exhaustive overview of the present invention. It is not intended to identify key or important aspects of the present invention, nor is it intended to limit the scope of the present invention. Its purpose is simply to present certain concepts in a simplified form as a prelude to the more detailed description discussed later.

[0006] In view of this, in order to solve the problem that traditional aircraft noise prediction methods in the prior art are difficult to achieve instantaneous and efficient aerodynamic noise prediction of rotorcraft in maneuvering states, the present invention provides a method for constructing an aerodynamic noise prediction model for rotorcraft in unsteady transient maneuvering states.

[0007] The technical solution is as follows: A method for constructing an aerodynamic noise prediction model for a rotorcraft in an unsteady transient maneuvering state includes the following steps:

[0008] S1. Obtain flight instruction files, rotorcraft parameter files, and aerodynamic data files, and integrate them into model input files;

[0009] S2. Establish a flight dynamics model for the rotorcraft based on the model input file, i.e., construct a six-degree-of-freedom linear model of the aircraft.

[0010] S3. Based on the six-degree-of-freedom linearized model of the body, solve the approximate inverse of the control loop to update the control variables and state variables of the rotorcraft based on the trajectory tracking control law, and obtain the updated six-degree-of-freedom linearized model of the body;

[0011] S4. Outputting the maneuver flight simulation data file using the updated six-degree-of-freedom linearized model of the airframe, which includes rotor control variables, airframe response data, rotor motion data, and blade load data;

[0012] S5. The output maneuver flight simulation data file, the obtained noise calculation parameter file and the blade geometry information file are passed as input to the noise calculation model;

[0013] S6. Based on the blade geometry information file, for each sound source moment, loop through each rotor blade sound source element and sequentially calculate the sound source element position, velocity, acceleration, and observation point time in the geodetic coordinate system;

[0014] S7. Calculate the position, velocity, acceleration, and observation time of the sound source element based on the Farassat 1A formula, and obtain the contribution of each sound source element to the sound pressure at the far-field observation point.

[0015] S8. interpolate the sound pressure of each sound source element in the time dimension at the observation time, sum the integrals of the sound pressure contributions of the sound source elements at the same observation time, and obtain the time history data of the sound pressure at the observation point;

[0016] S9. Perform discrete Fourier transform on the sound pressure time history data of each observation point to calculate the sound pressure spectrum curve and total sound pressure level, thereby analyzing the noise characteristics of the rotorcraft in the maneuvering state.

[0017] Furthermore, in S2, an aerodynamic model is established for each component of the rotorcraft, wherein the aerodynamic forces / torques of the fuselage and tail are calculated using aerodynamic data obtained from wind tunnel tests, and the aerodynamic forces / torques of the rotor / tail rotor are solved by coupling the Pitt-Peters dynamic inflow model, the Leishman-Beddoes airfoil unsteady aerodynamic model, and the blade flapping motion model, ultimately obtaining the forces and moments of each component acting on the center of gravity of the rotorcraft, namely, the first centroid force X, the second centroid force Y, the third centroid force Z, the first moment L, the second moment M, and the third moment N;

[0018] When the rotorcraft is an ideal rigid body, the motion equation of the body is the Euler equation including three linear motion degrees of freedom and three angular motion degrees of freedom, and a six-degree-of-freedom linear model of the body is established;

[0019] The six-degree-of-freedom linear model of the body is expressed as:

[0020]

[0021] Among them, I xx , I yy , I zz is the moment of inertia of the rotorcraft about the body axis, I xy , I yz , I xz is the product of inertia, p f ,q f 、r f is the attitude angular velocity, u f 、v f 、w f is the linear velocity, θ f 、φ f , ψ f is the attitude angle, m G is the mass of the rotorcraft, g is the acceleration due to gravity;

[0022] According to the rotor MR, fuselage F, horizontal tail H, vertical tail H and tail rotor TR, the six-degree-of-freedom linear model of the fuselage is expressed as:

[0023]

[0024] In addition, the kinematic equations between the attitude angle and angular velocity of the rotorcraft are satisfied, namely, equations (3)-(5);

[0025] The kinematic equation is expressed as:

[0026]

[0027] Furthermore, in S3, based on the six-degree-of-freedom linear model of the body, the nonlinear model of the rotorcraft in any flight state is expressed as:

[0028]

