A Method for Constructing Aerodynamic Noise Prediction Models for Rotorcraft in Unsteady Transient Maneuvering State

Abstract

This invention discloses a method for constructing an aerodynamic noise prediction model for rotorcraft in unsteady transient maneuvering states, belonging to the field of aircraft noise prediction technology. It solves the problem that traditional aircraft noise prediction methods in the prior art struggle to achieve efficient instantaneous aerodynamic noise prediction for rotorcraft in maneuvering states. This invention constructs a six-degree-of-freedom linearized equation for the aircraft body; updates the rotorcraft's control and state variables based on a trajectory tracking control law, and outputs a maneuvering flight simulation data file; calculates the sound pressure contribution of each sound source element to the far-field observation point based on the Farasat 1A formula, interpolates it in the time dimension at the observation time, integrates and sums the sound pressure contributions of the elements at the same observation time, obtains the sound pressure time-history data at the observation point, performs a discrete Fourier transform, and analyzes the noise characteristics of the rotorcraft in maneuvering states. This invention improves the computational efficiency of calculating the sound pressure contribution of elements at the observation point time and can be applied to predicting instantaneous aircraft noise.

Description

Technical Field

[0001] This invention relates to a method for constructing aerodynamic noise prediction models, and more particularly to a method for constructing aerodynamic noise prediction models for rotorcraft in unsteady transient maneuvering states, belonging to the field of aircraft noise prediction technology. Background Technology

[0002] Rotorcraft play a unique role in both civilian and military fields due to their advantages such as vertical takeoff and landing, hovering, and good low-altitude and low-speed performance. However, noise pollution from vehicles such as eVTOL (electric vertical takeoff and landing) can affect the comfort of people on the ground, and noise problems from helicopters can cause them to prematurely expose their targets, endangering their own safety and leading to mission failure. Therefore, research on rotorcraft noise prediction technology is of great significance.

[0003] Maneuvering is crucial for rotorcraft to perform missions. In unsteady transient maneuvering, the acceleration, deceleration, turning, climbing and descending of rotorcraft cause the direction and amplitude of noise to change significantly over time. In addition, due to the effects of kinematics and aerodynamics, maneuvering can lead to a significant increase in noise.

[0004] In summary, a method for constructing aerodynamic noise prediction models for rotorcraft in unsteady transient maneuvering states is needed. Summary of the Invention

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

[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 under maneuvering conditions, this invention provides a method for constructing an aerodynamic noise prediction model for rotorcraft under unsteady transient maneuvering conditions.

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

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

[0009] S2. Based on the model input file, establish the flight dynamics model of the rotorcraft, that is, construct a six-degree-of-freedom linearized model of the airframe;

[0010] S3. Based on the six-degree-of-freedom linearized model of the airframe, solve the approximate inverse of the control loop to realize the update of 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 airframe.

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

[0012] S5. Input the output maneuvering flight simulation data file, the acquired noise calculation parameter file, and the blade geometry information file into the noise calculation model;

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

[0014] S7. Based on the Farassat 1A formula, calculate the position, velocity, acceleration and observation time of the sound source element, and calculate 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, and sum the integrals of the sound pressure contribution of the element at the same observation time to obtain the sound pressure time history data of 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 the total sound pressure level, thereby analyzing the noise characteristics of the rotorcraft in maneuvering state.

[0017] Furthermore, in S2, aerodynamic models are established for each component of the rotorcraft. The aerodynamic forces / torques of the fuselage and tail are calculated using aerodynamic data obtained from wind tunnel tests. 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. Finally, the forces and torques of each component acting on the center of gravity of the rotorcraft are obtained, namely, the first center of gravity force X, the second center of gravity force Y, the third center of gravity force Z, the first torque L, the second torque M, and the third torque N.

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

[0019] The six-degree-of-freedom linearized model of the organism is represented as:

[0020]

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

[0022] Based on the rotor MR, fuselage F, horizontal stabilizer H, vertical stabilizer H, and tail rotor TR, the six-degree-of-freedom linearized model of the airframe is represented as follows:

[0023]

[0024] Furthermore, the attitude angle and angular velocity of the rotorcraft satisfy the kinematic equations, namely equations (3)-(5);

[0025] The kinematic equations are expressed as follows:

[0026]

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

[0028]

[0029] in, Let A be the derivative of the state variable, B be the aerodynamic derivative, y be the state variable of the rotorcraft, and u be the control input.

