Aircraft pneumatic-performance-quality integrated monitoring method under cumulus icing condition

Abstract

A pneumatic-performance-quality integrated monitoring method for an aircraft under the condition of cumulus icing comprises the following steps: acquiring geometric parameters, flight state parameters and environmental parameters of the aircraft, then sequentially calculating a pneumatic flow field and icing parameters of a clean aircraft configuration, performing surface equivalent roughness mapping, and obtaining a result obtained by pneumatic recalculation after icing; and then flight performance and flight quality evaluation is performed according to a result obtained by aerodynamic recalculation after icing, when a flight performance evaluation result or a flight quality evaluation result exceeds a preset safety threshold range, a flight control strategy is triggered, and compensation control is performed on the aircraft by adjusting engine thrust, a control surface deflection angle or flight control parameters, so that the flight quality is improved. Therefore, the aerodynamic stability and the flight safety of the aircraft under the icing condition are maintained. According to the method, the calculation complexity caused by traditional ice shape geometric reconstruction and re-division can be reduced, the flight parameter acquisition efficiency after icing is improved, and the flight state monitoring of the aircraft in the cumulus icing state is efficiently realized.

Description

Technical Field

[0001] This invention relates to a technology in the field of flight control, specifically an integrated monitoring method for aircraft aerodynamics, performance, and quality under cumulus icing conditions. Background Technology

[0002] When an aircraft flies in an icing environment, its aerodynamic characteristics, flight performance, and flight quality undergo significant changes, which can seriously affect flight safety. Current technologies perform aerodynamic analysis after geometric icing reconstruction and assess changes in aerodynamic performance accordingly. However, because this approach remains at the level of analyzing the impact of icing on single aerodynamic parameters such as lift and drag, it lacks a complete evaluation system that links icing to flight performance and flight quality, making it difficult to meet the needs of engineering airworthiness assessments and system-level analysis. Summary of the Invention

[0003] This invention addresses the shortcomings of existing technologies, which are difficult to apply to the absence of obvious macroscopic ice shapes under cumulus icing conditions and lack systematic coupling evaluation of icing effects with flight performance and flight quality. It proposes an integrated monitoring method for aircraft aerodynamics-performance-quality under cumulus icing conditions. By using surface equivalent roughness as a characterization method under cumulus icing conditions, a complete evaluation process linking aerodynamics, performance, and quality is established, realizing an automated integrated process from flow field calculation, icing calculation, roughness mapping, aerodynamic recalculation to flight performance and flight quality evaluation.

[0004] This invention is achieved through the following technical solution:

[0005] This invention relates to an integrated monitoring method for aircraft aerodynamics, performance, and quality under cumulus icing conditions. The method involves collecting aircraft geometric parameters, flight state parameters, and environmental parameters, then sequentially calculating the aerodynamic flow field of the clean aircraft configuration and icing parameters. Surface equivalent roughness mapping is then performed to obtain the recalculated aerodynamics results after icing. Based on these recalculated results, flight performance and quality are evaluated. When the flight performance or quality evaluation results exceed a preset safety threshold, a flight control strategy is triggered. This strategy adjusts engine thrust, control surface deflection, or flight control parameters to compensate for and control the aircraft, maintaining aerodynamic stability and flight safety under icing conditions.

[0006] The aforementioned aircraft geometric parameters include: wing area, chord length, span, aircraft mass, and engine thrust.

[0007] The flight status parameters include: flight altitude, speed, angle of attack, and aircraft wall temperature.

[0008] The environmental parameters include: air density, ambient temperature, viscosity coefficient, liquid water content in cumulus ice, average water droplet size, and freezing temperature.

[0009] The meteorological parameters for cumulus icing are obtained according to CCAR25 airworthiness rules, and the liquid water content, average effective water droplet size, and icing temperature are interrelated. That is, if two of these parameters are determined, the third parameter is determined.

[0010] The preferred icing temperature is equal to the ambient temperature, and the icing time is the time the aircraft spends traversing cumulus clouds. The icing time needs to be determined based on the flight mission, using the distance traversed through cumulus clouds and the corresponding flight speed.

[0011] Preferably, in the initial stage of the flow field calculation, the aircraft wall temperature needs to be set to be 10°C higher than the aircraft stagnation temperature.

[0012] The aerodynamic flow field of the clean aircraft configuration is calculated based on numerical fluid dynamics methods to obtain surface pressure distribution, wall shear stress, local velocity information, and aerodynamic coefficients. Specifically, this includes:

[0013] Step 1: Establishing the aircraft geometric model, specifically including:

[0014] 1.1 Obtain aircraft geometric parameters, including: wing airfoil parameters, span, chord length, fuselage length, wing-fuselage connection position, etc.

[0015] 1.2 Construct a three-dimensional geometric model of the aircraft based on the above geometric parameters.

[0016] 1.3 Simplify the geometric model, including: removing fine structures, smoothing surfaces, and defining the boundaries of the computational region.

[0017] Step 2: Perform computational mesh generation on the three-dimensional geometric model, specifically including:

[0018] 2.1 Generate boundary layer mesh on the aircraft surface.

[0019] 2.2 Generate unstructured volumetric meshes within the computational domain.

[0020] 2.3 Refine the mesh in key areas, including: wing leading edge, wing-body junction area, and tail area.

[0021] 2.4 Check the mesh quality, including: mesh orthogonality and mesh distortion rate.

[0022] Step 3: Solve the flow field for the clean aircraft configuration using numerical fluid dynamics methods, specifically including:

[0023] 3.1 Set the calculation input parameters, including: flight speed, angle of attack, sideslip angle, air density, ambient temperature, viscosity coefficient, etc.

[0024] 3.2 The Reynolds-averaged Navier-Stokes equations are adopted as the governing equations for fluid motion.

[0025] 3.3 Select a turbulence model for flow field calculation, such as the k-ω SST model or the SA model.

[0026] 3.4 Obtain a convergent flow field solution through iterative solution.

[0027] Step 4: Extract aircraft aerodynamic parameters based on the flow field calculation results, specifically including:

[0028] 4.1 Calculate the surface pressure coefficient of the aircraft.

[0029] 4.2 Calculate the wall shear stress.

[0030] 4.3 Calculate the local velocity distribution.

[0031] 4.4 Calculate the aerodynamic coefficients, specifically: lift coefficient: Drag coefficient: ,in: For lift, As resistance, For flight speed, For reference area.

[0032] 4.5 Output the aerodynamic flow field calculation results for the clean aircraft configuration.

[0033] The icing parameters are obtained by calculating the water droplet impact and icing accumulation on the aircraft surface based on the aerodynamic flow field of a clean aircraft configuration, thereby obtaining the equivalent roughness distribution of the aircraft surface.

[0034] Under cumulus conditions, since ice deposition is mainly characterized by roughness changes rather than macroscopic geometric growth, a single-step quasi-steady-state calculation method can meet the engineering accuracy requirements. Specifically, this includes:

[0035] Step 1: Solve the flow field for the clean aircraft configuration using numerical fluid dynamics methods, specifically including:

[0036] 1.1 Set the calculation input parameters, including: flight speed, angle of attack, sideslip angle, air density, ambient temperature, viscosity coefficient, etc.

[0037] 1.2 Set the temperature of the aircraft wall.