[0029] in, is the derivative of the state quantity, A is the aerodynamic derivative, B is the control derivative, y is the rotorcraft state quantity, and u is the control input quantity;

[0030] Under different state variables, the nonlinear model of the rotorcraft is linearized, and the approximate inverse of the control loop is obtained using the obtained linearized model of the rotorcraft;

[0031] The linearized model of the rotorcraft is expressed as:

[0032]

[0033] The control loop includes a six-degree-of-freedom linear model of the body, a fast loop inversion, a slower loop inversion and a slow loop inversion connected in sequence;

[0034] The six-degree-of-freedom linear model of the fuselage is an under-input system, whose input is the four helicopter control variables, namely the lateral periodic pitch δ e 、Longitudinal periodic pitch δ a , tail rotor pitch δ r and rotor pitch δ c The output is 9 helicopter state quantities, namely the speed of the body in three directions: u f 、v f 、w f , attitude angles in three directions: φ f ,θ f , ψ f , angular velocity in three directions: p f ,q f 、r f ;

[0035] The inverse input of the fast loop is the attitude angular velocity in three directions and the vertical velocity w of the body c , the output is the desired angular acceleration and the control amount when the desired angular acceleration is generated: δ e , δ a , δ r , δ c ;

[0036] The inverse input of the slower loop is the attitude angle in three directions: φ c ,θ c , ψ c , the output is the desired angular velocity: p c ,q c 、r c ;

[0037] The inverse input of the slow loop is the horizontal speed of the two bodies: u c 、v c , the output is the desired acceleration and desired attitude angle: φ c ,θ c ;

[0038] According to the principle of time scale separation, the control loop is divided into several subsystems with different time scales according to the speed of the rotorcraft state change. The angular velocity and the vertical velocity of the body are directly related to the control input. The angular velocity and the vertical velocity of the body are fast variables. The attitude angle is the first-order integral of the attitude angular velocity and is a slower variable. The horizontal velocity response under the body axis is related to the net external force and is a slow variable.

[0039] During trajectory tracking, the desired speed and heading angle are given by the read-in flight instructions, which are input into the control loop to complete trajectory tracking.

[0040] Furthermore, in said S6, the blade is segmented along the chord direction and the span direction, the area and normal vector of each element are calculated, and for each sound source moment, the coordinate transformation matrix, the transformation matrix derivative and the second-order derivative from the blade coordinate system to the earth coordinate system are solved, wherein the coordinate transformation between the earth coordinate system and the blade coordinate system involves the yaw, pitch, roll, longitudinal tilt of the rotation axis, the lateral tilt of the rotation axis, and the coordinate transformation between multiple coordinates caused by the rotation, flapping, shimmy and pitch variation of each rotor blade. According to the coordinates of the blade element in the blade fixed coordinate system, the coordinate transformation matrix and its derivative and second-order derivative are substituted, and combined with the body response data of the center of gravity position of the rotorcraft, the coordinate position, velocity and acceleration of the blade element in the earth coordinate system at each sound source moment are obtained;

[0041] Specifically: Substitute the sound source time τ and the infinitesimal position y(τ) into the delay time equation to obtain the observation point time t when the sound emitted by the sound source at the infinitesimal position y(τ) reaches the far-field observation point x;

[0042] The delay time equation is expressed as:

[0043] τ=t-|xy(τ)| / c (8)

[0044] Where c is the speed of sound.

[0045] Furthermore, in S7, the contribution of each sound source element to the sound pressure of the far-field observation point x is calculated using the Farassat1A formula;

[0046] The Farassat 1A formula is expressed as:

[0047] p'(x,t)=p' T (x,t)+p' L (x,t) (9)

[0048]

[0049]

[0050] Where p' is the disturbance sound pressure, p' T is the disturbance sound pressure of thickness noise, p' L is the disturbance sound pressure of the load noise, f(x,t)=0 represents the rotor blade surface, dS is the blade infinitesimal area, ρ0 represents the density in the undisturbed medium, v n =v i n i is the normal motion velocity of the blade surface, is the projection of the velocity derivative in the normal direction, is the dot product of the velocity and the normal vector derivative, r=|r i| is the distance between the sound source element and the observation point, M=|M i | is the Mach number of the infinitesimal motion, is the component of the infinitesimal motion Mach number in the noise propagation direction, The unit vector representing the direction of noise propagation, represents the component of blade surface load in the noise propagation direction, and M r and l r With respect to the time derivative, the subscript ret indicates that the integrand takes the value at the time of emission of the sound source.