[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 represented as follows:

[0032]

[0033] The control loop consists of a six-degree-of-freedom linearized model of the machine body, a fast loop inverse, a slower loop inverse, and a slow loop inverse connected in sequence.

[0034] The six-DOF linearized model of the airframe is an under-input system, with its inputs consisting of four helicopter control variables, namely the lateral cyclic pitch δ. e Longitudinal periodic pitch δ a Tail rotor pitch δ r and rotor pitch δ c The output consists of nine helicopter state variables, namely the airframe velocities in three directions: u f v f w f Three orientation angles: φ f θ f ψ f Attitude angular velocity in three directions: p f q f r f ;

[0035] The fast loop inverse input consists of the attitude angular velocity in three directions and the vertical velocity of the body, w. c The output is the desired angular acceleration and the manipulation amount used to generate the desired angular acceleration: δ e δ a δ r δ c ;

[0036] The slower loop inverse input consists of three attitude angles: φ c θ c ψ c The output is the desired angular velocity: p c q c r c ;

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

[0038] Based on the principle of time scale separation, the control loop is divided into several subsystems with different time scales according to the different rates of change of the rotorcraft's state. Angular velocity and vertical velocity of the aircraft are directly related to the control input, and angular velocity and vertical velocity of the aircraft are fast variables. Attitude angle is the first integral of attitude angular velocity, and attitude angle is a relatively slow variable. The horizontal velocity response under the aircraft 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 flight command. The flight command is then input into the control loop to complete the trajectory tracking.

[0040] Furthermore, in S6, the blade is segmented along the chord and spanwise directions, and the area and normal vector of each micro-element are calculated. For each sound source moment, the coordinate transformation matrix, the derivative of the transformation matrix, and the second derivative are solved from the blade coordinate system to the earth coordinate system. The coordinate transformation between the earth coordinate system and the blade coordinate system involves multiple coordinate transformations caused by the yaw, pitch, roll, spin axis pitch, spin axis roll of the rotorcraft, as well as the rotation, flapping, oscillation, and pitch changes of each rotor blade. Based on the coordinates of the blade micro-element in the fixed blade coordinate system, the coordinate transformation matrix and its derivative and second derivative are substituted into it. Combined with the rotorcraft's center of gravity position and body response data, the coordinate position, velocity, and acceleration of the blade micro-element in the earth coordinate system at each sound source moment are obtained.

[0041] Specifically: Substituting the sound source time τ and the infinitesimal position y(τ) into the delay time equation, we obtain the time t for the sound emitted at the sound source time τ at the infinitesimal position y(τ) to reach the observation point x at the far-field observation point;

[0042] The time delay equation is expressed as:

[0043] τ=t-|xy(τ)| / c (8)

[0044] Where c is the speed of sound.

[0045] Furthermore, in S7, the sound pressure contribution of each sound source element to the far-field observation point x is calculated using the Farssat1A 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 p' is the perturbation sound pressure of the thickness noise. L Let f(x,t) = 0 represent the rotor blade surface area, dS be the blade element area, ρ0 be the density in the undisturbed medium, and v be the load noise disturbance sound pressure. n =v i n i Let be the normal velocity of the blade surface. The projection of the derivative of the velocity onto the normal vector direction. The dot product of the velocity and the derivative of the normal vector, r = |r i| is the distance from the sound source element to the observation point, M = |M i | represents the Mach number of the infinitesimal motion. Let Mach number of the infinitesimal motion element be the component in the direction of noise propagation. A unit vector representing the direction of noise propagation. This represents the component of the blade surface load in the direction of noise propagation. and M respectively r and l r The derivative with respect to time, with the subscript ret, indicates the value of the integrand at the time of sound source emission.