[0038] 1.3 The Reynolds-averaged Navier-Stokes equations are adopted as the governing equations for fluid motion.

[0039] 1.4 Select a turbulence model for flow field calculation, such as the k-ω SST model or the SA model.

[0040] 1.5 Obtain a convergent flow field solution through iterative solution.

[0041] Step 2, calculation of water droplet trajectory and impact characteristics, specifically includes:

[0042] 2.1 Based on the Lagrange method, the equation of motion of the water droplet is established and combined with Newton's second law to calculate the trajectory of the water droplet. Specifically: ,in: For the mass of the water droplet, Let be the velocity vector of the water droplet. As resistance, For gravity, This is buoyancy.

[0043] 2.2 The fourth-order Runge-Kutta method is used to solve the above differential equations. Given the flow field velocity distribution and the initial coordinates of the droplets as boundary constraints, the mathematical solution to the droplet trajectory equations can be transformed into solving an initial value problem for a system of first-order ordinary differential equations. Given the initial position of each droplet, the droplet position after ∆t is calculated. Through continuous iteration, the calculation stops when the droplet collides with the wall or moves outside the given boundary, thus obtaining the droplet's trajectory.

[0044] 2.3 Calculation of Water Droplet Impact Characteristics. Among the various parameters characterizing the water droplet impact characteristics of a component surface, the local collection coefficient is the most important. It characterizes the distribution of impacting water volume at different points on the surface. Once the local collection coefficient is obtained, the other parameters can be obtained. Therefore, the calculation of water droplet impact characteristics is essentially the calculation of the local collection coefficient β, specifically: , where: β is the local water droplet collection coefficient on the wall, y is the initial range of water droplet impact, and s is the water droplet impact position.

[0045] 2.4 Set the calculation input parameters, including the average effective size of a single water droplet, liquid water content, freezing temperature, etc.

[0046] Step 3, freezing thermodynamic calculations, specifically including:

[0047] 3.1 Based on the principle of energy conservation, a Messier thermodynamic model is established to simulate the complex behaviors that occur after water droplet impact, such as freezing and liquid film flow. The mass and energy conservation in adjacent control volumes, i.e. grid cells, are repeatedly analyzed until the amount of freezing in each control volume is obtained.

[0048] mass conservation equation: ,in, To control the quality of water droplets freezing into ice in a given area, The mass of the water droplet impacting the control area. It refers to the mass of water droplets that overflowed into the control area. This refers to the mass of water droplets evaporating or ice sublimating in the controlled area. The mass of the water droplets overflowing from the control area;

[0049] Energy conservation equation: ,in, For heat conduction between ice and the wall, For convective heat transfer between ice and air, The sensible heat generated by the impact of the water droplets It is the latent heat of liquid film evaporation. It's the heat energy transferred from the aircraft walls. It is the latent heat released when water droplets freeze;

[0050] The aforementioned surface equivalent roughness mapping refers to mapping the equivalent roughness distribution of the aircraft surface to the surface nodes of the aerodynamic computational grid using a spatial interpolation algorithm, and applying the roughness as a wall roughness parameter to the aerodynamic computational model without performing icing geometry reconstruction. Specifically, this includes:

[0051] Step 1: Obtaining the icing roughness parameters, specifically including:

[0052] 1.1 A single-step quasi-steady-state calculation method is adopted to calculate the local icing characteristics based on the icing environment parameters, including: air density, ambient temperature, viscosity coefficient, liquid water content of cumulus icing, average water droplet size, and icing temperature.

[0053] 1.2 Calculate the equivalent roughness values ​​at different locations on the aircraft surface based on the icing model. .

[0054] 1.3 The roughness values ​​are mapped to the spatial coordinates (x, y, z) of the aircraft surface to form a roughness spatial distribution dataset.

[0055] Step 2: Extraction of surface nodes of the aerodynamic computational mesh, specifically including:

[0056] 2.1 Read the coordinates of the surface nodes of the aerodynamic calculation grid.

[0057] 2.2 Obtain the spatial location of each surface node ( ).

[0058] 2.3 Construct the set of aerodynamic mesh surface nodes.

[0059] Step 3: Map the equivalent roughness distribution to the surface nodes of the aerodynamic computational mesh using a spatial interpolation algorithm. This specifically includes:

[0060] 3.1 The inverse distance spatial interpolation algorithm is used to calculate the mesh nodal roughness. The formula for calculating nodal roughness is as follows:

[0061] ,in For the roughness of the mesh nodes, Given the roughness data points, The distance between the node and the roughness data point. This is the distance-weighted index.

[0062] 3.2 Obtain the roughness value of each surface node of the aerodynamic computational mesh.

[0063] Step 4: Apply the roughness mapping results to the aerodynamic calculation model, specifically including:

[0064] 4.1 Input the nodal roughness values ​​as wall roughness parameters into the aerodynamic calculation model.

[0065] 4.2 Roughness parameters are used for wall function correction during aerodynamic solution.

[0066] 4.3 Complete the calculation of aircraft aerodynamic characteristics under icing conditions.

[0067] The aforementioned post-icing aerodynamic recalculation refers to recalculating the flow field considering the influence of surface roughness to obtain the lift coefficient, drag coefficient, moment coefficient, static derivative, and dynamic derivative of the aircraft at different flight speeds, angles of attack, and sideslip angles, forming an aerodynamic database under icing conditions. This aerodynamic database under icing conditions serves as the input data source for the flight performance and flight quality evaluation module, meeting the needs of flight performance and flight quality evaluation, specifically including:

[0068] Step 1: Setting up aerodynamic calculation conditions after icing, specifically including...

[0069] 1.1 Set the flight status parameters of the aircraft after icing, including flight speed, angle of attack, sideslip angle, and flight altitude.

[0070] 1.2 Select multiple discrete operating point values ​​based on the flight envelope range to construct a set of aerodynamic calculation operating conditions after icing.

[0071] 1.3 For each operating point, the flow field is solved by calling the aircraft aerodynamic calculation model with surface roughness parameters applied.

[0072] Step 2: Recalculate the flow field considering the influence of surface roughness, specifically including:

[0073] 2.1 The surface equivalent roughness mapping result is applied as a wall roughness parameter to the boundary conditions of the aircraft surface.

[0074] 2.2 Based on numerical fluid dynamics, the external flow field of the aircraft after applying roughness parameters is solved to obtain the pressure distribution, wall shear stress distribution, and velocity distribution under icing conditions.

[0075] 2.3 Based on the converged flow field results, the aerodynamic forces and aerodynamic moments on the aircraft surface are calculated by integration.

[0076] Step 3: Extract the aerodynamic coefficients after icing, specifically including:

[0077] 3.1 Calculate the lift coefficient based on the aerodynamic integral results drag coefficient and lateral force coefficient .

[0078] 3.2 Calculate the rolling moment coefficient based on the integral results of the aerodynamic moment. Pitch moment coefficient and yaw moment coefficient .

[0079] Step 4: Calculate the static derivative in the icy state, specifically including:

[0080] 4.1 Apply small disturbances to the angle of attack α, sideslip angle β, or control surface deflection near the reference operating point.

[0081] 4.2 Calculate the changes in aerodynamic coefficients before and after the disturbance.