[0051] The beneficial effects of the present invention are as follows: the method proposed in the present invention adopts a trajectory tracking control loop based on dynamic inversion to control the rotorcraft to move according to a predetermined maneuvering flight trajectory, which is more in line with actual flight conditions. In the process of calculating maneuvering noise, the influence of the pitch, yaw and roll motion responses of the aircraft body is taken into account, and the characteristics of unsteady transient maneuvering noise can be more clearly reflected; the method proposed in the present invention calculates the contribution of the blade sound source microelement to the sound pressure of the observation point at the sound source time. Compared with the traditional delay time algorithm for calculating the microelement sound pressure contribution at the observation point time, the number of coordinate conversions between the blade coordinate system and the earth coordinate system required is greatly reduced, and the calculation efficiency is higher. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0053] Figure 1 A flowchart of a method for constructing an aerodynamic noise prediction model for rotorcraft in unsteady transient maneuvering conditions;

[0054] Figure 2 A schematic flow chart of an embodiment of a method for constructing an aerodynamic noise prediction model for a rotorcraft in an unsteady transient maneuvering state;

[0055] Figure 3 This is a structural diagram of the dynamic inverse control loop. DETAILED DESCRIPTION

[0056] To make the technical solutions and advantages of the embodiments of the present invention more clearly understood, exemplary embodiments of the present invention are further described in detail below with reference to the accompanying drawings. It should be noted that the embodiments described are only a portion of the embodiments of the present invention, and are not an exhaustive list of all embodiments. It should be noted that the embodiments of the present invention and the features thereof may be combined with each other unless they conflict.

[0057] refer to Figure 1-Figure 3The present embodiment is described in detail. The method for constructing an aerodynamic noise prediction model for a rotorcraft in an unsteady transient maneuvering state specifically includes the following steps:

[0058] S1. Obtain flight instruction files, rotorcraft parameter files, and aerodynamic data files, and integrate them into model input files;

[0059] S2. Establish a flight dynamics model for the rotorcraft based on the model input file, i.e., construct a six-degree-of-freedom linear model of the aircraft.

[0060] S3. Based on the six-degree-of-freedom linearized model of the body, solve the approximate inverse of the control loop to update the control variables and state variables of the rotorcraft based on the trajectory tracking control law, and obtain the updated six-degree-of-freedom linearized model of the body;

[0061] S4. Outputting the maneuver flight simulation data file using the updated six-degree-of-freedom linearized model of the airframe, which includes rotor control variables, airframe response data, rotor motion data, and blade load data;

[0062] S5. The output maneuver flight simulation data file, the obtained noise calculation parameter file and the blade geometry information file are passed as input to the noise calculation model;

[0063] S6. Based on the blade geometry information file, for each sound source moment, loop through each rotor blade sound source element and sequentially calculate the sound source element position, velocity, acceleration, and observation point time in the geodetic coordinate system;

[0064] S7. Calculate the position, velocity, acceleration, and observation time of the sound source element based on the Farassat 1A formula, and obtain the contribution of each sound source element to the sound pressure at the far-field observation point.

[0065] S8. interpolate the sound pressure of each sound source element in the time dimension at the observation time, sum the integrals of the sound pressure contributions of the sound source elements at the same observation time, and obtain the time history data of the sound pressure at the observation point;

[0066] S9. Performing a discrete Fourier transform on the sound pressure time history data at each observation point to calculate the sound pressure spectrum curve and total sound pressure level, thereby analyzing the noise characteristics of the rotorcraft in the maneuvering state;

[0067] Specifically, in S1, the flight instruction file includes the change history of the aircraft's longitudinal speed, lateral speed, vertical speed / flight altitude, and heading angle over time;

[0068] The rotorcraft parameter file includes rotorcraft weight parameters (mass, center position, body moment of inertia), rotor design parameters (number of blades, rotor radius, rotor steering, rotor blade flapping moment of inertia, flapping hinge stiffness, blade pre-taper angle, rotor hub center position, rotor shaft forward tilt angle, advance control angle), fuselage parameters (aerodynamic reference area, longitudinal aerodynamic reference length, lateral aerodynamic reference length, fuselage aerodynamic action point position), horizontal tail parameters (horizontal tail aerodynamic action point position, horizontal tail position, aerodynamic reference area), vertical tail parameters (vertical tail aerodynamic action point position, vertical tail position, vertical tail mounting angle, aerodynamic reference area, aerodynamic reference length) and tail rotor parameters (number of tail rotor blades, tail rotor radius, tail rotor design speed, tail rotor steering, tail rotor hub center position, tail rotor shaft tilt angle);