[0051] The beneficial effects of this invention are as follows: The method proposed in this 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 maneuvering noise calculation, the influence of the pitch, yaw and roll motion response of the aircraft is considered, which can more clearly reflect the characteristics of unsteady transient maneuvering noise. The method proposed in this invention calculates the contribution of the blade sound source element to the sound pressure at the observation point at the sound source time. Compared with the traditional time delay algorithm that calculates the contribution of the element sound pressure at the observation point time, the number of coordinate transformations between the blade coordinate system and the geodetic coordinate system required is greatly reduced, and the calculation efficiency is higher. Attached Figure Description

[0052] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings:

[0053] Figure 1 A flowchart illustrating the method for constructing an aerodynamic noise prediction model for rotorcraft in unsteady transient maneuvering states;

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

[0055] Figure 3 This is a schematic diagram of the dynamic inverse control loop. Detailed Implementation

[0056] To make the technical solutions and advantages of the embodiments of the present invention clearer, the exemplary embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not an exhaustive list of all embodiments. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0057] refer to Figures 1-3This embodiment details the method for constructing an aerodynamic noise prediction model for a rotorcraft in unsteady transient maneuvering states, specifically including the following steps:

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

[0059] S2. Based on the model input file, establish the flight dynamics model of the rotorcraft, that is, construct a six-degree-of-freedom linearized model of the airframe;

[0060] S3. Based on the six-degree-of-freedom linearized model of the airframe, solve the approximate inverse of the control loop to realize the update of 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 airframe.

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

[0062] S5. Input the output maneuvering flight simulation data file, the acquired noise calculation parameter file, and the blade geometry information file into the noise calculation model;

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

[0064] S7. Based on the Farassat 1A formula, calculate the position, velocity, acceleration and observation time of the sound source element, and calculate 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, and sum the integrals of the sound pressure contribution of the element at the same observation time to obtain the sound pressure time history data of the observation point.

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

[0067] Specifically, in S1, the flight command file includes 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, fuselage moment of inertia), rotor design parameters (number of blades, rotor radius, rotor direction, rotor blade flapping moment of inertia, flapping hinge stiffness, blade pre-cone angle, rotor hub center position, rotor shaft tilt angle, advance control angle), fuselage parameters (aerodynamic reference area, longitudinal aerodynamic reference length, lateral aerodynamic reference length, fuselage aerodynamic force application point position), horizontal stabilizer parameters (horizontal stabilizer aerodynamic force application point position, horizontal stabilizer position, aerodynamic reference area), vertical stabilizer parameters (vertical stabilizer aerodynamic force application point position, vertical stabilizer position, vertical stabilizer installation angle, aerodynamic reference area, aerodynamic reference length), and tail rotor parameters (tail rotor blade number, tail rotor radius, tail rotor design speed, tail rotor direction of rotation, 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 stabilizer aerodynamic data, and vertical stabilizer aerodynamic data;

[0070] In S4, the rotor control parameters include the time-history variation data of lateral cyclic pitch, longitudinal cyclic pitch, tail rotor pitch, and rotor collective pitch.

[0071] Aircraft response data includes longitudinal position, lateral position, vertical position, roll angle, pitch angle, yaw angle, and their derivatives and second derivatives;

[0072] The rotor motion data includes the temporal variations of the azimuth angle, flapping angle, flare angle, and pitch angle of each rotor blade;

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

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

[0075] In step S8, step S7 obtains the time series of the sound pressure contribution of each sound source micro-element to the observation point with respect to the sound source emission time. Since the arrival time of different sound source micro-elements on the blade is different at the same sound source emission time, it is necessary to interpolate the sound pressure time history of each sound source micro-element on the observation time so as to sum the contributions of each sound source micro-element to the relevant observation point time.

[0076] Furthermore, in S2, aerodynamic models are established for each component of the rotorcraft. The aerodynamic forces / torques of the fuselage and tail are calculated using aerodynamic data obtained from wind tunnel tests. 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. Finally, the forces and torques of each component acting on the center of gravity of the rotorcraft are obtained, namely, the first center of gravity force X, the second center of gravity force Y, the third center of gravity force Z, the first torque L, the second torque M, and the third torque N.