[0082] 4.3 The static derivative is calculated using the finite difference method, whereby the static derivative includes the slope of the lift curve. Pitch moment derivative Lateral force derivative Rolling torque derivative and the derivative of yaw moment ,in: , , .

[0083] Step 5: Calculate the dynamic derivative in the icing state, specifically including:

[0084] An angular velocity disturbance or motion mode disturbance is introduced under the reference operating condition, and the dynamic derivative is calculated based on the unsteady aerodynamic force changes caused by the disturbance. The disturbance includes pitch angular velocity q, roll angular velocity p, and yaw angular velocity r.

[0085] 5.2 Calculate the unsteady aerodynamic forces and aerodynamic torque response of the aircraft under disturbance conditions.

[0086] 5.3 Calculate the dynamic derivative based on the change in aerodynamic coefficients before and after the disturbance, wherein the dynamic derivative includes , , .

[0087] 5.4 The dynamic derivative includes , , ,in: For wingspan, The average aerodynamic chord length is given.

[0088] Step 6: Create an aerodynamic database for the icing state, specifically including:

[0089] 6.1 Store the aerodynamic coefficients, static derivatives, and dynamic derivatives calculated under different flight speeds, angles of attack, and sideslip angles.

[0090] 6.2 Establish a multidimensional aerodynamic database using flight state parameters as an index.

[0091] The aerodynamic database described in 6.3 is used for subsequent flight performance and flight quality assessments.

[0092] The aforementioned flight performance refers to: based on the equations of motion of a point mass and using aerodynamic parameters, simulating the aircraft's stall speed, takeoff climb gradient, approach climb gradient, landing climb gradient, and landing performance to obtain the aircraft's basic flight performance under icing conditions, and evaluating the impact of cumulus icing conditions on flight performance, specifically including:

[0093] Step 1: Constructing input parameters for flight performance simulation, specifically including:

[0094] 1.1 Read the lift coefficient, drag coefficient, moment coefficient and related derivatives from the aerodynamic database under icing conditions.

[0095] 1.2 Obtain the parameters required for aircraft flight performance calculation, including aircraft weight W, wing reference area S, thrust T, flight altitude, gravitational acceleration g, air density ρ, and configuration parameters.

[0096] 1.3 Set corresponding flight state boundary conditions according to different flight stages, including takeoff, approach and landing.

[0097] Step 2: Establish a flight performance calculation model based on the equations of motion of a point mass, specifically including:

[0098] 2.1 Treat the aircraft as a point mass and establish the force balance relationship in the longitudinal plane.

[0099] 2.2 Under quasi-steady conditions, the motion of the aircraft along its flight trajectory is specifically as follows: .

[0100] 3. The equilibrium equation perpendicular to the flight trajectory is: ,in: Let γ be the aircraft mass and γ be the track inclination angle.

[0101] 2.4 Under steady-state climb or steady-state approach conditions, set the acceleration term to zero to obtain the corresponding flight performance calculation conditions.

[0102] Step 3: Calculate the stall speed, specifically including:

[0103] 3.1 Based on the maximum balance lift coefficient under icing conditions Calculate the aircraft's stall speed:

[0104] 3.2 Stall speed .

[0105] 3.3 The stall velocity under icing conditions is compared with the stall velocity under clean configuration to obtain the stall velocity increment caused by icing.

[0106] Step 4: Calculate the takeoff climb gradient, which includes:

[0107] 4.1 Under safe takeoff conditions or at the preset takeoff climb rate, read the corresponding icing state aerodynamic parameters.

[0108] 4.2 Calculate the takeoff climb gradient based on the thrust-drag difference and the aircraft weight.

[0109] 4.3 Takeoff Climb Gradient .

[0110] 4.4 Based on different configuration states and icing levels, the results of climb capability changes during takeoff were obtained.

[0111] Step 5: Calculate the approach climb gradient and landing climb gradient, specifically including:

[0112] 5.1 Extract the corresponding velocity, thrust and aerodynamic parameters under approach or landing configuration conditions.

[0113] 5.2 Based on the lift-drag and thrust characteristics under icing conditions, calculate the approach climb gradient and landing climb gradient respectively.

[0114] The approach climb gradient and landing climb gradient mentioned in 5.3 are calculated using the same force balance principle as the takeoff climb gradient.

[0115] 5.4 Compare the results with the clean configuration to obtain the impact of ice contamination on approach and landing go-around capabilities.

[0116] Step 6: Calculate landing performance, specifically including:

[0117] 6.1 Based on the approach speed, lift-drag characteristics and force conditions during the deceleration phase under icy conditions, a landing run performance calculation model is established.

[0118] 6.2 Calculate the distance in the air from the obstacle crossing point to the touchdown point, and the distance of the runway after touchdown.

[0119] 6.3 Calculate the total landing distance based on the velocity decay process, wherein the total landing distance includes the approach distance, the leveling distance, and the ground skidding distance.

[0120] 6.4 Results of landing distance variation under ice contamination conditions were obtained.

[0121] Step 7: Generate flight performance evaluation results, specifically including:

[0122] 7.1 Summarize the stall speed, takeoff climb gradient, approach climb gradient, landing climb gradient, and landing distance under icing conditions.

[0123] 7.2 Compare the results with the flight performance results corresponding to the clean configuration to obtain the degradation amount of each flight performance.

[0124] 7.3 Assess the extent to which the basic flight performance of an aircraft is affected by cumulus icing conditions based on the amount of flight performance degradation.

[0125] When the stall speed increases, the climb gradient decreases, or the landing distance increases beyond a preset threshold under icing conditions, it is determined that ice contamination has a significant impact on the aircraft's flight performance, and this will serve as the basis for subsequent flight safety assessments and control decisions.

[0126] The aforementioned flight quality refers to the simulation analysis of the aircraft's stability quality, handling quality, and stall boundary characteristics based on the aircraft's six-degree-of-freedom equations of motion and utilizing aerodynamic derivatives under icing conditions. This simulation analysis includes assessments of maneuverability, lateral handling characteristics, longitudinal static stability, lateral static stability, lateral dynamic stability, and stall characteristics to obtain the aircraft's basic flight quality under icing conditions and to evaluate the impact of cumulus icing conditions on flight quality. Specifically, this includes:

[0127] Step 1: Constructing input parameters for flight quality assessment, specifically including:

[0128] 1.1 Read the aerodynamic coefficients, torque coefficients, static derivatives, and dynamic derivatives from the aerodynamic database under icing conditions.

[0129] 1.2 Obtain aircraft mass parameters and inertial parameters, including aircraft mass m, center of gravity position, and moment of inertia. and inertial product.

[0130] 1.3 Obtain flight status parameters, including flight speed, angle of attack, sideslip angle, altitude, thrust status, and configuration status.

[0131] 1.4 Construct an input dataset for aircraft flight quality analysis under icing conditions based on the parameters.

[0132] Step 2: Establish a 6-DOF motion equation model, specifically including:

[0133] 2.1 Based on the translational and rotational dynamics relationship at the aircraft's center of mass, a set of nonlinear motion equations for the aircraft with 6 degrees of freedom is established.

[0134] 2.2 The translation equations include the velocity component equations in the body coordinate system, and the rotation equations include the angular motion equations of roll angular velocity, pitch angular velocity, and yaw angular velocity.