[0069] The aerodynamic data files include rotor blade aerodynamic data, tail rotor blade aerodynamic data, fuselage aerodynamic data, horizontal tail aerodynamic data and vertical tail aerodynamic data;

[0070] In said S4, the rotor control variable includes the time history variation data of the lateral cyclic pitch, the longitudinal cyclic pitch, the tail rotor pitch and the rotor collective pitch;

[0071] The airframe response data includes the longitudinal position, lateral position, vertical position, roll angle, pitch angle, heading angle and their derivatives and second-order derivatives;

[0072] The rotor motion data includes the time history changes of the azimuth angle, flapping angle, swing angle and pitch angle of each rotor blade;

[0073] The blade load file includes the time-varying data of Mach number, lift coefficient and drag coefficient of each spanwise micro-segment of each blade of the rotor;

[0074] In the above S5, steps S1-S4 realize the simulation of the unsteady transient maneuvering state of the rotorcraft, and the output maneuvering flight simulation data will be passed as an input file to the noise calculation model. In addition, the noise calculation also needs to read the noise calculation parameter file (fluid density, far-field sound speed, incoming flow velocity, number of observation points, observation point locations, output file identifier, etc.) and the blade geometry information file (airfoil, number of blade chord-wise / span-wise segments, blade planform, blade sweep information, etc.);

[0075] In the above S8, through step S7, the time series of the contribution of each sound source element to the sound pressure at the observation point with respect to the sound source emission moment is obtained. Since at the same sound source emission moment, different sound source elements on the blade arrive at the observation point at different times, the sound pressure time history of each sound source element must be interpolated at the observation time so that the contribution of each sound source element can be summed at the relevant observation point time.

[0076] Furthermore, in S2, an aerodynamic model is established for each component of the rotorcraft, wherein the aerodynamic forces / torques of the fuselage and tail are calculated using aerodynamic data obtained from wind tunnel tests, and the aerodynamic forces / torques of the rotor / tail rotor are solved by coupling the Pitt-Peters dynamic inflow model, the Leishman-Beddoes airfoil unsteady aerodynamic model, and the blade flapping motion model, ultimately obtaining the forces and moments of each component acting on the center of gravity of the rotorcraft, namely, the first centroid force X, the second centroid force Y, the third centroid force Z, the first moment L, the second moment M, and the third moment N;

[0077] When the rotorcraft is an ideal rigid body, the motion equation of the body is the Euler equation including three linear motion degrees of freedom and three angular motion degrees of freedom, and a six-degree-of-freedom linear model of the body is established;

[0078] The six-degree-of-freedom linear model of the body is expressed as:

[0079]

[0080] Among them, I xx , I yy , I zz is the moment of inertia of the rotorcraft about the body axis, I xy , I yz , I xz is the product of inertia, p f ,q f 、r f is the attitude angular velocity, u f 、v f 、w f is the linear velocity, θ f 、φ f , ψ f is the attitude angle, m G is the mass of the rotorcraft, g is the acceleration due to gravity;

[0081] According to the rotor MR, fuselage F, horizontal tail H, vertical tail H and tail rotor TR, the six-degree-of-freedom linear model of the fuselage is expressed as:

[0082]

[0083] In addition, the kinematic equations between the attitude angle and angular velocity of the rotorcraft are satisfied, namely, equations (3)-(5);

[0084] The kinematic equation is expressed as:

[0085]

[0086] Furthermore, in S3, based on the six-degree-of-freedom linear model of the body, the nonlinear model of the rotorcraft in any flight state is expressed as:

[0087]

[0088] in, is the derivative of the state quantity, It is caused by the superposition of state variables and control variables, corresponding to acceleration, angular acceleration, and attitude angular rate. A is the aerodynamic derivative, B is the control derivative, y is the rotorcraft state variable, and u is the control input.