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

[0078] The six-degree-of-freedom linearized model of the organism is represented as:

[0079]

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

[0081] Based on the rotor MR, fuselage F, horizontal stabilizer H, vertical stabilizer H, and tail rotor TR, the six-degree-of-freedom linearized model of the airframe is represented as follows:

[0082]

[0083] Furthermore, the attitude angle and angular velocity of the rotorcraft satisfy the kinematic equations, namely equations (3)-(5);

[0084] The kinematic equations are expressed as follows:

[0085]

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

[0087]

[0088] in, The derivative of the state variable, 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 state variable of the rotorcraft, 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 represented as follows:

[0091]

[0092] The control loop consists of a six-degree-of-freedom linearized model of the machine body, a fast loop inverse, a slower loop inverse, and a slow loop inverse connected in sequence.

[0093] The six-DOF linearized model of the airframe is an under-input system, with its inputs consisting of four helicopter control variables, namely the lateral cyclic pitch δ. e Longitudinal periodic pitch δ a Tail rotor pitch δ r and rotor pitch δ c The output consists of nine helicopter state variables, namely the airframe velocities in three directions: u f v f w f Three orientation angles: φ f θ f ψ f Attitude angular velocity in three directions: p f q f r f ;

[0094] The fast loop inverse input consists of the attitude angular velocity in three directions and the vertical velocity of the body, w. c The output is the desired angular acceleration and the manipulation amount used to generate the desired angular acceleration: δ e δ a δ r δ c ;

[0095] The slower loop inverse input consists of three attitude angles: φ c θ c ψ c The output is the desired angular velocity: p c q c r c ;

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

[0097] Based on the principle of time scale separation, the control loop is divided into several subsystems with different time scales according to the different rates of change of the rotorcraft's state. Angular velocity and vertical velocity of the airframe are directly related to the control input and have the fastest response. Therefore, angular velocity and vertical velocity of the airframe are fast variables. Attitude angle is the first integral of attitude angular velocity and has a slower response. Attitude angle is a relatively slow variable. Horizontal velocity under the airframe 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 flight command. The flight command is then input into the control loop to complete the trajectory tracking.

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

[0100] Furthermore, in S6, the blade is segmented along the chord and spanwise directions, and the area and normal vector of each micro-element are calculated. For each sound source moment, the coordinate transformation matrix, the derivative of the transformation matrix, and the second derivative are solved from the blade coordinate system to the earth coordinate system. The coordinate transformation between the earth coordinate system and the blade coordinate system involves multiple coordinate transformations caused by the yaw, pitch, roll, spin axis pitch, spin axis roll of the rotorcraft, as well as the rotation, flapping, oscillation, and pitch changes of each rotor blade. Based on the coordinates of the blade micro-element in the fixed blade coordinate system, the coordinate transformation matrix and its derivative and second derivative are substituted into it. Combined with the rotorcraft's center of gravity position and body response data, the coordinate position, velocity, and acceleration of the blade micro-element in the earth coordinate system at each sound source moment are obtained.

[0101] Specifically: Substituting the sound source time τ and the infinitesimal position y(τ) into the delay time equation, we obtain the time t for the sound emitted at the sound source time τ at the infinitesimal position y(τ) to reach the observation point x at the far-field observation point;

[0102] The time delay equation is expressed as:

[0103] τ=t-|xy(τ)| / c (8)

[0104] Where c is the speed of sound.

[0105] Furthermore, in S7, the sound pressure contribution of each sound source element to the far-field observation point x is calculated using the Farssat1A 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 p' is the perturbation sound pressure of the thickness noise. L Let f(x,t) = 0 represent the rotor blade surface area, dS be the blade element area, ρ0 be the density in the undisturbed medium, and v be the load noise disturbance sound pressure. n =v i n i Let be the normal velocity of the blade surface. The projection of the derivative of the velocity onto the normal vector direction. The dot product of the velocity and the derivative of the normal vector, r = |r i | is the distance from the sound source element to the observation point, M = |M i | represents the Mach number of the infinitesimal motion. Let Mach number of the infinitesimal motion element be the component in the direction of noise propagation. A unit vector representing the direction of noise propagation. This represents the component of the blade surface load in the direction of noise propagation. and M respectively r and l r The derivative with respect to time, with the subscript ret, indicates the value of the integrand at the time of sound source emission.