[0135] 2.3 The 6-DOF motion equations described above use aerodynamic forces, aerodynamic torques, and thrust under icing conditions as inputs.

[0136] 2.4 In flight quality analysis, the 6-DOF nonlinear motion equations are linearized with small perturbations as needed to obtain the longitudinal motion equations and the lateral motion equations.

[0137] Step 3: Perform maneuverability simulation analysis, specifically including:

[0138] 3.1 Apply pitch, roll and yaw control inputs to the aircraft under preset flight conditions.

[0139] 3.2 Calculate the aircraft attitude response, angular velocity response and trajectory change based on the 6-DOF motion equations.

[0140] 3.3 Extract the aircraft's normal overload, attitude change rate, velocity change, and trajectory tracking capability during maneuvers.

[0141] 3.4 Assess the impact of ice contamination on aircraft maneuverability based on the difference in maneuverability between iced and clean configurations.

[0142] Step 4: Perform lateral maneuvering characteristic simulation analysis, specifically including:

[0143] 4.1 Apply aileron or rudder control inputs to the aircraft.

[0144] 4.2 Calculate the aircraft roll angle, roll rate, sideslip angle, and yaw response.

[0145] 4.3 Extract lateral handling characteristic indicators, including roll response time, peak roll angular velocity, steady-state roll capability, and sideslip coupling degree.

[0146] 4.4 The lateral maneuvering response under icing conditions is compared with the clean configuration response to obtain the results of lateral maneuvering capability degradation.

[0147] Step 5: Perform longitudinal static stability analysis, which includes:

[0148] 5.1 Apply a small disturbance to the angle of attack near the reference equilibrium flight state.

[0149] 5.2 Calculate the longitudinal static stability derivative based on the relationship between the pitching moment coefficient and the angle of attack. ,when At that time, it was determined that the aircraft possessed longitudinal static stability; based on the icing condition... The change in the amount of ice contamination was used to assess the impact of ice pollution on longitudinal static stability.

[0150] Step 6: Perform lateral static stability analysis, which includes:

[0151] 6.1 Apply a small disturbance to the sideslip angle near the baseline flight condition.

[0152] 6.2 Calculate the derivative of directional static stability based on the change in yaw moment coefficient caused by sideslip angle disturbance. .

[0153] 6.3 Calculate the derivative of lateral static stability based on the change in rolling moment coefficient caused by sideslip angle disturbance. .

[0154] 6.4 According to and The magnitude of the pattern is used to assess the changes in the lateral static stability characteristics of an aircraft under icing conditions.

[0155] Step 7: Perform lateral dynamic stability analysis, which includes:

[0156] 7.1 Establishing a state-space model based on linearized lateral motion equations.

[0157] 7.2 Obtain the eigenvalues ​​of the aircraft's lateral motion mode based on the aforementioned spatial model.

[0158] 7.3 Based on the transverse motion modes, the modes include Dutch roll mode, roll convergence mode, and spiral mode.

[0159] 7.4 Evaluate the lateral dynamic stability of the aircraft under icing conditions based on the damping ratio, natural frequency, and time response characteristics of each mode.

[0160] 7.5 When icing leads to a decrease in modal damping, a slowdown in oscillation decay, or an increase in the tendency of spiral divergence, it is determined that ice contamination has an adverse effect on lateral dynamic stability.

[0161] Step 8: Perform stall characteristic analysis, specifically including:

[0162] 8.1 Based on the lift coefficient, pitch moment coefficient and control response characteristics under icing conditions, analyze the changes in aerodynamic and attitude response of the aircraft as the angle of attack increases.

[0163] 8.2 Determine the critical angle of attack and critical speed when the lift reaches its maximum value or when the pitching moment characteristics undergo a significant abrupt change.

[0164] 8.3 Extract the lift decay characteristics, pitch moment change characteristics, and lateral response change characteristics before and after stall.

[0165] 8.4 Evaluate the impact of ice contamination on stall characteristics based on the differences in critical angle of attack, stall speed, and post-stall response between the icing and clean configurations.

[0166] Step 9 generates flight quality assessment results, specifically including:

[0167] 9.1 Summarize the analysis results of maneuverability, lateral handling characteristics, longitudinal static stability, lateral static stability, lateral dynamic stability, and stall characteristics.

[0168] 9.2 The flight quality indicators under icing conditions are compared with the corresponding flight quality indicators under clean configuration to obtain the amount of flight quality degradation.

[0169] 9.3 Determine the degree of impact of cumulus icing conditions on aircraft flight quality based on the amount of flight quality degradation, and generate flight quality assessment results.

[0170] The flight quality assessment results are used for subsequent flight safety analysis and flight control strategy generation.

[0171] Technical effect

[0172] This invention, under cumulus icing conditions, does not characterize icing contamination through ice shape geometry reconstruction. Instead, it applies roughness as a wall roughness parameter to the aerodynamic calculation model by spatial interpolation mapping between the equivalent roughness distribution of the aircraft surface and the surface nodes of the aerodynamic calculation grid. Based on the recalculated aerodynamic parameters, it conducts an integrated assessment of flight performance and flight quality. Compared with existing technologies, this invention reduces the computational complexity caused by traditional ice shape geometry reconstruction and re-meshing, improves the efficiency of obtaining icing aerodynamic parameters, and can simultaneously obtain flight performance and flight quality assessment results, providing a basis for monitoring and controlling aircraft flight safety status under cumulus icing conditions. Attached Figure Description

[0173] Figure 1 This is a flowchart of the present invention;

[0174] Figure 2 Flowchart for calculating aircraft icing under cumulus cloud conditions;

[0175] Figure 3 A schematic diagram illustrating the calculation process for aircraft icing under cumulus cloud conditions;

[0176] In the figure: (a) is the geometric shape; (b) is the initial mesh; (c) is the pressure distribution; (d) is the icing distribution;

[0177] Figure 4 A schematic diagram showing the calculation results of aircraft water droplet trajectory and impact characteristics under cumulus conditions;

[0178] In the figure: (a) Schematic diagram of water droplet collection coefficient on aircraft surface; (b) Schematic diagram of water droplet velocity distribution on aircraft surface;

[0179] Figure 5 This is a schematic diagram of the surface roughness distribution of an aircraft after icing.

[0180] Figure 6 A schematic diagram comparing the aerodynamic characteristics of an aircraft before and after icing under cumulus conditions;

[0181] In the figure: (a) Schematic diagram comparing lift coefficients before and after icing; (b) Schematic diagram comparing lift-to-drag ratios before and after icing; (c) Schematic diagram comparing moment coefficients before and after icing; (d) Schematic diagram comparing lateral force coefficients before and after icing;

[0182] Figure 7 A schematic diagram showing the calculated stall speed of an aircraft after icing under cumulus conditions;

[0183] Figure 8 This is a schematic diagram showing the calculation results of the takeoff climb gradient of an aircraft after icing under cumulus conditions.

[0184] Figure 9 This is a schematic diagram showing the calculation results of aircraft landing performance after icing under cumulus cloud conditions.

[0185] Figure 10 This is a schematic diagram showing the longitudinal static stability assessment results of an aircraft after icing under cumulus conditions.

[0186] Figure 11 This is a schematic diagram showing the results of the lateral static stability assessment of an aircraft after icing under cumulus conditions.