[0089] Under different state variables, the nonlinear model of the rotorcraft is linearized, and the approximate inverse of the control loop is obtained using the obtained linearized model of the rotorcraft;

[0090] The linearized model of the rotorcraft is expressed as:

[0091]

[0092] The control loop includes a six-degree-of-freedom linear model of the body, a fast loop inversion, a slower loop inversion and a slow loop inversion connected in sequence;

[0093] The six-degree-of-freedom linear model of the fuselage is an under-input system, whose input is the four helicopter control variables, namely the lateral periodic pitch δ e 、Longitudinal periodic pitch δ a , tail rotor pitch δ r and rotor pitch δ c The output is 9 helicopter state quantities, namely the speed of the body in three directions: u f 、v f 、w f , attitude angles in three directions: φ f ,θ f , ψ f , angular velocity in three directions: p f ,q f 、r f ;

[0094] The inverse input of the fast loop is the attitude angular velocity in three directions and the vertical velocity w of the body c , the output is the desired angular acceleration and the control amount when the desired angular acceleration is generated: δ e , δ a , δ r , δ c ;

[0095] The inverse input of the slower loop is the attitude angle in three directions: φ c ,θ c , ψ c , the output is the desired angular velocity: p c ,q c 、r c ;

[0096] The inverse input of the slow loop is the horizontal speed of the two bodies: u c 、v c , the output is the desired acceleration and desired attitude angle: φ c ,θ c ;

[0097] According to the principle of time scale separation, the control loop is divided into several subsystems with different time scales according to the speed of the rotorcraft state change. The angular velocity and the vertical velocity of the body are directly related to the control input and have the fastest response. Therefore, the angular velocity and the vertical velocity of the body are fast variables. The attitude angle is the first-order integral of the attitude angular velocity and has a slower response. The attitude angle is a slower variable. The horizontal velocity response under the body axis is related to the net external force and is a slow variable.

[0098] During trajectory tracking, the desired speed and heading angle are given by the read-in flight instructions, which are input into the control loop to complete trajectory tracking.

[0099] Specifically, refer to Figure 3 In the dynamic inverse control loop, the subscript c represents the input quantity.

[0100] Furthermore, in said S6, the blade is segmented along the chord direction and the span direction, the area and normal vector of each element are calculated, and for each sound source moment, the coordinate transformation matrix, the transformation matrix derivative and the second-order derivative from the blade coordinate system to the earth coordinate system are solved, wherein the coordinate transformation between the earth coordinate system and the blade coordinate system involves the yaw, pitch, roll, longitudinal tilt of the rotation axis, the lateral tilt of the rotation axis, and the coordinate transformation between multiple coordinates caused by the rotation, flapping, shimmy and pitch variation of each rotor blade. According to the coordinates of the blade element in the blade fixed coordinate system, the coordinate transformation matrix and its derivative and second-order derivative are substituted, and combined with the body response data of the center of gravity position of the rotorcraft, the coordinate position, velocity and acceleration of the blade element in the earth coordinate system at each sound source moment are obtained;

[0101] Specifically: Substitute the sound source time τ and the infinitesimal position y(τ) into the delay time equation to obtain the observation point time t when the sound emitted by the sound source at the infinitesimal position y(τ) reaches the far-field observation point x;

[0102] The delay time equation is expressed as:

[0103] τ=t-|xy(τ)| / c (8)

[0104] Where c is the speed of sound.

[0105] Furthermore, in S7, the contribution of each sound source element to the sound pressure of the far-field observation point x is calculated using the Farassat1A formula;

[0106] The Farassat 1A formula is expressed as:

[0107] p'(x,t)=p' T (x,t)+p' L (x,t) (9)

[0108]

[0109] Where p' is the disturbance sound pressure, p' T is the disturbance sound pressure of thickness noise, p' L is the disturbance sound pressure of the load noise, f(x,t)=0 represents the rotor blade surface, dS is the blade infinitesimal area, ρ0 represents the density in the undisturbed medium, v n =v i n i is the normal motion velocity of the blade surface, is the projection of the velocity derivative in the normal direction, is the dot product of the velocity and the normal vector derivative, r=|r i | is the distance between the sound source element and the observation point, M=|M i | is the Mach number of the infinitesimal motion, is the component of the infinitesimal motion Mach number in the noise propagation direction, The unit vector representing the direction of noise propagation, represents the component of blade surface load in the noise propagation direction, and M r and l r With respect to the time derivative, the subscript ret indicates that the integrand takes the value at the time of emission of the sound source.