[0110] Although the invention has been described with reference to a limited number of embodiments, those skilled in the art will understand from the foregoing description that other embodiments are conceivable within the scope of the invention described herein. Furthermore, it should be noted that the language used in this specification has been chosen primarily for readability and instructional purposes, and not for the purpose of interpreting or limiting the subject matter of the invention. Therefore, 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 invention is illustrative and not restrictive, and the scope of the invention is defined by the appended claims.

Claims

1. A method for constructing an aerodynamic noise prediction model for rotorcraft in unsteady transient maneuvering states, characterized in that, Includes the following steps: S1. Obtain flight command files, rotorcraft parameter files, and aerodynamic data files, and integrate them into a model input file; S2. Based on the model input file, establish the flight dynamics model of the rotorcraft, that is, construct a six-degree-of-freedom linearized model of the airframe; S3. Based on the six-degree-of-freedom linearized model of the airframe, solve the approximate inverse of the control loop to realize the update of 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 airframe. S4. Output the maneuvering flight simulation data file using the updated six-degree-of-freedom linearized model of the airframe, which includes rotor control parameters, airframe response data, rotor motion data, and blade load data; S5. Input the output maneuvering flight simulation data file, the acquired noise calculation parameter file, and the blade geometry information file into the noise calculation model; S6. Based on the blade geometry information file, for each sound source moment, cycle through the micro-elements of each sound source on the rotor blade and sequentially calculate the micro-element position, velocity, acceleration, and observation point time of the sound source in the geodetic coordinate system. S7. Based on the Farassat 1A formula, calculate the position, velocity, acceleration and observation time of the sound source element, and calculate 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, and sum the integrals of the sound pressure contribution of the element at the same observation time to obtain the sound pressure time history data of the observation point. S9. Perform 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 maneuvering state. In S3, based on the six-degree-of-freedom linearized model of the aircraft, the nonlinear model of the rotorcraft under any flight state is expressed as follows: in, Let A be the derivative of the state variables, A be the aerodynamic derivative, and B be the control derivative. For rotorcraft state variables, To manipulate input quantities; 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 represented as follows: The control loop consists of a six-degree-of-freedom linearized model of the machine body, a fast loop inverse, a slower loop inverse, and a slow loop inverse connected in sequence. The six-DOF linearized model of the airframe is an under-input system, with its inputs consisting of four helicopter control variables, namely the lateral cyclic pitch δ. e Longitudinal periodic pitch δ a Tail rotor pitch δ r and rotor pitch δ c The output consists of nine helicopter state variables, namely the airframe velocities in three directions: , , Three attitude angles: 𝜙 𝑓 , 𝑓 , 𝑓 Angular velocities in three directions: 𝑝 𝑓 , 𝑓 , 3 𝑓 ; The fast loop inverse input consists of the attitude angular velocity in three directions and the vertical velocity of the body, w. c The output is the desired angular acceleration and the manipulation amount used to generate the desired angular acceleration: δ e δ a δ r δ c ; The slower loop inverse input has three attitude angles: 𝜙 c , c , c The output is the desired angular velocity: 𝑝 c , c , 3 c ; The slow loop inverse input consists of the horizontal velocities of the two machine bodies: , The output is the desired acceleration and desired attitude angle: 𝜙 c , c ; Based on the principle of time scale separation, the control loop is divided into several subsystems with different time scales according to the different rates of change of the rotorcraft's state. Angular velocity and vertical velocity of the aircraft are directly related to the control input, and angular velocity and vertical velocity of the aircraft are fast variables. Attitude angle is the first integral of attitude angular velocity, and attitude angle is a relatively slow variable. The horizontal velocity response under the aircraft 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 flight command. The flight command is then input into the control loop to complete the trajectory tracking. In step S6, the blade is segmented along the chord and spanwise directions, and the area and normal vector of each micro-element are calculated. For each sound source moment, the coordinate transformation matrix, the derivative of the transformation matrix, and the second derivative are solved from the blade coordinate system to the earth coordinate system. The coordinate transformation between the earth coordinate system and the blade coordinate system involves multiple coordinate transformations caused by the yaw, pitch, roll, spin axis pitch, spin axis roll of the rotorcraft, as well as the rotation, flapping, oscillation, and pitch changes of each rotor blade. Based on the coordinates of the blade micro-element in the fixed blade coordinate system, the coordinate transformation matrix and its derivative and second derivative are substituted into it. Combined with the rotorcraft's center of gravity position and body response data, the coordinate position, velocity, and acceleration of the blade micro-element in the earth coordinate system at each sound source moment are obtained. Specifically: the sound source time and micro-element position Substituting into the time delay equation, we obtain the sound source time. At the micro element position The emitted sound reaches the far-field observation point Observation time at the location ; The time delay equation is expressed as: in, The speed of sound.