[0187] Figure 12 This is a schematic diagram showing the results of the directional static stability assessment of an aircraft after icing under cumulus conditions.

[0188] Figure 13 A schematic diagram showing the results of the dynamic stability assessment of an aircraft after icing under cumulus conditions;

[0189] Figure 14 This is a schematic diagram showing the results of the lateral static handling assessment of an aircraft after icing under cumulus conditions.

[0190] Figure 15 This is a schematic diagram showing the evaluation results of lateral dynamic control of an aircraft after icing under cumulus conditions.

[0191] Figure 16 This is a schematic diagram showing the assessment results of aircraft maneuverability after icing under cumulus conditions.

[0192] Figure 17This is a schematic diagram showing the evaluation results of the aircraft's stall characteristics after icing under cumulus conditions. Detailed Implementation

[0193] This embodiment uses a certain type of aircraft as the subject. Under the cumulus icing environment conditions required by CCAR25 airworthiness regulations, the performance of the aircraft after icing is evaluated sequentially according to the following steps: "clean configuration aerodynamic calculation → icing parameter calculation → post-icing roughness mapping → post-icing flight aerodynamic recalculation → flight performance evaluation → flight quality evaluation". In implementing this example, the aircraft geometric parameters, flight state parameters, and icing environment parameters are shown in Tables 1 and 2.

[0194] Table 1. Statistical table of performance parameters of a certain type of fixed-wing aircraft;

[0195] Table 2 is a statistical table of meteorological icing parameters;

[0196] like Figure 1 As shown in this embodiment, an integrated aerodynamic-performance-quality monitoring method for aircraft under cumulus icing conditions is proposed. By collecting aircraft geometric parameters, flight state parameters, and environmental parameters, aerodynamic flow field calculations are first performed on a clean-configuration aircraft, and icing calculations are completed based on cumulus icing environment parameters. Then, the aircraft surface roughness distribution obtained from the icing calculations is mapped to the aircraft surface mesh calculation nodes, and aerodynamic recalculation is completed after icing without ice shape reconstruction. Further, based on the aerodynamic dataset obtained from the post-icing aerodynamic recalculation, flight performance and flight quality assessments are performed on the aircraft. When the flight performance assessment result or flight quality assessment result exceeds a preset safety threshold range, a flight control strategy is triggered. Compensation control is performed on the aircraft by adjusting engine thrust, control surface deflection angle, or flight control parameters to maintain aerodynamic stability and flight safety under icing conditions.

[0197] like Figure 2The diagram illustrates the icing calculation process used in this embodiment, including steps such as initial geometric model preprocessing, flow field mesh generation, input parameter setting, aerodynamic flow field calculation, droplet trajectory and impact characteristic calculation, and icing thermodynamic calculation. Input parameters include, but are not limited to, flight state parameters, atmospheric environment parameters, and icing meteorological parameters. In this embodiment, the flow field mesh is constructed using a combination of hexahedral boundary layer meshes and tetrahedral unstructured meshes; the flow field computation domain is set as a cubic computational flow field domain centered on the aircraft with a side length of 100 times the wingspan; the aerodynamic flow field numerical calculation is based on the Navier-Stokes equations of RANS, combined with a preset turbulence model, discretization scheme, and boundary conditions. It should be noted that the above aerodynamic and icing calculation processes are one implementation method for this example, aimed at obtaining intermediate results required for subsequent flow field initiation, roughness distribution, and aerodynamic recalculation; the key technical feature of this invention does not involve the conventional numerical initiation process itself, but rather constructs the aircraft surface as a roughness distribution based on the icing results, and achieves integrated aerodynamic-performance-quality evaluation after icing through roughness mapping.

[0198] like Figure 3 The diagram shows the aircraft model at different stages during the icing calculation process, including the original geometric model, the aircraft surface mesh diagram, the surface pressure cloud map after aerodynamic calculation, and the surface ice distribution diagram after icing calculation. These staged results clearly demonstrate the complete calculation process from initial geometric modeling and flow field development to icing.

[0199] like Figure 4 As shown, the droplet collection coefficient and droplet velocity distribution on the aircraft surface are obtained after the calculation of droplet trajectory and impact characteristics. These serve as important inputs for subsequent icing thermodynamic calculations and surface roughness determination.

[0200] like Figure 5 The image shows the surface roughness distribution of the entire aircraft under cumulus icing conditions, obtained after the icing calculation is completed. This roughness model file will be subsequently inserted into the aircraft's surface mesh for aerodynamic calculations after cumulus icing. In this embodiment, the interpolation space mapping is implemented using the inverse distance weighted interpolation method.

[0201] like Figure 6The figure shows a comparison of the lift coefficient, lift-to-drag ratio, pitching moment coefficient, and lateral force coefficient of the aircraft before and after icing under the given icing conditions. The results show that compared to the ic-free state, icing increases the aircraft's drag coefficient by approximately 8.73%, decreases the lift slope by approximately 4.67%, reduces the maximum lift coefficient by approximately 5.25%, decreases the maximum lift-to-drag ratio by approximately 9.86%, and reduces the maximum pitching moment coefficient by approximately 18.33%, while the lateral force coefficient shows no significant change. These results quantitatively reflect the impact of cumulus icing on aircraft aerodynamic performance and directly affect subsequent flight performance and flight quality assessments.

[0202] like Figures 7 to 17 The figures show the calculated results for the aircraft's stall speed, climb gradient, landing performance, longitudinal static stability, lateral static stability, directional static stability, dynamic stability, lateral static control, lateral dynamic control, maneuverability, and stall characteristics after icing under cumulus icing conditions. The combined results show that cumulus icing deteriorates the aircraft's flight characteristics, further exacerbating stall, reducing climb and landing performance, and increasing stability and stall risk, thus adversely affecting flight safety. These assessment results can serve as triggers for subsequent control compensation or safety reversal strategies.

[0203] Compared with existing technologies, the improvement of this invention does not eliminate the conventional aerodynamic flow field calculation or icing thermal calculation itself. Instead, it proposes that after obtaining the aircraft icing thermodynamic results, instead of using ice shape geometry reconstruction to characterize the icing effect, the aircraft surface is used as a roughness distribution. This roughness distribution is mapped to the aircraft surface computational grid nodes, and the aerodynamic flow field after icing is recalculated in the form of roughness wall parameters. Based on this, the recalculated aerodynamic dataset is further used to uniformly evaluate flight performance and flight quality, and the flight control output is triggered based on the evaluation results. Therefore, this invention can reduce the additional calculations caused by ice shape and reconstructed mesh generation in traditional icing analysis, while achieving standardized monitoring of aircraft aerodynamic performance, flight performance, and flight quality. The above technical effects have been described by [the relevant authority / organization]. Figures 7 to 17 The results shown have been verified.

[0204] The above-described specific implementations can be partially adjusted by those skilled in the art in different ways without departing from the principles and purpose of the present invention. The scope of protection of the present invention is defined by the claims and is not limited to the above-described specific implementations. All implementation schemes within the scope of the claims are bound by the present invention.