[0110] Although the present invention has been described with respect to a limited number of embodiments, it will be apparent to those skilled in the art, having benefit of the foregoing description, that other embodiments are contemplated within the scope of the invention thus described. Furthermore, it should be noted that the language used in this specification has been selected primarily for readability and didactic purposes, rather than for the purpose of explaining or limiting the subject matter of the present invention. Consequently, many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the appended claims. The disclosure of the present invention is intended to be illustrative rather than restrictive of the scope of the invention, which is defined by the appended claims.

Claims

1. A method for constructing an aerodynamic noise prediction model for a rotorcraft in an unsteady transient maneuvering state, characterized in that: The following steps are involved: S1. Obtain flight instruction files, rotorcraft parameter files, and aerodynamic data files, and integrate them into model input files; S2. Establish a flight dynamics model for the rotorcraft based on the model input file, i.e., construct a six-degree-of-freedom linear model of the aircraft. S3. Based on the six-degree-of-freedom linearized model of the body, solve the approximate inverse of the control loop to update the control variables and state variables of the rotorcraft based on the trajectory tracking control law, and obtain the updated six-degree-of-freedom linearized model of the body; S4. Outputting the maneuver flight simulation data file using the updated six-degree-of-freedom linearized model of the airframe, which includes rotor control variables, airframe response data, rotor motion data, and blade load data; S5. The output maneuver flight simulation data file, the obtained noise calculation parameter file and the blade geometry information file are passed as input to the noise calculation model; S6. Based on the blade geometry information file, for each sound source moment, loop through each rotor blade sound source element and sequentially calculate the sound source element position, velocity, acceleration, and observation point time in the geodetic coordinate system; S7. Calculate the position, velocity, acceleration, and observation time of the sound source element based on the Farassat 1A formula, and obtain the contribution of each sound source element to the sound pressure at the far-field observation point. S8. interpolate the sound pressure of each sound source element in the time dimension at the observation time, sum the integrals of the sound pressure contributions of the sound source elements at the same observation time, and obtain the time history data of the sound pressure at the observation point; S9. Perform discrete Fourier transform on the sound pressure time history data of each observation point to calculate the sound pressure spectrum curve and total sound pressure level, thereby analyzing the noise characteristics of the rotorcraft in the maneuvering state.

2. The method for constructing an aerodynamic noise prediction model for a rotorcraft in an unsteady transient maneuvering state according to claim 1, characterized in that: In said S2, an aerodynamic model is established for each component of the rotorcraft, wherein: The aerodynamic forces / torques on the fuselage and tail are calculated using aerodynamic data obtained from wind tunnel tests. The aerodynamic forces / torques on the rotor / tail rotor are solved by coupling the Pitt-Peters dynamic inflow model, the Leishman-Beddoes airfoil unsteady aerodynamic model, and the blade flapping motion model. Ultimately, the forces and moments acting on the center of gravity of the rotorcraft by each component are obtained, namely the first centroid force X, the second centroid force Y, the third centroid force Z, the first moment L, the second moment M, and the third moment N. When the rotorcraft is an ideal rigid body, the motion equation of the body is the Euler equation including three linear motion degrees of freedom and three angular motion degrees of freedom, and a six-degree-of-freedom linear model of the body is established; The six-degree-of-freedom linear model of the body is expressed as: Among them, I xx , I yy , I zz is the moment of inertia of the rotorcraft about the body axis, I xy , I yz , I xz is the product of inertia, p f ,q f 、r f is the attitude angular velocity, u f 、v f 、w f is the linear velocity, θ f 、φ f , ψ f is the attitude angle, m G is the mass of the rotorcraft, g is the acceleration due to gravity; According to the rotor MR, fuselage F, horizontal tail H, vertical tail H and tail rotor TR, the six-degree-of-freedom linear model of the fuselage is expressed as: In addition, the kinematic equations between the attitude angle and angular velocity of the rotorcraft are satisfied, namely, equations (3)-(5); The kinematic equation is expressed as:

3. The method for constructing an aerodynamic noise prediction model for a rotorcraft in an unsteady transient maneuvering state according to claim 2, characterized in that: In S3, based on the six-degree-of-freedom linear model of the body, the nonlinear model of the rotorcraft in any flight state is expressed as: in, is the derivative of the state quantity, A is the aerodynamic derivative, B is the control derivative, y is the rotorcraft state quantity, and u is the control input quantity; Under different state variables, the nonlinear model of the rotorcraft is linearized, and the approximate inverse of the control loop is obtained using the obtained linearized model of the rotorcraft; The linearized model of the rotorcraft is expressed as: The control loop includes a six-degree-of-freedom linear model of the body, a fast loop inversion, a slower loop inversion and a slow loop inversion connected in sequence; The six-degree-of-freedom linear model of the fuselage is an under-input system, whose input is the four helicopter control variables, namely the lateral periodic pitch δ e 、Longitudinal periodic pitch δ a , tail rotor pitch δ r and rotor pitch δ c The output is 9 helicopter state quantities, namely the speed of the body in three directions: u f 、v f 、w f , attitude angles in three directions: φ f ,θ f , ψ f , angular velocity in three directions: p f ,q f 、r f ; The inverse input of the fast loop is the attitude angular velocity in three directions and the vertical velocity w of the body c , the output is the desired angular acceleration and the control amount when the desired angular acceleration is generated: δ e , δ a , δ r , δ c ; The inverse input of the slower loop is the attitude angle in three directions: φ c ,θ c , ψ c , the output is the desired angular velocity: p c ,q c 、r c ; The inverse input of the slow loop is the horizontal speed of the two bodies: u c 、v c , the output is the desired acceleration and desired attitude angle: φ c ,θ c ; According to the principle of time scale separation, the control loop is divided into several subsystems with different time scales according to the speed of the rotorcraft state change. The angular velocity and the vertical velocity of the body are directly related to the control input. The angular velocity and the vertical velocity of the body are fast variables. The attitude angle is the first-order integral of the attitude angular velocity and is a slower variable. The horizontal velocity response under the body axis is related to the net external force and is a slow variable. During trajectory tracking, the desired speed and heading angle are given by the read-in flight instructions, which are input into the control loop to complete trajectory tracking.

4. The method for constructing an aerodynamic noise prediction model for a rotorcraft in an unsteady transient maneuvering state according to claim 3, characterized in that: In the S6, the blade is segmented along the chord direction and the span direction, and the area and normal vector of each element are calculated. For each sound source moment, the coordinate transformation matrix, the transformation matrix derivative, and the second-order derivative from the blade coordinate system to the earth coordinate system are solved. The coordinate transformation between the earth coordinate system and the blade coordinate system involves the yaw, pitch, roll, longitudinal tilt of the rotation axis, the lateral tilt of the rotation axis, and the coordinate transformation between multiple coordinates caused by the rotation, flapping, shimmy, and pitch variation of each rotor blade. According to the coordinates of the blade element in the blade fixed coordinate system, the coordinate transformation matrix and its derivative and second-order derivative are substituted, and combined with the body response data of the center of gravity position of the rotorcraft, the coordinate position, velocity, and acceleration of the blade element in the earth coordinate system at each sound source moment are obtained; Specifically: Substitute the sound source time τ and the infinitesimal position y(τ) into the delay time equation to obtain the observation point time t when the sound emitted by the sound source at the infinitesimal position y(τ) reaches the far-field observation point x; The delay time equation is expressed as: τ=t-||xy(τ)|| / c (8) Where c is the speed of sound.

5. The method for constructing an aerodynamic noise prediction model for a rotorcraft in an unsteady transient maneuvering state according to claim 4, characterized in that: In S7, the contribution of each sound source element to the sound pressure of the far-field observation point x is calculated using the Farassat1A formula; The Farassat 1A formula is expressed as: p'(x,t)=p' T (x,t)+p' L (x,t) (9) Where p' is the disturbance sound pressure, p' T is the disturbance sound pressure of thickness noise, p' L is the disturbance sound pressure of the load noise, f(x,t)=0 represents the rotor blade surface, dS is the blade infinitesimal area, ρ0 represents the density in the undisturbed medium, v n =v i n i is the normal motion velocity of the blade surface, is the projection of the velocity derivative in the normal direction, is the dot product of the velocity and the normal vector derivative, r=||r i || is the distance between the sound source element and the observation point, M=||M i || is the Mach number of the infinitesimal motion, is the component of the infinitesimal motion Mach number in the noise propagation direction, The unit vector representing the direction of noise propagation, represents the component of blade surface load in the noise propagation direction, and M r and l r With respect to the time derivative, the subscript ret indicates that the integrand takes the value at the time of emission of the sound source.

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