2. The method for constructing an aerodynamic noise prediction model for a rotorcraft in unsteady transient maneuvering states according to claim 1, characterized in that, In step S2, aerodynamic models are established for each component of the rotorcraft, wherein... The aerodynamic forces and moments of the fuselage and tail were calculated using aerodynamic data obtained from wind tunnel tests. The aerodynamic forces and moments of the rotor / tail rotor were solved by coupling the Pitt-Peters dynamic inflow model, the Leishman-Beddoes airfoil unsteady aerodynamic model, and the blade flapping motion model. Finally, the forces and moments of each component acting on the center of gravity of the rotorcraft were obtained, i.e., the first center of gravity force. Second centripetal force Third centripetal force First torque Second torque and the third torque ; When the rotorcraft is an ideal rigid body, the equation of motion of the aircraft is the Euler equation, which includes three linear degrees of freedom and three angular degrees of freedom, and a six-degree-of-freedom linearized model of the aircraft is established. The six-degree-of-freedom linearized model of the organism is represented as follows: Among them, 𝐼 𝑥𝑥 , 𝑦𝑦 , 𝑧𝑧 Let be the moment of inertia of the rotorcraft about its body axis, 𝐼 𝑥𝑦 , 𝑦𝑧 , 𝑥𝑧 For the inertial product, 𝑝 𝑓 , 𝑓 , 3 𝑓 Let ω be the attitude angular velocity. 𝑓 , 𝑓 , 𝑓 Let be the linear velocity, 𝜃 𝑓 , 𝑓 , 𝑓 For attitude angle, 𝑚 𝐺 Let be the mass of the rotorcraft, and be the acceleration due to gravity. Based on the rotor MR, fuselage F, horizontal stabilizer H, vertical stabilizer H, and tail rotor TR, the six-degree-of-freedom linearized model of the airframe is represented as follows: Furthermore, the attitude angle and angular velocity of the rotorcraft satisfy the kinematic equations, namely equations (3)-(5); The kinematic equations are expressed as follows: 。 3. The method for constructing an aerodynamic noise prediction model for a rotorcraft in unsteady transient maneuvering states according to claim 2, characterized in that, In S7, for each sound source element at the far-field observation point The sound pressure contribution was calculated using the Farassat1A formula; The Farassat 1A formula is expressed as: in, To disturb the sound pressure, This refers to the perturbation sound pressure level of thickness noise. This refers to the disturbance sound pressure of the load noise. Let dS represent the surface area of ​​the rotor blade, and dS be the area of ​​a micro-element of the blade. This represents the density in a undisturbed medium. Let be the normal velocity of the blade surface. The derivative of the velocity is projected onto the normal vector direction. The dot product of the velocity and the derivative of the normal vector. The distance between the sound source element and the observation point. For infinitesimal motion, the Mach number is... Let Mach number of the infinitesimal motion element be the component in the direction of noise propagation. A unit vector representing the direction of noise propagation. This represents the component of the blade surface load in the direction of noise propagation. and They are respectively and The derivative with respect to time, with the subscript ret, indicates the value of the integrand at the time of sound source emission.

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