Claims

1. A method for integrated monitoring of aircraft aerodynamics, performance, and quality under cumulus icing conditions, characterized in that, include: By collecting aircraft geometric parameters, flight state parameters, and environmental parameters, the aerodynamic flow field and icing parameters of the clean aircraft configuration are calculated sequentially. Then, the surface equivalent roughness is mapped to obtain the aerodynamic recalculation results after icing. Based on the aerodynamic recalculation results after icing, the flight performance and flight quality are evaluated. When the flight performance evaluation results or flight quality evaluation results exceed the preset safety threshold range, the flight control strategy is triggered. The aircraft is compensated by adjusting the engine thrust, control surface deflection angle, or flight control parameters to maintain the aerodynamic stability and flight safety of the aircraft under icing conditions. The aforementioned aircraft geometric parameters include: wing area, chord length, span, aircraft mass, and engine thrust; The flight status parameters include: flight altitude, speed, angle of attack, and aircraft wall temperature; The environmental parameters include: air density, ambient temperature, viscosity coefficient, liquid water content in cumulus ice, average water droplet size, and freezing temperature.

2. The integrated monitoring method for aircraft aerodynamics, performance, and quality under cumulus icing conditions as described in claim 1, characterized in that, The aerodynamic flow field of the clean aircraft configuration is calculated based on numerical fluid dynamics methods to obtain surface pressure distribution, wall shear stress, local velocity information, and aerodynamic coefficients. Specifically, this includes: Step 1: Establishing the aircraft geometric model, specifically including: 1.1 Obtain aircraft geometric parameters, including: wing airfoil parameters, span, chord length, fuselage length, wing-fuselage connection position, etc.; 1.2 Construct a three-dimensional geometric model of the aircraft based on the above geometric parameters; 1.3 Simplify the geometric model, including: removing fine structures, smoothing surfaces, and defining the boundaries of the computational region; Step 2: Perform computational mesh generation on the three-dimensional geometric model, specifically including: 2.1 Generate boundary layer meshes on the aircraft surface; 2.2 Generate unstructured volumetric meshes within the computational domain; 2.3 Refine the mesh in key areas, including: wing leading edge, wing-body junction area, and tail area; 2.4 Check the mesh quality, including: mesh orthogonality and mesh distortion rate; Step 3: Solve the flow field for the clean aircraft configuration using numerical fluid dynamics methods, specifically including: 3.1 Set the calculation input parameters, including: flight speed, angle of attack, sideslip angle, air density, ambient temperature, viscosity coefficient, etc.; 3.2 The Reynolds-averaged Navier-Stokes equations are adopted as the governing equations for fluid motion; 3.3 Select a turbulence model for flow field calculation, such as the k-ω SST model or the SA model; 3.4 Obtain a convergent flow field solution through iterative solution; Step 4: Extract aircraft aerodynamic parameters based on the flow field calculation results, specifically including: 4.1 Calculate the surface pressure coefficient of the aircraft; 4.2 Calculate the wall shear stress; 4.3 Calculate the local velocity distribution; 4.4 Calculate the aerodynamic coefficients, specifically: lift coefficient: Drag coefficient: ,in: For lift, As resistance, For flight speed, For reference area; 4.5 Output the aerodynamic flow field calculation results for the clean aircraft configuration.

3. The integrated monitoring method for aircraft aerodynamics, performance, and quality under cumulus icing conditions as described in claim 1, characterized in that, The icing parameters are obtained as follows: Based on the aerodynamic flow field of a clean aircraft configuration, calculations are performed on water droplet impact and icing accumulation on the aircraft surface to obtain the equivalent roughness distribution of the aircraft surface, specifically including: Step 1: Solve the flow field for the clean aircraft configuration using numerical fluid dynamics methods, specifically including: 1.1 Set the calculation input parameters, including: flight speed, angle of attack, sideslip angle, air density, ambient temperature, viscosity coefficient, etc.; 1.2 Set the temperature of the aircraft wall; 1.3 The Reynolds-averaged Navier-Stokes equations are adopted as the governing equations for fluid motion; 1.4 Select a turbulence model for flow field calculation, such as the k-ω SST model or the SA model; 1.5 Obtain a convergent flow field solution through iterative solution; Step 2, calculation of water droplet trajectory and impact characteristics, specifically includes: 2.1 Based on the Lagrange method, the equation of motion of the water droplet is established and combined with Newton's second law to calculate the trajectory of the water droplet. Specifically: ,in: For the mass of the water droplet, Let be the velocity vector of the water droplet. As resistance, For gravity, For buoyancy; 2.2 The fourth-order Runge-Kutta method is used to solve the above differential equations. Under the boundary constraints of the given flow field velocity distribution and the initial coordinates of the droplet, the mathematical solution of the droplet trajectory equation is transformed into solving the initial value problem of the first-order ordinary differential equation system. Given the initial position of each droplet, the position of the droplet after ∆t is calculated. After continuous iteration, the calculation stops when the droplet collides with the wall or moves outside the given limit. The trajectory of the droplet can then be obtained. 2.3 Calculation of Water Droplet Impact Characteristics: Among the various parameters characterizing the water droplet impact characteristics of a component surface, the local collection coefficient is the most important. It characterizes the distribution of impacting water volume across the surface. Once the local collection coefficient is obtained, the other parameters are also obtained. Therefore, the calculation of water droplet impact characteristics is essentially the calculation of the local collection coefficient β, specifically: Where: β is the local water droplet collection coefficient on the wall, y is the initial range of water droplet impact, and s is the water droplet impact position; 2.4 Set the calculation input parameters, including the average effective size of a single water droplet, liquid water content, freezing temperature, etc.; Step 3, freezing thermodynamic calculations, specifically including: 3.1 A Messier thermodynamic model is established based on energy conservation to simulate the complex behaviors of water droplet impact, such as freezing and liquid film flow. The mass and energy conservation in adjacent control volumes (grid cells) are repeatedly analyzed until the amount of ice formation in each control volume is obtained. Specifically, this includes: mass conservation equation: ,in, To control the quality of water droplets freezing into ice in a given area, The mass of the water droplet impacting the control area. It refers to the mass of water droplets that overflowed into the control area. This refers to the mass of water droplets evaporating or ice sublimating in the controlled area. The mass of the water droplets overflowing from the control area; Energy conservation equation: ,in, For heat conduction between ice and the wall, For convective heat transfer between ice and air, The sensible heat generated by the impact of the water droplets It is the latent heat of liquid film evaporation. It's the heat energy transferred from the aircraft walls. It is the latent heat released when water droplets freeze.

4. The integrated monitoring method for aircraft aerodynamics, performance, and quality under cumulus icing conditions as described in claim 1, characterized in that, The aforementioned surface equivalent roughness mapping refers to mapping the equivalent roughness distribution of the aircraft surface to the surface nodes of the aerodynamic computational grid using a spatial interpolation algorithm, and applying the roughness as a wall roughness parameter to the aerodynamic computational model without performing icing geometry reconstruction. Specifically, this includes: Step 1: Obtaining the icing roughness parameters, specifically including: 1.1 A single-step quasi-steady-state calculation method is adopted to calculate the local icing characteristics based on the icing environment parameters, including: air density, ambient temperature, viscosity coefficient, liquid water content of cumulus icing, average water droplet size, and icing temperature; 1.2 Calculate the equivalent roughness values ​​at different locations on the aircraft surface based on the icing model. ; 1.3 The roughness values ​​are mapped to the spatial coordinates (x, y, z) of the aircraft surface to form a roughness spatial distribution dataset; Step 2: Extraction of surface nodes of the aerodynamic computational mesh, specifically including: 2.1 Read the coordinates of the nodes on the surface of the aerodynamic calculation mesh; 2.2 Obtain the spatial location of each surface node ( ); 2.3 Constructing the aerodynamic mesh surface node set; Step 3: Map the equivalent roughness distribution to the surface nodes of the aerodynamic computational mesh using a spatial interpolation algorithm. This specifically includes: 3.1 The inverse distance spatial interpolation algorithm is used to calculate the mesh nodal roughness. The formula for calculating nodal roughness is as follows: ,in For the roughness of the mesh nodes, Given the roughness data points, The distance between the node and the roughness data point. Distance weighting index; 3.2 Obtain the roughness value of each surface node in the aerodynamic computational mesh; Step 4: Apply the roughness mapping results to the aerodynamic calculation model, specifically including: 4.1 Input the nodal roughness values ​​as wall roughness parameters into the aerodynamic calculation model; 4.2 Roughness parameters are used for wall function correction during aerodynamic solution processing; 4.3 Complete the calculation of aircraft aerodynamic characteristics under icing conditions.

5. The integrated monitoring method for aircraft aerodynamics, performance, and quality under cumulus icing conditions according to claim 1, characterized in that, The aforementioned post-icing aerodynamic recalculation refers to: recalculating the flow field considering the influence of surface roughness to obtain the lift coefficient, drag coefficient, moment coefficient, static derivative, and dynamic derivative of the aircraft at different flight speeds, angles of attack, and sideslip angles, forming an aerodynamic database under icing conditions. This aerodynamic database under icing conditions serves as the input data source for the flight performance and flight quality evaluation module, meeting the needs of flight performance and flight quality evaluation, specifically including: Step 1: Setting up aerodynamic calculation conditions after icing, specifically including... 1.1 Set the flight status parameters of the aircraft after icing, including flight speed, angle of attack, sideslip angle, and flight altitude; 1.2 Select multiple discrete operating point values ​​based on the flight envelope range to construct a set of aerodynamic calculation operating conditions after icing; 1.3 For each operating point, the flow field is solved by calling the aircraft aerodynamic calculation model with surface roughness parameters applied; Step 2: Recalculate the flow field considering the influence of surface roughness, specifically including: 2.1 The surface equivalent roughness mapping result is applied as a wall roughness parameter to the boundary conditions of the aircraft surface. 2.2 Based on numerical fluid dynamics, the external flow field of the aircraft after applying roughness parameters is solved to obtain the pressure distribution, wall shear stress distribution, and velocity distribution under icing conditions. 2.3 Based on the converged flow field results, the aerodynamic forces and aerodynamic moments on the aircraft surface are calculated by integration. Step 3: Extract the aerodynamic coefficients after icing, specifically including: 3.1 Calculate the lift coefficient based on the aerodynamic integral results drag coefficient and lateral force coefficient ; 3.2 Calculate the rolling moment coefficient based on the integral results of the aerodynamic moment. Pitch moment coefficient and yaw moment coefficient ; Step 4: Calculate the static derivative in the icy state, specifically including: 4.1 Apply small disturbances to the angle of attack α, sideslip angle β, or control surface deflection near the reference operating point; 4.2 Calculate the changes in aerodynamic coefficients before and after the disturbance; 4.3 The static derivative is calculated using the finite difference method, whereby the static derivative includes the slope of the lift curve. Pitch moment derivative Lateral force derivative Rolling torque derivative and the derivative of yaw moment ,in: , , ; Step 5: Calculate the dynamic derivative in the icing state, specifically including: 5.1 Introduce angular velocity disturbances or motion mode disturbances under the reference operating conditions, and calculate the dynamic derivatives based on the unsteady aerodynamic force changes caused by the disturbances. The disturbances include pitch angular velocity q, roll angular velocity p, and yaw angular velocity r. 5.2 Calculate the unsteady aerodynamic forces and aerodynamic torques of the aircraft under disturbance conditions; 5.3 Calculate the dynamic derivative based on the change in aerodynamic coefficients before and after the disturbance, wherein the dynamic derivative includes , , ; 5.4 The dynamic derivative includes , , ,in: For wingspan, The average aerodynamic chord length; Step 6: Create an aerodynamic database for the icing state, specifically including: 6.1 Store the aerodynamic coefficients, static derivatives, and dynamic derivatives calculated under different flight speeds, angles of attack, and sideslip angles; 6.2 Establish a multidimensional aerodynamic database indexed by flight state parameters; The aerodynamic database described in 6.3 is used for subsequent flight performance and flight quality assessments.

6. The integrated monitoring method for aircraft aerodynamics, performance, and quality under cumulus icing conditions according to claim 1, characterized in that, The aforementioned flight performance refers to: based on the equations of motion of a point mass and using aerodynamic parameters, simulating the aircraft's stall speed, takeoff climb gradient, approach climb gradient, landing climb gradient, and landing performance to obtain the aircraft's basic flight performance under icing conditions, and evaluating the impact of cumulus icing conditions on flight performance, specifically including: Step 1: Constructing input parameters for flight performance simulation, specifically including: 1.1 Read the lift coefficient, drag coefficient, moment coefficient, and related derivatives from the aerodynamic database under icing conditions; 1.2 Obtain the parameters required for aircraft flight performance calculation, including aircraft weight W, wing reference area S, thrust T, flight altitude, gravitational acceleration g, air density ρ, and configuration parameters; 1.3 Set corresponding flight state boundary conditions according to different flight stages, wherein the flight stages include takeoff stage, approach stage and landing stage; Step 2: Establish a flight performance calculation model based on the equations of motion of a point mass, specifically including: 2.1 Treat the aircraft as a point mass and establish the force equilibrium relationship in the longitudinal plane; 2.2 Under quasi-steady conditions, the motion of the aircraft along its flight trajectory is specifically as follows: ; 3. The equilibrium equation perpendicular to the flight trajectory is: ,in: Let γ be the aircraft mass and γ be the track inclination angle. 2.4 Under steady-state climb or steady-state approach conditions, set the acceleration term to zero to obtain the corresponding flight performance calculation conditions; Step 3: Calculate the stall speed, specifically including: 3.1 Based on the maximum balance lift coefficient under icing conditions Calculate the aircraft's stall speed: 3.2 Stall speed ; 3.3 The stall velocity under icing conditions is compared with the stall velocity under clean configuration to obtain the stall velocity increment caused by icing; Step 4: Calculate the takeoff climb gradient, which includes: 4.1 Under safe takeoff conditions or at the preset takeoff climb rate, read the corresponding aerodynamic parameters for the icing state; 4.2 Calculate the takeoff climb gradient based on the thrust-drag difference and aircraft weight; 4.3 Takeoff Climb Gradient ; 4.4 Based on different configuration states and degrees of icing, the results of climb capability changes during takeoff were obtained; Step 5: Calculate the approach climb gradient and landing climb gradient, specifically including: 5.1 Extract the corresponding velocity, thrust, and aerodynamic parameters under approach or landing configuration conditions; 5.2 Based on the lift-drag and thrust characteristics under icing conditions, calculate the approach climb gradient and landing climb gradient respectively; 5.3 The approach climb gradient and landing climb gradient mentioned above are calculated using the same force balance principle as the takeoff climb gradient; 5.4 By comparing the results with the clean configuration, the impact of ice contamination on approach and landing go-around capability was obtained; Step 6: Calculate landing performance, specifically including: 6.1 Based on the approach velocity, lift-drag characteristics, and force conditions during the deceleration phase under icy conditions, a landing run performance calculation model is established; 6.2 Calculate the distance in the air from the obstacle crossing point to the touchdown point, and the takeoff distance after touchdown; 6.3 Calculate the total landing distance based on the velocity decay process, wherein the total landing distance includes the approach distance, the leveling distance, and the ground skid distance; 6.4 Results of landing distance variation under ice contamination conditions were obtained; Step 7: Generate flight performance evaluation results, specifically including: 7.1 Summarize the stall speed, takeoff climb gradient, approach climb gradient, landing climb gradient, and landing distance under icing conditions; 7.2 Compare the results with the flight performance results corresponding to the clean configuration to obtain the degradation amount of each flight performance; 7.3 Assess the extent to which the basic flight performance of an aircraft is affected under cumulus icing conditions based on the amount of flight performance degradation; When the stall speed increases, the climb gradient decreases, or the landing distance increases beyond a preset threshold under icing conditions, it is determined that ice contamination has a significant impact on the aircraft's flight performance, and this will serve as the basis for subsequent flight safety assessments and control decisions.

7. The integrated monitoring method for aircraft aerodynamics, performance, and quality under cumulus icing conditions according to claim 1, characterized in that, The aforementioned flight quality refers to the simulation analysis of the aircraft's stability quality, handling quality, and stall boundary characteristics based on the aircraft's six-degree-of-freedom equations of motion and utilizing aerodynamic derivatives under icing conditions. This simulation analysis includes assessments of maneuverability, lateral handling characteristics, longitudinal static stability, lateral static stability, lateral dynamic stability, and stall characteristics to obtain the aircraft's basic flight quality under icing conditions and to evaluate the impact of cumulus icing conditions on flight quality. Specifically, this includes: Step 1: Constructing input parameters for flight quality assessment, specifically including: 1.1 Read the aerodynamic coefficients, moment coefficients, static derivatives, and dynamic derivatives from the aerodynamic database under icing conditions; 1.2 Obtain aircraft mass parameters and inertial parameters, including aircraft mass m, center of gravity position, and moment of inertia. and inertial product; 1.3 Obtain flight status parameters, including flight speed, angle of attack, sideslip angle, altitude, thrust status, and configuration status; 1.4 Construct an input dataset for aircraft flight quality analysis under icing conditions based on the parameters described above; Step 2: Establish a 6-DOF motion equation model, specifically including: 2.1 Based on the translational and rotational dynamics relationship at the aircraft's center of mass, a set of nonlinear equations of motion for the aircraft with six degrees of freedom is established; 2.2 The translational equations include the velocity component equations in the body coordinate system, and the rotational equations include the angular motion equations of roll angular velocity, pitch angular velocity, and yaw angular velocity; 2.3 The 6-DOF motion equations described above use aerodynamic forces, aerodynamic torques, and thrust under icing conditions as inputs; 2.4 In flight quality analysis, the 6-DOF nonlinear motion equations are linearized with small perturbations as needed to obtain the longitudinal motion equations and the lateral motion equations. Step 3: Perform maneuverability simulation analysis, specifically including: 3.1 Under preset flight conditions, apply pitch, roll, and yaw control inputs to the aircraft; 3.2 Calculation of aircraft attitude response, angular velocity response, and trajectory changes based on 6-DOF motion equations; 3.3 Extract the aircraft's normal overload, attitude change rate, velocity change, and trajectory tracking capability during maneuvers; 3.4 Evaluate the impact of ice contamination on aircraft maneuverability based on the difference in maneuverability between iced and clean configurations; Step 4: Perform lateral maneuvering characteristic simulation analysis, specifically including: 4.1 Apply aileron or rudder control inputs to the aircraft; 4.2 Calculate the aircraft's roll angle, roll rate, sideslip angle, and yaw response; 4.3 Extract lateral handling characteristic indicators, including roll response time, peak roll angular velocity, steady-state roll capability, and sideslip coupling degree; 4.4 The lateral maneuvering response under icing conditions is compared with the clean configuration response to obtain the results of lateral maneuvering capability degradation; Step 5: Perform longitudinal static stability analysis, which includes: 5.1 Apply a small disturbance to the angle of attack near the reference equilibrium flight state; 5.2 Calculate the longitudinal static stability derivative based on the relationship between the pitching moment coefficient and the angle of attack. ,when At that time, it was determined that the aircraft possessed longitudinal static stability; based on the icing condition... The change in the amount of ice contamination was used to assess the impact of ice contamination on longitudinal static stability. Step 6: Perform lateral static stability analysis, which includes: 6.1 Apply a small disturbance to the sideslip angle near the baseline flight condition; 6.2 Calculate the derivative of directional static stability based on the change in yaw moment coefficient caused by sideslip angle disturbance. ; 6.3 Calculate the derivative of lateral static stability based on the change in rolling moment coefficient caused by sideslip angle disturbance. ; 6.4 According to and The magnitude pattern is used to assess the changes in the lateral static stability characteristics of an aircraft under icing conditions; Step 7: Perform lateral dynamic stability analysis, specifically... include: 7.1 Establishing a state-space model based on linearized lateral motion equations; 7.2 Obtain the eigenvalues ​​of the aircraft's lateral motion mode based on the aforementioned spatial model; 7.3 Based on the lateral motion modes, the modes include Dutch roll mode, roll convergence mode, and spiral mode; 7.4 Evaluate the lateral dynamic stability of the aircraft under icing conditions based on the damping ratio, natural frequency, and time response characteristics of each mode; 7.5 When icing leads to a decrease in modal damping, a slowdown in oscillation decay, or an increase in spiral divergence, it is determined that ice contamination has an adverse effect on lateral dynamic stability. Step 8: Perform stall characteristic analysis, specifically including: 8.1 Based on the lift coefficient, pitch moment coefficient, and control response characteristics under icing conditions, analyze the changes in aerodynamic and attitude response of the aircraft as the angle of attack increases; 8.2 Determine the critical angle of attack and critical velocity when the lift reaches its maximum value or when the pitch moment characteristics undergo a significant abrupt change; 8.3 Extract the lift decay characteristics, pitch moment change characteristics, and lateral response change characteristics before and after stall; 8.4 Evaluate the impact of ice contamination on stall characteristics based on the differences in critical angle of attack, stall speed, and post-stall response between the icing and clean configurations; Step 9 generates flight quality assessment results, specifically including: 9.1 Summarize the analysis results of maneuverability, lateral handling characteristics, longitudinal static stability, lateral static stability, lateral dynamic stability, and stall characteristics; 9.2 The flight quality indicators under icing conditions are compared with the corresponding flight quality indicators under clean configuration to obtain the amount of flight quality degradation; 9.3 Determine the impact of cumulus icing conditions on aircraft flight quality based on the amount of flight quality degradation, and generate flight quality assessment results for subsequent flight safety analysis and flight control strategy generation.

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